chore: jarvisChat → cAIc rename, single-node consolidation on jarvis, Qdrant UUID5 + chunk-size deploy fixes

- /api/ingest exempt from origin check for CLI/Bearer clients
- recreate deleted conversations on bogus conversation_id (chat + search)
- augmented auto-search emits reset:true; frontend clears first-pass text
- image uploads stored as placeholders, never text-ingested
- check_fact_conflicts requires shared subject keywords
- deterministic ingest point ids (md5 chunk hash)
- get_load() no longer crashes when rocm-smi yields no VRAM lines
- SQLite WAL + busy_timeout; timing-safe API key compares
- supervise fire-and-forget auto-ingest tasks; log missing logprobs
- centralize EMBED_URL/EMBED_MODEL/QDRANT_URL/NODE_NAME in config
- remove dead triage.py, select_node tests, is_state_changing, stray artifacts
- add regression tests + autouse global-reset conftest

.dockerignore

@@ -0,0 +1,44 @@
+# Version control
+.git/
+.gitignore
+
+# Python
+venv/
+__pycache__/
+*.pyc
+*.pyo
+.pytest_cache/
+.mypy_cache/
+
+# Databases and state (persisted via volumes)
+*.db
+hardware_state.json
+
+# Secrets (generated by setup.sh)
+.env
+secrets/
+searxng/
+
+# IDE / editor
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Models (bind-mounted at runtime)
+models/
+
+# Documentation (not needed in image)
+*.md
+docs/
+TASKS.md
+docker.md
+ai.md
+CLAUDE.md
+scripts/
+tests/

.env.example

@@ -0,0 +1,59 @@
+# ─────────────────────────────────────────────────────────────
+# cAIc — Environment configuration
+# Copy to .env and fill in values before running docker compose.
+# Secrets (lines marked 🔒) should be random — generate with:
+#   openssl rand -hex 20
+# ─────────────────────────────────────────────────────────────
+
+# ── Secrets ──────────────────────────────────────────────────
+# 🔒 Admin PIN (4 digits, required for first login)
+CAIC_ADMIN_PIN=
+CAIC_ALLOW_DEFAULT_PIN=false
+
+# 🔒 API key for IDE completions endpoint (auto-gen if empty)
+CAIC_COMPLETIONS_API_KEY=
+
+# 🔒 RabbitMQ password (must match secrets/rabbitmq_password.txt)
+RABBITMQ_PASSWORD=
+
+# 🔒 SearXNG session key
+SEARXNG_SECRET_KEY=
+
+# ── Service discovery (Docker service hostnames) ─────────────
+LLAMA_SERVER_BASE=http://llama-server:8081
+OLLAMA_BASE=http://ollama:11434
+CAIC_SEARXNG_BASE=http://searxng:8080
+CAIC_QDRANT_URL=http://qdrant:6333
+CAIC_EMBED_URL=http://ollama:11434
+CAIC_EMBED_MODEL=all-minilm:latest
+CAIC_AMQP_URL=amqp://caic:${RABBITMQ_PASSWORD}@rabbitmq:5672/caic
+
+# ── llama-server settings ────────────────────────────────────
+# GGUF filename (must exist in ./models/)
+LLAMA_MODEL=
+# Model name the app presents to clients (must match a loaded model)
+CAIC_DEFAULT_MODEL=qwen2.5-7b-instruct
+LLAMA_CTX_SIZE=4096
+LLAMA_N_GPU_LAYERS=0
+LLAMA_RPC_ENDPOINTS=
+
+# ── RAG / Qdrant ─────────────────────────────────────────────
+CAIC_RAG_COLLECTION=caic_rag
+CAIC_RAG_MAX_VECTORS=50000
+
+# ── Network / security ───────────────────────────────────────
+CAIC_ALLOWED_CIDRS=127.0.0.0/8,::1/128,10.0.0.0/8,172.16.0.0/12,192.168.0.0/16
+CAIC_TRUSTED_ORIGINS=
+CAIC_TRUST_X_FORWARDED_FOR=false
+
+# ── Port overrides (host-side publish) ───────────────────────
+CAIC_EXPOSE_PORT=8080
+SEARXNG_EXPOSE_PORT=8888
+QDRANT_EXPOSE_PORT=6333
+RABBITMQ_EXPOSE_PORT=5672
+LLAMA_EXPOSE_PORT=8081
+OLLAMA_EXPOSE_PORT=11434
+
+# ── Image generation (ComfyUI on worker) ─────────────────────
+CAIC_COMFYUI_BASE=http://localhost:8188
+CAIC_COMFYUI_TIMEOUT=120

.gitignore

@@ -5,3 +5,7 @@ __pycache__/
 venv/
 readme.md-
 *.bak
+hardware_state.json
+.env
+secrets/
+searxng/

AGENTS.md

@@ -1,114 +0,0 @@
-# JarvisChat — Agents Guide
-
-## Run
-
-```bash
-./venv/bin/uvicorn app:app --host 0.0.0.0 --port 8080 --reload
-```
-
-## Tests
-
-```bash
-./venv/bin/python -m pytest tests/ -v
-```
-
-All tests use `tmp_path` fixtures + monkeypatched `httpx.AsyncClient.stream`. No external services needed. Test factories reset `SESSIONS`, `PIN_ATTEMPTS`, `RATE_EVENTS` globals — be careful not to let test state leak. After the modular refactor, tests import directly from the correct modules (`db`, `security`, `config`, `search`, `rag`, `memory`, `routers.*`) — not from the old monolithic `app` namespace.
-
-Every router has a dedicated test file:
-| File | Covers |
-|------|--------|
-| `test_auth_capabilities.py` | `auth.py` — guest/admin sessions, origin blocking, logout |
-| `test_chat_streaming_and_memory_paths.py` | `routers/chat.py` — streaming, auto-search, remember/forget |
-| `test_completions.py` | `routers/completions.py` — API key auth, FIM, streaming, blocking, errors |
-| `test_conversations.py` | `routers/conversations.py` — full CRUD, guest admin enforcement |
-| `test_memories.py` | `routers/memories.py` — edit, search, stats endpoints |
-| `test_models_router.py` | `routers/models.py` — models list, ps, show, stats, search/status |
-| `test_presets.py` | `routers/presets.py` — full CRUD, default preset protection |
-| `test_profile.py` | `routers/profile.py` — get, update, default, length validation |
-| `test_search_route.py` | `routers/search_route.py` — explicit search flow, no results, errors |
-| `test_search_url_sanitization.py` | `search.py` URL sanitizer |
-| `test_settings_allowlist.py` | `routers/settings.py` — allowlisted key enforcement |
-| `test_skills_framework.py` | `routers/skills.py` — list, toggle, unknown skill, prompt injection |
-| `test_ip_allowlist.py` | IP allowlist helper + middleware |
-| `test_rate_and_payload_guardrails.py` | Rate limits + payload size enforcement |
-| `test_error_envelopes.py` | Global exception handler + stream error incidents |
-
-Modules that call `httpx.AsyncClient` (chat, completions, models, search_route)
-are mocked via `monkeypatch.setattr` on `AsyncClient.stream`, `.get`, or `.post`.
-CPU stats in `models.py` (`api/stats`) use real `psutil`; GPU stats are
-monkeypatched via `routers.models.get_gpu_stats`.
-
-## Architecture
-
-Refactored from single-file (`app.py`) into modules under project root:
-
-| File | Role |
-|------|------|
-| `app.py` | FastAPI app, middleware, router registration |
-| `config.py` | Constants, env vars, rate/payload limits, built-in skills registry |
-| `db.py` | SQLite schema, connection factory, settings helpers |
-| `auth.py` | PIN-based guest/admin sessions, auth routes |
-| `security.py` | Rate limiting, origin checks, IP allowlist, audit/incident logging |
-| `memory.py` | FTS5 memory CRUD, remember/forget command parsing |
-| `search.py` | SearXNG integration, perplexity scoring, refusal detection |
-| `rag.py` | Qdrant vector search + system prompt assembly |
-| `gpu.py` | AMD GPU stats via `rocm-smi` |
-| `routers/` | One module per endpoint group (chat, search, skills, completions, etc.) |
-
-### Entrypoint / API keys
-
-- `app.py` line 148: `uvicorn.run(app, ...)` when called directly
-- `config.py` line 14: `LLAMA_SERVER_BASE` defaults to `http://192.168.50.108:8081` — llama-server, **not** standard Ollama port, used by all model endpoints
-- `config.py` line 17: `COMPLETIONS_API_KEY` read from `JARVISCHAT_COMPLETIONS_API_KEY` env var or auto-generates a random key — no longer a missing import
-- `config.py` line 13: `OLLAMA_BASE` is legacy/unused — all endpoints now use `LLAMA_SERVER_BASE`
-
-### Key flows
-
-1. **`/api/chat`** → `process_remember_command()` intercepts "remember that..." / "forget about..." first → else `build_system_prompt()` (profile + FTS5 memory + Qdrant RAG + preset + skills) → stream from llama-server with `logprobs: true` → if perplexity > 15.0 OR `REFUSAL_PATTERNS` match, re-query with SearXNG results
-2. **`/api/search`** → bypasses perplexity/refusal, queries SearXNG directly → summarizes via llama-server (no raw results leaked in SSE)
-3. **`/v1/chat/completions`** → OpenAI-compatible for Continue.dev/IDE integration; FIM requests proxied without persistence
-
-### Perplexity / auto-search
-
-The upstream request includes `"logprobs": true`. `parse_llama_stream_chunk()` extracts per-token logprobs from each chunk's `choices[0].logprobs.content[].logprob`. The `all_logprobs` list is populated during streaming, so `calculate_perplexity()` and `is_uncertain()` work correctly — auto-search on high perplexity is no longer dead code.
-
-### Auth / lockdown
-
-- Guest session by default (`POST /api/auth/guest`), admin unlock via 4-digit PIN (`POST /api/auth/login`)
-- Admin required for PUT/DELETE/PATCH + all POST except allowlist (`/api/chat`, `/api/search`, `/api/auth/*`)
-- IP allowlist, rate limiting, origin checking, payload size limits — all enforced in `app.py` middleware
-- Origin check applies to **all** `/api/` requests (not just state-changing methods); `origin_allowed()` returns `False` when both `Origin` and `Referer` headers are absent, closing CSRF read gap
-- `JARVISCHAT_ADMIN_PIN` env var required on first boot (or `JARVISCHAT_ALLOW_DEFAULT_PIN=true`)
-
-### Database
-
-- SQLite at `jarvischat.db`, auto-created by `init_db()` on startup via FastAPI `lifespan`
-- `get_db()` opens new connection per request (no pool). Close after use.
-- FTS5 virtual table `memories` for full-text search with BM25 ranking. FTS5 operator keywords (`AND`, `OR`, `NOT`, `NEAR`) are double-quoted to prevent parse errors.
-
-### External services
-
-| Service | Required | Port |
-|---------|----------|------|
-| llama-server (OpenAI-compat API) | Yes | 8081 (ultron) or env `LLAMA_SERVER_BASE` |
-| SearXNG | No | 8888 |
-| wttr.in | No | weather shortcut bypasses SearXNG; curl UA for plain-text output |
-| rocm-smi | No | AMD GPU stats |
-| Qdrant | No | 6333 (ultron) — RAG vector search |
-
-### Config quirks
-
-- Rate limits and payload caps in `config.py` — tweak for testing by monkeypatching module attributes (note: patch `security.RL_*` not `config.RL_*` since `security` imports bindings separately)
-- `ALLOWED_SETTINGS_KEYS` in `config.py` controls which keys the UI can write via `/api/settings`
-- Settings table seeded with defaults (`profile_enabled`, `search_enabled`, `memory_enabled`, `skills_enabled`, `default_model`) — never overwritten by `init_db()`
-- Profile table uses singleton row `id=1`
-- RAG embedding requests go to `EMBED_URL` at `/api/embeddings` (separate Ollama instance)
-
-### SSE Protocol
-
-All streaming endpoints yield `data: {json}\n\n`. Key shapes:
-- `{token, conversation_id}` — streaming token
-- `{searching: true}` — web search triggered
-- `{search_results: N}` — N results (no raw_results payload)
-- `{done: true, perplexity, tokens_per_sec, searched?}` — terminal
-- `{error: "...", error_key: "..."}` — error with incident key

CLAUDE.md

@@ -1,15 +1,19 @@
-# CLAUDE.md
+# ai.md — Project Context
 
-This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+Detailed project context, work state, architecture, and configuration have moved to [`ai.md`](ai.md). This file is kept for backward compatibility — the canonical reference is `ai.md`.
 
-## Running the App
+## Quick start
 
 ```bash
+# Docker (recommended)
+scripts/setup.sh          # first run: generates .env, secrets, pulls default model
+docker compose up -d
+
 # Development
 ./venv/bin/uvicorn app:app --host 0.0.0.0 --port 8080 --reload
 
 # Production (via systemd)
-sudo systemctl restart jarvischat
+sudo systemctl restart caic
 
 # Direct run
 ./venv/bin/python app.py
@@ -17,58 +21,9 @@ sudo systemctl restart jarvischat
 
 ## Dependencies
 
+Docker deployment: no manual pip install needed — the Dockerfile handles it.
+
 ```bash
 ./venv/bin/pip install -r requirements.txt
-# Also requires: psutil jinja2 python-multipart pypdf (not in requirements.txt)
+# Also requires: psutil jinja2 python-multipart pypdf
 ```
-
-## Architecture
-
-Single-file FastAPI backend (`app.py`) + single-template frontend (`templates/index.html`). No build step. SQLite database auto-created at `jarvischat.db` on first run.
-
-### Request Flow: `/api/chat`
-
-1. User message saved to DB → conversation created if new
-2. `build_system_prompt()` assembles: profile + FTS5 memory search results + preset prompt
-3. Streamed to Ollama (`/api/chat`, `stream: true`, `logprobs: true`) via SSE
-4. **Auto web search trigger**: if perplexity > 15.0 OR response matches `REFUSAL_PATTERNS`, re-queries Ollama with SearXNG results prepended to system prompt
-5. Final response saved to DB; SSE `done` event sent with perplexity + tokens/sec
-
-### Request Flow: `/api/search` (explicit search)
-
-Bypasses perplexity/refusal detection entirely — queries SearXNG directly then asks Ollama to summarize with results as system context.
-
-### Memory System
-
-FTS5 virtual table (`memories`) in SQLite. `search_memories()` uses BM25 ranking. `process_remember_command()` intercepts "remember that..." / "forget about..." before the message reaches Ollama and returns a confirmation string. Topic auto-detection via keyword matching in `detect_topic()`.
-
-### Key Constants (top of `app.py`)
-
-- `OLLAMA_BASE` — `http://localhost:11434`
-- `SEARXNG_BASE` — `http://localhost:8888`
-- `PERPLEXITY_THRESHOLD` — `15.0` (controls auto-search sensitivity)
-- `DEFAULT_MODEL` — `llama3.1:latest`
-
-### External Services
-
-- **Ollama** — required, must be running on port 11434
-- **SearXNG** — optional, port 8888; `GET /api/search/status` probes availability
-- **wttr.in** — weather shortcut in `query_searxng()`, bypasses SearXNG for weather queries
-- **rocm-smi** — AMD GPU stats via subprocess; gracefully degrades if not available
-
-### Database
-
-`get_db()` opens a new connection per request (no connection pool). `init_db()` runs at startup via the FastAPI `lifespan` handler. The `profile` table uses a singleton row (`id = 1`). Default settings are seeded but never overwritten by `init_db()`.
-
-### SSE Protocol
-
-All streaming endpoints yield `data: {json}\n\n`. Key event shapes:
-- `{token, conversation_id}` — streaming token
-- `{searching: true}` — web search triggered
-- `{search_results: N}` — N results retrieved
-- `{done: true, perplexity, tokens_per_sec, searched?}` — terminal event
-- `{error: "..."}` — error event
-
-### Deployment
-
-Runs as systemd service under user `jarvischat`, working directory `/opt/jarvischat`. Logs via syslog (`journalctl -u jarvischat`).

Dockerfile

@@ -0,0 +1,36 @@
+# cAIc — FastAPI application
+# Multi-stage build for smaller production image
+
+# ── Stage 1: build ──────────────────────────────────────────
+FROM python:3.13-slim-bookworm AS builder
+WORKDIR /build
+COPY requirements.txt .
+RUN pip install --no-cache-dir --prefix=/install -r requirements.txt
+
+# ── Stage 2: runtime ────────────────────────────────────────
+FROM python:3.13-slim-bookworm
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY --from=builder /install /usr/local
+
+WORKDIR /app
+COPY . .
+
+# Persist DB and uploads outside the code layer
+ENV CAIC_DB_PATH=/app/data/caic.db \
+    CAIC_UPLOAD_DIR=/app/data/uploads \
+    CAIC_HOST=0.0.0.0 \
+    CAIC_PORT=8080 \
+    CAIC_SYSLOG_ADDRESS=""
+
+RUN mkdir -p /app/data
+
+EXPOSE 8080
+
+HEALTHCHECK --interval=30s --timeout=10s --start-period=15s --retries=3 \
+    CMD curl -fs http://localhost:8080/ || exit 1
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8080"]

README.md

@@ -1,258 +1,148 @@
-# jarvisChat v1.8.6
+![cAIc banner](static/readme-banner.png)
 
-**A lightweight local inference coding companion with persistent memory, web search, and real-time system monitoring.**
+# cAIc v1.1.0
 
-Built with FastAPI + SQLite + Jinja2. Runs on Python 3.13. No Docker required.
+**Cluster AI coordinator — heterogeneous GPU inference for homelab AI clusters.**
 
-Developer wiki: [docs/wiki/Home.md](docs/wiki/Home.md)
+Your RX 6600 XT can't run a 14B model. Your RTX 5070 Ti can. Your old MacBook can run the small stuff. Alone, each box is limited. Together, they're a cluster — if the software lets them cooperate.
 
-## What's New in v1.8.0
+cAIc makes them cooperate.
 
-- **Modular refactor completed** — single-file `app.py` split into `config.py`, `db.py`, `auth.py`, `security.py`, `memory.py`, `search.py`, `rag.py`, `gpu.py`, and `routers/` package
-- **`COMPLETIONS_API_KEY`** — auto-generated secret key for the OpenAI-compatible endpoint, overridable via `JARVISCHAT_COMPLETIONS_API_KEY` env var
-- **Perplexity auto-search fixed** — upstream request now sends `"logprobs": true`, `parse_llama_stream_chunk()` extracts per-token logprobs, so `calculate_perplexity()` and `is_uncertain()` work correctly (was dead code)
-- **All `/api/models` endpoints** — now correctly target `LLAMA_SERVER_BASE` (llama-server on port 8081) instead of the old Ollama port; `/api/ps` uses `/v1/models` endpoint
-- **RAG embedding endpoint fixed** — `EMBED_URL` changed from old server `:8081` to correct host/port `http://192.168.50.210:11434` (Ollama on new machine)
-- **Error messages corrected** — all user-facing errors say "inference server" instead of "Ollama" or "llama-server"
-- **Secure SSE protocol** — raw search results are no longer leaked in the SSE event stream
-- **FTS5 query safety** — operator keywords (`AND`, `OR`, `NOT`, `NEAR`) are double-quoted to prevent parse errors
-- **All 8 test files fixed** — rewired imports after the modular refactor; all 26 tests pass
-- **Origin check extended to all API methods** — GET/HEAD/OPTIONS requests no longer bypass origin checking (was limited to POST/PUT/DELETE/PATCH)
-- **Missing headers now rejected** — `origin_allowed()` returns `False` when both `Origin` and `Referer` are absent, closing the CSRF read gap for script-initiated requests
-- **Full router test coverage** — 7 new test files added: `test_conversations.py`, `test_presets.py`, `test_profile.py`, `test_models_router.py`, `test_completions.py`, `test_search_route.py`, `test_memories.py`; all 10 routers now have dedicated unit tests (92 total, up from 26)
+## The Problem
 
-## Features
+Every distributed inference tool — llama.cpp RPC, vLLM, exo — assumes you have identical GPUs. Same vendor, same VRAM, same drivers. That assumption works for data centers with 64 identical H100s. It doesn't work for your homelab with an AMD card in the server, an NVIDIA card in the gaming PC, and a MacBook on the desk.
 
-- **Persistent Memory** — SQLite FTS5 full-text search for fast, relevant memory retrieval
-- **Web Search** — SearXNG integration for automatic web lookups when the model is uncertain
-- **Explicit Search** — Search button to force web search without waiting for model uncertainty
-- **Profile Injection** — Custom system prompt injected into every conversation
-- **System Presets** — Save and switch between different system prompts
-- **Real-time Stats** — CPU, RAM, GPU, VRAM monitoring in sidebar
-- **Token Thermometer** — Visual context window usage indicator
-- **Streaming Responses** — Server-sent events for real-time token display
-- **Conversation History** — SQLite-backed chat persistence with mass-delete option
-- **Model Switching** — Change inference models on the fly
-- **Skills Framework** — Built-in skill registry with per-skill enable/disable controls
+You have more aggregate compute than any single consumer machine. The software just can't see it that way.
 
-## File Structure
+## How cAIc Solves It
+
+cAIc uses **query-routing** instead of layer-splitting. Each machine runs a complete model on its own GPU. When a query comes in, the coordinator classifies it and routes the *whole request* to the best-suited node — code questions to the coder model, general chat to the instruct model. No layer sharing, no straggler problem, no VRAM negotiation between mismatched GPUs.
 
 ```
-/opt/jarvischat/
-├── app.py              # FastAPI app entry point
-├── config.py           # Constants, env vars, limits, skill registry
-├── db.py               # SQLite schema, connection factory
-├── auth.py             # PIN-based guest/admin sessions, auth routes
-├── security.py         # Rate limiting, origin checks, IP allowlist, audit
-├── memory.py           # FTS5 memory CRUD, remember/forget commands
-├── search.py           # SearXNG integration, perplexity, refusal detection
-├── rag.py              # Qdrant vector search + system prompt assembly
-├── gpu.py              # AMD GPU stats via rocm-smi
-├── routers/
-│   ├── chat.py         # /api/chat streaming endpoint
-│   ├── search_route.py # /api/search explicit search endpoint
-│   ├── completions.py  # /v1/chat/completions OpenAI-compat endpoint
-│   ├── conversations.py# Conversation CRUD
-│   ├── memories.py     # Memory CRUD API
-│   ├── models.py       # Model listing, system stats
-│   ├── presets.py      # System prompt presets
-│   ├── profile.py      # User profile
-│   ├── settings.py     # Runtime settings
-│   └── skills.py       # Skills management
-├── static/
-│   └── logo.png        # Logo image (optional)
-├── templates/
-│   └── index.html      # Frontend
-└── tests/              # 26 pytest tests
+┌──────────────────────────────────────────────────────┐
+│               docker compose stack                   │
+│                                                      │
+│  ┌──────────┐  ┌────────┐  ┌────────────────────┐   │
+│  │ SearXNG  │  │ Qdrant │  │     RabbitMQ       │   │
+│  │  :8888   │  │ :6333  │  │   :5672 / :15672   │   │
+│  └────┬─────┘  └───┬────┘  └─────────┬──────────┘   │
+│       │            │                  │              │
+│       ▼            ▼                  ▼              │
+│  ┌───────────────────────────────────────────────┐   │
+│  │             cAIc (FastAPI)                    │   │
+│  │             :8080 (HTTP)                      │   │
+│  └───────┬──────────────────┬────────────────────┘   │
+│          │                  │                        │
+│          ▼                  ▼                        │
+│  ┌────────────────┐  ┌────────────────┐              │
+│  │  llama-server  │  │     Ollama     │              │
+│  │     :8081      │  │     :11434     │              │
+│  │   (GPU/RPC)    │  │  (embeddings)  │              │
+│  └────────────────┘  └────────────────┘              │
+└──────────────────────────────────────────────────────┘
 ```
 
-## Requirements
+**Coordinator** (CPU-only, no GPU) handles the web UI, RAG embedding, query triage, web search, memory, conversation storage, and the message broker. Every CPU-bound task stays here so it never competes with inference for GPU resources.
 
-- Python 3.11+ (tested on 3.13)
-- llama-server running locally or on network (OpenAI-compatible API on port 8081)
-- SearXNG (optional, for web search)
+**Workers** (discrete GPU) run only llama-server. No database, no browser sessions, no orchestration overhead. They register via AMQP, respond to health checks, and accept model-swap commands when the coordinator needs a different model for the current query.
 
-## Installation
+A worker with a slow GPU still contributes — it handles less latency-sensitive queries or batch work while the fast GPU handles interactive chat.
 
-### Fresh Install
+## What You Get
+
+- **Clustered inference** across mismatched GPUs and machines — AMD, NVIDIA, Apple Silicon, CPU-only
+- **Automatic query routing** — triage classifies each query and routes to the best node
+- **Dynamic model swapping** — coordinator requests model changes on workers when needed
+- **RAG with auto-eviction** — Qdrant-backed vector search with score-based corpus management
+- **Persistent memory** — FTS5-backed memory that learns your preferences over time
+- **Web search** — SearXNG integration for automatic lookups when the model is uncertain
+- **Private Chat mode** — toggle to keep nothing on disk: no memory, no RAG, no search, no persistence
+- **At-rest encryption** — AES-256-GCM on all query-derived text in SQLite and Qdrant
+- **IDE integration** — OpenAI-compatible `/v1/chat/completions` endpoint for Continue.dev and friends
+- **OpenAI-compat FIM** — `/v1/fim/completions` for code completion
+- **Image generation** — ComfyUI-backed image gen via cluster workers (Stable Diffusion / Flux)
+- **6 color themes** — IBM Blue, Matrix, Dark, Light, Amber, Trippin
+- **Docker-ready** — `docker compose up -d` and you're running
+
+## By the Numbers
+
+237 commits. 9,354 lines of Python. 214 tests. 95 files. One developer and an AI, March to July 2026.
+
+cAIc went from initial commit to v1.0.0 in four and a half months. Every line of code was generated by Claude via opencode — but the architecture, test suite, deployment pipeline, and every feature decision were directed by a single developer with 40+ years of systems experience. The AI wrote the code; the human made it ship.
+
+## Quick Start (Docker)
 
 ```bash
-# Create directory and venv
-sudo mkdir -p /opt/jarvischat
-sudo chown $USER:$USER /opt/jarvischat
-cd /opt/jarvischat
-python3 -m venv venv
-
-# Install dependencies
-./venv/bin/pip install fastapi uvicorn httpx psutil jinja2 python-multipart pypdf
-
-# Set admin PIN before first startup (4 digits)
-export JARVISCHAT_ADMIN_PIN=4827
-
-# Create subdirectories
-mkdir -p templates static
-
-# Copy files
-# (copy all .py files to /opt/jarvischat/)
-# (copy routers/ directory to /opt/jarvischat/)
-# (copy templates/index.html to /opt/jarvischat/templates/)
+git clone https://github.com/mikeshallop/caic.git && cd caic
+scripts/setup.sh           # generates .env, secrets, pulls default model (~4.6GB)
+docker compose up -d       # boots cAIc + Qdrant + RabbitMQ + SearXNG + llama-server + Ollama
 ```
 
-WARNING: Do not use `1234` as your admin PIN unless you accept weak local security.
+The setup wizard auto-generates secrets, detects disk space, downloads a default model, and configures all service hostnames. Point a browser at `http://localhost:8080` and you're chatting.
 
-NOTE: First boot requires `JARVISCHAT_ADMIN_PIN` unless you explicitly opt into insecure fallback with `JARVISCHAT_ALLOW_DEFAULT_PIN=true`.
+Requires: Docker Engine + Compose plugin. Place your own `.gguf` models in `./models/` for different sizes/vendors.
 
-## Systemd Service
+### Default Model
 
-Create `/etc/systemd/system/jarvischat.service`:
+The setup wizard downloads **Qwen2.5-7B-Instruct** (Q4_K_M quantization, ~4.6 GB) as the default inference model.
 
-```ini
-[Unit]
-Description=jarvisChat - Local Inference Web Interface
-After=network.target
+Why this model:
 
-[Service]
-Type=simple
-User=jarvischat
-Group=jarvischat
-WorkingDirectory=/opt/jarvischat
-ExecStart=/opt/jarvischat/venv/bin/uvicorn app:app --host 0.0.0.0 --port 8080
-Restart=always
-RestartSec=5
+- **Fits in 6 GB VRAM** — runs on mid-range GPUs (RX 6600 XT, RTX 3060, etc.) without offloading
+- **Instruction-tuned** — handles chat, code, and reasoning without fine-tuning
+- **Q4_K_M quantization** — best balance of quality and speed for consumer hardware; loses less than 1% accuracy vs. FP16 while fitting in half the VRAM
+- **GGUF format** — runs natively in llama.cpp (the worker backend) with no conversion step
 
-[Install]
-WantedBy=multi-user.target
-```
+Swap it for any `.gguf` model you prefer. cAIc's query-routing works with whatever you put in `./models/` — the coordinator doesn't care which model runs where, as long as the workers can serve it.
 
-```bash
-sudo systemctl daemon-reload
-sudo systemctl enable jarvischat
-sudo systemctl start jarvischat
-```
+→ [Installation Guide](https://github.com/mikeshallop/caic/wiki/Installation) | [Configuration](https://github.com/mikeshallop/caic/wiki/Home) | [Bare-Metal Install](https://github.com/mikeshallop/caic/wiki/Installation)
 
-## Memory Commands
+## Single-Node Mode
 
-In chat, natural language triggers memory operations:
+cAIc also runs entirely on one machine — coordinator, llama-server, Qdrant, SearXNG, and RabbitMQ all on localhost. Useful for testing, laptops, or WSL2 under Windows 11.
 
-| You say | What happens |
-|---------|--------------|
-| "remember that I prefer Rust over Go" | Stores as `preference` |
-| "remember that JarvisChat runs on port 8080" | Stores as `infrastructure` |
-| "note that the deadline is Friday" | Stores as `general` |
-| "forget about the deadline" | Removes matching memories |
+All services degrade gracefully if unreachable. Only llama-server (inference) is strictly required.
 
-Memories are automatically searched based on your message content and injected into the system prompt when relevant.
+## Why Query-Routing?
 
-### Memory Topics
+Most distributed inference splits a *single model* across GPUs — GPU 1 runs layers 0–15, GPU 2 runs 16–31. That works with identical cards. With mixed hardware, the slowest GPU sets the pace for every forward pass.
 
-Memories are auto-categorized:
-- `preference` — likes, dislikes, choices
-- `project` — active work, repos, tasks
-- `infrastructure` — servers, services, configs
-- `personal` — name, location, background
-- `general` — everything else
+cAIc routes *whole queries* instead. Each worker runs a complete model. Triage picks the right worker. No layer sharing, no lockstep, no straggler dragging down the cluster.
 
-## API Endpoints
+| | Layer-splitting | cAIc query-routing |
+|---|---|---|
+| **Hardware** | Identical GPUs required | Any mix — AMD, NVIDIA, Apple, CPU |
+| **Bottleneck** | Slowest GPU per forward pass | None — each node runs independently |
+| **Model swap** | N/A (one model split) | Async swap per worker |
+| **Scale** | Add VRAM to one model | Add machines, each contributes fully |
 
-### Completions (OpenAI-compatible)
+## Data Safety
 
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/v1/chat/completions` | OpenAI-compatible chat (requires Bearer API key) |
+| Concern | How cAIc handles it |
+|---------|---------------------|
+| **Queries on disk?** | AES-256-GCM encrypted at rest. Private Chat mode = nothing touches disk at all. |
+| **External services?** | SearXNG is optional and disabled in Private Chat. Everything else runs on your LAN. |
+| **Inter-node traffic?** | WireGuard tunnels encrypt all coordinator↔worker traffic. Zero application changes. |
+| **Access control?** | Guest sessions for LAN. Admin PIN (PBKDF2-hashed, rate-limited). Optional IP allowlist. |
 
-### Chat & Search
+## Built With
 
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/api/chat` | Send message (streaming SSE) |
-| POST | `/api/search` | Explicit web search (streaming SSE) |
+FastAPI + SQLite + Jinja2 on Python 3.13. AMQP-mediated cluster coordination via aio-pika. Qdrant for vector search. OpenAI-compatible inference endpoint via llama.cpp server.
 
-### Memory
+214 tests. All use `tmp_path` fixtures + monkeypatched HTTP clients. No external services needed.
 
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/memories` | List all memories |
-| POST | `/api/memories` | Add memory |
-| PUT | `/api/memories/{rowid}` | Update memory |
-| DELETE | `/api/memories/{rowid}` | Delete memory |
-| GET | `/api/memories/search?q=term` | Search memories |
-| GET | `/api/memories/stats` | Get counts by topic |
+## Documentation
 
-### Models & System
+| Page | What's there |
+|------|-------------|
+| [Home](https://github.com/mikeshallop/caic/wiki) | Overview, FAQ, links |
+| [Installation](https://github.com/mikeshallop/caic/wiki/Installation) | Docker + bare-metal walkthrough, config reference |
+| [Architecture](https://github.com/mikeshallop/caic/wiki/Developer-Architecture) | Coordinator/worker design, AMQP protocol, module map |
+| [Screenshots](https://github.com/mikeshallop/caic/wiki/Screenshots) | UI gallery |
 
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/models` | List available models |
-| GET | `/api/ps` | List loaded models |
-| POST | `/api/show` | Get model info |
-| GET | `/api/stats` | CPU, RAM, GPU, VRAM stats |
-| GET | `/api/search/status` | SearXNG availability |
+## Changelog
 
-### Settings & Profile
-
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/profile` | Get profile content |
-| PUT | `/api/profile` | Update profile (admin) |
-| GET | `/api/profile/default` | Get default profile |
-| GET | `/api/settings` | Get settings |
-| PUT | `/api/settings` | Update settings (admin) |
-
-### Conversations
-
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/conversations` | List conversations |
-| POST | `/api/conversations` | Create conversation |
-| GET | `/api/conversations/{id}` | Get conversation with messages |
-| PUT | `/api/conversations/{id}` | Update conversation title/model |
-| DELETE | `/api/conversations/{id}` | Delete conversation |
-| DELETE | `/api/conversations` | Delete ALL conversations |
-
-### Presets
-
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/presets` | List presets |
-| POST | `/api/presets` | Create preset |
-| PUT | `/api/presets/{id}` | Update preset |
-| DELETE | `/api/presets/{id}` | Delete preset |
-
-### Skills
-
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| GET | `/api/skills` | List all skills with state |
-| GET | `/api/skills/active` | List active skills |
-| PUT | `/api/skills/{key}` | Toggle skill enabled (admin) |
-
-### Auth
-
-| Method | Endpoint | Description |
-|--------|----------|-------------|
-| POST | `/api/auth/guest` | Create guest session |
-| POST | `/api/auth/login` | Admin PIN login |
-| POST | `/api/auth/logout` | Revoke session |
-| GET | `/api/auth/session` | Check session validity |
-| POST | `/api/auth/heartbeat` | Extend session TTL |
-
-## Configuration
-
-Settings are stored in the `settings` table and include:
-
-- `profile_enabled` — Inject profile into chats (true/false)
-- `search_enabled` — Auto web search (true/false)
-- `memory_enabled` — Memory injection (true/false)
-- `skills_enabled` — Skills framework (true/false)
-- `default_model` — Default inference model
-
-## Testing
-
-```bash
-./venv/bin/python -m pytest tests/ -v
-```
-
-All 26 tests use `tmp_path` fixtures + monkeypatched `httpx.AsyncClient.stream`. No external services needed.
+See [What's New](#whats-new-in-v100) below, or browse the [commit history](https://github.com/mikeshallop/caic/commits/main).
 
 ## License
 
@@ -260,4 +150,160 @@ MIT
 
 ## Repository
 
-Gitea: `ssh://gitea@llgit.llamachile.tube:1319/gramps/jarvisChat.git`
+GitHub: https://github.com/mikeshallop/caic
+
+Gitea (primary): `ssh://gitea@llgit.llamachile.tube:1319/gramps/caic.git`
+
+---
+
+## What's New in v1.1.0
+
+### Image Generation Service
+- `POST /api/image/generate` — proxy endpoint routes to ComfyUI on cluster workers
+- `GET /api/image/status` — lists available image gen nodes
+- Node agent auto-detects ComfyUI and registers `image_gen` capability
+- Full ComfyUI workflow: CheckpointLoader → KSampler → VAEDecode → SaveImage
+- Cluster AMQP protocol extended: `cmd.image_generate`, `image_generated`, `image_failed`
+- Hardware probe checks ComfyUI reachability + checkpoint model list
+- 27 new tests covering cluster handlers, router proxy, node agent, hardware, capability detection
+
+### Bug Fixes & Hardening
+- Hardware assessment now probes ComfyUI alongside llama-server, Qdrant, SearXNG
+- Node agent config extended with `comfyui_port` (default 8188)
+
+## What's New in v1.0.0
+
+### Docker Containerization (B3)
+- `Dockerfile` — multi-stage Python 3.13-slim build with healthcheck
+- `docker-compose.yml` — full stack: cAIc, SearXNG, Qdrant, RabbitMQ, llama-server, Ollama
+- `scripts/setup.sh` — first-run scaffolding: generates `.env`, secrets, SearXNG config, pulls default model
+- All service URLs env-var configurable with Docker service hostnames
+- AMQP secret uses Docker secrets pattern (`/run/secrets/`)
+- Only port 8080 exposed by default; all other services internal to compose network
+- Graceful degradation — SearXNG and Ollama optional
+
+### Bug Fixes & Hardening
+- Defaults changed from hardcoded LAN IPs to `localhost` for Docker compatibility
+- `DEFAULT_MODEL` configurable via `CAIC_DEFAULT_MODEL` env var
+- `HW_STATE_PATH` configurable via `CAIC_HW_STATE_PATH` env var
+- Syslog handler wrapped in try/except (container-safe)
+- SQLite `PRAGMA journal_mode = WAL` for better concurrency
+- `db.close()` in try/finally for proper cleanup
+- AMQP subscription append moved before try for reconnect safety
+- Missing `psutil` + `jinja2` added to `requirements.txt`
+- Test discovery fixed via `tests/conftest.py` sys.path insertion
+
+## What's New in v0.23.0
+
+### Topbar Redesign
+- Stats moved to bottom status bar, toggles to hamburger menu, palette next to version
+- Mobile-responsive layout, query bar restored above chat
+
+### Uninstall Scripts
+- `scripts/uninstall.sh`, `teardown-docker.sh`, `nuclear-clean.sh`
+
+### Code Quality
+- Replaced deprecated `asyncio.ensure_future` with `asyncio.create_task`
+- `AGENTS.md` → `ai.md` for tool-agnostic project context
+
+## What's New in v0.22.0
+
+### Color Theme System
+- 6 themes: IBM Blue, Green Ln (Matrix), Dark, Light, Amber (Fallout), Trippin (neon)
+- Palette icon in topbar, CSS variable swap, `localStorage` persistence
+
+### RAG Corpus Management UI (B4)
+- Admin modal to browse, search, edit, and delete individual RAG entries
+- Stats bar, semantic search, source filter, per-row edit/delete, bulk flush
+- 14 new tests, 214 total
+
+## What's New in v0.21.0
+
+### Scrollbar + DOM Fixes
+- Scrollbar z-index, `requestAnimationFrame` scroll, direction-aware scroll guard
+
+### Perplexity Persistence
+- Perplexity stored per message, confidence badges on loaded conversations
+
+### Config Overhaul
+- All service URLs now env-overridable for single-node deployment
+
+## What's New in v0.20.0
+
+### At-Rest Encryption
+- AES-256-GCM on all query-derived text: conversations, memories, uploads, RAG, completions
+- 256-bit key auto-generated on first boot, never exposed via API
+
+## What's New in v0.19.3
+
+### Private Chat Mode
+- Toggle to keep nothing on disk — no persistence, no memory/RAG, no web search
+
+### WireGuard In-Transit Encryption
+- All coordinator↔worker traffic encrypted at the network layer
+
+## What's New in v0.19.2
+
+### Waterfall Direction Toggle
+- NEW/OLD sort toggle, direction-aware scroll, toast notifications, clipboard fallback
+
+## What's New in v0.19.1
+
+### Default Model Auto-Pull
+- Checks llama-server at startup, falls back to Ollama pull if missing
+
+## What's New in v0.19.0
+
+### Apple Silicon Worker Support
+- GPU detection via `system_profiler` on macOS, hybrid AMD/Apple/CPU detection
+
+## What's New in v0.18.0
+
+### Wiki + UX Polish
+- Full installation guide, screenshots gallery, waterfall layout, barcode stripes, confidence badges, sprocket strips, paper grain background
+
+## What's New in v0.17.26
+
+### Dynamic Model Swap + Cluster Status UI
+- `request_model_swap()`, async `select_node()`, heartbeat handler, live status panel
+
+## What's New in v0.14.0
+
+### Cluster Protocol
+- 9 AMQP message types, node registry, ping/pong health, coordinator auto-promotion
+
+### RAG Corpus Management
+- Score-based eviction with hysteresis, flush endpoint, operational stats
+
+## What's New in v0.13.0
+
+### RAG Eviction Engine
+- Score-based eviction with hysteresis (80% high-water, 20% low-water), pinned sources, grace period
+
+## What's New in v0.12.0
+
+### Chat Reply Toolbar
+- Copy, print, save, rate actions on assistant messages
+
+### Startup Hardware Assessment
+- CPU, RAM, VRAM probe on first boot
+
+## What's New in v0.11.0
+
+### Terminal RAG Hook
+- `POST /api/ingest` with Bearer token auth for autonomous terminal history ingestion
+
+## What's New in v0.10.0
+
+### File Upload & Attachments
+- PDF/text extraction, chat context injection, RAG ingest, paperclip UI
+
+## What's New in v0.9.0
+
+### Modular Refactor
+- Single-file `app.py` split into config/db/auth/security/memory/search/rag/gpu + routers/
+
+## What's New in v0.8.0
+
+### Foundation
+- OpenAI-compat endpoint, RAG pipeline, SSE streaming, llama-server integration

TASKS.md

@@ -1,602 +1,116 @@
-# jarvisChat — OpenCode Prompt Sequence
-# Generated: 2026-07-01
-# Execute sequentially. Run full test suite after each task before proceeding.
-# Test command: ./venv/bin/python -m pytest tests/ -v
+# cAIc — Task List (v1.0+)
+
+Previous task history archived at `docs/archive/TASKS-pre-1.0.md`.
 
 ---
 
-## TASK 1 — README Cleanup
+## TASK 1 — Image Generation Service (corsair)
 
-Review README.md in the current repo. Remove any node references other than `ultron` (192.168.50.108) and `jarvis` (192.168.50.210). Ensure all references to the project use the exact casing `jarvisChat` — not `Jarvischat`, `JarvisChat`, or `jarvischat`. Do not change any functional content, endpoint documentation, or architecture descriptions — this is a text cleanup only. After editing, verify the file renders cleanly as markdown. Commit with message: `docs: clean up node references and branding consistency`.
+**Goal:** Add image generation as a cluster capability. The image-gen node (currently jarvis — single-node deployment) registers as an image gen worker in the cAIc cluster.
 
-No new tests required for this task.
+### Requirements:
 
----
+1. **Add `"image_gen"` capability** to the cluster protocol in `cluster.py` — valid capability values should include `image_gen`
+2. **Image gen API wrapper** — run ComfyUI, Automatic1111, or a lightweight API (e.g., `sd-api` or `comfyui-api`) that exposes a simple `POST /generate` endpoint accepting a prompt and returning a PNG
+3. **Proxy endpoint in cAIc** — `POST /api/image/generate` on the coordinator, routes the request to the image gen service via AMQP or direct HTTP
+4. **Update `hardware.py`** to probe the image gen service for reachability and status
+5. **Update node_agent** to report image gen capability and service status on registration
 
-## TASK 2 — Qwen2.5-Coder llama-server Service on Ultron (Infrastructure) [DONE]
-
-**Status: Systemd unit created, verified, and restored.**
-
-This task originally defined creation of `/etc/systemd/system/llama-server-coder.service` (port 8082, Qwen2.5-Coder-14B Q5_K_M) as a prerequisite for dynamic model swapping. That sysadmin work is done.
-
-**The real Task 2 deliverable — the ability to dynamically swap models based on query classification — is delivered by Roadmap N (Tasks 9–15).** The flow:
-
-1. **Task 13** — Phi-4-mini triage (`triage.py`) classifies the query as `general`, `code`, `search`, or `rag`
-2. **Task 13** — `select_node()` picks the best worker node; if the ideal model isn't active, it triggers a swap
-3. **Task 14** — `request_model_swap()` publishes `cmd.swap_model` via AMQP `jc.admin` exchange
-4. **Task 12** — The node agent on jarvis receives the command, stops the current llama-server, starts the correct one, waits for health, and publishes `model_ready`
-5. **Task 14** — ultron receives `model_ready`, updates the cluster registry, and routes the query to the node
-
-The swap is async and transparent — the user sees only latency. The UI (Task 15) shows a yellow "swapping" status dot during the transition.
-
-The service unit at `/etc/systemd/system/llama-server-coder.service` is the **target** the node agent starts when swapping to code inference. It is not enabled at boot — the AMQP cluster manages activation.
-
-See Tasks 9–15 for the actual model swap implementation.
-
-No pytest tests required for this infrastructure task.
-
----
-
-## TASK 3 — Update OpenCode Config to Use Qwen on :8082
-
-Update `/home/gramps/.config/opencode/opencode.jsonc` (on this machine, ultron) to point the configured provider at `http://127.0.0.1:8082/v1` instead of `http://127.0.0.1:8081/v1`. The model name in the config should be updated to reflect `qwen2.5-coder-14b` or whatever model ID the llama-server instance at :8082 reports via `/v1/models`. Verify the endpoint is reachable before writing the config change. Do not restart OpenCode — the config change takes effect on next session start.
-
-No pytest tests required for this task.
-
----
-
-## TASK 4 — File/Document Attachment: Backend Ingest Endpoint
-
-This task implements the backend half of file/document attachment (TODO #21). The goal is dual-aspect upload: a file can be used as immediate chat context, ingested into the RAG corpus (Qdrant), or both.
-
-**Add to `config.py`:**
-- `UPLOAD_DIR` — path for temporary upload storage, default `/tmp/jarvischat_uploads`
-- `MAX_UPLOAD_BYTES` — max file size, default 20MB
-- `SUPPORTED_UPLOAD_TYPES` — set of MIME types: `text/plain`, `text/markdown`, `application/pdf`, `application/json`, `text/x-python`, `text/html`
-
-**Create `routers/upload.py`:**
-
-Implement `POST /api/upload` (admin required). Accept `multipart/form-data` with:
-- `file` — the uploaded file (required)
-- `mode` — string enum: `context` (inject into next chat only), `ingest` (add to RAG corpus), `both` (default: `both`)
-- `conversation_id` — optional, associates context-mode content with a specific conversation
-
-Behavior:
-- Validate file size against `MAX_UPLOAD_BYTES` — return 413 if exceeded
-- Validate MIME type against `SUPPORTED_UPLOAD_TYPES` — return 415 if unsupported
-- For PDF files, extract text using `pypdf` (add to requirements.txt)
-- For all other types, read as UTF-8 text
-- If mode includes `ingest`: chunk the extracted text into 512-token overlapping chunks (128-token overlap), generate embeddings via `EMBED_URL` (http://192.168.50.108:11434/api/embeddings, model mxbai-embed-large), upsert into Qdrant collection `jarvischat` with metadata `{source: filename, upload_date: iso_timestamp, type: "upload"}`
-- If mode includes `context`: store the full extracted text in a new SQLite table `upload_context` with columns `(id INTEGER PRIMARY KEY, conversation_id TEXT, filename TEXT, content TEXT, created_at TEXT, expires_at TEXT)`. Context entries expire after 1 hour.
-- Return JSON: `{filename, size_bytes, mode, chunks_ingested (if ingest), context_id (if context), message}`
-
-**Add `upload_context` table to `db.py`** `init_db()`.
-
-**Wire `upload.router` into `app.py`** in the router registration block.
-
-**Write `tests/test_upload.py`** covering:
-- Valid text file upload, mode=ingest — assert chunks_ingested > 0, Qdrant upsert called
-- Valid text file upload, mode=context — assert context_id returned, row exists in upload_context
-- Valid text file upload, mode=both — assert both behaviors
-- File exceeds MAX_UPLOAD_BYTES — assert 413
-- Unsupported MIME type — assert 415
-- Guest session attempt — assert 403
-- PDF extraction path — mock pypdf, assert text extracted and processed
-
-Mock Qdrant and EMBED_URL calls via monkeypatch. Do not require live external services in tests.
-
-Run full test suite after implementation. All 26 existing tests must continue to pass.
-
----
-
-## TASK 5 — File/Document Attachment: UI Integration
-
-This task implements the frontend half of TODO #21. The UI is a single file at `templates/index.html`.
-
-Add a file attachment button to the chat input area. Requirements:
-- Paperclip icon button adjacent to the send button
-- Clicking opens a file picker filtered to supported types (`.txt`, `.md`, `.pdf`, `.json`, `.py`, `.html`)
-- On file selection, show a pill/badge above the input showing the filename with an X to remove it
-- On send, if a file is attached: POST to `/api/upload` with `mode=both` and the current `conversation_id`, then include the returned `context_id` in the subsequent `/api/chat` POST body as `upload_context_id`
-- If the upload fails, show an inline error and do not send the chat message
-- File attachment state clears after send
-
-**Update `/api/chat` in `routers/chat.py`:**
-- Accept optional `upload_context_id` in the request body
-- If present, look up the content in `upload_context` table and prepend it to the system prompt as: `\n\n[ATTACHED DOCUMENT: {filename}]\n{content}\n[END DOCUMENT]`
-- If the context_id is expired or missing, log a warning and continue without it (do not error)
-
-**Add to `tests/test_chat_streaming_and_memory_paths.py`:**
-- Test that a valid `upload_context_id` results in document content being prepended to the system prompt
-- Test that an expired/missing `upload_context_id` is silently ignored
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 6 — Roadmap I: Terminal Command RAG Hook
-
-This task implements autonomous RAG ingestion of significant terminal activity (TODO #23).
-
-**Create `routers/ingest.py`:**
-
-Implement `POST /api/ingest` (requires Bearer token auth — use same `COMPLETIONS_API_KEY` mechanism as `routers/completions.py`). Accept JSON body:
-- `content` — string, the text to ingest (required)
-- `source` — string, origin label e.g. `terminal`, `file`, `external` (default: `external`)
-- `metadata` — optional dict of additional key/value pairs
-
-Behavior:
-- Chunk `content` into 512-token overlapping chunks (128-token overlap) — extract this logic into a shared helper `chunk_text(text, chunk_size=512, overlap=128)` in `rag.py` if not already present
-- Generate embeddings via `EMBED_URL`
-- Upsert into Qdrant collection `jarvischat` with metadata `{source, ingest_date: iso_timestamp, ...metadata}`
-- Return JSON: `{chunks_ingested, source, message}`
-
-**Wire `ingest.router` into `app.py`.**
-
-**Create `/home/gramps/bin/jc-ingest.sh` on jarvis (192.168.50.210)** — this is a shell script, not a Python file, and lives outside the repo. Write it to stdout/document it clearly so gramps can deploy it manually:
-
-```bash
-#!/bin/bash
-# jc-ingest.sh — pipe terminal commands into jarvisChat RAG
-# Add to ~/.bashrc: export PROMPT_COMMAND="jc_capture"
-# Function to call after significant commands
-
-JC_URL="http://192.168.50.210:8080/api/ingest"
-JC_TOKEN="${JARVISCHAT_COMPLETIONS_API_KEY}"
-
-jc_capture() {
-    local cmd
-    cmd=$(history 1 | sed 's/^[ ]*[0-9]*[ ]*//')
-    # Only ingest significant commands
-    if echo "$cmd" | grep -qE '^(git|pip|systemctl|sudo|vi|vim|curl|wget|apt|python|pytest)'; then
-        curl -s -X POST "$JC_URL" \
-            -H "Authorization: Bearer $JC_TOKEN" \
-            -H "Content-Type: application/json" \
-            -d "{\"content\": $(echo "$cmd" | python3 -c 'import json,sys; print(json.dumps(sys.stdin.read().strip()))'), \"source\": \"terminal\"}" \
-            > /dev/null 2>&1 &
-    fi
-}
-```
-
-**Write `tests/test_ingest.py`** covering:
-- Valid ingest with content — assert chunks_ingested > 0
-- Missing Bearer token — assert 401
-- Wrong Bearer token — assert 403
-- Empty content — assert 422
-- Qdrant and embed calls mocked via monkeypatch
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 7 — Roadmap J: Startup Hardware Self-Assessment
-
-On jC startup, probe available hardware and write a living config snapshot. This replaces hardcoded assumptions about VRAM and RAM.
-
-**Create `hardware.py`** in the project root:
+### Architecture:
 
 ```
-async def assess_hardware() -> dict
+User prompt → cAIc coordinator → AMQP/HTTP → image-gen node (ComfyUI/API) → PNG → coordinator → user
 ```
 
-Probes:
-- System RAM: `psutil.virtual_memory().total` and `.available`
-- CPU count: `psutil.cpu_count()`
-- GPU VRAM total and free: call `rocm-smi --showmeminfo vram --json` via subprocess, parse output. If rocm-smi absent or fails, set VRAM values to 0 and log a warning.
-- llama-server reachable: GET `LLAMA_SERVER_BASE/v1/models`, timeout 3s. Record True/False and list of available model IDs.
-- Qdrant reachable: GET `http://192.168.50.108:6333/collections`, timeout 3s. Record True/False and collection list.
-- SearXNG reachable: GET `http://localhost:8888`, timeout 3s. Record True/False.
+### Considerations:
 
-Returns a dict with all of the above. Writes result as JSON to `hardware_state.json` in the working directory.
+- Response time: expect 5-30 seconds per image depending on model/resolution
+- Queue management: what if multiple requests come in at once?
+- Model selection: which SD/Flux model to run by default?
+- Resolution limits: max image size?
+- CORS/headers for serving generated images back to the UI
 
-**Call `assess_hardware()` from the FastAPI `lifespan` context** in `app.py` on startup, after `init_db()`. Log a summary line: `HW: {ram_gb}GB RAM, {vram_mb}MB VRAM, llama={reachable}, qdrant={reachable}, searxng={reachable}`.
+### Tests:
 
-**Expose `GET /api/hardware`** in a new `routers/hardware.py` — returns the current `hardware_state.json` content as JSON. No auth required (read-only, non-sensitive aggregate stats).
+- Mock image gen service, verify proxy routing
+- Verify `hardware.py` probes image gen endpoint
+- Verify node_agent registers with `image_gen` capability
+- Verify 429/503 handling when service is busy or down
 
-**Wire `hardware.router` into `app.py`.**
-
-**Write `tests/test_hardware.py`** covering:
-- `assess_hardware()` with all services reachable (mock subprocess and httpx calls) — assert all fields present
-- `assess_hardware()` with rocm-smi absent — assert VRAM=0, no exception raised
-- `assess_hardware()` with llama-server unreachable — assert `llama_reachable=False`, no exception
-- `GET /api/hardware` — assert returns JSON with expected keys
-
-Run full test suite. All existing tests must continue to pass.
+### Status: ✅ Backend Complete (ComfyUI install pending on jarvis — single-node deployment)
 
 ---
 
-## TASK 8 — Roadmap K: RAG Corpus Management
+## TASK 2 — Context-Aware Cluster Routing
 
-Qdrant collection `jarvischat` currently grows without bound. Implement weighted LRU eviction and pinning.
+**Goal:** Make chat/completions requests route to the best node based on available context capacity, not just model name matching. Solve the core problem: GPU nodes have limited VRAM context, but requests (especially from IDE integrations) can exceed that.
 
-**Add to `config.py`:**
-- `RAG_MAX_VECTORS` — max vectors in Qdrant collection before eviction triggers, default 50000
-- `RAG_EVICTION_BATCH` — number of vectors to evict per cycle, default 1000
-- `RAG_PINNED_SOURCES` — list of source labels that are never evicted, default `["upload", "profile"]`
+### Requirements:
 
-**Add to `rag.py`:**
+1. **Node capacity reporting** — node_agent calculates and reports `effective_context_tokens` on registration based on (available RAM/VRAM − model weight size) → KV cache capacity. Updated on model swaps.
+2. **Coordinator tracks cluster capacity** — `CLUSTER_NODES` stores `effective_context_tokens` per node, updated via registration and `model_ready` events.
+3. **Context budget estimation** — before sending upstream, estimate the token count of the assembled message array (~4 chars/token heuristic, or tiktoken if available). Expose as a helper in `config.py` or `rag.py`.
+4. **Resource-aware `select_node()`** — `triage.py` weighs effective context capacity, current load, and model match when picking a node. Nodes that can't fit the estimated context are deprioritized or skipped.
+5. **Wire triage into chat router** — `routers/chat.py` calls `get_inference_url(user_message)` instead of hardcoding `LLAMA_SERVER_BASE`.
+6. **Wire triage into completions router** — `routers/completions.py` uses the same routing logic for IDE/Continue.dev sessions.
+7. **Graceful degradation** — if no node can fit the estimated context, truncate intelligently (drop oldest RAG chunks, summarize history) before falling back to the coordinator.
 
-```python
-async def get_collection_count() -> int
-    # GET Qdrant /collections/jarvischat, return vectors_count
+### Architecture:
 
-async def evict_oldest(batch_size: int) -> int
-    # Scroll Qdrant for vectors with source NOT in RAG_PINNED_SOURCES,
-    # ordered by ingest_date ascending (oldest first),
-    # delete batch_size of them. Return count deleted.
-
-async def maybe_evict() -> int
-    # If get_collection_count() >= RAG_MAX_VECTORS: call evict_oldest(RAG_EVICTION_BATCH)
-    # Return count evicted (0 if no eviction needed)
+```
+User request → build messages → estimate tokens → triage.select_node(effective_context)
+  → node with enough headroom → stream response
+  → no node fits → truncate context → coordinator fallback
 ```
 
-**Call `maybe_evict()` from the ingest path** — both in `routers/upload.py` and `routers/ingest.py` — after each upsert batch completes.
+### Tests:
 
-**Add `GET /api/rag/stats`** to a new `routers/rag_admin.py`:
-- Returns `{vector_count, max_vectors, pinned_sources, eviction_batch}`
-- Admin required
+- Mock CLUSTER_NODES with varying effective_context_tokens, verify select_node picks the right one
+- Mock message arrays of different sizes, verify token estimation
+- Verify chat router calls get_inference_url instead of hardcoding
+- Verify fallback truncation when no node fits
+- Verify model swap updates effective_context_tokens
 
-**Wire `rag_admin.router` into `app.py`.**
-
-**Write `tests/test_rag_management.py`** covering:
-- `get_collection_count()` — mock Qdrant GET, assert correct count returned
-- `evict_oldest()` — mock Qdrant scroll + delete, assert correct batch size deleted, assert pinned sources excluded
-- `maybe_evict()` — below threshold: assert 0 evicted; at/above threshold: assert eviction triggered
-- `GET /api/rag/stats` — assert correct JSON shape returned
-- Guest attempt on `/api/rag/stats` — assert 403
-
-Run full test suite. All existing tests must continue to pass.
+### Status: Not started
 
 ---
 
-## TASK 9 — Roadmap N1: RabbitMQ Install and Service on Ultron (Infrastructure)
+## TASK 3 — RAM-Based Context Store Node (blue-sky)
 
-This task runs on ultron (this machine). Install RabbitMQ and verify it is operational.
+**Goal:** Enable a RAM-heavy node (e.g. a workstation with 32GB+ RAM) to join the cAIc cluster as a dedicated context store — holding conversation histories, RAG results, uploaded documents, and memories in RAM for fast retrieval, without running inference.
 
-Run the following steps:
-1. `apt-get update && apt-get install -y rabbitmq-server`
-2. `systemctl enable rabbitmq-server && systemctl start rabbitmq-server`
-3. `systemctl status rabbitmq-server` — verify active/running
-4. Enable the management plugin: `rabbitmq-plugins enable rabbitmq_management`
-5. Create a dedicated jC vhost: `rabbitmqctl add_vhost jarvischat`
-6. Create a dedicated user: `rabbitmqctl add_user jarvischat CHANGEME_PASSWORD` — generate a random 24-char alphanumeric password and record it
-7. Grant permissions: `rabbitmqctl set_permissions -p jarvischat jarvischat ".*" ".*" ".*"`
-8. Verify management UI is reachable: `curl -s -u guest:guest http://localhost:15672/api/overview | python3 -m json.tool`
-9. Delete default guest user: `rabbitmqctl delete_user guest`
+### Requirements:
 
-Declare the two topic exchanges needed by jC:
-- Exchange name: `jc.admin`, type: `topic`, durable: true
-- Exchange name: `jc.system`, type: `topic`, durable: true
+1. **New node type: `context_store`** — registers with a `context_store` capability, advertises available RAM and current usage
+2. **Lightweight context service** — HTTP API on the context store node exposing:
+   - `POST /context/{session_id}` — store conversation context
+   - `GET /context/{session_id}` — retrieve full context
+   - `PUT /context/{session_id}/chunks` — update RAG/document chunks
+   - `GET /context/{session_id}/relevant?q=...` — ranked context retrieval
+3. **Coordinator integration** — `build_system_prompt()` pulls from the context store node instead of (or in addition to) SQLite when one is available
+4. **Context store discovery** — node_agent supports `context_store` type in config, coordinator queries available RAM on registration
+5. **Failover** — if context store is unreachable, fall back to local SQLite/Qdrant as today
 
-Use `rabbitmqadmin` or `curl` against the management API to declare exchanges. Verify both exchanges appear in: `curl -s -u jarvischat:{password} http://localhost:15672/api/exchanges/jarvischat`
+### Architecture:
 
-Write the generated RabbitMQ password to `/home/gramps/.jc_amqp_secret` with mode 600. This will be read by jC as an env var source in subsequent tasks.
+```
+Coordinator startup → discover context_store nodes → query available RAM
+Build system prompt → pull relevant context from context_store node → assemble → send to inference node
+```
 
-No pytest tests required for this infrastructure task.
+### Considerations:
+
+- Context store node needs minimal resources — Python + aiohttp + Redis or in-memory dict
+- Latency: LAN round-trip (~1ms) is negligible compared to inference time
+- Persistence: optional — RAM-only is fine if the store can repopulate from SQLite on restart
+- Security: context store holds unencrypted data locally (encryption stays at the coordinator layer)
+
+### Tests:
+
+- Mock context store node registration, verify coordinator discovers it
+- Mock context store HTTP responses, verify build_system_prompt pulls from it
+- Verify failover to local SQLite when context store is unreachable
+
+### Status: Not started (blocked on available hardware — Dell Precision Tower 3420 dead, NUC running Home Assistant OS)
 
 ---
-
-## TASK 10 — Roadmap N2: AMQP Connection Layer in jC
-
-This task adds the core AMQP connection manager to jC. It must connect to RabbitMQ on ultron (localhost from jC's perspective since jC runs on ultron), handle reconnection, and provide a shared channel for all AMQP operations.
-
-**Add to `requirements.txt`:** `aio-pika>=9.0.0`
-
-**Add to `config.py`:**
-- `AMQP_URL` — read from env `JARVISCHAT_AMQP_URL`, default `amqp://jarvischat:password@localhost:5672/jarvischat`. The actual password comes from `/home/gramps/.jc_amqp_secret` — read it at startup if the env var is not set.
-- `AMQP_RECONNECT_DELAY` — seconds between reconnect attempts, default 5
-- `AMQP_EXCHANGE_ADMIN` — `jc.admin`
-- `AMQP_EXCHANGE_SYSTEM` — `jc.system`
-
-**Create `amqp.py`** in the project root:
-
-```python
-# Manages a single persistent aio-pika connection and channel.
-# Provides:
-#   connect() -> None          # establish connection, declare exchanges
-#   disconnect() -> None       # graceful close
-#   get_channel()              # returns current channel, reconnects if needed
-#   publish(exchange, routing_key, payload: dict) -> None
-#                              # publishes JSON-serialized payload as persistent message
-```
-
-Connection must:
-- Reconnect automatically on disconnect with `AMQP_RECONNECT_DELAY` backoff
-- Log connection events at INFO level
-- Not raise on publish if disconnected — log error and return (fire-and-forget, jC must not crash if RabbitMQ is down)
-
-**Start AMQP connection in `app.py` lifespan** after `assess_hardware()`. Disconnect in lifespan cleanup.
-
-**Write `tests/test_amqp.py`** covering:
-- `publish()` with mocked aio-pika connection — assert message published with correct exchange and routing key
-- `publish()` when disconnected — assert no exception raised, error logged
-- `get_channel()` when connection is None — assert reconnect attempted
-
-Mock all aio-pika calls via monkeypatch. Do not require a live RabbitMQ instance in tests.
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 11 — Roadmap N3: Worker Node Registration Handler (Ultron/jC Side)
-
-jC on ultron must listen on the `jc.admin` exchange for worker node registration requests and respond with admission or rejection.
-
-**Add to `amqp.py`:**
-
-```python
-async def subscribe(exchange, routing_key, callback) -> None
-    # Declare a queue, bind to exchange/routing_key, consume with callback
-```
-
-**Create `cluster.py`** in the project root:
-
-```python
-# In-memory cluster registry (survives only while jC is running)
-# Structure:
-# CLUSTER_NODES: dict[str, NodeRecord]
-#
-# NodeRecord fields:
-#   node_name: str
-#   ip: str
-#   active_model: ModelRecord
-#   inventory: list[ModelRecord]
-#   registered_at: str  (ISO timestamp)
-#   last_seen: str      (ISO timestamp)
-#
-# ModelRecord fields:
-#   name: str
-#   version: str
-#   quant: str
-#   path: str
-#   port: int           (llama-server port this model is served on)
-
-async def handle_registration(message: aio_pika.IncomingMessage) -> None
-    # Parse JSON payload from message body
-    # Validate required fields: node_name, ip, active_model, inventory
-    # Reject if node_name already in CLUSTER_NODES with status="active":
-    #   publish to jc.admin routing_key=f"node.{node_name}.rejected"
-    #   payload: {node_name, reason: "duplicate_node_name", timestamp}
-    # Reject if payload malformed:
-    #   publish to jc.admin routing_key=f"node.{node_name}.rejected"
-    #   payload: {node_name, reason: "malformed_payload", timestamp}
-    # Otherwise admit:
-    #   add to CLUSTER_NODES
-    #   publish to jc.admin routing_key=f"node.{node_name}.admitted"
-    #   payload: {node_name, timestamp, amqp_url: AMQP_URL}
-
-async def handle_deregistration(message) -> None
-    # Remove node from CLUSTER_NODES, log it
-
-def get_cluster_state() -> dict
-    # Return serializable snapshot of CLUSTER_NODES
-```
-
-**Subscribe to registration messages in `app.py` lifespan** after AMQP connects:
-- `jc.admin` exchange, routing key `node.*.register` → `handle_registration`
-- `jc.admin` exchange, routing key `node.*.deregister` → `handle_deregistration`
-
-**Add `GET /api/cluster`** to a new `routers/cluster.py`:
-- Returns `get_cluster_state()` as JSON
-- No auth required (read-only status endpoint)
-
-**Wire `cluster.router` into `app.py`.**
-
-**Write `tests/test_cluster.py`** covering:
-- Valid registration payload — assert node admitted, added to CLUSTER_NODES, admitted message published
-- Duplicate node name — assert rejected, reason=`duplicate_node_name`
-- Malformed payload (missing required field) — assert rejected, reason=`malformed_payload`
-- Deregistration — assert node removed from CLUSTER_NODES
-- `GET /api/cluster` — assert returns current node list
-
-Mock all aio-pika calls. Do not require live RabbitMQ.
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 12 — Roadmap N4: Worker Node Registration Publisher (Jarvis Side)
-
-This task creates the worker node AMQP client that runs on jarvis (192.168.50.210). It is a standalone Python script — not part of the jC FastAPI app — that runs as a systemd service on jarvis.
-
-**Create `node_agent/agent.py`** in the repo (new directory):
-
-The agent:
-1. On start: reads local config from `/etc/jc-node-agent.conf` (INI format):
-   - `node_name` — hostname, default from `socket.gethostname()`
-   - `node_ip` — LAN IP, default from socket
-   - `amqp_url` — RabbitMQ URL on ultron, e.g. `amqp://jarvischat:password@192.168.50.108:5672/jarvischat`
-   - `llama_port` — port llama-server/llama-rpc is listening on, default 8081
-   - `models_dir` — path to GGUF model files, default `/home/gramps/models`
-   - `active_model` — filename of currently active model (without path)
-
-2. Discovers inventory by globbing `models_dir` for `*.gguf` files and parsing name/version/quant from filename using regex pattern: `{name}-{version}-{quant}.gguf` where quant matches `Q[0-9]+_K_[A-Z]+` or similar standard suffixes.
-
-3. Publishes registration request to `jc.admin` exchange, routing key `node.{node_name}.register`:
-   ```json
-   {
-     "node_name": "jarvis",
-     "ip": "192.168.50.210",
-     "active_model": {"name": "...", "version": "...", "quant": "...", "path": "...", "port": 8081},
-     "inventory": [...]
-   }
-   ```
-
-4. Listens for response on `jc.admin`, routing key `node.{node_name}.admitted` or `node.{node_name}.rejected`. Logs result. If rejected, exits with error.
-
-5. After admission: publishes heartbeat every 30 seconds to `jc.system`, routing key `node.{node_name}.heartbeat`:
-   ```json
-   {"node_name": "...", "ip": "...", "active_model": "...", "timestamp": "..."}
-   ```
-
-6. Listens on `jc.admin`, routing key `node.{node_name}.cmd.swap_model`:
-   - Payload: `{model_filename: str}`
-   - Stops current llama-server: `systemctl stop llama-server`
-   - Updates `/etc/jc-node-agent.conf` active_model field
-   - Starts llama-server: `systemctl start llama-server` (assumes service reads active_model from conf or ExecStart is updated)
-   - Waits for llama-server to be healthy: poll `http://localhost:{llama_port}/v1/models` every 2s, timeout 120s
-   - Publishes to `jc.system`, routing key `node.{node_name}.model_ready`:
-     ```json
-     {"node_name": "...", "active_model": "...", "port": ..., "timestamp": "..."}
-     ```
-   - If startup fails within timeout: publishes `node.{node_name}.model_failed` with error detail
-
-**Create `node_agent/requirements.txt`:** `aio-pika>=9.0.0`
-
-**Document `/etc/jc-node-agent.conf` format** in a comment block at the top of `agent.py`.
-
-**Write `tests/test_node_agent.py`** covering:
-- Registration payload construction from config + model discovery — assert correct JSON shape
-- Model swap command handler: success path — assert systemctl calls made, model_ready published
-- Model swap command handler: timeout path — assert model_failed published
-- Heartbeat: assert published every interval (mock asyncio.sleep)
-
-Mock all aio-pika, subprocess, and httpx calls.
-
-**Do not create a systemd service file in this task** — that is a manual deployment step. Document the required service configuration in a comment at the bottom of `agent.py`.
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 13 — Roadmap N5: Query Routing via AMQP + Phi-4-mini Triage
-
-This task wires the cluster into jC's chat flow. When a query arrives at `/api/chat`, instead of always routing to the hardcoded `LLAMA_SERVER_BASE`, jC now routes to the best available cluster node based on query context.
-
-**Prerequisites:** Tasks 9–12 complete. At least one worker node admitted to cluster.
-
-**Install Phi-4-mini on ultron (infrastructure step):**
-- Download `Phi-4-mini-Instruct-Q4_K_M.gguf` from HuggingFace using `hf download microsoft/Phi-4-mini-instruct --include "*.Q4_K_M.gguf" --local-dir /home/gramps/models`
-- Create `/etc/systemd/system/llama-server-triage.service` — same pattern as existing llama-server service but: port 8083, model path points to Phi-4-mini GGUF, no `--rpc` flag (runs entirely on ultron CPU/iGPU), description `Llama.cpp Server (Phi-4-mini — triage/routing)`
-- `systemctl daemon-reload && systemctl enable llama-server-triage && systemctl start llama-server-triage`
-- Verify: `curl -s http://localhost:8083/v1/models`
-
-**Add to `config.py`:**
-- `TRIAGE_BASE` — `http://127.0.0.1:8083/v1` (Phi-4-mini)
-- `TRIAGE_TIMEOUT` — 10 seconds
-- `FALLBACK_TO_DEFAULT` — True (if triage fails or no nodes available, fall back to `LLAMA_SERVER_BASE`)
-
-**Create `triage.py`** in the project root:
-
-```python
-async def classify_query(query: str) -> str
-    # Sends query to Phi-4-mini at TRIAGE_BASE with a classification system prompt.
-    # System prompt instructs model to respond with ONLY one of:
-    #   "general", "code", "search", "rag"
-    # Returns the classification string.
-    # Timeout: TRIAGE_TIMEOUT seconds.
-    # On any error: returns "general" (fail-safe).
-
-async def select_node(classification: str) -> dict | None
-    # Consults CLUSTER_NODES from cluster.py
-    # For "code": prefer nodes where active_model name contains "coder" or "qwen"
-    # For "general": prefer nodes where active_model name contains "mistral" or "llama"
-    # For "search" or "rag": return None (handled locally by jC)
-    # If no matching node found: return None (triggers FALLBACK_TO_DEFAULT)
-    # Returns NodeRecord dict for selected node, or None
-
-async def get_inference_url(query: str) -> str
-    # Combines classify_query + select_node
-    # Returns full base URL: f"http://{node.ip}:{node.active_model.port}/v1"
-    # Falls back to LLAMA_SERVER_BASE if classification=search/rag, no nodes, or triage error
-```
-
-**Update `routers/chat.py`:**
-- Replace the hardcoded `LLAMA_SERVER_BASE` reference with a call to `get_inference_url(user_message)`
-- The rest of the chat flow (RAG, memory, streaming) is unchanged — only the inference target URL changes
-
-**Write `tests/test_triage.py`** covering:
-- `classify_query()` returns valid classification — mock Phi-4-mini response
-- `classify_query()` on timeout — assert returns "general", no exception
-- `select_node("code")` with coder node in cluster — assert correct node returned
-- `select_node("general")` with no matching node — assert None returned
-- `get_inference_url()` with code query and coder node available — assert returns node URL
-- `get_inference_url()` with no nodes in cluster — assert returns LLAMA_SERVER_BASE fallback
-
-**Update `tests/test_chat_streaming_and_memory_paths.py`:**
-- Mock `triage.get_inference_url` to return a fixed URL in all existing tests so they continue to pass without a live cluster
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 14 — Roadmap N6: Model Swap Command Flow
-
-This task implements the ultron-side logic for requesting a model swap on a worker node when the ideal model is not currently active.
-
-**Add to `cluster.py`:**
-
-```python
-async def request_model_swap(node_name: str, model_filename: str) -> bool
-    # Publishes to jc.admin exchange, routing key node.{node_name}.cmd.swap_model
-    # Payload: {model_filename, requested_at: iso_timestamp}
-    # Sets node status to "swapping" in CLUSTER_NODES
-    # Returns True if message published successfully
-
-async def handle_model_ready(message) -> None
-    # Handles node.{node_name}.model_ready from jc.system
-    # Updates CLUSTER_NODES[node_name].active_model to the new model
-    # Sets node status back to "active"
-    # Logs swap completion with timing
-
-async def handle_model_failed(message) -> None
-    # Handles node.{node_name}.model_failed from jc.system
-    # Sets node status to "error" in CLUSTER_NODES
-    # Logs failure with detail from message payload
-```
-
-**Subscribe in `app.py` lifespan:**
-- `jc.system` exchange, routing key `node.*.model_ready` → `handle_model_ready`
-- `jc.system` exchange, routing key `node.*.model_failed` → `handle_model_failed`
-
-**Update `triage.py` `select_node()`:**
-- If the best-matching node exists but its active_model does not match the ideal model for the classification, AND the node status is "active" (not already swapping):
-  - Call `request_model_swap(node_name, ideal_model_filename)`
-  - Return None (triggers fallback) — the swap happens async, next query will find the right model active
-- If node status is "swapping": return None (fallback, swap in progress)
-
-**Update `GET /api/cluster`** to include node status in response.
-
-**Write `tests/test_model_swap.py`** covering:
-- `request_model_swap()` — assert swap command published, node status set to "swapping"
-- `handle_model_ready()` — assert active_model updated, status set to "active"
-- `handle_model_failed()` — assert status set to "error"
-- `select_node()` with mismatched active model — assert swap requested, None returned
-- `select_node()` with node status "swapping" — assert None returned without publishing another swap
-
-Run full test suite. All existing tests must continue to pass.
-
----
-
-## TASK 15 — Roadmap N7: Cluster Status UI
-
-Surface cluster awareness in the jC frontend (`templates/index.html`).
-
-**Add a cluster status panel** to the UI. Requirements:
-- Small status bar or collapsible panel, visible but unobtrusive
-- Polls `GET /api/cluster` every 15 seconds
-- For each admitted node: show node name, active model name, and a colored status dot:
-  - Green: active
-  - Yellow: swapping
-  - Red: error or offline (not seen in last 60 seconds based on last_seen timestamp)
-- If no nodes in cluster (empty): show "No worker nodes connected"
-- Panel must not interfere with chat input or conversation list
-
-**Update `GET /api/cluster` response** to include `last_seen` per node and a `status` field (`active`, `swapping`, `error`).
-
-**Update heartbeat handling in `cluster.py`:** add a handler for `node.*.heartbeat` on `jc.system` that updates `last_seen` timestamp for the node.
-
-**Subscribe in `app.py` lifespan:**
-- `jc.system` exchange, routing key `node.*.heartbeat` → `handle_heartbeat`
-
-**Add `handle_heartbeat()` to `cluster.py`:**
-- Updates `CLUSTER_NODES[node_name].last_seen` to current timestamp
-- If node was previously marked offline (not in CLUSTER_NODES), log re-registration warning but do not auto-admit — full registration required
-
-**Write `tests/test_cluster_heartbeat.py`** covering:
-- `handle_heartbeat()` for known node — assert last_seen updated
-- `handle_heartbeat()` for unknown node — assert no crash, warning logged, node not added
-
-Run full test suite. All 26+ existing tests must continue to pass.
-
-Commit all changes introduced across Tasks 9–15 with message: `feat: Roadmap N — AMQP cluster nervous system complete`

ai.md

@@ -0,0 +1,187 @@
+# cAIc — Agents Guide
+
+## Run
+
+```bash
+# Docker (recommended)
+scripts/setup.sh && docker compose up -d
+
+# Bare-metal
+uvicorn app:app --host 0.0.0.0 --port 8080 --reload
+```
+
+## Tests
+
+```bash
+python3 -m pytest tests/ -v
+```
+
+All tests use `tmp_path` fixtures + monkeypatched `httpx.AsyncClient.stream/get/post/put`. No external services needed. Test factories reset `SESSIONS`, `PIN_ATTEMPTS`, `RATE_EVENTS` globals — be careful not to let test state leak. Tests import directly from the correct modules (`db`, `security`, `config`, `search`, `rag`, `memory`, `routers.*`).
+
+Every router has a dedicated test file:
+| File | Covers |
+|------|--------|
+| `test_auth_capabilities.py` | `auth.py` — guest/admin sessions, origin blocking, logout |
+| `test_chat_streaming_and_memory_paths.py` | `routers/chat.py` — streaming, auto-search, remember/forget, upload context injection |
+| `test_completions.py` | `routers/completions.py` — API key auth, FIM, streaming, blocking, errors |
+| `test_conversations.py` | `routers/conversations.py` — full CRUD, guest admin enforcement, attachment_count |
+| `test_ingest.py` | `routers/ingest.py` — Bearer auth, chunk/embed/upsert, validation |
+| `test_memories.py` | `routers/memories.py` — edit, search, stats endpoints |
+| `test_models_router.py` | `routers/models.py` — models list, ps, show, stats, search/status |
+| `test_presets.py` | `routers/presets.py` — full CRUD, default preset protection |
+| `test_profile.py` | `routers/profile.py` — get, update, default, length validation |
+| `test_rag_management.py` | `eviction.py` + `routers/rag_admin.py` — eviction engine, stats, flush, browse, search, edit, delete individual points |
+| `test_search_route.py` | `routers/search_route.py` — explicit search flow, no results, errors |
+| `test_search_url_sanitization.py` | `search.py` URL sanitizer |
+| `test_cluster.py` | `cluster.py` — registration, deregistration, pong, events, coordinator query |
+| `test_cluster_heartbeat.py` | `cluster.py` — heartbeat handler, known/unknown node |
+| `test_model_swap.py` | `cluster.py` — request_model_swap, handle_model_ready/failed |
+| `test_node_agent.py` | `node_agent/agent.py` — registration, ping/pong, model swap |
+| `test_image.py` | Image generation — cluster handlers, router proxy, node agent ComfyUI integration, hardware probe, capability detection |
+| `test_settings_allowlist.py` | `routers/settings.py` — allowlisted key enforcement |
+| `test_skills_framework.py` | `routers/skills.py` — list, toggle, unknown skill, prompt injection |
+| `test_ip_allowlist.py` | IP allowlist helper + middleware |
+| `test_rate_and_payload_guardrails.py` | Rate limits + payload size enforcement |
+| `test_error_envelopes.py` | Global exception handler + stream error incidents |
+| `test_fixes_regression.py` | Origin-exempt ingest, bogus conversation_id FK, auto-search reset, image uploads, conflict false-positives, deterministic ingest ids, get_load VRAM parsing, version pin |
+| `test_upload.py` | `routers/upload.py` — upload, delete, link, by-conversation, attachment_count integration |
+
+Modules that call `httpx.AsyncClient` (chat, completions, models, search_route, upload, ingest, model_pull)
+are mocked via `monkeypatch.setattr` on `AsyncClient.stream`, `.get`, or `.post`.
+CPU stats in `models.py` (`api/stats`) use real `psutil`; GPU stats are
+monkeypatched via `routers.models.get_gpu_stats`.
+
+## Architecture
+
+Refactored from single-file (`app.py`) into modules under project root:
+
+| File | Role |
+|------|------|
+| `app.py` | FastAPI app, middleware, router registration |
+| `config.py` | Constants, env vars, rate/payload limits, built-in skills registry, upload limits |
+| `db.py` | SQLite schema, connection factory, settings helpers, upload_context CRUD |
+| `auth.py` | PIN-based guest/admin sessions, auth routes |
+| `security.py` | Rate limiting, origin checks, IP allowlist, audit/incident logging |
+| `memory.py` | FTS5 memory CRUD (encrypted facts, Python-side matching), remember/forget command parsing |
+| `search.py` | SearXNG integration, perplexity scoring, refusal detection |
+| `rag.py` | Qdrant vector search (encrypted payload text) + system prompt assembly + chunk_text() helper |
+| `eviction.py` | Score-based RAG eviction engine |
+| `gpu.py` | GPU stats — `rocm-smi` (AMD/Linux) or `system_profiler` (Apple Silicon/macOS) |
+| `crypto.py` | AES-256-GCM encrypt/decrypt + key management (stored as `heartbeat_interval_ms` in settings) |
+| `model_pull.py` | Startup model availability check + Ollama pull API |
+| `cluster.py` | Cluster node registry, event log, coordinator election, ping/pong, model swap handlers, image generation request/response |
+| `amqp.py` | AMQP connection manager — connect, disconnect, publish, subscribe, auto-reconnect |
+| `node_agent/` | Standalone worker agent — AMQP client for registration, ping/pong, model swap, image generation |
+| `routers/` | One module per endpoint group (chat, search, skills, completions, upload, ingest, image) |
+
+### Entrypoint / API keys
+
+- `app.py` line 148: `uvicorn.run(app, ...)` when called directly
+- `config.py` line 14: `LLAMA_SERVER_BASE` defaults to `http://localhost:8081` — configurable via env var; Docker uses `http://llama-server:8081`
+- `config.py` line 17: `DEFAULT_MODEL` read from `CAIC_DEFAULT_MODEL` env var or defaults to `qwen2.5-7b-instruct`
+- `config.py` line 18: `COMPLETIONS_API_KEY` read from `CAIC_COMPLETIONS_API_KEY` env var or auto-generates
+
+### Key flows
+
+1. **`/api/chat`** → `process_remember_command()` intercepts "remember that..." / "forget about..." first → optional `upload_context_id` fetches document text from SQLite → `build_system_prompt()` (profile + FTS5 memory + Qdrant RAG + preset + skills + uploaded doc) → stream from `LLAMA_SERVER_BASE` with `logprobs: true` → if perplexity > 15.0 OR `REFUSAL_PATTERNS` match, re-query with SearXNG results
+2. **`/api/search`** → bypasses perplexity/refusal, queries SearXNG directly → summarizes via llama-server
+3. **`/v1/chat/completions`** → OpenAI-compatible for Continue.dev/IDE integration; FIM requests proxied without persistence
+4. **`/api/upload`** → multipart file upload, PDF/text extraction, `mode=(context|ingest|both)`, stores SQLite context (1hr expiry) + Qdrant upsert
+5. **`/api/ingest`** → Bearer token auth, programmatic RAG ingest (terminal hook, external tools)
+6. **`POST /api/image/generate`** → admin required, routes to an image-gen node via AMQP → ComfyUI workflow → returns PNG; `GET /api/image/status` lists available image gen nodes
+
+### Perplexity / auto-search
+
+The upstream request includes `"logprobs": true`. `parse_llama_stream_chunk()` extracts per-token logprobs from each chunk's `choices[0].logprobs.content[].logprob`. The `all_logprobs` list is populated during streaming, so `calculate_perplexity()` and `is_uncertain()` work correctly.
+
+### Auth / lockdown
+
+- Guest session by default (`POST /api/auth/guest`), admin unlock via 4-digit PIN (`POST /api/auth/login`)
+- Admin required for PUT/DELETE/PATCH + all POST except allowlist (`/api/chat`, `/api/search`, `/api/auth/*`)
+- `/api/ingest` is exempt from session auth — self-authenticates via Bearer token
+- IP allowlist, rate limiting, origin checking, payload size limits — all enforced in `app.py` middleware
+- Origin check applies to **all** `/api/` requests; returns `False` when both `Origin` and `Referer` are absent
+- `CAIC_ADMIN_PIN` env var required on first boot (or `CAIC_ALLOW_DEFAULT_PIN=true`)
+
+### Database
+
+- SQLite at `caic.db`, auto-created by `init_db()` on startup via FastAPI `lifespan`
+- `get_db()` opens new connection per request (no pool). Close after use.
+- FTS5 virtual table `memories` for full-text search with BM25 ranking.
+- `upload_context` table: auto-expiring document storage for chat context injection.
+
+### External services
+
+All services are available bare-metal or as containers in `docker compose up`.
+
+| Service | Required | Port | Docker service name |
+|---------|----------|------|---------------------|
+| llama-server (coordinator) | Yes | 8081 + RPC :50052 (worker GPU) | `llama-server` |
+| SearXNG | No | 8888 | `searxng` |
+| RabbitMQ (coordinator) | No | 5672 — AMQP broker | `rabbitmq` |
+| wttr.in | No | weather shortcut | — |
+| rocm-smi | No | AMD GPU stats | — |
+| Qdrant | No | 6333 (coordinator) — RAG vector search | `qdrant` |
+| Ollama (worker) | No | 11434 — embeddings + model pull | `ollama` |
+| ComfyUI (worker) | No | 8188 — image generation API | — |
+
+### Config quirks
+
+- `BODY_LIMIT_UPLOAD_BYTES` = 20MB for `/api/upload`; other paths use smaller limits
+- `SUPPORTED_UPLOAD_TYPES` includes images (png/jpeg/gif/svg/webp) + text + PDF + JSON
+- `UPLOAD_CONTEXT_EXPIRY_HOURS` = 1 hour
+- Rate limits and payload caps in `config.py` — patch `security.RL_*` not `config.RL_*` for tests
+- `COMFYUI_BASE` defaults to `http://localhost:8188` (overridable via `CAIC_COMFYUI_BASE`)
+- `COMFYUI_TIMEOUT` defaults to `120` seconds (overridable via `CAIC_COMFYUI_TIMEOUT`)
+- RAG embedding requests go to `EMBED_URL` at `/api/embeddings` (Ollama on worker :11434)
+
+### SSE Protocol
+
+All streaming endpoints yield `data: {json}\n\n`. Key shapes:
+- `{token, conversation_id}` — streaming token
+- `{searching: true}` — web search triggered
+- `{search_results: N}` — N results (no raw_results payload)
+- `{done: true, perplexity, tokens_per_sec, searched?}` — terminal
+- `{error: "...", error_key: "..."}` — error with incident key
+
+## Work State
+
+### Completed this session
+- **Pre-Docker review**: Full findings report delivered -- 30+ issues across 7 categories (hardcoded hosts/paths, config/secrets, AMQP gaps, resource cleanup, SQLite container safety, completions concurrency, TASKS.md accuracy).
+- **Project rename**: `jarvisChat` → **cAIc** ("cake") — swept remaining branding (router docstrings, jc-ingest.sh env var), deleted stale `AGENTS.md.local`.
+- **Single-node consolidation**: all services moved to jarvis (192.168.50.212) — `COMFYUI_BASE` default → `localhost:8188`, AMQP URL default → `localhost:5672`, `NODE_NAME` default → `jarvis`, `DEFAULT_PROFILE` topology rewritten, cluster/AMQP/node_agent left in place (degrades gracefully).
+- **Deprecation fix**: Replaced `asyncio.ensure_future` with `asyncio.create_task` in `rag.py` and `routers/chat.py`.
+- **Documentation**: Added inline comments and docstrings to all functions in `db.py`.
+- **Uninstall scripts**: Created and committed `scripts/uninstall.sh`, `teardown-docker.sh`, `nuclear-clean.sh`.
+- **README**: Added "Uninstalling cAIc" section.
+- **Docker containerization (B3)**: Created `Dockerfile`, `docker-compose.yml`, `.env.example`, `scripts/setup.sh`, `.dockerignore`, `searxng-settings.yml.dist`, `models/README.txt`. Fixed hardcoded defaults in `config.py` (localhost, Docker secrets path, `CAIC_DEFAULT_MODEL` env var, `CAIC_HW_STATE_PATH` env var). Added missing `psutil` + `jinja2` to `requirements.txt`. Fixed test discovery via `tests/conftest.py` sys.path insertion. 214 tests pass.
+
+### Active
+- Image generation service backend complete — cluster handlers, router proxy, node agent ComfyUI integration, hardware probe. 27 tests pass. ComfyUI install pending on jarvis (single-node).
+
+### Deployed (2026-08-07) — v1.1.0 to production
+- **Fixed crash-loop**: ultron `llama-server.service` had 911 restarts — its `--rpc 192.168.50.210:50052` pointed at a dead IP. Corrected to `192.168.50.212:50052` (jarvis GPU rpc-server). Model now loads, `/health` = ok.
+- **Deployed v1.1.0**: workspace repo synced to `/opt/jarvischat` (jarvischat.service cwd). caic.db + venv preserved; `aio-pika` installed into prod venv (was missing → AMQP disabled).
+- **Env fixes** (`/etc/systemd/system/jarvischat.service.d/override.conf`): added `LLAMA_SERVER_BASE=http://192.168.50.108:8081`, `CAIC_QDRANT_URL=http://192.168.50.108:6333`, `CAIC_COMPLETIONS_API_KEY` (was set as legacy `JARVISCHAT_` name), kept `CAIC_EMBED_URL=http://192.168.50.108:11434` + `CAIC_ADMIN_PIN=1319`. Wrote `/opt/jarvischat/.completions_key` (jc-ingest.sh).
+- **Deploy-blocking bug fixes** (uncommitted, workspace + deploy):
+  - `rag.py` `chunk_text`: chunk_size 512→200 (chunks exceeded mxbai-embed-large's 512-token context → ollama 500).
+  - Qdrant 1.18.2 rejects non-UUID point IDs: wrapped `ingest-*`/`auto-*`/`upload-*` string IDs in `uuid5` in `routers/ingest.py`, `rag.py`, `routers/upload.py`.
+  - `docs/jc-ingest.sh`: `JC_URL` updated `.210`→`.212`.
+- **Docs rebuilt**: 159 chunks (source `docs`) re-ingested via `/api/ingest` (README, ai.md, docker.md, CLAUDE.md, wiki/*). RAG now 378 vectors; chat verified injecting "Retrieved Context".
+- **Tests**: all 244 pass (run per-file in a throwaway venv; the full-suite run deadlocks on TestClient/AMQP ordering, not a code failure).
+
+### Follow-ups
+- AMQP wiring: cluster subs degrade gracefully — **moot in the single-node (jarvis) deployment** until a multi-node cluster is stood back up. Needs `CAIC_AMQP_URL` + credentials if that happens.
+- `CAIC_TRIAGE_BASE` set but triage not yet invoked by chat (config-only until TASK 2 wiring).
+
+### Blocked
+- Ball Gunner assets — waiting on Canva designs
+
+### Upcoming (backlog)
+- ~~B3 — Docker distribution~~ [DONE]
+
+### Key config values (current)
+- **Current VERSION**: `v1.1.0` in `config.py`.
+- `SESSION_TIMEOUT_SECONDS = 3600`
+- `DEFAULT_MODEL = "qwen2.5-7b-instruct"` (overridable via `CAIC_DEFAULT_MODEL`)
+- `LLAMA_SERVER_BASE = "http://localhost:8081"` (overridable via env var)

amqp.py

@@ -0,0 +1,142 @@
+"""
+cAIc — AMQP connection manager.
+Single persistent aio-pika connection with auto-reconnect.
+"""
+import asyncio
+import json
+import logging
+
+try:
+    import aio_pika
+    from aio_pika import DeliveryMode, ExchangeType
+    from aio_pika import RobustConnection, RobustChannel
+    HAS_AIO_PIKA = True
+except ImportError:
+    HAS_AIO_PIKA = False
+
+from config import (
+    AMQP_RECONNECT_DELAY,
+    AMQP_EXCHANGE_ADMIN,
+    AMQP_EXCHANGE_SYSTEM,
+    get_amqp_url,
+)
+
+log = logging.getLogger("caic")
+
+_connection = None
+_channel = None
+_lock = asyncio.Lock()
+_subscriptions = []  # list of (exchange, routing_keys, handler_fn)
+
+
+async def subscribe(exchange: str, routing_keys: list[str], handler) -> None:
+    """Subscribe to routing keys on an exchange.
+
+    Creates an exclusive anonymous queue bound to the given routing keys.
+    Handler receives (exchange, routing_key, payload_dict).
+    On reconnect: _rebind_subscriptions recreates all subscriptions.
+    """
+    if not HAS_AIO_PIKA:
+        log.warning("aio-pika not installed — cannot subscribe")
+        return
+    ch = await get_channel()
+    if ch is None:
+        log.error("cannot subscribe — no AMQP channel")
+        return
+    # Track subscription before attempting so reconnect catches it even if this try fails
+    _subscriptions.append((exchange, routing_keys, handler))
+    try:
+        queue = await ch.declare_queue("", exclusive=True)
+        ex = await ch.get_exchange(exchange)
+        for rk in routing_keys:
+            await queue.bind(ex, rk)
+
+        async def _dispatch(msg: aio_pika.IncomingMessage):
+            async with msg.process():
+                try:
+                    payload = json.loads(msg.body.decode())
+                    await handler(exchange, msg.routing_key, payload)
+                except Exception:
+                    log.exception("AMQP handler error for %s %s", exchange, msg.routing_key)
+
+        await queue.consume(_dispatch)
+    except Exception:
+        log.exception("AMQP subscribe failed for %s %s", exchange, routing_keys)
+
+
+async def _rebind_subscriptions() -> None:
+    """Re-create all subscriptions after reconnect."""
+    subs = list(_subscriptions)
+    _subscriptions.clear()
+    for exchange, routing_keys, handler in subs:
+        await subscribe(exchange, routing_keys, handler)
+    if subs:
+        log.info("AMQP subscriptions rebound")
+
+
+async def connect() -> None:
+    if not HAS_AIO_PIKA:
+        log.warning("aio-pika not installed — AMQP disabled")
+        return
+    async with _lock:
+        global _connection, _channel
+        if _connection and not _connection.is_closed:
+            return
+        url = get_amqp_url()
+        log.info("connecting to AMQP broker")
+        try:
+            conn = await aio_pika.connect_robust(url)
+        except Exception as exc:
+            log.warning("AMQP connection failed — %s", exc)
+            return
+        ch = await conn.channel()
+        for ex in (AMQP_EXCHANGE_ADMIN, AMQP_EXCHANGE_SYSTEM):
+            await ch.declare_exchange(ex, ExchangeType.TOPIC, durable=True)
+        _connection = conn
+        _channel = ch
+        await _rebind_subscriptions()
+        log.info("AMQP connected, exchanges declared")
+
+
+async def disconnect() -> None:
+    if not HAS_AIO_PIKA:
+        return
+    async with _lock:
+        global _connection, _channel
+        if _channel and not _channel.is_closed:
+            await _channel.close()
+        if _connection and not _connection.is_closed:
+            await _connection.close()
+        _channel = None
+        _connection = None
+        log.info("AMQP disconnected")
+
+
+async def get_channel():
+    if not HAS_AIO_PIKA:
+        return None
+    if _channel is None or _channel.is_closed:
+        log.warning("AMQP channel missing, attempting reconnect")
+        try:
+            await connect()
+        except Exception:
+            log.exception("AMQP reconnect failed")
+            return None
+    return _channel
+
+
+async def publish(exchange: str, routing_key: str, payload: dict) -> None:
+    if not HAS_AIO_PIKA:
+        log.error("cannot publish — aio-pika not installed")
+        return
+    ch = await get_channel()
+    if ch is None:
+        log.error("cannot publish — no AMQP channel available")
+        return
+    try:
+        body = json.dumps(payload).encode()
+        msg = aio_pika.Message(body, delivery_mode=DeliveryMode.PERSISTENT)
+        ex = await ch.get_exchange(exchange)
+        await ex.publish(msg, routing_key)
+    except Exception:
+        log.exception("AMQP publish failed")

app.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-JarvisChat - Entry point.
+cAIc - Entry point.
 Creates the FastAPI app, registers middleware, mounts all routers.
 """
 import logging
@@ -14,12 +14,15 @@ from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 from fastapi.templating import Jinja2Templates
 
-from config import VERSION, RATE_WINDOW_SECONDS, UPLOAD_DIR
-from db import init_db
+from amqp import connect as amqp_connect, disconnect as amqp_disconnect
+from cluster import start_cluster_subscriptions
+from config import VERSION, DEFAULT_MODEL, RATE_WINDOW_SECONDS, UPLOAD_DIR, RAG_MAX_VECTORS, RAG_EVICTION_HIGH_WATER, RAG_EVICTION_LOW_WATER, RAG_EVICTION_BATCH
+from db import init_db, get_db, get_setting
+from hardware import assess_hardware
 from memory import get_memory_count
 from security import (
     get_client_ip, is_ip_allowed, check_rate_limit, rate_policy,
-    origin_allowed, is_state_changing, request_body_limit,
+    origin_allowed, request_body_limit,
     audit_event, customer_error_envelope, log_incident,
 )
 from auth import get_session, is_admin_only, router as auth_router
@@ -34,13 +37,23 @@ import routers.chat as chat
 import routers.search_route as search_route
 import routers.completions as completions
 import routers.upload as upload
+import routers.ingest as ingest
+import routers.hardware as hardware
+import routers.rag_admin as rag_admin
+import routers.cluster as cluster_router
+import routers.image as image_router
 
 # --- Logging ---
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 log.setLevel(logging.DEBUG)
-syslog_handler = logging.handlers.SysLogHandler(address="/dev/log")
-syslog_handler.setFormatter(logging.Formatter("jarvischat[%(process)d]: %(levelname)s %(message)s"))
+syslog_address = os.environ.get("CAIC_SYSLOG_ADDRESS", "/dev/log")
+if syslog_address:
+    try:
+        syslog_handler = logging.handlers.SysLogHandler(address=syslog_address)
+        syslog_handler.setFormatter(logging.Formatter("caic[%(process)d]: %(levelname)s %(message)s"))
         log.addHandler(syslog_handler)
+    except Exception:
+        log.warning("syslog not available at %s -- skipping", syslog_address)
 
 BASE_DIR = Path(__file__).parent
 templates = Jinja2Templates(directory=str(BASE_DIR / "templates"))
@@ -48,15 +61,38 @@ templates = Jinja2Templates(directory=str(BASE_DIR / "templates"))
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    log.info(f"JarvisChat {VERSION} starting up")
+    log.info(f"cAIc {VERSION} starting up")
     os.makedirs(UPLOAD_DIR, exist_ok=True)
     init_db()
+    from crypto import ensure_key
+    ensure_key()
     log.info(f"Memory system: {get_memory_count()} memories loaded")
+    await assess_hardware()
+    from model_pull import ensure_model
+    _db = get_db()
+    _user_model = get_setting(_db, "default_model", DEFAULT_MODEL)
+    _db.close()
+    await ensure_model(_user_model)
+    await amqp_connect()
+    await start_cluster_subscriptions()
+
+    if RAG_MAX_VECTORS > 0:
+        if RAG_EVICTION_HIGH_WATER <= RAG_EVICTION_LOW_WATER:
+            log.warning(
+                f"RAG_EVICTION_HIGH_WATER={RAG_EVICTION_HIGH_WATER} <= "
+                f"RAG_EVICTION_LOW_WATER={RAG_EVICTION_LOW_WATER} — eviction will never fire"
+            )
+        if RAG_EVICTION_BATCH <= 0:
+            log.warning(f"RAG_EVICTION_BATCH={RAG_EVICTION_BATCH} clamped to 1")
+    else:
+        log.warning("RAG_MAX_VECTORS <= 0 — RAG eviction disabled")
+
     yield
-    log.info("JarvisChat shutting down")
+    log.info("cAIc shutting down")
+    await amqp_disconnect()
 
 
-app = FastAPI(title="JarvisChat", lifespan=lifespan)
+app = FastAPI(title="cAIc", lifespan=lifespan)
 
 
 @app.exception_handler(Exception)
@@ -102,10 +138,15 @@ async def session_auth_middleware(request: Request, call_next):
 
     unauth_paths = {
         "/api/auth/login", "/api/auth/logout", "/api/auth/session",
-        "/api/auth/heartbeat", "/api/auth/guest",
+        "/api/auth/heartbeat", "/api/auth/guest", "/api/ingest", "/api/hardware",
     }
 
-    if path.startswith("/api/"):
+    # Bearer-token-authenticated endpoints are reached by CLI/terminal tooling
+    # (curl, caic-ingest.sh) that sends no Origin/Referer header — exempt them
+    # from the browser origin check.
+    origin_exempt_paths = {"/api/ingest"}
+
+    if path.startswith("/api/") and path not in origin_exempt_paths:
         if not origin_allowed(request):
             audit_event("origin_check", "denied", ip=ip, role="none",
                         details=f"{request.method} {path}", warning=True)
@@ -141,11 +182,12 @@ async def index(request: Request):
 for router_module in [
     auth_router, conversations.router, memories.router, models.router,
     presets.router, profile.router, settings.router, skills.router,
-    chat.router, search_route.router, completions.router, upload.router,
+    chat.router, search_route.router, completions.router, upload.router, ingest.router, hardware.router,
+    rag_admin.router, cluster_router.router, image_router.router,
 ]:
     app.include_router(router_module)
 
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8080)
+    uvicorn.run(app, host=os.environ.get("CAIC_HOST", "0.0.0.0"), port=int(os.environ.get("CAIC_PORT", "8080")))

auth.py

@@ -1,5 +1,5 @@
 """
-JarvisChat - Auth: session management, PIN verification, middleware, auth routes.
+cAIc - Auth: session management, PIN verification, middleware, auth routes.
 """
 import hashlib
 import hmac
@@ -17,11 +17,11 @@ from db import get_db, get_setting
 from security import (
     SESSIONS, PIN_ATTEMPTS, SESSION_LOCK, BODY_LIMIT_DEFAULT_BYTES,
     audit_event, get_client_ip, is_ip_allowed, check_rate_limit,
-    rate_policy, origin_allowed, is_state_changing, request_body_limit,
+    rate_policy, origin_allowed, request_body_limit,
     read_json_body, hash_pin, customer_error_envelope, log_incident,
 )
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 

cluster.py

@@ -0,0 +1,327 @@
+"""
+cAIc — Cluster protocol implementation.
+Maintains node registry, event log, coordinator state, and ping-based health checks.
+"""
+import asyncio
+import logging
+import os
+import uuid
+from collections import deque
+from datetime import datetime, timezone
+
+from amqp import publish, subscribe
+from config import AMQP_EXCHANGE_ADMIN, AMQP_EXCHANGE_SYSTEM
+
+log = logging.getLogger("caic")
+
+CLUSTER_NODES: dict[str, dict] = {}
+CLUSTER_EVENTS: deque = deque(maxlen=1000)
+CLUSTER_COORDINATOR: str | None = None
+_pending_pings: dict[str, tuple[str, asyncio.Event]] = {}
+_pending_image: dict[str, tuple[str, asyncio.Event]] = {}
+NODE_NAME: str = os.environ.get("CAIC_NODE_NAME", "jarvis")
+PING_TIMEOUT: float = 5.0
+
+
+def _push_event(category: str, severity: str, node_name: str | None, message: str, details: dict | None = None) -> dict:
+    record = {
+        "category": category,
+        "severity": severity,
+        "node": node_name,
+        "message": message,
+        "details": details or {},
+        "timestamp": datetime.now(timezone.utc).isoformat() + "Z",
+    }
+    CLUSTER_EVENTS.append(record)
+    level = {"info": logging.INFO, "warn": logging.WARNING, "error": logging.ERROR, "critical": logging.CRITICAL}.get(severity, logging.INFO)
+    log.log(level, "[cluster] %s: %s", node_name or "system", message)
+    return record
+
+
+async def handle_registration(exchange: str, routing_key: str, payload: dict) -> None:
+    global CLUSTER_COORDINATOR
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    node_type = payload.get("node_type", "worker")
+
+    if node_name in CLUSTER_NODES:
+        _push_event("cluster", "warn", node_name, "Duplicate registration rejected")
+        await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.rejected", {
+            "from": NODE_NAME, "node_name": node_name, "type": "rejected",
+            "reason": "duplicate_node_name",
+            "timestamp": datetime.now(timezone.utc).isoformat() + "Z",
+        })
+        return
+
+    if "node_type" not in payload or "capabilities" not in payload:
+        _push_event("cluster", "warn", node_name, "Malformed registration rejected")
+        await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.rejected", {
+            "from": NODE_NAME, "node_name": node_name, "type": "rejected",
+            "reason": "malformed_payload",
+            "timestamp": datetime.now(timezone.utc).isoformat() + "Z",
+        })
+        return
+
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    node = {
+        "name": node_name,
+        "type": node_type,
+        "status": "active",
+        "ip": payload.get("ip"),
+        "capabilities": payload.get("capabilities", []),
+        "active_model": payload.get("active_model"),
+        "inventory": payload.get("inventory", []),
+        "load": payload.get("load"),
+        "registered_at": now,
+        "last_seen": now,
+    }
+    CLUSTER_NODES[node_name] = node
+    _push_event("cluster", "info", node_name, f"Node registered (type={node_type})")
+
+    await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.admitted", {
+        "from": NODE_NAME, "node_name": node_name, "type": "admitted",
+        "coordinator": CLUSTER_COORDINATOR,
+        "timestamp": now,
+    })
+
+    if node_type == "coordinator" and CLUSTER_COORDINATOR is None:
+        CLUSTER_COORDINATOR = node_name
+        _push_event("cluster", "info", node_name, "Elected as coordinator")
+        await publish(AMQP_EXCHANGE_SYSTEM, "cluster.coordinator.response", {
+            "from": NODE_NAME, "type": "coord_response",
+            "coordinator": node_name, "nodes": list(CLUSTER_NODES.keys()),
+            "timestamp": now,
+        })
+
+
+async def handle_deregistration(exchange: str, routing_key: str, payload: dict) -> None:
+    global CLUSTER_COORDINATOR
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+
+    removed = CLUSTER_NODES.pop(node_name, None)
+    if not removed:
+        log.warning("[cluster] deregistration for unknown node %s", node_name)
+        return
+
+    _push_event("cluster", "info", node_name, "Node deregistered")
+
+    if CLUSTER_COORDINATOR == node_name:
+        CLUSTER_COORDINATOR = None
+        _push_event("cluster", "warn", node_name, "Coordinator deregistered — no coordinator active")
+
+
+async def handle_pong(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    correlation_id = payload.get("correlation_id")
+
+    if correlation_id and correlation_id in _pending_pings:
+        _, event = _pending_pings.pop(correlation_id)
+        event.set()
+
+    if node_name in CLUSTER_NODES:
+        now = datetime.now(timezone.utc).isoformat() + "Z"
+        CLUSTER_NODES[node_name]["last_seen"] = now
+        if "status" in payload:
+            CLUSTER_NODES[node_name]["status"] = payload["status"]
+        if "active_model" in payload:
+            CLUSTER_NODES[node_name]["active_model"] = payload["active_model"]
+        if "load" in payload:
+            CLUSTER_NODES[node_name]["load"] = payload["load"]
+    else:
+        log.warning("[cluster] pong from unknown node %s", node_name)
+
+
+async def handle_event(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    severity = payload.get("severity", "info")
+    message = payload.get("message", "")
+    details = payload.get("details")
+    _push_event("application", severity, node_name, message, details)
+
+
+async def handle_coordinator_query(exchange: str, routing_key: str, payload: dict) -> None:
+    if CLUSTER_COORDINATOR is None:
+        return
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    await publish(AMQP_EXCHANGE_SYSTEM, "cluster.coordinator.response", {
+        "from": NODE_NAME, "type": "coord_response",
+        "coordinator": CLUSTER_COORDINATOR,
+        "nodes": list(CLUSTER_NODES.keys()),
+        "timestamp": now,
+    })
+
+
+async def ping_node(node_name: str) -> bool:
+    global CLUSTER_COORDINATOR
+    if node_name not in CLUSTER_NODES:
+        return False
+
+    correlation_id = str(uuid.uuid4())
+    event = asyncio.Event()
+    _pending_pings[correlation_id] = (node_name, event)
+
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.ping", {
+        "from": NODE_NAME, "node_name": node_name, "type": "ping",
+        "correlation_id": correlation_id, "timestamp": now,
+    })
+
+    try:
+        await asyncio.wait_for(event.wait(), timeout=PING_TIMEOUT)
+        return True
+    except asyncio.TimeoutError:
+        _pending_pings.pop(correlation_id, None)
+        CLUSTER_NODES.pop(node_name, None)
+        _push_event("cluster", "warn", node_name, "Node unresponsive — deregistered after ping timeout")
+        if CLUSTER_COORDINATOR == node_name:
+            CLUSTER_COORDINATOR = None
+            _push_event("cluster", "warn", node_name, "Coordinator unresponsive — no coordinator active")
+        return False
+
+
+async def request_model_swap(node_name: str, model_filename: str) -> bool:
+    """Request a worker node to swap its active model."""
+    if node_name not in CLUSTER_NODES:
+        log.warning("request_model_swap: unknown node %s", node_name)
+        return False
+
+    CLUSTER_NODES[node_name]["status"] = "swapping"
+    _push_event("cluster", "info", node_name, f"Model swap requested: {model_filename}")
+
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.cmd.swap_model", {
+        "model_filename": model_filename,
+        "requested_at": now,
+    })
+    return True
+
+
+async def handle_model_ready(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    model_filename = payload.get("active_model")
+    port = payload.get("port", 8081)
+
+    if node_name not in CLUSTER_NODES:
+        log.warning("handle_model_ready: unknown node %s", node_name)
+        return
+
+    inventory = CLUSTER_NODES[node_name].get("inventory") or []
+    model_info = None
+    for inv in inventory:
+        if inv.get("filename") == model_filename:
+            model_info = {**inv, "port": port}
+            break
+    if model_info is None:
+        model_info = {"filename": model_filename, "port": port}
+
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    CLUSTER_NODES[node_name]["active_model"] = model_info
+    CLUSTER_NODES[node_name]["status"] = "active"
+    CLUSTER_NODES[node_name]["last_seen"] = now
+    _push_event("cluster", "info", node_name, f"Model swap complete: {model_filename}")
+
+
+async def handle_heartbeat(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    if node_name not in CLUSTER_NODES:
+        log.warning("heartbeat from unknown node %s — ignore, full registration required", node_name)
+        return
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    CLUSTER_NODES[node_name]["last_seen"] = now
+
+
+async def handle_model_failed(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    error = payload.get("error", "unknown error")
+
+    if node_name not in CLUSTER_NODES:
+        log.warning("handle_model_failed: unknown node %s", node_name)
+        return
+
+    CLUSTER_NODES[node_name]["status"] = "error"
+    _push_event("cluster", "error", node_name, f"Model swap failed: {error}")
+
+
+async def handle_image_generated(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    request_id = payload.get("request_id")
+
+    if request_id and request_id in _pending_image:
+        _, event = _pending_image.pop(request_id)
+        _pending_image[request_id] = (payload.get("image_base64", ""), event)
+        event.set()
+
+    if node_name in CLUSTER_NODES:
+        CLUSTER_NODES[node_name]["last_seen"] = datetime.now(timezone.utc).isoformat() + "Z"
+
+
+async def handle_image_failed(exchange: str, routing_key: str, payload: dict) -> None:
+    node_name = payload.get("node_name", routing_key.split(".")[1] if "." in routing_key else "unknown")
+    request_id = payload.get("request_id")
+    error = payload.get("error", "unknown error")
+
+    if request_id and request_id in _pending_image:
+        _pending_image[request_id] = ("", _pending_image[request_id][1])
+        _pending_image[request_id][1].set()
+
+    _push_event("application", "error", node_name, f"Image generation failed: {error}")
+
+
+async def request_image_generate(
+    node_name: str, prompt: str, negative_prompt: str = "",
+    width: int = 1024, height: int = 1024, steps: int = 20,
+    seed: int = -1, model: str = "", timeout: float = 120,
+) -> str | None:
+    if node_name not in CLUSTER_NODES:
+        log.warning("request_image_generate: unknown node %s", node_name)
+        return None
+
+    caps = CLUSTER_NODES[node_name].get("capabilities", [])
+    if "image_gen" not in caps:
+        log.warning("request_image_generate: node %s lacks image_gen capability", node_name)
+        return None
+
+    request_id = str(uuid.uuid4())
+    event = asyncio.Event()
+    _pending_image[request_id] = ("", event)
+
+    now = datetime.now(timezone.utc).isoformat() + "Z"
+    _push_event("application", "info", node_name, f"Image generation requested: {prompt[:60]}...")
+
+    await publish(AMQP_EXCHANGE_ADMIN, f"node.{node_name}.cmd.image_generate", {
+        "from": NODE_NAME, "type": "image_generate",
+        "request_id": request_id,
+        "prompt": prompt,
+        "negative_prompt": negative_prompt,
+        "width": width, "height": height,
+        "steps": steps, "seed": seed, "model": model,
+        "timestamp": now,
+    })
+
+    try:
+        await asyncio.wait_for(event.wait(), timeout=timeout)
+        result = _pending_image.pop(request_id, (None, None))
+        return result[0]
+    except asyncio.TimeoutError:
+        _pending_image.pop(request_id, None)
+        _push_event("application", "warn", node_name, "Image generation timed out")
+        return None
+
+
+SUBSCRIBE_TABLE = [
+    (AMQP_EXCHANGE_ADMIN, ["node.*.register"], handle_registration),
+    (AMQP_EXCHANGE_ADMIN, ["node.*.deregister"], handle_deregistration),
+    (AMQP_EXCHANGE_ADMIN, ["node.*.pong"], handle_pong),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.event"], handle_event),
+    (AMQP_EXCHANGE_SYSTEM, ["cluster.coordinator.query"], handle_coordinator_query),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.heartbeat"], handle_heartbeat),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.model_ready"], handle_model_ready),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.model_failed"], handle_model_failed),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.image_generated"], handle_image_generated),
+    (AMQP_EXCHANGE_SYSTEM, ["node.*.image_failed"], handle_image_failed),
+]
+
+
+async def start_cluster_subscriptions() -> None:
+    for exchange, routing_keys, handler in SUBSCRIBE_TABLE:
+        await subscribe(exchange, routing_keys, handler)
+    log.info("cluster subscriptions started")

config.py

@@ -1,37 +1,61 @@
 """
-JarvisChat - Central configuration.
+cAIc - Central configuration.
 All constants, environment variables, limits, and skill registry live here.
 """
 import os
 import re
 import ipaddress
 import logging
+from pathlib import Path
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
-VERSION = "v1.10.0"
+VERSION = "v1.1.0"
 OLLAMA_BASE = os.environ.get("OLLAMA_BASE", "http://localhost:11434")
-LLAMA_SERVER_BASE = os.environ.get("LLAMA_SERVER_BASE", "http://192.168.50.108:8081")
-SEARXNG_BASE = "http://localhost:8888"
-DEFAULT_MODEL = "llama3.1:latest"
-COMPLETIONS_API_KEY = os.environ.get("JARVISCHAT_COMPLETIONS_API_KEY", "jc-sk-" + os.urandom(24).hex())
+LLAMA_SERVER_BASE = os.environ.get("LLAMA_SERVER_BASE", "http://localhost:8081")
+SEARXNG_BASE = os.environ.get("CAIC_SEARXNG_BASE", "http://localhost:8888")
+DEFAULT_MODEL = os.environ.get("CAIC_DEFAULT_MODEL", "qwen2.5-7b-instruct")
+COMPLETIONS_API_KEY = os.environ.get("CAIC_COMPLETIONS_API_KEY", "caic-sk-" + os.urandom(24).hex())
+MODEL_CONTEXT_LENGTH = 4096
+
+# --- AMQP ---
+AMQP_RECONNECT_DELAY = 5
+AMQP_EXCHANGE_ADMIN = "jc.admin"
+AMQP_EXCHANGE_SYSTEM = "jc.system"
+AMQP_SECRET_PATH = os.environ.get("CAIC_AMQP_SECRET_PATH", "/run/secrets/caic_amqp_secret")
+
+def get_amqp_url() -> str:
+    url = os.environ.get("CAIC_AMQP_URL")
+    if url:
+        return url
+    try:
+        with open(AMQP_SECRET_PATH) as f:
+            pw = f.read().strip()
+    except (FileNotFoundError, OSError):
+        pw = "password"
+        log.warning("AMQP secret file not found at %s — using default password", AMQP_SECRET_PATH)
+    return f"amqp://caic:{pw}@localhost:5672/caic"
 
 # --- Auth ---
-SESSION_TIMEOUT_SECONDS = 90
+SESSION_TIMEOUT_SECONDS = 3600
 MAX_PIN_ATTEMPTS = 5
 PIN_LOCKOUT_SECONDS = 300
-ALLOW_DEFAULT_PIN = os.getenv("JARVISCHAT_ALLOW_DEFAULT_PIN", "false").lower() == "true"
+ALLOW_DEFAULT_PIN = os.getenv("CAIC_ALLOW_DEFAULT_PIN", "false").lower() == "true"
 TRUSTED_ORIGINS = {
     origin.strip().rstrip("/")
-    for origin in os.getenv("JARVISCHAT_TRUSTED_ORIGINS", "").split(",")
+    for origin in os.getenv("CAIC_TRUSTED_ORIGINS", "").split(",")
     if origin.strip()
 }
 DEFAULT_ALLOWED_CIDRS = "127.0.0.0/8,::1/128,10.0.0.0/8,172.16.0.0/12,192.168.0.0/16"
-ALLOWED_CIDRS_RAW = os.getenv("JARVISCHAT_ALLOWED_CIDRS", DEFAULT_ALLOWED_CIDRS)
+ALLOWED_CIDRS_RAW = os.getenv("CAIC_ALLOWED_CIDRS", DEFAULT_ALLOWED_CIDRS)
 TRUST_X_FORWARDED_FOR = (
-    os.getenv("JARVISCHAT_TRUST_X_FORWARDED_FOR", "false").lower() == "true"
+    os.getenv("CAIC_TRUST_X_FORWARDED_FOR", "false").lower() == "true"
 )
 
+# --- Image generation (ComfyUI) ---
+COMFYUI_BASE = os.environ.get("CAIC_COMFYUI_BASE", "http://localhost:8188")
+COMFYUI_TIMEOUT = int(os.environ.get("CAIC_COMFYUI_TIMEOUT", "120"))
+
 # --- Rate limits ---
 RATE_WINDOW_SECONDS = 60
 RL_LOGIN_PER_WINDOW = 10
@@ -47,12 +71,25 @@ BODY_LIMIT_CHAT_BYTES = 128 * 1024
 BODY_LIMIT_PROFILE_BYTES = 256 * 1024
 
 # --- Upload ---
-UPLOAD_DIR = "/tmp/jarvischat_uploads"
+UPLOAD_DIR = os.environ.get("CAIC_UPLOAD_DIR", "/tmp/caic_uploads")
 MAX_UPLOAD_BYTES = 20 * 1024 * 1024
 SUPPORTED_UPLOAD_TYPES = {"text/plain", "text/markdown", "application/pdf", "application/json", "text/x-python", "text/html", "image/png", "image/jpeg", "image/gif", "image/svg+xml", "image/webp"}
+QDRANT_URL = os.environ.get("CAIC_QDRANT_URL", "http://localhost:6333")
+RAG_COLLECTION = os.environ.get("CAIC_RAG_COLLECTION", "caic_rag")
 UPLOAD_CONTEXT_EXPIRY_HOURS = 1
 BODY_LIMIT_UPLOAD_BYTES = MAX_UPLOAD_BYTES
 
+# --- RAG eviction ---
+RAG_MAX_VECTORS = int(os.environ.get("CAIC_RAG_MAX_VECTORS", "50000"))
+HW_STATE_PATH = os.environ.get("CAIC_HW_STATE_PATH", str(Path(__file__).parent / "hardware_state.json"))
+RAG_EVICTION_HIGH_WATER = 0.80
+RAG_EVICTION_LOW_WATER = 0.20
+RAG_EVICTION_BATCH = 1000
+RAG_PINNED_SOURCES = ["upload", "profile"]
+RAG_GRACE_HOURS = 1
+RAG_ACCESS_WEIGHT = 1.0
+RAG_AGE_WEIGHT = 0.1
+
 MAX_CHAT_MESSAGE_CHARS = 8000
 MAX_SEARCH_QUERY_CHARS = 500
 MAX_PROFILE_CHARS = 32000
@@ -73,6 +110,11 @@ ALLOWED_SETTINGS_KEYS = {
     "skills_enabled",
 }
 
+# --- Triage / query routing ---
+TRIAGE_BASE = os.environ.get("CAIC_TRIAGE_BASE", "http://127.0.0.1:8083/v1")
+TRIAGE_TIMEOUT = 10
+FALLBACK_TO_DEFAULT = True
+
 # --- Perplexity ---
 PERPLEXITY_THRESHOLD = 15.0
 
@@ -137,12 +179,10 @@ ALLOWED_NETWORKS = parse_allowed_cidrs(ALLOWED_CIDRS_RAW)
 DEFAULT_PROFILE = """You are a coding companion running locally on a machine called "jarvis".
 
 ## Environment
-- jarvis: Debian 13 (trixie) x86_64, AMD Ryzen 5 5600X, 16GB RAM, AMD RX 6600 XT (8GB VRAM)
-- ultron: Debian 13, Ryzen 7 7840HS, 16GB RAM, primary AI inference node, IP 192.168.50.108
-- Corsair: Windows 11, gaming/streaming rig, RTX 5070 Ti
+- jarvis: Debian 13 (trixie) x86_64, AMD Ryzen 5 5600X, 16GB RAM, AMD RX 6600 XT (8GB VRAM), IP 192.168.50.212
+- Single-node deployment — all cAIc services run on jarvis: llama-server :8081 (OpenAI-compat API), Qdrant :6333, Ollama :11434, SearXNG :8888, RabbitMQ :5672, ComfyUI :8188
 - pivault: RPi 5, 8GB RAM, Debian 13, 11TB RAID5 NAS at /mnt/pivault, IP 192.168.50.158
 - Router: ASUS ROG Rapture GT-BE98 Pro "BigBlinkyRouter" at 192.168.50.1
-- llama-server on ultron:8081 (OpenAI-compat API), Qdrant on ultron:6333
 
 ## About the User
 - Experienced developer, BS in Computer Science (Oklahoma State), coding since 1981 (TRS-80)

crypto.py

@@ -0,0 +1,78 @@
+"""
+cAIc — Storage encryption layer.
+AES-256-GCM for all user-query-derived text content.
+Key stored in settings table as a non-obvious key name.
+"""
+import base64
+import logging
+import os
+
+from cryptography.hazmat.primitives.ciphers.aead import AESGCM
+
+log = logging.getLogger("caic")
+
+SETTINGS_KEY = "heartbeat_interval_ms"
+
+
+def _load_key() -> bytes | None:
+    from db import get_db
+    db = get_db()
+    row = db.execute("SELECT value FROM settings WHERE key = ?", (SETTINGS_KEY,)).fetchone()
+    db.close()
+    if row:
+        return base64.b64decode(row["value"])
+    return None
+
+
+def _store_key(key: bytes) -> None:
+    from db import get_db
+    db = get_db()
+    b64 = base64.b64encode(key).decode()
+    db.execute("INSERT OR REPLACE INTO settings (key, value) VALUES (?, ?)", (SETTINGS_KEY, b64))
+    db.commit()
+    db.close()
+
+
+def ensure_key() -> bytes:
+    key = _load_key()
+    if key is not None:
+        return key
+    key = AESGCM.generate_key(bit_length=256)
+    _store_key(key)
+    log.info("storage encryption key generated")
+    return key
+
+
+def encrypt(plaintext: str) -> str:
+    if not plaintext:
+        return plaintext
+    key = ensure_key()
+    aesgcm = AESGCM(key)
+    nonce = os.urandom(12)
+    ct = aesgcm.encrypt(nonce, plaintext.encode(), None)
+    return base64.b64encode(nonce + ct).decode()
+
+
+def decrypt(cipherb64: str) -> str:
+    if not cipherb64:
+        return cipherb64
+    try:
+        key = ensure_key()
+        data = base64.b64decode(cipherb64)
+        nonce, ct = data[:12], data[12:]
+        aesgcm = AESGCM(key)
+        return aesgcm.decrypt(nonce, ct, None).decode()
+    except Exception:
+        return cipherb64
+
+
+def encrypt_text(value: str | None) -> str | None:
+    if value is None:
+        return None
+    return encrypt(value)
+
+
+def decrypt_text(value: str | None) -> str | None:
+    if value is None:
+        return None
+    return decrypt(value)

db.py

@@ -1,5 +1,5 @@
 """
-JarvisChat - Database layer.
+cAIc - Database layer.
 Schema init, connection factory, settings helpers, skill state management.
 """
 import logging
@@ -15,26 +15,33 @@ from config import (
     BUILTIN_SKILLS, DEFAULT_MODEL, DEFAULT_PRESETS, DEFAULT_PROFILE,
     MAX_SKILL_PROMPT_CHARS, ALLOWED_NETWORKS,
 )
+from crypto import encrypt_text, decrypt_text
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
 BASE_DIR = Path(__file__).parent
-DB_PATH = BASE_DIR / "jarvischat.db"
+DB_PATH = Path(os.environ.get("CAIC_DB_PATH", str(BASE_DIR / "caic.db")))
 
 
 def get_db():
+    """Return a new SQLite connection. Each call creates a fresh connection
+    (not pooled) so callers must close() when done."""
     conn = sqlite3.connect(DB_PATH)
     conn.row_factory = sqlite3.Row
     conn.execute("PRAGMA foreign_keys = ON")
+    conn.execute("PRAGMA journal_mode = WAL")
+    conn.execute("PRAGMA busy_timeout = 5000")
     return conn
 
 
 def get_setting(db, key: str, default: str = "") -> str:
+    """Read a single settings row, returning *default* if the key is missing."""
     row = db.execute("SELECT value FROM settings WHERE key = ?", (key,)).fetchone()
     return row["value"] if row else default
 
 
 def list_skills_with_state(db) -> list:
+    """Merge built-in skill definitions with per-skill enabled/disabled state from the DB."""
     rows = db.execute("SELECT skill_key, enabled, updated_at FROM skills").fetchall()
     state_by_key = {
         row["skill_key"]: {"enabled": bool(row["enabled"]), "updated_at": row["updated_at"]}
@@ -48,6 +55,7 @@ def list_skills_with_state(db) -> list:
 
 
 def set_skill_enabled(db, skill_key: str, enabled: bool) -> None:
+    """Insert or replace a skill's enabled state (UPSERT)."""
     now = datetime.now(timezone.utc).isoformat()
     db.execute(
         "INSERT OR REPLACE INTO skills (skill_key, enabled, updated_at) VALUES (?, ?, ?)",
@@ -56,6 +64,7 @@ def set_skill_enabled(db, skill_key: str, enabled: bool) -> None:
 
 
 def format_active_skills_prompt(skills: list) -> str:
+    """Build the 'Active Skills' section of the system prompt from the provided skill list."""
     lines = [
         "## Active Skills",
         "Use these skills only when needed. Prefer concise answers over unnecessary tool usage.",
@@ -69,15 +78,17 @@ def format_active_skills_prompt(skills: list) -> str:
 
 
 def insert_upload_context(db, conversation_id: str, filename: str, content: str, expires_at: str, content_type: str = "text/plain") -> int:
+    """Persist an upload context entry (encrypted content) tied to a conversation."""
     now = datetime.now(timezone.utc).isoformat()
     cur = db.execute(
         "INSERT INTO upload_context (conversation_id, filename, content, content_type, created_at, expires_at) VALUES (?, ?, ?, ?, ?, ?)",
-        (conversation_id, filename, content, content_type, now, expires_at),
+        (conversation_id, filename, encrypt_text(content), content_type, now, expires_at),
     )
     return cur.lastrowid
 
 
 def list_upload_context_by_conversation(db, conversation_id: str):
+    """Return all upload contexts for a given conversation (content excluded for brevity)."""
     rows = db.execute(
         "SELECT id, conversation_id, filename, content_type, created_at, expires_at FROM upload_context WHERE conversation_id = ? ORDER BY id ASC",
         (conversation_id,),
@@ -86,11 +97,16 @@ def list_upload_context_by_conversation(db, conversation_id: str):
 
 
 def delete_upload_context_by_id(db, context_id: int) -> bool:
+    """Delete an upload context entry, returning True if a row was actually removed."""
     cur = db.execute("DELETE FROM upload_context WHERE id = ?", (context_id,))
     return cur.rowcount > 0
 
 
 def get_upload_context(db, context_id: int):
+    """Fetch a single upload context, returning its decrypted content.
+
+    If the context has expired (past expires_at), it is deleted and None returned.
+    """
     row = db.execute(
         "SELECT id, conversation_id, filename, content, content_type, expires_at FROM upload_context WHERE id = ?",
         (context_id,),
@@ -102,14 +118,25 @@ def get_upload_context(db, context_id: int):
         db.execute("DELETE FROM upload_context WHERE id = ?", (context_id,))
         db.commit()
         return None
-    return dict(row)
+    d = dict(row)
+    d["content"] = decrypt_text(d["content"])
+    return d
 
 
 def init_db():
+    """Run initial schema creation and seed default data.
+
+    Idempotent — safe to call on every startup. Creates tables if missing,
+    runs ALTER TABLE to add columns that may not exist on legacy databases,
+    and inserts defaults for profile, presets, settings, skills, and admin PIN.
+    """
     from security import hash_pin
     conn = sqlite3.connect(DB_PATH)
     conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA journal_mode = WAL")
+    conn.execute("PRAGMA busy_timeout = 5000")
 
+    # --- Core tables ---
     conn.execute("""
         CREATE TABLE IF NOT EXISTS conversations (
             id TEXT PRIMARY KEY, title TEXT NOT NULL DEFAULT 'New Chat',
@@ -120,6 +147,7 @@ def init_db():
         CREATE TABLE IF NOT EXISTS messages (
             id INTEGER PRIMARY KEY AUTOINCREMENT, conversation_id TEXT NOT NULL,
             role TEXT NOT NULL, content TEXT NOT NULL, created_at TEXT NOT NULL,
+            perplexity REAL,
             FOREIGN KEY (conversation_id) REFERENCES conversations(id) ON DELETE CASCADE
         )
     """)
@@ -140,6 +168,7 @@ def init_db():
             skill_key TEXT PRIMARY KEY, enabled INTEGER NOT NULL DEFAULT 1, updated_at TEXT NOT NULL
         )
     """)
+    # FTS5 virtual table for full-text memory search
     conn.execute("""
         CREATE VIRTUAL TABLE IF NOT EXISTS memories USING fts5(
             fact, topic, source, created_at UNINDEXED
@@ -156,11 +185,18 @@ def init_db():
             expires_at TEXT NOT NULL
         )
     """)
+
+    # --- Backfill columns for legacy databases (safe to run every time) ---
     try:
         conn.execute("ALTER TABLE upload_context ADD COLUMN content_type TEXT DEFAULT 'text/plain'")
+    except Exception:
+        pass  # column already exists
+    try:
+        conn.execute("ALTER TABLE messages ADD COLUMN perplexity REAL")
     except Exception:
         pass
 
+    # --- Seed default data (only if tables are empty) ---
     if not conn.execute("SELECT id FROM profile WHERE id = 1").fetchone():
         now = datetime.now(timezone.utc).isoformat()
         conn.execute("INSERT INTO profile (id, content, updated_at) VALUES (1, ?, ?)", (DEFAULT_PROFILE, now))
@@ -186,19 +222,22 @@ def init_db():
         if not conn.execute("SELECT skill_key FROM skills WHERE skill_key = ?", (skill["key"],)).fetchone():
             conn.execute("INSERT INTO skills (skill_key, enabled, updated_at) VALUES (?, 1, ?)", (skill["key"], now))
 
+    # --- Admin PIN bootstrap ---
+    # If no PIN hash exists on disk, seed one from env var CAIC_ADMIN_PIN
+    # or, if CAIC_ALLOW_DEFAULT_PIN=true, from the hardcoded default "1234".
     existing_pin_hash = conn.execute("SELECT value FROM settings WHERE key = 'admin_pin_hash'").fetchone()
     existing_pin_salt = conn.execute("SELECT value FROM settings WHERE key = 'admin_pin_salt'").fetchone()
     if not existing_pin_hash or not existing_pin_salt:
         from config import ALLOW_DEFAULT_PIN
-        configured_pin = os.getenv("JARVISCHAT_ADMIN_PIN", "").strip()
+        configured_pin = os.getenv("CAIC_ADMIN_PIN", "").strip()
         if re.fullmatch(r"\d{4}", configured_pin):
             seed_pin, pin_source = configured_pin, "env"
         elif ALLOW_DEFAULT_PIN:
             seed_pin, pin_source = "1234", "default"
         else:
             raise RuntimeError(
-                "Admin PIN bootstrap blocked: set JARVISCHAT_ADMIN_PIN to a 4-digit PIN "
-                "or set JARVISCHAT_ALLOW_DEFAULT_PIN=true."
+                "Admin PIN bootstrap blocked: set CAIC_ADMIN_PIN to a 4-digit PIN "
+                "or set CAIC_ALLOW_DEFAULT_PIN=true."
             )
         salt_hex, pin_hash_hex = hash_pin(seed_pin)
         conn.execute("INSERT OR REPLACE INTO settings (key, value) VALUES (?, ?)", ("admin_pin_hash", pin_hash_hex))

docker-compose.yml

@@ -0,0 +1,118 @@
+# cAIc — Docker Compose stack
+# Coordinator: cAIc + SearXNG + Qdrant + RabbitMQ + llama-server + Ollama
+#
+# Usage:
+#   cp .env.example .env    # edit with your values
+#   mkdir -p models secrets searxng
+#   # place .gguf model in ./models/
+#   docker compose up -d
+
+services:
+  # ── cAIc (FastAPI) ──────────────────────────────────────
+  caic:
+    build: .
+    ports:
+      - "${CAIC_EXPOSE_PORT:-8080}:8080"
+    volumes:
+      - caic_data:/app/data
+    secrets:
+      - rabbitmq_password
+    environment:
+      - CAIC_AMQP_SECRET_PATH=/run/secrets/rabbitmq_password
+      - CAIC_COMFYUI_BASE=${CAIC_COMFYUI_BASE:-http://localhost:8188}
+      - CAIC_COMFYUI_TIMEOUT=${CAIC_COMFYUI_TIMEOUT:-120}
+    env_file: .env
+    depends_on:
+      qdrant:        { condition: service_started }
+      rabbitmq:      { condition: service_healthy }
+      llama-server:  { condition: service_healthy }
+    restart: unless-stopped
+
+  # ── SearXNG (web search) ────────────────────────────────
+  searxng:
+    image: searxng/searxng:latest
+    ports:
+      - "${SEARXNG_EXPOSE_PORT:-8888}:8080"
+    volumes:
+      - ./searxng/settings.yml:/etc/searxng/settings.yml:ro
+      - searxng_config:/etc/searxng
+    environment:
+      - SEARXNG_BASE_URL=http://localhost:8888
+    restart: unless-stopped
+
+  # ── Qdrant (vector DB) ──────────────────────────────────
+  qdrant:
+    image: qdrant/qdrant:latest
+    ports:
+      - "${QDRANT_EXPOSE_PORT:-6333}:6333"
+    volumes:
+      - qdrant_storage:/qdrant/storage
+    restart: unless-stopped
+
+  # ── RabbitMQ (AMQP broker) ──────────────────────────────
+  rabbitmq:
+    image: rabbitmq:4-management
+    ports:
+      - "${RABBITMQ_EXPOSE_PORT:-5672}:5672"
+    volumes:
+      - rabbitmq_data:/var/lib/rabbitmq
+    environment:
+      RABBITMQ_DEFAULT_USER: caic
+      RABBITMQ_DEFAULT_PASS_FILE: /run/secrets/rabbitmq_password
+      RABBITMQ_DEFAULT_VHOST: /
+    secrets:
+      - rabbitmq_password
+    healthcheck:
+      test: ["CMD", "rabbitmq-diagnostics", "check_port_connectivity"]
+      interval: 15s
+      timeout: 5s
+      retries: 3
+    restart: unless-stopped
+
+  # ── llama-server (LLM inference) ────────────────────────
+  llama-server:
+    image: ghcr.io/ggml-org/llama.cpp:server
+    ports:
+      - "${LLAMA_EXPOSE_PORT:-8081}:8081"
+    volumes:
+      - ./models:/models:ro
+    command: >
+      --model /models/${LLAMA_MODEL:?Set LLAMA_MODEL in .env}
+      --host 0.0.0.0 --port 8081
+      --ctx-size ${LLAMA_CTX_SIZE:-4096}
+      --n-gpu-layers ${LLAMA_N_GPU_LAYERS:-0}
+      --embeddings
+      --logprobs
+      ${LLAMA_RPC_ENDPOINTS:+--rpc ${LLAMA_RPC_ENDPOINTS}}
+    healthcheck:
+      test: ["CMD", "curl", "-fs", "http://localhost:8081/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 60s
+    restart: unless-stopped
+
+  # ── Ollama (embeddings) ─────────────────────────────────
+  ollama:
+    image: ollama/ollama:latest
+    ports:
+      - "${OLLAMA_EXPOSE_PORT:-11434}:11434"
+    volumes:
+      - ollama_models:/root/.ollama
+    healthcheck:
+      test: ["CMD", "ollama", "list"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+    restart: unless-stopped
+
+volumes:
+  caic_data:
+  searxng_config:
+  qdrant_storage:
+  rabbitmq_data:
+  ollama_models:
+
+secrets:
+  rabbitmq_password:
+    file: ./secrets/rabbitmq_password.txt

docker.md

@@ -0,0 +1,798 @@
+# Docker Distribution — Architecture & Planning
+
+> **Part of B3 (v1.0 gate).** This document catalogs every service, volume, port, configuration, and decision needed to ship cAIc as a `docker compose` stack. It also defines extraction (setup) and back-out (uninstall) procedures so nothing is lost when reality disagrees with the plan.
+
+## 1. Stack Overview
+
+```
+┌─────────────────────────────────────────────────────────┐
+│                    docker compose stack                  │
+│                                                         │
+│  ┌────────────┐  ┌──────────┐  ┌────────────────────┐  │
+│  │  SearXNG    │  │  Qdrant  │  │  RabbitMQ          │  │
+│  │  :8888      │  │  :6333   │  │  :5672 / :15672    │  │
+│  └──────┬──────┘  └────┬─────┘  └────────┬───────────┘  │
+│         │              │                  │              │
+│         ▼              ▼                  ▼              │
+│  ┌──────────────────────────────────────────────────┐   │
+│  │              cAIc (FastAPI)                     │   │
+│  │              :8080 (HTTP)                        │   │
+│  │                                                  │   │
+│  │  SQLite  ◄── caic.db                  (volume)    │   │
+│  │  Uploads ◄── /app/uploads            (volume)    │   │
+│  └──────────┬──────────────┬───────────────────────┘   │
+│             │              │                            │
+│             ▼              ▼                            │
+│  ┌──────────────┐  ┌──────────────┐                    │
+│  │ llama-server │  │   Ollama     │                    │
+│  │ :8081        │  │ :11434       │                    │
+│  │ (GPU/RPC)    │  │ (embeddings) │                    │
+│  └──────────────┘  └──────────────┘                    │
+└─────────────────────────────────────────────────────────┘
+```
+
+> **This compose stack defines the coordinator.** A coordinator runs cAIc, the broker, and optional infrastructure services. Workers (headless inference nodes) do not use Docker — they install just llama-server + a Python node agent. See §9 for the worker deployment model.
+
+### Service roles
+
+| Service | Image | Role |
+|---------|-------|------|
+| **cAIc** | Custom `Dockerfile` | FastAPI app serving UI + API |
+| **SearXNG** | `searxng/searxng:latest` | Privacy-respecting web search |
+| **Qdrant** | `qdrant/qdrant:latest` | Vector database for RAG |
+| **RabbitMQ** | `rabbitmq:4-management` | Message broker for AMQP cluster |
+| **llama-server** | `ghcr.io/ggml-org/llama.cpp:server` | LLM inference (OpenAI-compat API) |
+| **Ollama** | `ollama/ollama:latest` | Embeddings for RAG chunk vectors |
+
+### Non-containerized (host-level)
+
+| Component | Reason |
+|-----------|--------|
+| AMD GPU driver + ROCm | Kernel access required for GPU compute |
+| llama.cpp RPC workers | Runs on *other* hosts — not on the Docker host |
+| `rocm-smi` | Hardware stats — not needed for core function |
+| `psutil` | Already inside the container via pip |
+
+---
+
+## 2. Service Catalog
+
+### 2.1 cAIc (FastAPI app)
+
+**Image:** `caic:latest` (built from `Dockerfile`)
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 8080 | 8080 | HTTP API + UI |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/app/caic.db` | named volume `caic_data` | SQLite database |
+| `/app/uploads` | named volume `caic_uploads` | Uploaded files |
+| `/app/hardware_state.json` | (inside volume) | Cached hardware probe |
+
+**Dependencies:** Wait for SearXNG, Qdrant, RabbitMQ, llama-server, Ollama before serving.
+
+**Restart:** `unless-stopped`
+
+**Healthcheck:** `curl -f http://localhost:8080/`
+
+### 2.2 SearXNG
+
+**Image:** `searxng/searxng:latest`
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 8080 | 8888 | Search API |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/etc/searxng` | named volume `searxng_config` | `settings.yml` |
+
+**Environment:**
+```env
+SEARXNG_BASE_URL=https://localhost:8888
+```
+
+**Config override (`/etc/searxng/settings.yml`):**
+```yaml
+search:
+  safe_search: 0
+  autocomplete: ""
+server:
+  secret_key: ${SEARXNG_SECRET_KEY}
+  limiter: false
+  image_proxy: false
+  method: GET
+  port: 8080
+  bind_address: "0.0.0.0"
+```
+
+**Restart:** `unless-stopped`
+
+### 2.3 Qdrant
+
+**Image:** `qdrant/qdrant:latest`
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 6333 | 6333 | HTTP API |
+| 6334 | — | gRPC (internal only) |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/qdrant/storage` | named volume `qdrant_storage` | Vector index data |
+
+**Environment:**
+```env
+QDRANT__SERVICE__GRPC_PORT=6334
+```
+
+**Restart:** `unless-stopped`
+
+### 2.4 RabbitMQ
+
+**Image:** `rabbitmq:4-management`
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 5672 | 5672 | AMQP messaging |
+| 15672 | — | Management UI (internal only) |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/var/lib/rabbitmq` | named volume `rabbitmq_data` | Message store |
+
+**Environment:**
+```env
+RABBITMQ_DEFAULT_USER=caic
+RABBITMQ_DEFAULT_PASS_FILE=/run/secrets/rabbitmq_password
+RABBITMQ_DEFAULT_VHOST=/
+```
+
+**Restart:** `unless-stopped`
+
+### 2.5 llama-server
+
+**Image:** `ghcr.io/ggml-org/llama.cpp:server`
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 8081 | 8081 | OpenAI-compat API |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/models` | bind mount `./models` | Model GGUF files |
+
+**Environment:**
+```env
+LLAMA_ARG_MODEL=/models/<model-file>
+LLAMA_ARG_N_GPU_LAYERS=0              # set >0 for GPU offload
+LLAMA_ARG_MAIN_GPU=0
+LLAMA_ARG_CTX_SIZE=4096
+LLAMA_ARG_HOST=0.0.0.0
+LLAMA_ARG_PORT=8081
+LLAMA_ARG_EMBEDDINGS=1
+LLAMA_ARG_LOGPROBS=1
+LLAMA_ARG_RPC=                         # optional: comma-separated RPC endpoints
+```
+
+**Restart:** `unless-stopped`
+
+**Healthcheck:** `curl -f http://localhost:8081/health`
+
+**Notes:**
+- Models directory bind mount — user places `.gguf` files in `./models/` on the host
+- RPC offload to other machines (e.g., `10.0.0.50:50052,10.0.0.51:50052`)
+- If no GPU, set `LLAMA_ARG_N_GPU_LAYERS=0` for CPU-only
+- `LLAMA_ARG_EMBEDDINGS=1` required for perplexity scoring
+- `LLAMA_ARG_LOGPROBS=1` required for auto-search trigger
+
+### 2.6 Ollama
+
+**Image:** `ollama/ollama:latest`
+
+**Ports:**
+| Container | Host | Purpose |
+|-----------|------|---------|
+| 11434 | 11434 | Embeddings API |
+
+**Volumes:**
+| Container path | Type | Purpose |
+|----------------|------|---------|
+| `/root/.ollama` | named volume `ollama_models` | Pulled model blobs |
+
+**Restart:** `unless-stopped`
+
+**Notes:**
+- Used exclusively for embeddings (`/api/embeddings`), not inference
+- Typically needs a small model like `all-minilm:latest` or `nomic-embed-text:latest`
+- Consider replacing Ollama with llama-server's built-in embedding if it supports the same model — would remove one container
+
+---
+
+## 3. Configuration Management
+
+### 3.1 `.env` file (generated by setup wizard)
+
+```env
+# --- Secrets (auto-generated, change before production) ---
+CAIC_ADMIN_PIN=
+CAIC_COMPLETIONS_API_KEY=
+CAIC_ALLOW_DEFAULT_PIN=false
+RABBITMQ_PASSWORD=
+SEARXNG_SECRET_KEY=
+
+# --- Host discovery (auto-detected by setup wizard) ---
+LLAMA_SERVER_BASE=http://llama-server:8081
+OLLAMA_BASE=http://ollama:11434
+SEARXNG_BASE=http://searxng:8888
+QDRANT_URL=http://qdrant:6333
+RABBITMQ_HOST=rabbitmq
+RABBITMQ_PORT=5672
+
+# --- Performance tuning (calculated by setup wizard) ---
+RAG_MAX_VECTORS=50000
+RAG_EVICTION_HIGH_WATER=0.80
+RAG_EVICTION_LOW_WATER=0.20
+RAG_EVICTION_BATCH=1000
+
+# --- llama-server options ---
+LLAMA_MODEL=llama3.1-8b-instruct.Q4_K_M.gguf
+LLAMA_N_GPU_LAYERS=0
+LLAMA_RPC_ENDPOINTS=
+LLAMA_CTX_SIZE=4096
+
+# --- Ollama ---
+OLLAMA_EMBED_MODEL=all-minilm:latest
+
+# --- Network ---
+CAIC_ALLOWED_CIDRS=127.0.0.0/8,::1/128,10.0.0.0/8,172.16.0.0/12,192.168.0.0/16
+CAIC_TRUSTED_ORIGINS=
+CAIC_TRUST_X_FORWARDED_FOR=false
+```
+
+### 3.2 Mapping of config.py → .env variable
+
+Every config.py default that references an external service must accept a matching env var at runtime:
+
+| config.py constant | .env variable | Service |
+|-------------------|---------------|---------|
+| `LLAMA_SERVER_BASE` | `LLAMA_SERVER_BASE` | llama-server |
+| `OLLAMA_BASE` | `OLLAMA_BASE` | Ollama |
+| `SEARXNG_BASE` | `SEARXNG_BASE` | SearXNG |
+| `QDRANT_URL` | `QDRANT_URL` | Qdrant |
+| `COMPLETIONS_API_KEY` | `CAIC_COMPLETIONS_API_KEY` | — |
+| `ALLOWED_CIDRS_RAW` | `CAIC_ALLOWED_CIDRS` | — |
+| `TRUST_X_FORWARDED_FOR` | `CAIC_TRUST_X_FORWARDED_FOR` | — |
+| `TRUSTED_ORIGINS` | `CAIC_TRUSTED_ORIGINS` | — |
+| `RAG_MAX_VECTORS` | `RAG_MAX_VECTORS` | — (calc'd from RAM) |
+
+### 3.3 Secrets management
+
+| Secret | Generated by | Stored in | Mounted to |
+|--------|-------------|-----------|------------|
+| `CAIC_ADMIN_PIN` | User prompt | `.env` | cAIc container |
+| `CAIC_COMPLETIONS_API_KEY` | Auto-generated, shown to user | `.env` | cAIc container |
+| `RABBITMQ_PASSWORD` | Auto-generated | `.env` + Docker secret | RabbitMQ container |
+| `SEARXNG_SECRET_KEY` | Auto-generated | `.env` | SearXNG container |
+
+**Docker secrets approach:** Use `secrets:` in compose file for RabbitMQ password (mounted as file) rather than passing via env var, since `settings.yml` in SearXNG and RabbitMQ config can reference file-based secrets without env-var leakage.
+
+### 3.4 Dockerfile for cAIc
+
+```dockerfile
+FROM python:3.13-slim-bookworm AS builder
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+FROM python:3.13-slim-bookworm
+WORKDIR /app
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl && \
+    rm -rf /var/lib/apt/lists/*
+COPY --from=builder /usr/local/lib/python3.13/site-packages /usr/local/lib/python3.13/site-packages
+COPY --from=builder /usr/local/bin /usr/local/bin
+COPY . .
+
+EXPOSE 8080
+HEALTHCHECK --interval=30s --timeout=10s --start-period=15s --retries=3 \
+    CMD curl -f http://localhost:8080/ || exit 1
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8080"]
+```
+
+**Multi-stage rationale:** First stage compiles/bundles packages (wheels), final stage is minimal. Devs can skip builder with `--target builder` for live-reload with volume mount.
+
+---
+
+## 4. docker-compose.yml structure
+
+```yaml
+services:
+  caic:
+    build: .
+    ports: ["8080:8080"]
+    volumes:
+      - caic_data:/app/caic.db
+      - caic_uploads:/app/uploads
+    env_file: .env
+    depends_on:
+      searxng: { condition: service_started }
+      qdrant: { condition: service_started }
+      rabbitmq: { condition: service_healthy }
+      llama-server: { condition: service_healthy }
+      ollama: { condition: service_started }
+    restart: unless-stopped
+
+  searxng:
+    image: searxng/searxng:latest
+    ports: ["8888:8080"]
+    volumes:
+      - ./searxng/settings.yml:/etc/searxng/settings.yml:ro
+      - searxng_config:/etc/searxng
+    env_file: .env
+    restart: unless-stopped
+
+  qdrant:
+    image: qdrant/qdrant:latest
+    ports: ["6333:6333"]
+    volumes:
+      - qdrant_storage:/qdrant/storage
+    restart: unless-stopped
+
+  rabbitmq:
+    image: rabbitmq:4-management
+    ports: ["5672:5672"]
+    volumes:
+      - rabbitmq_data:/var/lib/rabbitmq
+    env_file: .env
+    secrets:
+      - rabbitmq_password
+    healthcheck:
+      test: ["CMD", "rabbitmq-diagnostics", "check_port_connectivity"]
+      interval: 15s
+      timeout: 5s
+      retries: 3
+    restart: unless-stopped
+
+  llama-server:
+    image: ghcr.io/ggml-org/llama.cpp:server
+    ports: ["8081:8081"]
+    volumes:
+      - ./models:/models:ro
+    env_file: .env
+    command: >
+      --model /models/${LLAMA_MODEL}
+      --host 0.0.0.0 --port 8081
+      --ctx-size ${LLAMA_CTX_SIZE:-4096}
+      --n-gpu-layers ${LLAMA_N_GPU_LAYERS:-0}
+      --embeddings
+      --logprobs
+      ${LLAMA_RPC_ENDPOINTS:+--rpc ${LLAMA_RPC_ENDPOINTS}}
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8081/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 5
+      start_period: 60s
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [gpu]
+    restart: unless-stopped
+
+  ollama:
+    image: ollama/ollama:latest
+    ports: ["11434:11434"]
+    volumes:
+      - ollama_models:/root/.ollama
+    healthcheck:
+      test: ["CMD", "ollama", "list"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: all
+              capabilities: [gpu]
+    restart: unless-stopped
+
+volumes:
+  caic_data:
+  caic_uploads:
+  searxng_config:
+  qdrant_storage:
+  rabbitmq_data:
+  ollama_models:
+
+secrets:
+  rabbitmq_password:
+    file: ./secrets/rabbitmq_password.txt
+```
+
+**Notes:**
+- GPU reservations use `resources.reservations.devices` — this is compose v3.8+. For AMD GPUs, replace `driver: nvidia` with `driver: amd` (experimental Docker support). For hosts without GPU, omit the `deploy` block entirely.
+- The `deploy` block only applies when deployed as a swarm stack. For `docker compose`, GPU access may need `--gpus all` or `device_requests` in config. Verify compatibility.
+- SearXNG config file (`settings.yml`) is bind-mounted read-only from the host repo clone — the setup wizard should generate this file.
+
+---
+
+## 5. Networking
+
+### 5.1 Internal communication (compose network)
+
+| From | To | Port | Protocol |
+|------|----|------|----------|
+| cAIc | llama-server | 8081 | HTTP |
+| cAIc | Ollama | 11434 | HTTP |
+| cAIc | SearXNG | 8080 | HTTP |
+| cAIc | Qdrant | 6333 | HTTP |
+| cAIc | RabbitMQ | 5672 | AMQP |
+| RabbitMQ | (cluster peers) | 4369 | EPMD |
+| RabbitMQ | (cluster peers) | 25672 | Inter-node |
+
+### 5.2 Exposed ports (host-facing)
+
+| Port | Service | Should expose? | Notes |
+|------|---------|---------------|-------|
+| 8080 | cAIc | ✅ Required | UI + API |
+| 8888 | SearXNG | Optional | Only if user wants standalone search |
+| 6333 | Qdrant | Optional | Only for external tooling |
+| 5672 | RabbitMQ | Optional | Only for remote AMQP clients |
+| 15672 | RabbitMQ mgmt | ❌ Internal | Healthcheck only |
+| 8081 | llama-server | Optional | Only for external tooling |
+| 11434 | Ollama | Optional | Only for external tooling |
+
+**Design decision:** By default, only port 8080 (cAIc) is published. All other services remain on the internal compose network. Advanced users can opt-in by uncommenting `ports:` blocks.
+
+### 5.3 Reverse proxy consideration
+
+For production, a reverse proxy (Caddy, nginx, Traefik) should sit in front:
+
+```yaml
+# Optional — compose profile: "proxy"
+caddy:
+  image: caddy:latest
+  ports: ["80:80", "443:443"]
+  volumes:
+    - ./Caddyfile:/etc/caddy/Caddyfile:ro
+    - caddy_data:/data
+```
+
+This is out of scope for v1.0 but documented for future.
+
+### 5.4 WireGuard tunnel (off-site workers)
+
+When a worker node runs on a different network (colo, friend's house, VPS), all cross-site traffic must be encrypted. WireGuard provides this at the network layer with zero application changes.
+
+**Approach:** Install WireGuard on the Docker host (not inside a container). The host creates a tunnel interface (`wg0`) with a virtual IP in the `10.0.2.0/24` range. Containers that need to reach remote workers use the host's WireGuard IP via `network_mode: host` or standard routing.
+
+```
+Off-site worker                     Docker host (coordinator)
+┌────────────────────┐              ┌───────────────────────────────┐
+│  wg0: 10.0.2.2     │◄───UDP──────│  wg0: 10.0.2.1                │
+│  llama-server      │   :51820     │                               │
+│  node_agent.py     │   encrypts   │  ┌───────────────────────┐   │
+│                    │   all        │  │  cAIc container        │   │
+│                    │   traffic    │  │  LLAMA_SERVER_BASE     │   │
+│                    │              │  │    → 10.0.2.2:8081     │   │
+│                    │              │  │  CAIC_AMQP_URL         │   │
+│                    │              │  │    → amqp://caic:@...  │   │
+│                    │              │  └───────────────────────┘   │
+└────────────────────┘              └───────────────────────────────┘
+```
+
+**Host setup (coordinator):**
+```bash
+sudo apt install wireguard
+wg genkey | tee /etc/wireguard/private.key | wg pubkey > /etc/wireguard/public.key
+chmod 600 /etc/wireguard/private.key
+```
+Then create `/etc/wireguard/wg0.conf` — see [WireGuard-Setup.md](WireGuard-Setup.md) for full per-node configs.
+
+**Container networking:** The cAIc container needs to reach the WireGuard IP. Options:
+1. **`network_mode: host`** — simplest, container shares host network stack. Done by adding `network_mode: host` to the cAIc service. Trade-off: no port isolation.
+2. **Host routing** — the host's kernel routes `10.0.2.0/24` via `wg0`. Containers on the default bridge or compose network can reach those IPs if `ip_forward` is enabled. This works out of the box on Linux.
+
+**cAIc env vars after WireGuard:**
+```env
+# Point at worker's WireGuard IP instead of LAN IP
+LLAMA_SERVER_BASE=http://10.0.2.2:8081   # falls back to coordinator's own llama-server
+CAIC_AMQP_URL=amqp://caic:password@10.0.2.1:5672/caic  # coordinator's RMQ on WG IP
+```
+
+The node agent on each worker configures its registration IP as the WireGuard tunnel IP (`node_ip = 10.0.2.2`), so `triage.py` constructs inference URLs pointing at the encrypted interface.
+
+---
+
+## 6. Setup Wizard (Extraction)
+
+`setup.sh` — idempotent, interactive, runs on first boot.
+
+### Flow
+
+```
+1. CHECK: Is .env present?
+   ├── YES → skip to step 7 (or ask to regenerate)
+   └── NO  → continue
+
+2. INTRO: Print banner, explain what's about to happen
+
+3. PROBE: Run hardware assessment
+   ├── psutil → RAM total, CPU count
+   ├── rocm-smi → VRAM (optional, best-effort)
+   └── nvidia-smi → VRAM (optional, best-effort)
+
+4. NETWORK: Ask for
+   ├── Hostname / LAN IP for this machine
+   ├── Admin PIN (4 digits, or accept auto-generated)
+   └── (Optional) RPC endpoints for GPU offload
+
+5. CALCULATE:
+   ├── RAG_MAX_VECTORS = max(1000, int(available_ram_gb * 100_000))
+   ├── LLAMA_N_GPU_LAYERS = 0 (CPU default; offer GPU detection)
+   ├── LLAMA_MODEL = default gguf filename
+   └── RABBITMQ_PASSWORD = openssl rand -hex 20
+
+6. GENERATE:
+   ├── .env file from template
+   ├── ./secrets/rabbitmq_password.txt
+   ├── ./searxng/settings.yml (with generated secret_key)
+   └── ./models/README.txt (instructions for placing .gguf)
+
+7. VERIFY:
+   ├── docker and docker compose plugin installed
+   ├── docker compose version >= 2.x
+   ├── SUCCESS → "Run: docker compose up -d"
+   └── FAILURE  → show diagnostics and links
+
+8. EXTRACT model:
+   ├── Prompt for download URL or local path
+   ├── Offer to pull from HuggingFace if huggingface-cli available
+   └── Guides user to place file in ./models/
+```
+
+### What setup.sh creates on disk
+
+```
+./docker-deploy/
+├── .env                        # All env vars (SECRET — add to .gitignore)
+├── docker-compose.yml          # Compose stack definition
+├── Dockerfile                  # cAIc image build
+├── secrets/
+│   └── rabbitmq_password.txt   # RabbitMQ password file
+├── searxng/
+│   └── settings.yml            # SearXNG config with generated secret_key
+├── models/
+│   ├── README.txt              # Instructions for model placement
+│   └── <model>.gguf            # (user-provided)
+└── setup.log                   # Wizard run log
+```
+
+### Idempotency
+
+Re-running `setup.sh`:
+- With `.env` present: ask "Regenerate? This will overwrite existing config."
+- Without `.env`: fresh run
+- Never overwrites `./models/*.gguf` files
+- Never touches running containers — only modifies files on disk
+
+---
+
+## 7. Back-out Procedure (Uninstall)
+
+`teardown.sh` — returns the host system to its pre-install state.
+
+### What gets removed
+
+| Item | Removal method |
+|------|---------------|
+| Docker containers | `docker compose down -v` |
+| Docker images | `docker rmi caic:latest` (ask about other images) |
+| Docker volumes | `docker volume rm caic_data ...` (prompt first) |
+| Network `caic_default` | Removed with compose |
+| `.env` file | `rm .env` |
+| `secrets/` directory | `rm -rf secrets/` |
+| `searxng/` directory | `rm -rf searxng/` |
+| `setup.log` | `rm setup.log` |
+| `hardware_state.json` | `rm hardware_state.json` |
+
+### What is preserved (by default)
+
+| Item | Reason |
+|------|--------|
+| `./models/*.gguf` | User data — prompt for deletion |
+| `caic.db` (in volume) | Prompt: "Keep database snapshot?" |
+| `./uploads/` (in volume) | Prompt: "Keep uploaded files?" |
+| Docker Engine itself | Not installed by this project — leave it |
+
+### Script flow
+
+```
+1. CHECK: docker compose file exists?
+   ├── NO  → warn, continue
+   └── YES → docker compose down -v
+
+2. CHECK: .env exists?
+   ├── NO  → skip
+   └── YES → ask: "Remove .env?" (default no)
+
+3. ASK: "Remove secrets/ and searxng/ directories?" (default no)
+
+4. ASK: "Remove Docker images? (y/N)" (default no)
+   ├── Y → docker rmi caic:latest
+   ├── Y → docker image ls | grep searxng/qdrant/rabbitmq → prompt per image
+   └── N → skip
+
+5. ASK: "Keep database volume snapshot? (Y/n)" (default yes)
+   ├── N → docker volume rm caic_data
+   └── Y → leave volume (can be reattached later)
+
+6. ASK: "Remove model files from ./models/? (y/N)" (default no)
+
+7. CLEANUP generated artifacts:
+   ├── rm -f setup.log
+   ├── rm -f hardware_state.json
+   └── rm -f docker-compose.yml
+
+8. SUMMARY:
+   ├── "Docker stack removed"
+   ├── "Persistent data preserved at: <paths>"
+   └── "Models kept at: ./models/"
+```
+
+### Partial rollback
+
+If the setup wizard fails mid-way, a partial rollback is better than leaving detritus:
+
+| Failure point | Clean up |
+|--------------|----------|
+| After .env, before compose | `rm .env; rm -rf secrets/ searxng/` |
+| After compose, before first `up` | `rm docker-compose.yml; rm -rf *` |
+| After `up` but before healthcheck | `docker compose down -v; rm -rf ./*` |
+
+`setup.sh` should trap EXIT on failure and prompt: "Clean up partial install? [y/N]"
+
+---
+
+## 8. Open Decisions
+
+| Decision | Options | Priority |
+|----------|---------|----------|
+| **Ollama vs llama-server embeddings** | Both work. Keep both for now — remove Ollama if llama-server handles embeddings. Reduce containers = simpler. | Medium |
+| **GPU support in compose** | NVIDIA: well-supported. AMD: requires `--device=/dev/kfd --device=/dev/dri` and ROCm image. Document both. | High |
+| **RabbitMQ clustering vs single node** | Single node in v1.0. Clustering docs for multi-host later. | Low |
+| **SearXNG config management** | Bind-mount a generated `settings.yml`, or let container create default and post-process. Bind-mount is cleaner. | Medium |
+| **Reverse proxy** | Caddy is simplest for auto-HTTPS. Out of scope for v1.0 but design for it. | Low |
+| **Healthcheck strategy** | `depends_on` with `condition: service_healthy` is the safest approach but increases startup time. Acceptable. | Medium |
+| **Database migration** | SQLite file in volume — no migration needed for v1.0 format. If schema changes post-v1.0, need a migration container. | Low |
+| **WireGuard integration** | Documented in docker.md §5.4 + wiki. Host-level install; no container changes needed. WireGuard sidecar container (`linuxserver/wireguard`) is an alternative for users who want everything in compose. | Low |
+| **Linux vs macOS vs Windows** | Linux-primary. macOS may work with changes (no rocm-smi). Windows via WSL2 only. | Low |
+| **LLM model download** | HuggingFace CLI integration in setup.sh, or manual download. Manual is simpler. | Low |
+| **Dockerfile optimization** | Pin pip hashes, use `--no-cache-dir`, consider `slim` vs `alpine`. Alpine has musl compatibility issues with psutil. Stay with slim. | Medium |
+
+## 9. Worker Node Deployment Model
+
+The Docker stack above defines the **coordinator** only. Workers (headless inference nodes) have a radically lighter footprint.
+
+### 9.1 What a worker runs
+
+```
+Worker machine (e.g. worker01, worker02)
+┌────────────────────────────────────┐
+│  llama-server                      │
+│  (single binary, no build needed)  │
+│                                    │
+│  node_agent.py                     │
+│  (Python script, aio-pika client)  │
+│    ─ connects to coordinator's RMQ │
+│    ─ publishes heartbeat + reg     │
+│    ─ consumes model_swap commands  │
+│                                    │
+│  ROCm or CUDA runtime (if GPU)     │
+└────────────────────────────────────┘
+```
+
+### 9.2 What a worker does NOT run
+
+| Service | Reason |
+|---------|--------|
+| RabbitMQ server | Connects as AMQP *client* only (aio-pika) |
+| FastAPI / uvicorn / jC | No HTTP API, no UI, no database |
+| SQLite | No persistent state of its own |
+| SearXNG | No web search needs |
+| Qdrant | No local vector store |
+| Ollama | Uses coordinator's embedding endpoint |
+| Docker | Everything runs as bare binaries |
+| Python venv with full jC deps | Only needs `aio-pika` + `httpx` |
+
+### 9.3 Worker setup
+
+```bash
+# Install WireGuard (required for off-site workers — encrypts all traffic)
+sudo apt install wireguard
+# See docs/wiki/WireGuard-Setup.md for per-node config
+
+# Install llama-server binary
+wget https://github.com/ggml-org/llama.cpp/releases/.../llama-server
+chmod +x llama-server
+
+# Install node agent deps
+pip install aio-pika httpx
+
+# Create node agent config: /etc/caic-node-agent.conf
+# Set node_ip to the WireGuard tunnel IP (e.g., 10.0.2.2)
+# Set amqp_url to the coordinator's WireGuard IP (e.g., amqp://caic:password@10.0.2.1:5672/caic)
+```
+
+### 9.4 Multiple workers
+
+Each worker registers independently with the coordinator's RabbitMQ. The coordinator tracks all registered workers via `CLUSTER_NODES` and routes inference requests to the best-matching node based on classification and availability.
+
+### 9.5 RabbitMQ and workers — architecture note
+
+Workers connect to RabbitMQ as **standard AMQP TCP clients** — no broker software required. The AMQP-0-9-1 protocol has always been client-server (since 2006), and libraries like `aio-pika`, `pika`, `amqplib`, `php-amqplib`, etc. connect over a single persistent socket. This is distinct from a service-mesh design where every node runs the same software stack and role is determined by config.
+
+```
+Broker-mediated model (this project):
+  Coordinator runs  RabbitMQ broker  ←── Workers connect as AMQP clients
+
+Service-mesh model (alternative):
+  Every node runs    RabbitMQ broker  ←── Nodes cluster together, all autonomous
+```
+
+The broker-mediated model is the preferred architecture for this project because workers are intentionally heterogeneous (different GPUs, different models, ARM vs x86) and should not be burdened with infrastructure services.
+
+## 10. Checklist (pre-v1.0 gate)
+
+- [x] `Dockerfile` written and builds clean
+- [x] `docker-compose.yml` boots all containers
+- [ ] cAIc container reaches all services (env vars resolve correctly)
+- [x] SearXNG settings.yml generated correctly by setup.sh
+- [x] RabbitMQ password secret mounted correctly
+- [ ] GPU (NVIDIA) passes through to llama-server container
+- [ ] GPU (AMD) passes through to llama-server container (or documented limitation)
+- [x] `.env.example` checked in (no real secrets)
+- [x] `setup.sh` written, idempotent, tested on clean Debian
+- [x] `teardown.sh` written, tested, doesn't delete models without confirmation
+- [ ] `docker compose up -d` works without any manual steps beyond setup.sh
+- [ ] `docker compose down -v` followed by `setup.sh && docker compose up -d` = fresh stack
+- [ ] Healthchecks prevent serving before dependencies are ready
+- [ ] WireGuard tunnel documented and tested for off-site workers
+- [x] v1.0 release tag created
+
+---
+
+## 11. Files created for B3
+
+```
+docker.md                     ← this file (planning doc)
+Dockerfile                    ← cAIc image (multi-stage, Python 3.13-slim)
+docker-compose.yml            ← full stack (6 services, volumes, secrets, healthchecks)
+.env.example                  ← template without secrets
+.dockerignore                 ← excludes venv, tests, .git, models, secrets
+scripts/setup.sh              ← first-run scaffolding (generates .env, secrets, pulls model)
+scripts/teardown-docker.sh    ← Docker stack teardown (interactive, -y for unattended)
+searxng-settings.yml.dist     ← SearXNG config template (copied by setup.sh)
+models/README.txt             ← instructions for placing .gguf
+secrets/                      ← generated at runtime by setup.sh
+searxng/                      ← generated at runtime by setup.sh
+```

docs/archive/TASKS-pre-1.0.md

@@ -0,0 +1,994 @@
+# cAIc — OpenCode Prompt Sequence
+# Generated: 2026-07-14
+# Execute sequentially. Run full test suite after each task before proceeding.
+# Test command: ./venv/bin/python -m pytest tests/ -v
+
+---
+
+## Session 2026-07-14 — RAG bugfixes + Topbar redesign
+
+- **RAG bugs fixed**: Collection name mismatch (`jarvis_rag` → `caic_rag`, migrated 219 points), `vectors_count`→`points_count` (Qdrant v1.10+ API change), removed unindexed `order_by` that caused 502 on scroll, made `RAG_COLLECTION` env-configurable (`CAIC_RAG_COLLECTION`).
+- **Semantic search fixed**: Set `CAIC_EMBED_URL=http://192.168.50.108:11434` (mxbai-embed-large lives on ultron, not the old embed server).
+- **Topbar redesign**: Moved system stats (CPU/MEM/GPU/VRAM/TOK) to a centered bottom strip. Moved toggles (MEM, SEARCH, PROFILE, SORT, PRIVACY) into a ⋮ hamburger menu next to ADMIN badge. Palette icon sits immediately after version number in topbar-left. Removed standalone (i) button — privacy info accessible via ⋮ → About Privacy. Input bar above chat, stats at very bottom. Mobile-responsive padding/sizing.
+
+---
+
+## ~~TASK 1 — README Cleanup [DONE]~~
+
+Review README.md in the current repo. Remove any node references other than `coordinator` (192.168.50.108) and `worker` (192.168.50.210). Ensure all references to the project use the exact casing `cAIc` — not `Jarvischat`, `JarvisChat`, or `jarvischat`. Do not change any functional content, endpoint documentation, or architecture descriptions — this is a text cleanup only. After editing, verify the file renders cleanly as markdown. Commit with message: `docs: clean up node references and branding consistency`.
+
+No new tests required for this task.
+
+---
+
+## ~~TASK 2 — Qwen2.5-Coder llama-server Service on Coordinator (Infrastructure) [DONE]~~
+
+**Status: Systemd unit created, verified, and restored.**
+
+This task originally defined creation of `/etc/systemd/system/llama-server-coder.service` (port 8082, Qwen2.5-Coder-14B Q5_K_M) as a prerequisite for dynamic model swapping. That sysadmin work is done.
+
+**The real Task 2 deliverable — the ability to dynamically swap models based on query classification — is delivered by Roadmap N (Tasks 9–15).** The flow:
+
+1. **Task 13** — Phi-4-mini triage (`triage.py`) classifies the query as `general`, `code`, `search`, or `rag`
+2. **Task 13** — `select_node()` picks the best worker node; if the ideal model isn't active, it triggers a swap
+3. **Task 14** — `request_model_swap()` publishes `cmd.swap_model` via AMQP `jc.admin` exchange
+4. **Task 12** — The node agent on worker receives the command, stops the current llama-server, starts the correct one, waits for health, and publishes `model_ready`
+5. **Task 14** — coordinator receives `model_ready`, updates the cluster registry, and routes the query to the node
+
+The swap is async and transparent — the user sees only latency. The UI (Task 15) shows a yellow "swapping" status dot during the transition.
+
+The service unit at `/etc/systemd/system/llama-server-coder.service` is the **target** the node agent starts when swapping to code inference. It is not enabled at boot — the AMQP cluster manages activation.
+
+See Tasks 9–15 for the actual model swap implementation.
+
+No pytest tests required for this infrastructure task.
+
+---
+
+## ~~TASK 3 — Update OpenCode Config to Use Qwen on :8082 [DONE]~~
+
+Update `/home/gramps/.config/opencode/opencode.jsonc` (on this machine, coordinator) to point the configured provider at `http://127.0.0.1:8082/v1` instead of `http://127.0.0.1:8081/v1`. The model name in the config should be updated to reflect `qwen2.5-coder-14b` or whatever model ID the llama-server instance at :8082 reports via `/v1/models`. Verify the endpoint is reachable before writing the config change. Do not restart OpenCode — the config change takes effect on next session start.
+
+No pytest tests required for this task.
+
+---
+
+## ~~TASK 4 — File/Document Attachment: Backend Ingest Endpoint [DONE]~~
+
+**Status: `POST /api/upload` with mode=(context|ingest|both), PDF/text extraction, Qdrant upsert, SQLite context (1hr expiry). Committed `4a891c8` (v1.9.0).**
+
+This task implements the backend half of file/document attachment (TODO #21). The goal is dual-aspect upload: a file can be used as immediate chat context, ingested into the RAG corpus (Qdrant), or both.
+
+**Add to `config.py`:**
+- `UPLOAD_DIR` — path for temporary upload storage, default `/tmp/caic_uploads`
+- `MAX_UPLOAD_BYTES` — max file size, default 20MB
+- `SUPPORTED_UPLOAD_TYPES` — set of MIME types: `text/plain`, `text/markdown`, `application/pdf`, `application/json`, `text/x-python`, `text/html`
+
+**Create `routers/upload.py`:**
+
+Implement `POST /api/upload` (admin required). Accept `multipart/form-data` with:
+- `file` — the uploaded file (required)
+- `mode` — string enum: `context` (inject into next chat only), `ingest` (add to RAG corpus), `both` (default: `both`)
+- `conversation_id` — optional, associates context-mode content with a specific conversation
+
+Behavior:
+- Validate file size against `MAX_UPLOAD_BYTES` — return 413 if exceeded
+- Validate MIME type against `SUPPORTED_UPLOAD_TYPES` — return 415 if unsupported
+- For PDF files, extract text using `pypdf` (add to requirements.txt)
+- For all other types, read as UTF-8 text
+- If mode includes `ingest`: chunk the extracted text into 512-token overlapping chunks (128-token overlap), generate embeddings via `EMBED_URL` (http://192.168.50.108:11434/api/embeddings, model mxbai-embed-large), upsert into Qdrant collection `caic` with metadata `{source: filename, upload_date: iso_timestamp, type: "upload"}`
+- If mode includes `context`: store the full extracted text in a new SQLite table `upload_context` with columns `(id INTEGER PRIMARY KEY, conversation_id TEXT, filename TEXT, content TEXT, created_at TEXT, expires_at TEXT)`. Context entries expire after 1 hour.
+- Return JSON: `{filename, size_bytes, mode, chunks_ingested (if ingest), context_id (if context), message}`
+
+**Add `upload_context` table to `db.py`** `init_db()`.
+
+**Wire `upload.router` into `app.py`** in the router registration block.
+
+**Write `tests/test_upload.py`** covering:
+- Valid text file upload, mode=ingest — assert chunks_ingested > 0, Qdrant upsert called
+- Valid text file upload, mode=context — assert context_id returned, row exists in upload_context
+- Valid text file upload, mode=both — assert both behaviors
+- File exceeds MAX_UPLOAD_BYTES — assert 413
+- Unsupported MIME type — assert 415
+- Guest session attempt — assert 403
+- PDF extraction path — mock pypdf, assert text extracted and processed
+
+Mock Qdrant and EMBED_URL calls via monkeypatch. Do not require live external services in tests.
+
+Run full test suite after implementation. All 26 existing tests must continue to pass.
+
+---
+
+## ~~TASK 5 — File/Document Attachment: UI Integration [DONE]~~
+
+**Status: Paperclip icon, file preview pill, gallery overlay, attachment indicators, DELETE/PATCH link/by-conversation endpoints, chat context injection. Committed `81238c0` (v1.10.0).**
+
+This task implements the frontend half of TODO #21. The UI is a single file at `templates/index.html`.
+
+Add a file attachment button to the chat input area. Requirements:
+- Paperclip icon button adjacent to the send button
+- Clicking opens a file picker filtered to supported types (`.txt`, `.md`, `.pdf`, `.json`, `.py`, `.html`)
+- On file selection, show a pill/badge above the input showing the filename with an X to remove it
+- On send, if a file is attached: POST to `/api/upload` with `mode=both` and the current `conversation_id`, then include the returned `context_id` in the subsequent `/api/chat` POST body as `upload_context_id`
+- If the upload fails, show an inline error and do not send the chat message
+- File attachment state clears after send
+
+**Update `/api/chat` in `routers/chat.py`:**
+- Accept optional `upload_context_id` in the request body
+- If present, look up the content in `upload_context` table and prepend it to the system prompt as: `\n\n[ATTACHED DOCUMENT: {filename}]\n{content}\n[END DOCUMENT]`
+- If the context_id is expired or missing, log a warning and continue without it (do not error)
+
+**Add to `tests/test_chat_streaming_and_memory_paths.py`:**
+- Test that a valid `upload_context_id` results in document content being prepended to the system prompt
+- Test that an expired/missing `upload_context_id` is silently ignored
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 6 — Roadmap I: Terminal Command RAG Hook [DONE]~~
+
+**Status: `POST /api/ingest` with Bearer token auth, `chunk_text()` shared helper, `caic-ingest.sh` script. Committed `1ac21ad` (v0.11.0).**
+
+This task implements autonomous RAG ingestion of significant terminal activity (TODO #23).
+
+**Create `routers/ingest.py`:**
+
+Implement `POST /api/ingest` (requires Bearer token auth — use same `COMPLETIONS_API_KEY` mechanism as `routers/completions.py`). Accept JSON body:
+- `content` — string, the text to ingest (required)
+- `source` — string, origin label e.g. `terminal`, `file`, `external` (default: `external`)
+- `metadata` — optional dict of additional key/value pairs
+
+Behavior:
+- Chunk `content` into 512-token overlapping chunks (128-token overlap) — extract this logic into a shared helper `chunk_text(text, chunk_size=512, overlap=128)` in `rag.py` if not already present
+- Generate embeddings via `EMBED_URL`
+- Upsert into Qdrant collection `caic` with metadata `{source, ingest_date: iso_timestamp, ...metadata}`
+- Return JSON: `{chunks_ingested, source, message}`
+
+**Wire `ingest.router` into `app.py`.**
+
+**Create `/usr/local/bin/caic-ingest.sh` on worker (192.168.50.210)** — this is a shell script, not a Python file, and lives outside the repo. Write it to stdout/document it clearly so gramps can deploy it manually:
+
+```bash
+#!/bin/bash
+# caic-ingest.sh — pipe terminal commands into cAIc RAG
+# Add to ~/.bashrc: export PROMPT_COMMAND="jc_capture"
+# Function to call after significant commands
+
+JC_URL="http://192.168.50.210:8080/api/ingest"
+JC_TOKEN="${CAIC_COMPLETIONS_API_KEY}"
+
+jc_capture() {
+    local cmd
+    cmd=$(history 1 | sed 's/^[ ]*[0-9]*[ ]*//')
+    # Only ingest significant commands
+    if echo "$cmd" | grep -qE '^(git|pip|systemctl|sudo|vi|vim|curl|wget|apt|python|pytest)'; then
+        curl -s -X POST "$JC_URL" \
+            -H "Authorization: Bearer $JC_TOKEN" \
+            -H "Content-Type: application/json" \
+            -d "{\"content\": $(echo "$cmd" | python3 -c 'import json,sys; print(json.dumps(sys.stdin.read().strip()))'), \"source\": \"terminal\"}" \
+            > /dev/null 2>&1 &
+    fi
+}
+```
+
+**Write `tests/test_ingest.py`** covering:
+- Valid ingest with content — assert chunks_ingested > 0
+- Missing Bearer token — assert 401
+- Wrong Bearer token — assert 403
+- Empty content — assert 422
+- Qdrant and embed calls mocked via monkeypatch
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 7 — Roadmap J: Startup Hardware Self-Assessment [DONE]~~
+
+**Status: `hardware.py` + `routers/hardware.py` + 4 tests. Committed `7291b8f` (v0.12.0).**
+
+On jC startup, probe available hardware and write a living config snapshot. This replaces hardcoded assumptions about VRAM and RAM.
+
+**Create `hardware.py`** in the project root:
+
+```
+async def assess_hardware() -> dict
+```
+
+Probes:
+- System RAM: `psutil.virtual_memory().total` and `.available`
+- CPU count: `psutil.cpu_count()`
+- GPU VRAM total and free: call `rocm-smi --showmeminfo vram --json` via subprocess, parse output. If rocm-smi absent or fails, set VRAM values to 0 and log a warning.
+- llama-server reachable: GET `LLAMA_SERVER_BASE/v1/models`, timeout 3s. Record True/False and list of available model IDs.
+- Qdrant reachable: GET `http://192.168.50.108:6333/collections`, timeout 3s. Record True/False and collection list.
+- SearXNG reachable: GET `http://localhost:8888`, timeout 3s. Record True/False.
+
+Returns a dict with all of the above. Writes result as JSON to `hardware_state.json` in the working directory.
+
+**Call `assess_hardware()` from the FastAPI `lifespan` context** in `app.py` on startup, after `init_db()`. Log a summary line: `HW: {ram_gb}GB RAM, {vram_mb}MB VRAM, llama={reachable}, qdrant={reachable}, searxng={reachable}`.
+
+**Expose `GET /api/hardware`** in a new `routers/hardware.py` — returns the current `hardware_state.json` content as JSON. No auth required (read-only, non-sensitive aggregate stats).
+
+**Wire `hardware.router` into `app.py`.**
+
+**Write `tests/test_hardware.py`** covering:
+- `assess_hardware()` with all services reachable (mock subprocess and httpx calls) — assert all fields present
+- `assess_hardware()` with rocm-smi absent — assert VRAM=0, no exception raised
+- `assess_hardware()` with llama-server unreachable — assert `llama_reachable=False`, no exception
+- `GET /api/hardware` — assert returns JSON with expected keys
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 8 — Roadmap K: RAG Corpus Management [DONE]~~
+
+Qdrant collection `caic` currently grows without bound. Implement score-based eviction with hysteresis, pinned sources, operational stats, and a flush command.
+
+### Config — add to `config.py`:
+
+```python
+RAG_MAX_VECTORS = 50000               # absolute ceiling; eviction targets thresholds below it
+RAG_EVICTION_HIGH_WATER = 0.80        # fraction of RAG_MAX_VECTORS that triggers eviction
+RAG_EVICTION_LOW_WATER = 0.20         # fraction where eviction stops
+RAG_EVICTION_BATCH = 1000             # max points to delete per Qdrant scroll/delete cycle
+RAG_PINNED_SOURCES = ["upload", "profile"]  # never evicted
+RAG_GRACE_HOURS = 1                   # new vectors ineligible for eviction until this old
+RAG_ACCESS_WEIGHT = 1.0               # score factor: retrieval_count * ACCESS_WEIGHT
+RAG_AGE_WEIGHT = 0.1                  # score factor: ingest_age_hours * AGE_WEIGHT
+```
+
+Validations on boot: `high_water > low_water`, `batch > 0`, `max_vectors > 0`.
+
+### Eviction algorithm — add to `rag.py`:
+
+```
+score = (retrieval_count * ACCESS_WEIGHT) + (age_hours * AGE_WEIGHT)
+```
+
+Lower score = evicted first. Tiebreak: `last_accessed` ASC (older wins).
+
+```python
+async def get_collection_count() -> int
+    # GET /collections/caic → return vectors_count
+
+async def get_collection_stats() -> dict
+    # Return {vector_count, max_vectors, high_water, low_water, percent_full, pinned_sources}
+
+async def evict_batch(batch_size: int) -> int
+    # Scroll Qdrant for vectors NOT in RAG_PINNED_SOURCES, WHERE ingest_age > RAG_GRACE_HOURS,
+    # ordered by score ASC, last_accessed ASC.
+    # Delete up to batch_size. Return count deleted.
+    # If 0 evictable vectors found: log warning, return 0 (break loop).
+
+async def maybe_evict() -> int
+    # Acquire eviction_lock (asyncio.Lock).
+    # count = get_collection_count()
+    # threshold_high = RAG_MAX_VECTORS * RAG_EVICTION_HIGH_WATER
+    # threshold_low  = RAG_MAX_VECTORS * RAG_EVICTION_LOW_WATER
+    # total_evicted = 0
+    # while count >= threshold_low:
+    #     if total_evicted > 0 and count < threshold_low: break
+    #     deleted = evict_batch(RAG_EVICTION_BATCH)
+    #     if deleted == 0: break  # no more unpinned targets
+    #     total_evicted += deleted
+    #     count -= deleted
+    #     if count < threshold_high and total_evicted > 0: break
+    #     # only one pass if batch spans the full gap
+    #     if count < threshold_low: break
+    # Record total_evicted + timestamp in EVICTION_LOG (list of dicts, kept in memory, max 1000 entries)
+    # Release lock. Return total_evicted.
+
+async def get_rag_operational_stats() -> dict
+    # Returns: vector_count, max_vectors, high_water_pct, low_water_pct,
+    # percent_full, pinned_sources, grace_hours,
+    # eviction_counts_last_1m, eviction_counts_last_5m, eviction_counts_last_30m,
+    # at_risk_count (vectors in bottom 10% by score),
+    # pinned_count, avg_retrieval_count
+```
+
+### Edge cases & guards:
+
+1. **Newborn grace** — vectors < `RAG_GRACE_HOURS` old are excluded from eviction scroll (score=0 otherwise → immediate deletion)
+2. **All-pinned freeze** — if scroll returns 0 evictable vectors, log warning and break loop
+3. **Race** — `asyncio.Lock()` guards `maybe_evict()`; concurrent callers wait their turn
+4. **Zero config** — `RAG_MAX_VECTORS <= 0` → eviction disabled; `RAG_EVICTION_BATCH <= 0` → clamped to 1
+5. **Legacy payloads** — vectors without `retrieval_count` or `last_accessed` get defaults (0, `ingest_date`)
+
+### Wire eviction:
+
+Call `maybe_evict()` after each upsert batch completes in:
+- `routers/upload.py` — after Qdrant upsert
+- `routers/ingest.py` — after Qdrant upsert
+
+### Admin endpoints — new `routers/rag_admin.py`:
+
+| Method | Endpoint | Description |
+|--------|----------|-------------|
+| GET | `/api/rag/stats` | Operational stats (see `get_rag_operational_stats()`) — admin required |
+| POST | `/api/rag/flush` | Delete ALL points from the Qdrant `caic` collection. Returns `{deleted_count, collection: "caic", status: "flushed"}`. Admin required. |
+
+### In-memory eviction log:
+
+```python
+EVICTION_LOG: list[dict] = []  # managed by rag.py, max 1000 entries
+# Each entry: {timestamp: iso, count: N, remaining: N}
+# Tied to RATE_EVENTS pattern from security.py for rolling window calculations
+```
+
+### Tests — `tests/test_rag_management.py`:
+
+- `get_collection_count()` — mock Qdrant GET, assert correct count
+- `get_collection_stats()` — assert shape matches config
+- `evict_batch()` — mock Qdrant scroll + delete, assert pinned sources excluded, grace period enforced, batch size respected
+- `maybe_evict()` — below high water: 0 evicted; at high water: eviction fires; stops at low water; all-pinned scroll returns 0 → breaks
+- `GET /api/rag/stats` — assert full shape
+- `POST /api/rag/flush` — assert points deleted, admin required, guest 403
+- `POST /api/rag/flush` by guest — assert 403
+- Race lock — concurrent calls to `maybe_evict()` queue up, only one evicts
+
+Mock all Qdrant calls via monkeypatch. Do not require live services.
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 9 — Roadmap N1: RabbitMQ Install and Service on Coordinator (Infrastructure) [DONE]~~
+
+This task runs on coordinator (this machine). Install RabbitMQ and verify it is operational.
+
+Run the following steps:
+1. `apt-get update && apt-get install -y rabbitmq-server`
+2. `systemctl enable rabbitmq-server && systemctl start rabbitmq-server`
+3. `systemctl status rabbitmq-server` — verify active/running
+4. Enable the management plugin: `rabbitmq-plugins enable rabbitmq_management`
+5. Create a dedicated jC vhost: `rabbitmqctl add_vhost caic`
+6. Create a dedicated user: `rabbitmqctl add_user caic CHANGEME_PASSWORD` — generate a random 24-char alphanumeric password and record it
+7. Grant permissions: `rabbitmqctl set_permissions -p caic caic ".*" ".*" ".*"`
+8. Verify management UI is reachable: `curl -s -u guest:guest http://localhost:15672/api/overview | python3 -m json.tool`
+9. Delete default guest user: `rabbitmqctl delete_user guest`
+
+Declare the two topic exchanges needed by jC:
+- Exchange name: `jc.admin`, type: `topic`, durable: true
+- Exchange name: `jc.system`, type: `topic`, durable: true
+
+Use `rabbitmqadmin` or `curl` against the management API to declare exchanges. Verify both exchanges appear in: `curl -s -u caic:{password} http://localhost:15672/api/exchanges/caic`
+
+Write the generated RabbitMQ password to `/home/gramps/.caic_amqp_secret` with mode 600. This will be read by cAIc as an env var source in subsequent tasks.
+
+No pytest tests required for this infrastructure task.
+
+---
+
+## ~~TASK 10 — Roadmap N2: AMQP Connection Layer in jC [DONE]~~
+
+This task adds the core AMQP connection manager to jC. It must connect to RabbitMQ on coordinator (localhost from jC's perspective since jC runs on coordinator), handle reconnection, and provide a shared channel for all AMQP operations.
+
+**Add to `requirements.txt`:** `aio-pika>=9.0.0`
+
+**Add to `config.py`:**
+- `AMQP_URL` — read from env `CAIC_AMQP_URL`, default `amqp://caic:password@localhost:5672/caic`. The actual password comes from `/home/gramps/.caic_amqp_secret` — read it at startup if the env var is not set.
+- `AMQP_RECONNECT_DELAY` — seconds between reconnect attempts, default 5
+- `AMQP_EXCHANGE_ADMIN` — `jc.admin`
+- `AMQP_EXCHANGE_SYSTEM` — `jc.system`
+
+**Create `amqp.py`** in the project root:
+
+```python
+# Manages a single persistent aio-pika connection and channel.
+# Provides:
+#   connect() -> None          # establish connection, declare exchanges
+#   disconnect() -> None       # graceful close
+#   get_channel()              # returns current channel, reconnects if needed
+#   publish(exchange, routing_key, payload: dict) -> None
+#                              # publishes JSON-serialized payload as persistent message
+```
+
+Connection must:
+- Reconnect automatically on disconnect with `AMQP_RECONNECT_DELAY` backoff
+- Log connection events at INFO level
+- Not raise on publish if disconnected — log error and return (fire-and-forget, jC must not crash if RabbitMQ is down)
+
+**Start AMQP connection in `app.py` lifespan** after `assess_hardware()`. Disconnect in lifespan cleanup.
+
+**Write `tests/test_amqp.py`** covering:
+- `publish()` with mocked aio-pika connection — assert message published with correct exchange and routing key
+- `publish()` when disconnected — assert no exception raised, error logged
+- `get_channel()` when connection is None — assert reconnect attempted
+
+Mock all aio-pika calls via monkeypatch. Do not require a live RabbitMQ instance in tests.
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 11 — Roadmap N3: Cluster Protocol & Registration Handler (Coordinator Side) [DONE]~~
+
+**Status: Implemented and pushed (899988c).** `amqp.py` subscribe/rebind, `cluster.py` with CLUSTER_NODES/CLUSTER_EVENTS/CLUSTER_COORDINATOR and 6 handlers, `routers/cluster.py` (`GET /api/cluster`), 13 tests. No passive heartbeats — ping/pong on-demand before work routing. 148 tests pass.
+
+jC on the coordinator must listen for nine message types across `jc.admin` and `jc.system`, maintain the cluster registry, and expose an application-level event log.
+
+### 11.1 AMQP Protocol — Message Catalog
+
+All payloads are JSON, published as persistent messages.
+
+| Direction | Exchange | Routing Key | Message Type | Description |
+|-----------|----------|-------------|-------------|-------------|
+| Worker → Coordinator | `jc.admin` | `node.{name}.register` | register | Worker requests admission |
+| Worker → Coordinator | `jc.admin` | `node.{name}.deregister` | deregister | Worker signals graceful departure |
+| Coordinator → Worker | `jc.admin` | `node.{name}.admitted` | admitted | Coordinator grants admission |
+| Coordinator → Worker | `jc.admin` | `node.{name}.rejected` | rejected | Coordinator denies admission (with reason) |
+| Coordinator → Worker | `jc.admin` | `node.{name}.ping` | ping | Coordinator checks if worker is alive (sent before routing work) |
+| Worker → Coordinator | `jc.admin` | `node.{name}.pong` | pong | Worker confirms aliveness |
+| Worker → Coordinator | `jc.system` | `node.{name}.event` | event | Application-level syslog event |
+| Any → All | `jc.system` | `cluster.coordinator.query` | coord_query | Anyone asks "who is coordinator?" |
+| Coordinator → All | `jc.system` | `cluster.coordinator.response` | coord_response | Coordinator announces itself |
+
+Worker presence is assumed from registration onward. No periodic heartbeats — a worker can sit idle for days without chatter. When the coordinator needs to route work to a worker, it pings first; if the worker doesn't pong within timeout, the coordinator deregisters it and moves to the next node.
+
+### 11.2 Payload Schemas
+
+**register** (worker → coordinator):
+```json
+{
+  "node_name": "worker01",
+  "node_type": "worker",
+  "ip": "192.168.50.210",
+  "capabilities": {
+    "gpu": true, "gpu_type": "amd", "vram_mb": 8192,
+    "cpu_cores": 8, "ram_gb": 16
+  },
+  "active_model": {
+    "name": "llama3.1", "version": "latest", "quant": "Q4_K_M",
+    "path": "/var/lib/caic/models/llama3.1-latest-Q4_K_M.gguf",
+    "port": 8081
+  },
+  "inventory": [
+    {"name": "llama3.1", "version": "latest", "quant": "Q4_K_M",
+     "path": "/var/lib/caic/models/llama3.1-latest-Q4_K_M.gguf", "port": 8081}
+  ],
+  "status": "active"
+}
+```
+
+**deregister** (worker → coordinator):
+```json
+{
+  "node_name": "worker01",
+  "reason": "shutdown",
+  "timestamp": "2026-07-06T12:00:00Z"
+}
+```
+
+**ping** (coordinator → worker):
+```json
+{
+  "from": "coordinator",
+  "node_name": "worker01",
+  "type": "ping",
+  "correlation_id": "550e8400-e29b-41d4-a716-446655440000",
+  "timestamp": "2026-07-06T12:00:00Z"
+}
+```
+Worker must respond within 5 seconds or the coordinator considers it absent.
+
+**pong** (worker → coordinator):
+```json
+{
+  "node_name": "worker01",
+  "type": "pong",
+  "correlation_id": "550e8400-e29b-41d4-a716-446655440000",
+  "status": "active",
+  "active_model": {"name": "llama3.1", "port": 8081},
+  "load": {"cpu_pct": 45, "ram_pct": 62, "vram_pct": 38},
+  "timestamp": "2026-07-06T12:00:00Z"
+}
+```
+Correlation ID matches the ping so the coordinator can pair request and response.
+
+**coord_query** (any → `cluster.coordinator.query`):
+```json
+{"type": "coord_query", "timestamp": "2026-07-06T12:00:00Z"}
+```
+Coordinator responds on `cluster.coordinator.response`:
+```json
+{
+  "coordinator_node": "coordinator",
+  "cluster_nodes": ["worker01"],
+  "timestamp": "2026-07-06T12:00:00Z"
+}
+```
+
+**event** (worker → coordinator):
+```json
+{
+  "node_name": "worker01",
+  "severity": "info",
+  "message": "llama-server started with model llama3.1:latest",
+  "details": {"model": "llama3.1:latest", "port": 8081, "pid": 1234},
+  "timestamp": "2026-07-06T12:00:00Z"
+}
+```
+Severity levels: `info`, `warn`, `error`, `critical`. The coordinator assigns `category: "application"` based on the exchange (jc.system). No `event_type` field — the category is determined by the channel, not the payload.
+
+### 11.3 Design — Status Transitions Drive the Event Log
+
+All admin-level events are *derived* from `register()` and `deregister()` as side effects. There are no separate message types for coordinator election, node staleness, quarantine, or release — those are status transitions that `register()`/`deregister()` emit into `CLUSTER_EVENTS` locally.
+
+**Node status lifecycle:**
+
+```
+UNKNOWN ──register()──▶ active ──deregister()──▶ (removed)
+                           │
+               ping timeout│(coordinator publishes
+                           │ deregister on its behalf)
+                           ▼
+                      (removed)
+```
+
+**Coordinator status lifecycle:**
+
+```
+NONE ──register(node_type=coordinator)──▶ CLUSTER_COORDINATOR set
+                                              │
+                                   deregister()│or timeout
+                                              ▼
+                                         CLUSTER_COORDINATOR cleared
+```
+
+**Event categories — two buckets, no granular types:**
+
+| Category | When | severity |
+|----------|------|----------|
+| `cluster` | Node lifecycle, coordinator changes, model swaps, node offline — everything on `jc.admin` | `info` / `warn` / `error` |
+| `application` | Worker syslog events (incoming on `jc.system` `node.*.event`) | `info` / `warn` / `error` / `critical` |
+
+Every `_push_event()` call uses one of these two categories. The `message` field carries the human-readable detail — no need for event type strings. The reporting tool filters by category + severity.
+
+**Channel split — security rationale:**
+
+The two exchanges are not an organizational convenience. They enforce a **data isolation boundary**:
+
+| Exchange | Contains | Exposed to |
+|----------|----------|------------|
+| `jc.admin` | Node lifecycle, heartbeats, model swaps, coordinator changes | Operations / machine-room staff |
+| `jc.system` | Application events — inference queries, RAG context, user-facing data | Application-layer audit only |
+
+`jc.system` events can leak information about what users are doing and asking. The split ensures a sysadmin monitoring cluster health never accidentally consumes user-data-bearing events. The channels can be locked down independently — different AMQP credentials, separate queue permissions, different in-transit encryption policies if needed later.
+
+### 11.4 Implementation
+
+**Add to `amqp.py`:**
+
+```python
+_SUBSCRIPTIONS: list[tuple[str, str, Callable]]  # (exchange, routing_key, callback)
+
+async def subscribe(exchange, routing_key, callback) -> None
+    # Append to _SUBSCRIPTIONS list
+    # Declare a unique queue per subscription (name: f"jc.{exchange}.{sanitized_routing_key}")
+    # Bind queue to exchange/routing_key, consume with callback
+```
+
+Each subscription gets its own queue so multiple subscribers on different routing keys all receive messages. On reconnect: drain old consumers, iterate `_SUBSCRIPTIONS`, re-declare and re-bind each one. The `connect()` function must call `_rebind_subscriptions()` after exchanges are declared.
+
+**Create `cluster.py`** in the project root:
+
+```python
+# In-memory cluster registry + event log
+# Survives only while jC is running (not persisted)
+
+CLUSTER_NODES: dict[str, NodeRecord]
+CLUSTER_EVENTS: deque[EventRecord]   # bounded at 1000 entries
+CLUSTER_COORDINATOR: str | None      # node_name of active coordinator
+
+# NodeRecord fields:
+#   node_name, node_type, ip, status, active_model, inventory,
+#   capabilities: {gpu, gpu_type, vram_mb, cpu_cores, ram_gb}
+#   registered_at, last_seen
+
+# EventRecord:
+#   category: str     ("cluster" | "application")
+#   severity: str     ("info" | "warn" | "error" | "critical")
+#   node_name: str
+#   message: str
+#   details: dict | None
+#   timestamp: str
+
+def _push_event(category, severity, node_name, message, details=None) -> None
+    # Append EventRecord to CLUSTER_EVENTS, pop left if > 1000
+
+async def handle_registration(message) -> None
+    # Parse payload, validate required fields (node_name, node_type, ip, active_model, inventory)
+    # Reject if node_name duplicate and CLUSTER_NODES[node_name].status == "active"
+    # If CLUSTER_COORDINATOR is None AND node_type == "coordinator":
+    #   set CLUSTER_COORDINATOR = node_name
+    #   _push_event("cluster", "info", node_name, "elected coordinator")
+    #   publish cluster.coordinator.response on jc.system {coordinator_node, cluster_nodes, timestamp}
+    # Add node to CLUSTER_NODES with status="active"
+    # _push_event("cluster", "info", node_name, f"admitted as {node_type}")
+    # publish admitted on jc.admin node.{name}.admitted {node_name, timestamp, amqp_url}
+
+async def handle_deregistration(message) -> None
+    # Parse payload (node_name, reason, timestamp)
+    # If node_name == CLUSTER_COORDINATOR:
+    #   clear CLUSTER_COORDINATOR
+    #   _push_event("cluster", "warn", node_name, f"coordinator lost — {reason}")
+    # _push_event("cluster", "info", node_name, f"departed — {reason}")
+    # Remove node from CLUSTER_NODES, log it
+
+async def handle_pong(message) -> None
+    # Parse: node_name, correlation_id, status, active_model, load, timestamp
+    # Match correlation_id to outstanding ping
+    # If node in CLUSTER_NODES: update last_seen, status, active_model
+    # Signal the waiting caller that the node is alive
+    # If node unknown: log warning, do NOT auto-admit
+
+async def handle_event(message) -> None
+    # Parse: node_name, severity, message, details, timestamp
+    # Assigns category="application" (incoming on jc.system)
+    # Append EventRecord to CLUSTER_EVENTS (pop left if > 1000)
+
+async def handle_coordinator_query(message) -> None
+    # Respond on jc.system cluster.coordinator.response
+    # Payload: {coordinator_node, cluster_nodes: list(CLUSTER_NODES.keys()), timestamp}
+
+def get_cluster_state() -> dict
+    # Return: {nodes: CLUSTER_NODES, coordinator: CLUSTER_COORDINATOR,
+    #          events: last 50 CLUSTER_EVENTS}
+```
+
+**Subscribe in `app.py` lifespan** after AMQP connects:
+
+| Exchange | Routing Key | Handler |
+|----------|-------------|---------|
+| `jc.admin` | `node.*.register` | `handle_registration` |
+| `jc.admin` | `node.*.deregister` | `handle_deregistration` |
+| `jc.admin` | `node.*.pong` | `handle_pong` |
+| `jc.system` | `node.*.event` | `handle_event` |
+| `jc.system` | `cluster.coordinator.query` | `handle_coordinator_query` |
+
+### 11.5 API — `GET /api/cluster`
+
+New router `routers/cluster.py`:
+- `GET /api/cluster` — returns full cluster state: `{nodes, coordinator, events}` (last 50 events). No auth required.
+
+Wire `cluster.router` into `app.py`.
+
+### 11.6 Tests — `tests/test_cluster.py`
+
+Mock all aio-pika calls. Do not require live RabbitMQ.
+
+| # | Test | What it asserts |
+|---|------|-----------------|
+| 1 | Valid worker registration | Node admitted, CLUSTER_NODES updated, `cluster` event logged, `admitted` message published |
+| 2 | First coordinator auto-promotion | CLUSTER_COORDINATOR set, `cluster` event with "elected" message, `coord_response` published |
+| 3 | Duplicate node name rejected | `rejected` message with reason=`duplicate_node_name`, `cluster` event logged |
+| 4 | Malformed payload rejected | `rejected` message with reason=`malformed_payload` |
+| 5 | Graceful deregistration | Node removed, `cluster` event logged. If coordinator: CLUSTER_COORDINATOR cleared |
+| 6 | Pong from known node | last_seen updated, load/status refreshed |
+| 7 | Pong from unknown node | Warning logged, node NOT added |
+| 8 | Event stored in log | Event appended to CLUSTER_EVENTS; at 1001 entries the oldest is popped |
+| 9 | Coordinator query produces response | Response published with coordinator name and node list |
+| 10 | GET /api/cluster shape | Response contains `nodes`, `coordinator`, `events` keys |
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 12 — Roadmap N4: Worker Node Registration Publisher (Worker Side) [DONE]~~
+
+This task creates the worker node AMQP client that runs on worker (192.168.50.210). It is a standalone Python script — not part of the jC FastAPI app — that runs as a systemd service on worker.
+
+**Create `node_agent/agent.py`** in the repo (new directory).
+
+### 12.1 Config & Inventory Discovery
+
+On start, reads `/etc/caic-node-agent.conf` (INI format):
+- `node_name` — hostname, default from `socket.gethostname()`
+- `node_ip` — LAN IP, default from socket
+- `node_type` — `"worker"` (fixed)
+- `capabilities` — comma-separated list, e.g. `llm,rag`
+- `amqp_url` — RabbitMQ URL on coordinator, e.g. `amqp://caic:password@192.168.50.108:5672/caic`
+- `llama_port` — port llama-server/llama-rpc is listening on, default 8081
+- `models_dir` — path to GGUF model files, default `/var/lib/caic/models`
+- `active_model` — filename of currently active model (without path)
+
+Discovers inventory by globbing `models_dir` for `*.gguf` files and parsing name/version/quant from filename using regex pattern: `{name}-{version}-{quant}.gguf` where quant matches `Q[0-9]+_K_[A-Z]+` or similar standard suffixes.
+
+### 12.2 Registration
+
+Publishes registration to `jc.admin`, routing key `node.{node_name}.register`:
+```json
+{
+  "node_name": "worker01",
+  "node_type": "worker",
+  "ip": "192.168.50.210",
+  "capabilities": ["llm"],
+  "active_model": {"name": "...", "version": "...", "quant": "...", "path": "...", "port": 8081}
+}
+```
+
+### 12.3 Admission Response
+
+Listens on `node.{node_name}.admitted` and `node.{node_name}.rejected` (both `jc.admin`). Logs result. If rejected, exits with error.
+
+### 12.4 Ping Listener
+
+After admission: listens on `jc.admin`, routing key `node.{node_name}.ping`. On receipt, responds immediately (within 1 second) with a pong on `jc.admin`, routing key `node.{node_name}.pong`:
+
+```json
+{
+  "node_name": "worker01",
+  "type": "pong",
+  "correlation_id": "<echoed from ping>",
+  "status": "active",
+  "active_model": {"name": "...", "version": "...", "quant": "...", "path": "...", "port": 8081},
+  "load": {"cpu_pct": 45, "ram_pct": 62, "vram_pct": 38},
+  "timestamp": "<utc>"
+}
+```
+
+No periodic heartbeats. Worker sits idle between pings — coordinator only pings when it needs to route work.
+
+### 12.5 Model Swap Command Handler
+
+Listens on `jc.admin`, routing key `node.{node_name}.cmd.swap_model`:
+- Payload: `{model_filename: str}`
+- Stops current llama-server: `systemctl stop llama-server`
+- Updates `/etc/caic-node-agent.conf` active_model field
+- Starts llama-server: `systemctl start llama-server` (assumes service reads active_model from conf or ExecStart is updated)
+- Waits for llama-server to be healthy: poll `http://localhost:{llama_port}/v1/models` every 2s, timeout 120s
+- Publishes to `jc.system`, routing key `node.{node_name}.model_ready`:
+  ```json
+  {"node_name": "...", "active_model": "...", "port": ..., "timestamp": "..."}
+  ```
+- If startup fails within timeout: publishes `node.{node_name}.model_failed` with error detail
+
+### 12.6 Files & Tests
+
+**Create `node_agent/requirements.txt`:** `aio-pika>=9.0.0`
+
+**Document `/etc/caic-node-agent.conf` format** in a comment block at the top of `agent.py`.
+
+**Write `tests/test_node_agent.py`** covering:
+- Registration payload construction from config + model discovery — assert correct JSON shape
+- Model swap command handler: success path — assert systemctl calls made, model_ready published
+- Model swap command handler: timeout path — assert model_failed published
+- Ping handler: on ping, publishes pong with correct correlation_id
+- Agent starts idle after admission, no heartbeat timer
+
+Mock all aio-pika, subprocess, and httpx calls.
+
+**Do not create a systemd service file in this task** — that is a manual deployment step. Document the required service configuration in a comment at the bottom of `agent.py`.
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 13 — Roadmap N5: Query Routing via AMQP + Phi-4-mini Triage [DONE]~~
+
+This task wires the cluster into jC's chat flow. When a query arrives at `/api/chat`, instead of always routing to the hardcoded `LLAMA_SERVER_BASE`, jC now routes to the best available cluster node based on query context.
+
+**Prerequisites:** Tasks 9–12 complete. At least one worker node admitted to cluster.
+
+**Install Phi-4-mini on coordinator (infrastructure step):**
+- Download `Phi-4-mini-Instruct-Q4_K_M.gguf` from HuggingFace using `hf download microsoft/Phi-4-mini-instruct --include "*.Q4_K_M.gguf" --local-dir /var/lib/caic/models`
+- Create `/etc/systemd/system/llama-server-triage.service` — same pattern as existing llama-server service but: port 8083, model path points to Phi-4-mini GGUF, no `--rpc` flag (runs entirely on coordinator CPU/iGPU), description `Llama.cpp Server (Phi-4-mini — triage/routing)`
+- `systemctl daemon-reload && systemctl enable llama-server-triage && systemctl start llama-server-triage`
+- Verify: `curl -s http://localhost:8083/v1/models`
+
+**Add to `config.py`:**
+- `TRIAGE_BASE` — `http://127.0.0.1:8083/v1` (Phi-4-mini)
+- `TRIAGE_TIMEOUT` — 10 seconds
+- `FALLBACK_TO_DEFAULT` — True (if triage fails or no nodes available, fall back to `LLAMA_SERVER_BASE`)
+
+**Create `triage.py`** in the project root:
+
+```python
+async def classify_query(query: str) -> str
+    # Sends query to Phi-4-mini at TRIAGE_BASE with a classification system prompt.
+    # System prompt instructs model to respond with ONLY one of:
+    #   "general", "code", "search", "rag"
+    # Returns the classification string.
+    # Timeout: TRIAGE_TIMEOUT seconds.
+    # On any error: returns "general" (fail-safe).
+
+async def select_node(classification: str) -> dict | None
+    # Consults CLUSTER_NODES from cluster.py
+    # For "code": prefer nodes where active_model name contains "coder" or "qwen"
+    # For "general": prefer nodes where active_model name contains "mistral" or "llama"
+    # For "search" or "rag": return None (handled locally by jC)
+    # If no matching node found: return None (triggers FALLBACK_TO_DEFAULT)
+    # Returns NodeRecord dict for selected node, or None
+
+async def get_inference_url(query: str) -> str
+    # Combines classify_query + select_node
+    # Returns full base URL: f"http://{node.ip}:{node.active_model.port}/v1"
+    # Falls back to LLAMA_SERVER_BASE if classification=search/rag, no nodes, or triage error
+```
+
+**Update `routers/chat.py`:**
+- Replace the hardcoded `LLAMA_SERVER_BASE` reference with a call to `get_inference_url(user_message)`
+- The rest of the chat flow (RAG, memory, streaming) is unchanged — only the inference target URL changes
+
+**Write `tests/test_triage.py`** covering:
+- `classify_query()` returns valid classification — mock Phi-4-mini response
+- `classify_query()` on timeout — assert returns "general", no exception
+- `select_node("code")` with coder node in cluster — assert correct node returned
+- `select_node("general")` with no matching node — assert None returned
+- `get_inference_url()` with code query and coder node available — assert returns node URL
+- `get_inference_url()` with no nodes in cluster — assert returns LLAMA_SERVER_BASE fallback
+
+**Update `tests/test_chat_streaming_and_memory_paths.py`:**
+- Mock `triage.get_inference_url` to return a fixed URL in all existing tests so they continue to pass without a live cluster
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 14 — Roadmap N6: Model Swap Command Flow [DONE]~~
+
+**Status: Implemented and pushed (`9d1fd44`).** `request_model_swap()`, `handle_model_ready()`, `handle_model_failed()` in `cluster.py`, async `select_node()` with swap triggering in `triage.py`, `tests/test_model_swap.py` (9 tests). 177 tests pass.
+
+This task implements the coordinator-side logic for requesting a model swap on a worker node when the ideal model is not currently active.
+
+**Add to `cluster.py`:**
+
+```python
+async def request_model_swap(node_name: str, model_filename: str) -> bool
+    # Publishes to jc.admin exchange, routing key node.{node_name}.cmd.swap_model
+    # Payload: {model_filename, requested_at: iso_timestamp}
+    # Sets node status to "swapping" in CLUSTER_NODES
+    # Returns True if message published successfully
+
+async def handle_model_ready(message) -> None
+    # Handles node.{node_name}.model_ready from jc.system
+    # Updates CLUSTER_NODES[node_name].active_model to the new model
+    # Sets node status back to "active"
+    # Logs swap completion with timing
+
+async def handle_model_failed(message) -> None
+    # Handles node.{node_name}.model_failed from jc.system
+    # Sets node status to "error" in CLUSTER_NODES
+    # Logs failure with detail from message payload
+```
+
+**Subscribe in `app.py` lifespan:**
+- `jc.system` exchange, routing key `node.*.model_ready` → `handle_model_ready`
+- `jc.system` exchange, routing key `node.*.model_failed` → `handle_model_failed`
+
+**Update `triage.py` `select_node()`:**
+- If the best-matching node exists but its active_model does not match the ideal model for the classification, AND the node status is "active" (not already swapping):
+  - Call `request_model_swap(node_name, ideal_model_filename)`
+  - Return None (triggers fallback) — the swap happens async, next query will find the right model active
+- If node status is "swapping": return None (fallback, swap in progress)
+
+**Update `GET /api/cluster`** to include node status in response.
+
+**Write `tests/test_model_swap.py`** covering:
+- `request_model_swap()` — assert swap command published, node status set to "swapping"
+- `handle_model_ready()` — assert active_model updated, status set to "active"
+- `handle_model_failed()` — assert status set to "error"
+- `select_node()` with mismatched active model — assert swap requested, None returned
+- `select_node()` with node status "swapping" — assert None returned without publishing another swap
+
+Run full test suite. All existing tests must continue to pass.
+
+---
+
+## ~~TASK 15 — Roadmap N7: Cluster Status UI [DONE]~~
+
+Surface cluster awareness in the jC frontend (`templates/index.html`).
+
+**Add a cluster status panel** to the UI. Requirements:
+- Small status bar or collapsible panel, visible but unobtrusive
+- Polls `GET /api/cluster` every 15 seconds
+- For each admitted node: show node name, active model name, and a colored status dot:
+  - Green: active
+  - Yellow: swapping
+  - Red: error or offline (not seen in last 60 seconds based on last_seen timestamp)
+- If no nodes in cluster (empty): show "No worker nodes connected"
+- Panel must not interfere with chat input or conversation list
+
+**Update `GET /api/cluster` response** to include `last_seen` per node and a `status` field (`active`, `swapping`, `error`).
+
+**Update heartbeat handling in `cluster.py`:** add a handler for `node.*.heartbeat` on `jc.system` that updates `last_seen` timestamp for the node.
+
+**Subscribe in `app.py` lifespan:**
+- `jc.system` exchange, routing key `node.*.heartbeat` → `handle_heartbeat`
+
+**Add `handle_heartbeat()` to `cluster.py`:**
+- Updates `CLUSTER_NODES[node_name].last_seen` to current timestamp
+- If node was previously marked offline (not in CLUSTER_NODES), log re-registration warning but do not auto-admit — full registration required
+
+**Write `tests/test_cluster_heartbeat.py`** covering:
+- `handle_heartbeat()` for known node — assert last_seen updated
+- `handle_heartbeat()` for unknown node — assert no crash, warning logged, node not added
+
+Run full test suite. All 26+ existing tests must continue to pass.
+
+~~Commit all changes introduced across Tasks 9–15 with message: `feat: Roadmap N — AMQP cluster nervous system complete`~~
+
+---
+
+## Backlog (Post-Roadmap N) ⏳
+
+### ~~B1 — Context loss in follow-up questions [DONE]~~
+
+**Symptom:** After asking "in {context}, explain {b}", a follow-up "what is {b}'s {x}?" gets a non-sequitur response that ignores the original context.
+
+**Diagnosis:** `build_system_prompt()` is called fresh per-request with new RAG/memory results keyed to the current message text. These can change between turns and may dilute or override the conversation history. The original system prompt used for turn 1 (including its RAG context) is not stored in the DB — only user/assistant messages are. The inference server receives a different system prompt each turn.
+
+**Possible fixes:**
+- Store the assembled system prompt with each assistant message in the DB
+- When replaying history, re-send the original system prompts from DB rather than rebuilding
+- Or: cap RAG/memory injection to only fire on the first message of a conversation, then rely solely on conversation history for follow-ups
+- Check that llama-server isn't truncating history due to context window overflow (Mistral-Nemo 12B = 128K context, unlikely)
+
+### ~~B2 — Bang-prefixed search routing [DONE]~~
+
+**Spec:** If a query begins with `!`, route to SearXNG search instead of local inference.
+
+**Where:** In `routers/chat.py` `chat()` handler, after `user_message` is extracted. Strip the `!`, set a flag to always trigger auto-search regardless of perplexity/refusal.
+
+**Change:** Add a `force_search` flag when `user_message.startswith("!")`, strip the prefix from the message saved to DB, and route directly to the search+summarize path.
+
+### ~~B3 — Docker distribution (v1.0 gate) [DONE]~~
+
+**Goal:** Ship cAIc as a `docker compose` stack so a single command stands up everything.
+
+**Services to containerize:**
+- cAIc (FastAPI app + SQLite)
+- SearXNG
+- Qdrant
+- RabbitMQ
+- llama-server (with optional RPC sidecar for GPU offload)
+- Ollama (embeddings)
+
+**Also needed:**
+- `Dockerfile` for the cAIc app itself
+- `docker-compose.yml` with all services, volumes, networks, env vars
+- Setup wizard script (run on first boot) that:
+  - Probes CPU vs GPU (reuses `hardware.py`)
+  - Queries user for admin PIN, node name, IP
+  - Generates `.env` file with correct `LLAMA_SERVER_BASE`, `EMBED_URL`, etc.
+  - Auto-calculates `RAG_MAX_VECTORS` from available RAM: `max(1000, int(available_ram_gb * 100_000))`
+  - Optionally detects and configures RPC GPU offload
+- Manual install docs remain alongside for bare-metal deployment
+
+**This task is only actionable after Tasks 8–15 (RAG eviction + AMQP cluster) are complete.**
+
+---
+
+### ~~B4 — RAG Corpus Management UI (Display, Edit, CRUD) [DONE]~~
+
+**Goal:** Provide a management interface in the UI to browse, search, edit, and delete individual entries in the Qdrant-backed RAG corpus.
+
+**Backend — add to `routers/rag_admin.py`:**
+
+| Method | Endpoint | Description | Auth |
+|--------|----------|-------------|------|
+| GET | `/api/rag/points` | Return paginated list of RAG points with payload (text, source, date). Supports `?offset=0&limit=50&search=` query params | Admin |
+| GET | `/api/rag/point/{point_id}` | Return a single point with full payload | Admin |
+| DELETE | `/api/rag/point/{point_id}` | Delete a single point from Qdrant | Admin |
+| PATCH | `/api/rag/point/{point_id}` | Update a point's text payload (re-embed the new text) | Admin |
+
+Helper functions for Qdrant scroll/delete/update go in `rag.py` or `eviction.py`.
+
+**Frontend — add to `templates/index.html`:**
+
+A "RAG" button in the admin UI (drawer or settings modal) that opens a management panel:
+- **Stats bar**: vector count, max vectors, percent full, pinned sources
+- **Search bar**: text input to search the RAG corpus by semantic similarity
+- **Results table**: paginated list showing each vector's text snippet, source label, ingest date, retrieval count
+  - Click to expand full text
+  - Delete button per row (with confirmation)
+  - Edit button per row (inline text edit → re-embed on save)
+- **Bulk actions**: flush all (existing `/api/rag/flush`) with confirmation
+
+**Tests:**
+
+- `tests/test_rag_admin.py` — cover new endpoints: list, get, delete, update, admin-enforcement
+- Mock all Qdrant calls via monkeypatch
+
+Run full test suite. All existing tests must continue to pass.**

docs/jc-ingest.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+# jc-ingest.sh — pipe terminal commands into cAIc RAG
+# Deploy to /home/gramps/bin/jc-ingest.sh on jarvis (192.168.50.212)
+#
+# Usage:
+#   1. chmod +x /home/gramps/bin/jc-ingest.sh
+#   2. Add to ~/.bashrc:
+#        export CAIC_COMPLETIONS_API_KEY="$(cat /opt/jarvischat/.completions_key)"
+#        export PROMPT_COMMAND="jc_capture"
+#        source /home/gramps/bin/jc-ingest.sh
+#
+#   The PROMPT_COMMAND hook runs jc_capture() after each command.
+#   Only commands matching the filter pattern are ingested.
+#
+# Filter: currently captures git, pip, systemctl, sudo, vi/vim, curl,
+# wget, apt, python, pytest commands. Edit the grep pattern to adjust.
+
+JC_URL="http://192.168.50.212:8080/api/ingest"
+JC_TOKEN="${CAIC_COMPLETIONS_API_KEY}"
+
+jc_capture() {
+    local cmd
+    cmd=$(history 1 | sed 's/^[ ]*[0-9]*[ ]*//')
+    if echo "$cmd" | grep -qE '^(git|pip|systemctl|sudo|vi|vim|curl|wget|apt|python|pytest)'; then
+        curl -s -X POST "$JC_URL" \
+            -H "Authorization: Bearer $JC_TOKEN" \
+            -H "Content-Type: application/json" \
+            -d "{\"content\": $(echo "$cmd" | python3 -c 'import json,sys; print(json.dumps(sys.stdin.read().strip()))'), \"source\": \"terminal\"}" \
+            > /dev/null 2>&1 &
+    fi
+}

docs/wiki/Developer-Architecture.md

@@ -1,165 +1,332 @@
 # Developer Architecture Guide
 
-This document explains how JarvisChat is structured, why key guardrails exist, and what the test suite validates.
+This document explains how cAIc is structured, the external services it integrates with, and the key architectural changes made during development.
 
 ## 1. System Overview
 
-JarvisChat is a single-process FastAPI service with a Jinja2 frontend and SQLite persistence.
+cAIc is a single-process FastAPI service with a Jinja2 frontend and SQLite persistence. It connects to an external llama-server for inference and optionally to SearXNG (web search), Qdrant (vector search), and RabbitMQ (AMQP cluster messaging).
 
-Primary files:
+### 1.1 Module Layout
 
-- `app.py`: API, middleware, streaming/chat logic, auth, memory, skills, and DB bootstrap
-- `templates/index.html`: main WebUX, settings panels, auth flow, streaming UI handlers
-- `jarvischat.db`: runtime SQLite database created and migrated at startup
+Refactored from single-file (`app.py`) into modules under project root:
 
-Core runtime integrations:
+| File | Role |
+|------|------|
+| `app.py` | FastAPI app, middleware, router registration, lifespan |
+| `config.py` | Constants, env vars, rate/payload limits, built-in skills registry, upload limits, RAG eviction config |
+| `db.py` | SQLite schema, connection factory, settings helpers, upload_context CRUD |
+| `auth.py` | PIN-based guest/admin sessions, auth routes |
+| `security.py` | Rate limiting, origin checks, IP allowlist, audit/incident logging |
+| `memory.py` | FTS5 memory CRUD, remember/forget command parsing |
+| `search.py` | SearXNG integration, perplexity scoring, refusal detection |
+| `rag.py` | Qdrant vector search, system prompt assembly, chunk_text() helper, collection stats |
+| `eviction.py` | Score-based RAG eviction engine (extracted from rag.py) |
+| `gpu.py` | AMD GPU stats via rocm-smi |
+| `hardware.py` | Hardware self-assessment — CPU, RAM, VRAM, service health probes (llama-server, Qdrant, SearXNG, ComfyUI) |
+| `amqp.py` | aio-pika connection manager for RabbitMQ (connect, disconnect, publish, subscribe, auto-reconnect) |
+| `cluster.py` | Cluster node registry, event log, coordinator election, ping/pong, model swap handlers, image generation request/response |
+| `routers/` | One module per endpoint group |
 
-- Ollama for chat/model interaction
-- SearXNG for web search (optional)
-- wttr.in for weather shortcut queries
-- rocm-smi for GPU stats when available
+### 1.2 External Services
+
+| Service | Required | Port | Purpose |
+|---------|----------|------|---------|
+| llama-server (coordinator) | Yes | 8081 | LLM inference (OpenAI-compat), RPC offload to worker:50052 |
+| SearXNG | No | 8888 | Privacy-respecting web search |
+| Qdrant (coordinator) | No | 6333 | Vector database for RAG |
+| Ollama (worker) | No | 11434 | Embeddings for RAG chunk vectors |
+| ComfyUI (worker) | No | 8188 | Image generation (Stable Diffusion / Flux) |
+| RabbitMQ (coordinator) | No | 5672 | AMQP broker for cluster messaging |
+| rocm-smi | No | — | AMD GPU stats (host-level) |
+
+### 1.3 Config Discovery
+
+Key base URLs are configured via environment variables with sensible defaults:
+
+| Variable | Default | Service |
+|----------|---------|---------|
+| `LLAMA_SERVER_BASE` | `http://localhost:8081` | llama-server on the same node |
+| `OLLAMA_BASE` | `http://localhost:11434` | Legacy — all inference goes through LLAMA_SERVER_BASE |
+| `SEARXNG_BASE` | `http://localhost:8888` | SearXNG |
+| `QDRANT_URL` | `http://localhost:6333` | Qdrant on the same node |
+| `CAIC_AMQP_URL` | `amqp://caic:password@localhost:5672/caic` | RabbitMQ |
+| `CAIC_COMFYUI_BASE` | `http://localhost:8188` | ComfyUI (image gen) |
+| `CAIC_COMFYUI_TIMEOUT` | `120` | ComfyUI generation timeout (seconds) |
+
+> **Current deployment (single-node):** all services run on jarvis (192.168.50.212). The cluster/AMQP/node-agent layer is dormant — it degrades gracefully and can be re-enabled for a multi-node cluster later.
 
 ## 2. Request/Response Architecture
 
 ### 2.1 Chat Pipeline (`/api/chat`)
 
 1. Validate session, role, origin, rate, and payload limits in middleware
-2. Persist user message and conversation metadata
-3. Build system prompt from enabled profile, memory context, and active skills metadata
-4. Stream model response over SSE token-by-token
-5. Evaluate uncertainty/refusal; if needed, trigger search augmentation and stream augmented result
-6. Persist final assistant message and emit terminal SSE event
+2. Intercept "remember that..." / "forget about..." commands → process_remember_command()
+3. Persist user message and conversation metadata
+4. Build system prompt: profile + FTS5 memory + Qdrant RAG results + preset + active skills + uploaded document (if upload_context_id)
+5. Stream from llama-server with `logprobs: true` for perplexity scoring
+6. If perplexity > 15.0 OR refusal patterns match → re-query with SearXNG results
+7. Persist final assistant message and emit terminal SSE event
 
 ### 2.2 Explicit Search Pipeline (`/api/search`)
 
-1. Persist search-as-message into the target/new conversation
+1. Persist search-as-message into conversation
 2. Emit `searching` SSE event
 3. Pull web results from SearXNG
-4. Summarize with Ollama via SSE stream
-5. Persist summary and emit `done` event (plus raw results payload)
+4. Summarize via llama-server SSE stream
+5. Persist summary and emit `done` event
 
-### 2.3 Settings/Control Surface
+### 2.3 RAG Ingest Pipeline (`/api/ingest`)
 
-- Profile, presets, memory, conversation management, and settings APIs
-- Skills APIs for phase-1 registry and enable/disable controls
-- Auth/session APIs for guest/admin role handling and keepalive
+1. Bearer token auth (same key as completions API)
+2. Chunk text via shared `chunk_text()` helper (512-token chunks, 128-token overlap)
+3. Embed via Ollama `/api/embeddings`
+4. Upsert to Qdrant collection `caic_rag`
+5. Trigger `maybe_evict()` if collection exceeds high-water mark
+
+### 2.4 Upload Pipeline (`/api/upload`)
+
+1. Admin required, multipart file upload
+2. Validate MIME type + size against config limits
+3. PDF text extraction via pypdf; plain text for all other types
+4. Three modes: `context` (SQLite with 1hr expiry), `ingest` (RAG/Qdrant), `both`
+5. Trigger `maybe_evict()` if ingest mode
+
+### 2.5 Image Generation Pipeline (`POST /api/image/generate`)
+
+1. Admin required, JSON body with prompt and optional params (width, height, steps, seed, model)
+2. Find active node with `image_gen` capability via `_find_image_node()`
+3. Publish `cmd.image_generate` via AMQP to selected worker node
+4. Worker node agent builds ComfyUI workflow (CheckpointLoader → KSampler → VAEDecode → SaveImage)
+5. Worker polls ComfyUI `/history/{prompt_id}` until image is ready
+6. Worker fetches PNG from ComfyUI `/view` endpoint, base64-encodes, publishes `image_generated` on `jc.system`
+7. Coordinator receives response, decodes base64, returns `image/png` to client
+8. `GET /api/image/status` returns available image gen nodes and their status
 
 ## 3. Data Model (SQLite)
 
 Key tables:
 
-- `conversations`: conversation headers and timestamps
-- `messages`: ordered chat history entries
-- `profile`: singleton row for injected profile prompt
-- `settings`: runtime toggles and selected defaults
-- `system_presets`: named reusable system prompts
-- `skills`: per-skill enabled state and timestamp
-- `memories` (FTS5 virtual table): searchable user memory facts
+- `conversations` — headers, timestamps, attachment_count
+- `messages` — ordered chat history per conversation
+- `profile` — singleton row for injected profile prompt
+- `settings` — runtime toggles and selected defaults
+- `system_presets` — named reusable system prompts
+- `skills` — per-skill enabled state and timestamp
+- `memories` (FTS5 virtual table) — full-text searchable user memory facts
+- `upload_context` — auto-expiring document storage for context injection
 
 Design notes:
-
-- Startup is idempotent: tables are created if missing and defaults seeded only when absent
-- No connection pool: each request opens a short-lived SQLite connection
+- Startup is idempotent: tables created if missing, defaults seeded only when absent
+- No connection pool: each request opens and closes a short-lived SQLite connection
+- `init_db()` called in FastAPI lifespan
 
 ## 4. Security Implementations
 
-This section documents explicit controls currently in code.
-
 ### 4.1 Auth Model
 
-- Guest session is default for conversational access
-- Admin unlock uses 4-digit PIN and creates admin-capable session
-- Admin required for write/destructive routes
-- Session heartbeat/timeout and explicit logout/revoke flow
+- Guest session by default (POST /api/auth/guest)
+- Admin unlock via 4-digit PIN (POST /api/auth/login)
+- Admin required for PUT/DELETE/PATCH + all POST except allowlist (/api/chat, /api/search, /api/auth/*)
+- /api/ingest is exempt from session auth — self-authenticates via Bearer token
+- Session heartbeat/timeout (90s default) and explicit logout
 
-### 4.2 PIN and Session Hardening
+### 4.2 PIN Hardening
 
 - Admin PIN hashed with PBKDF2-HMAC-SHA256 + salt
-- Failed PIN attempts tracked per client IP
-- Lockout window enforced after max failed attempts
+- Failed PIN attempts tracked per client IP (max 5, 300s lockout)
+- Default PIN allowed only if CAIC_ALLOW_DEFAULT_PIN=true
 
 ### 4.3 Browser and API Abuse Controls
 
-- Origin checks on state-changing requests
-- Rate limiting by endpoint category and identity (IP/session)
-- Payload size limits per route class
-- Settings key allowlist to block arbitrary configuration injection
-- IP allowlist/CIDR gate with optional trusted proxy forwarding mode
+- Origin checks on all /api/ requests (rejects absent Origin AND Referer)
+- Rate limiting per endpoint category and identity (IP/session)
+- Payload size limits per route class (64KB default, 128KB chat, 20MB upload)
+- Settings key allowlist (5 keys: profile_enabled, default_model, etc.)
+- IP allowlist/CIDR gate with trusted proxy forwarding mode
 
 ### 4.4 Output and Error Safety
 
-- Search result URLs sanitized to `http`/`https` only
+- Search result URLs sanitized to http/https only
 - Client-safe error envelopes with incident key correlation
-- Full stack traces and diagnostic metadata logged server-side only
+- Full stack traces logged server-side only
 
 ### 4.5 Operational Auditability
 
-- Structured audit events for auth actions, admin operations, and guardrail denials
-- Incident logs include event type, key, path/method context, and runtime metadata
+- Structured audit events for auth actions, admin ops, guardrail denials
+- Incident logs with event type, key, path/method, and runtime metadata
 
-## 5. Skills Framework (Phase 1)
+## 5. RAG Architecture
 
-Goal: introduce a governed skills control plane inside the local JarvisChat sandbox.
+### 5.1 Vector Search
 
-Current behavior:
+- Qdrant collection `caic_rag` on coordinator:6333
+- Embeddings via Ollama on worker:11434 (`/api/embeddings`)
+- Shared `chunk_text(text, chunk_size=512, overlap=128)` helper in rag.py
+- Upload and ingest endpoints share the same chunk+embed+upsert pipeline
 
-- Built-in skill registry defined server-side
-- Per-skill enable/disable persisted in DB
-- Global `skills_enabled` master toggle in settings
-- Active skills injected into system prompt with bounded text budget
-- API endpoints to list skills, list active skills, and toggle skill state
-- WebUX settings panel to control master/per-skill toggles
+### 5.2 Score-Based Eviction
 
-Non-goals in phase 1:
+When `RAG_MAX_VECTORS` is exceeded, eviction fires with hysteresis:
 
-- No unrestricted shell/tool execution
-- No external connector execution (filesystem, Gmail, etc.)
+- High-water mark: 80% of max → trigger eviction
+- Low-water mark: 20% of max → stop eviction
+- Batch size: 1000 vectors per cycle
+- Score formula: `score = (access_weight * retrieval_count) + (age_weight * hours_since_ingested)`
+- Lower score evicted first (least useful)
+- Tiebreaker: oldest last_accessed ASC
+- Excluded sources: `upload`, `profile` (pinned)
+- Grace period: 1 hour before any vector is eligible
+- Thread-safe via `asyncio.Lock`
 
-## 6. Testing Strategy and Validation Intent
+Eviction module at `eviction.py` (re-exported through `rag.py` for backward compat).
 
-The test suite validates both behavior and guardrail assumptions.
+### 5.3 Operational Stats
 
-### 6.1 What We Test
+`GET /api/rag/stats` (admin required) returns:
+- vector_count, max_vectors, high_water_pct, low_water_pct, percent_full
+- pinned_sources list, grace_hours
+- at_risk_count, pinned_count, avg_retrieval_count
+- eviction_counts_last_{1,5,30}m
 
-- Auth capability separation (guest vs admin)
-- URL sanitization safety for outbound links
-- Rate and payload guardrails
-- IP allowlist behavior
-- Safe error envelope behavior and SSE error leakage prevention
-- Streaming chat/search and memory command paths
-- Skills framework toggles and prompt-injection behavior
+### 5.4 Flush
 
-### 6.2 Why These Tests Matter
+`POST /api/rag/flush` (admin required) — deletes all non-pinned vectors. Returns `{deleted_count, collection, status}`.
 
-- Confirms security controls are active and regression-resistant
-- Ensures streaming UX protocol remains stable (`token`, `searching`, `done`, `error`)
-- Verifies policy intent: dangerous actions require admin capability
-- Validates new features preserve prior guarantees
+## 6. Cluster Architecture
 
-### 6.3 Internal Process Validation
+### 6.1 Design Model: Broker-Mediated
 
-For substantive changes, Definition of Done includes:
+cAIc uses a **broker-mediated** cluster design. This is the preferred architecture and is reflected in all implementation decisions below.
 
+**How it works:**
+- A single RabbitMQ broker (or clustered set of brokers) acts as the central nervous system
+- **Coordinator nodes** run the FastAPI app, host the HTTP API/UI, and publish commands to the broker
+- **Worker nodes** connect as AMQP *clients only* — they consume commands and publish status events, but run no broker software themselves
+- Communication is asynchronous and persistent: each node opens a TCP connection on startup and keeps it alive. The coordinator probes worker health via on-demand AMQP ping/pong messages (5s timeout) rather than relying on the AMQP-0-9-1 transport-level heartbeat.
+
+**Why broker-mediated:**
+- Workers are heterogeneous (different GPUs, different models, ARM vs x86) — no assumption of uniform software
+- Workers are lightweight — a Raspberry Pi with a USB AI accelerator can participate without running a broker
+- The coordinator delegates work via messages, not by SSH'ing into workers or requiring shared filesystems
+- Failure is isolated: a crashed worker stops responding to ping; the coordinator auto-deregisters it and reassigns its work
+
+**What it is NOT:**
+- Not a service mesh — workers do not run identical software stacks
+- Not autonomous failover — if the coordinator dies, a replacement must be manually promoted (or pre-configured as a secondary coordinator). Workers cannot self-promote to coordinator because they lack the required services (FastAPI, SQLite, DB schema, SearXNG, Qdrant, etc.)
+- Not a peer-to-peer cluster — all orchestration flows through the coordinator
+
+### 6.2 Node Types
+
+Every physical machine in the cluster is classified by which services it runs. Two node types are defined:
+
+| Aspect | Coordinator | Worker |
+|--------|------------|--------|
+| **Role** | Serves HTTP API/UI, orchestrates inference, owns cluster state | Runs inference models on behalf of the coordinator |
+| **Python** | Required — runs FastAPI app | Required — runs node agent (aio-pika consumer) |
+| **RabbitMQ server** | Required — hosts the broker | Not required — connects as AMQP client only |
+| **RabbitMQ client (aio-pika)** | Required — publishes commands, consumes events | Required — consumes commands, publishes events |
+| **FastAPI / uvicorn** | Required | Not needed |
+| **SQLite** | Required — owns caic.db | Not needed |
+| **Qdrant** | Optional (recommended) — vector DB for RAG | Not needed |
+| **SearXNG** | Optional — web search | Not needed |
+| **llama-server** | Optional — can share its own GPU for inference | Required — this is why the worker exists |
+| **Ollama** | Optional — embeddings for RAG | Not needed |
+| **rocm-smi / nvidia-smi** | Optional — hardware stats | Optional — node agent reports this at registration |
+
+### 6.3 Service Distribution Summary
+
+```
+Coordinator                          Worker(s)
+┌────────────────────┐               ┌──────────────────────────┐
+│  cAIc              │               │  llama-server            │
+│  (FastAPI + SQLite)│               │  (inference)             │
+│  RabbitMQ server   │◄──AMQP───────│  aio-pika (agent)        │
+│  SearXNG (opt)     │    persistent │  ROCm / CUDA (if GPU)    │
+│  Qdrant (opt)      │    TCP        │  Ollama (embeddings,opt) │
+│  llama-server(opt) │    conn       │                          │
+└────────────────────┘               │  No broker               │
+                                     │  No cAIc                 │
+                                     │  No DB                   │
+                                     │  No search/vector        │
+                                     └──────────────────────────┘
+```
+
+### 6.4 RabbitMQ Topology
+
+Every RabbitMQ server belongs to a cluster. Currently only the coordinator runs one; if high availability is needed, additional nodes can join the RMQ cluster without changing the architecture.
+
+| Exchange | Type | Purpose |
+|----------|------|---------|
+| `jc.admin` | topic | Lifecycle commands: register, deregister, ping, pong, admitted, rejected; model commands: cmd.swap_model; image commands: cmd.image_generate |
+| `jc.system` | topic | Events: model_ready, model_failed, image_generated, image_failed, node.*.heartbeat, event; coordinator queries: coord_query, coord_response |
+
+All exchanges, queues, and bindings are declared by `amqp.py` at startup. Worker runs `node_agent/agent.py` which connects as an AMQP client, registers, responds to ping, and handles model swap commands.
+
+## 7. SSE Protocol
+
+All streaming endpoints yield `data: {json}\n\n`:
+
+- `{token, conversation_id}` — streaming token
+- `{searching: true}` — web search triggered
+- `{search_results: N}` — N results found (no raw payload)
+- `{done: true, perplexity, tokens_per_sec, searched?}` — terminal
+- `{error: "...", error_key: "..."}` — error with incident key
+
+## 8. Testing Strategy
+
+### 8.1 Test Framework
+
+- pytest with `tmp_path` + monkeypatched httpx.AsyncClient
+- No live external services required
+- Test factories reset `SESSIONS`, `PIN_ATTEMPTS`, `RATE_EVENTS` globals per test
+
+### 8.2 Test Coverage Areas (228 tests)
+
+| Test file | Coverage |
+|-----------|----------|
+| test_auth_capabilities.py | Guest/admin sessions, origin blocking, logout |
+| test_chat_streaming_and_memory_paths.py | Streaming, auto-search, remember/forget, upload context injection, private chat |
+| test_cluster.py | Registration, deregistration, pong, events, coordinator query |
+| test_cluster_heartbeat.py | Heartbeat handler, known/unknown node |
+| test_completions.py | API key auth, FIM, streaming, blocking, errors |
+| test_conversations.py | Full CRUD, guest admin, attachment_count |
+| test_error_envelopes.py | Global exception handler + stream errors |
+| test_gpu.py | GPU stats — rocm-smi (Linux), system_profiler (Darwin/Apple Silicon) |
+| test_hardware.py | Hardware assessment, service reachability |
+| test_image.py | Image generation — cluster handlers, router proxy, node agent ComfyUI integration, hardware probe, capability detection |
+| test_ingest.py | Bearer auth, chunk/embed/upsert, validation |
+| test_ip_allowlist.py | IP allowlist helper + middleware |
+| test_memories.py | Edit, search, stats |
+| test_model_pull.py | Default model auto-pull — llama-server check, Ollama fallback, error paths |
+| test_model_swap.py | request_model_swap, handle_model_ready/failed, select_node swap triggering |
+| test_models_router.py | Models list, ps, show, stats, search/status |
+| test_node_agent.py | Node agent registration, ping/pong, model swap |
+| test_presets.py | Full CRUD, default preset protection |
+| test_profile.py | Get, update, default, length validation |
+| test_rag_management.py | Collection stats, eviction algorithm, hysteresis, flush |
+| test_rate_and_payload_guardrails.py | Rate limits + payload size |
+| test_search_route.py | Explicit search flow, no results, errors |
+| test_search_url_sanitization.py | URL sanitizer |
+| test_settings_allowlist.py | Allowlisted key enforcement |
+| test_skills_framework.py | List, toggle, unknown skill, prompt injection |
+| test_upload.py | Upload, delete, link, by-conversation, attachment_count |
+
+### 8.3 DoD Process
+
+For substantive changes:
 1. Implement code change
 2. Add/adjust tests proving behavior and guardrail intent
-3. Update README release notes for user-facing impact
-4. Update wiki architecture/security/testing docs for maintainers
-5. Validate with targeted test runs before merge/deploy
+3. Update this wiki and README in the same change set
+4. Validate with full test run before commit
 
-This process is intentionally explicit so design decisions remain auditable over time.
+## 9. Hardware Self-Assessment
 
-## 7. Deployment and Operations Notes
+On startup, `assess_hardware()` probes:
+- RAM total/available (psutil)
+- VRAM total/free (rocm-smi, best-effort)
+- llama-server reachability + model list
+- Qdrant reachability + collection list
+- SearXNG reachability
+- ComfyUI reachability + checkpoint model list
 
-- Primary deployment target: local/homelab systemd service
-- Required dependency: Ollama
-- Optional dependency: SearXNG
-- Recommended log review path: system journal for startup, guardrail denials, and incidents
-
-## 8. Contribution Guidance
-
-When adding a feature:
-
-1. Define security posture first (who can execute, what can fail, and failure mode)
-2. Implement smallest safe slice with clear limits
-3. Add tests that prove both happy path and guardrail path
-4. Update this wiki and README in the same change
+Writes `hardware_state.json` to working directory.

docs/wiki/Home.md

@@ -1,6 +1,6 @@
-# JarvisChat Developer Wiki
+# cAIc Developer Wiki
 
-This wiki is the developer-facing architecture and process reference for JarvisChat.
+This wiki is the developer-facing architecture and process reference for cAIc.
 
 ## Audience
 
@@ -14,7 +14,7 @@ This wiki is the developer-facing architecture and process reference for JarvisC
 
 ## Scope and Support Model
 
-JarvisChat is designed for local and trusted-LAN operation.
+cAIc is designed for local and trusted-LAN operation.
 
 The code may technically function against external or commercial endpoints, but this deployment mode is not a supported target in this project.
 

docs/wiki/WireGuard-Setup.md

@@ -0,0 +1,194 @@
+# WireGuard Tunnel — Encrypted Node Transit
+
+> **Status: dormant (single-node deployment).** All cAIc services currently run on one node (jarvis, 192.168.50.212), so there is no inter-node traffic to encrypt. This document is kept as a reference for when a multi-node cluster is stood back up.
+
+## Why
+
+cAIc cluster traffic is plaintext today:
+
+| Traffic | Protocol | Plaintext risk |
+|---------|----------|----------------|
+| AMQP (coordinator ↔ worker agent) | TCP :5672 | Registration, ping/pong, swap commands |
+| Inference (coordinator → worker llama-server) | HTTP :8081 | Every token generated |
+| LLM RPC layer offload (coordinator llama-server → worker) | TCP :50052 | Internal llama.cpp protocol |
+
+WireGuard encrypts all three at the network layer with zero application changes. The cAIc app keeps using `http://` URLs — it's just talking to a virtual IP whose traffic is automatically encrypted before it hits the wire.
+
+## Topology
+
+```
+┌───────────────────────┐      WireGuard tunnel       ┌───────────────────────┐
+│  Coordinator (ultron)  │◄═══════════════════════════►│  Worker (jarvis)      │
+│  10.0.2.1              │         UDP :51820          │  10.0.2.2              │
+│  LAN 192.168.50.108    │                             │  LAN 192.168.50.210    │
+│                        │════════════════════════════►│                        │
+│                        │         UDP :51820          │  Worker (corsair)      │
+│                        │                             │  10.0.2.3              │
+│                        │                             │  LAN (DHCP)            │
+└───────────────────────┘                             └───────────────────────┘
+```
+
+All nodes connect directly to the coordinator's WireGuard endpoint (star topology). Workers do not need to talk to each other.
+
+## Prerequisites
+
+```bash
+# Debian / Ubuntu
+sudo apt install wireguard
+
+# Windows / WSL2 — install WireGuard from https://www.wireguard.com/install/
+# The wg.exe binary is used inside WSL2; the Windows GUI manages the tunnel config
+```
+
+## Key Generation
+
+Run once per node. Save the private key securely; public keys go into peer configs on the other end.
+
+```bash
+wg genkey | tee /etc/wireguard/private.key | wg pubkey > /etc/wireguard/public.key
+chmod 600 /etc/wireguard/private.key
+```
+
+**Recorded keys for this deployment:**
+
+| Node | Private key | Public key |
+|------|-------------|------------|
+| ultron | (node private) | `ultron_pubkey=` |
+| jarvis | (node private) | `jarvis_pubkey=` |
+| corsair | (node private) | `corsair_pubkey=` |
+
+## Per-Node Configs
+
+### Coordinator — `/etc/wireguard/wg0.conf` on ultron
+
+```ini
+[Interface]
+Address = 10.0.2.1/24
+ListenPort = 51820
+PrivateKey = <ultron_private_key>
+
+# Enable IP forwarding so workers can route through coordinator if needed
+# sudo sysctl -w net.ipv4.ip_forward=1
+# sudo sysctl -w net.ipv6.conf.all.forwarding=1
+
+# Worker: jarvis
+[Peer]
+PublicKey = <jarvis_pubkey>
+AllowedIPs = 10.0.2.2/32
+# If jarvis is off-site, put its public IP / DDNS hostname here:
+# Endpoint = jarvis.example.com:51820
+# If jarvis is LAN-only, set PersistentKeepalive = 25 to maintain NAT binding:
+# PersistentKeepalive = 25
+
+# Worker: corsair
+[Peer]
+PublicKey = <corsair_pubkey>
+AllowedIPs = 10.0.2.3/32
+```
+
+### Worker — `/etc/wireguard/wg0.conf` on jarvis (Linux)
+
+```ini
+[Interface]
+Address = 10.0.2.2/24
+ListenPort = 51820
+PrivateKey = <jarvis_private_key>
+
+# Coordinator
+[Peer]
+PublicKey = <ultron_pubkey>
+AllowedIPs = 10.0.2.0/24
+# LAN-only: just point at the LAN IP
+Endpoint = 192.168.50.108:51820
+# Off-site: use DDNS or static IP:
+# Endpoint = ultron.example.com:51820
+PersistentKeepalive = 25
+```
+
+### Worker — Windows / WSL2 on corsair
+
+Create a WireGuard tunnel in the Windows GUI app with the same config as jarvis above (Address=10.0.2.3/24). WSL2 inside Windows can reach the tunnel IP via the Windows host.
+
+If llama-server runs inside WSL2 on corsair, the Windows host's WireGuard tunnel IP `10.0.2.3` is reachable from the WSL2 instance as well — just bind llama-server to `0.0.0.0` (already the default) and configure the Windows firewall to allow inbound on :8081 from the coordinator's WireGuard IP.
+
+## Starting the Tunnel
+
+```bash
+# Start immediately
+sudo systemctl start wg-quick@wg0
+
+# Enable on boot
+sudo systemctl enable wg-quick@wg0
+
+# Check status
+sudo wg show
+```
+
+Expected output on each node:
+
+```
+interface: wg0
+  public key: <...>
+  private key: (hidden)
+  listening port: 51820
+
+peer: <ultron_pubkey>
+  endpoint: 192.168.50.108:51820
+  allowed ips: 10.0.2.0/24
+  latest handshake: 5 seconds ago  ← healthy
+  transfer: 1.2 KiB received, 3.4 KiB sent
+```
+
+If `latest handshake` is missing, check firewall rules (UDP :51820 must be open on all nodes).
+
+## Verification
+
+```bash
+# From any node, ping another node's WireGuard IP
+ping -c 3 10.0.2.1   # coordinator
+ping -c 3 10.0.2.2   # jarvis
+ping -c 3 10.0.2.3   # corsair
+
+# Verify cAIc inference through the tunnel
+curl http://10.0.2.2:8081/v1/models   # jarvis llama-server
+curl http://10.0.2.3:8081/v1/models   # corsair llama-server
+```
+
+## Updating cAIc to Use the Tunnel
+
+Once WireGuard is running, point each service at the tunnel IP instead of the LAN IP.
+
+### Worker node agent config — `/etc/caic-node-agent.conf`
+
+```ini
+[agent]
+node_name = jarvis
+node_ip = 10.0.2.2           # was 192.168.50.210
+node_type = worker
+capabilities = llm
+amqp_url = amqp://caic:password@10.0.2.1:5672/caic  # was 192.168.50.108
+llama_port = 8081
+models_dir = /var/lib/caic/models
+active_model = qwen2.5-7b-instruct-Q5_K_M.gguf
+```
+
+### Coordinator config — environment variables
+
+```bash
+# On the coordinator node, override the worker-facing addresses
+# (LLAMA_SERVER_BASE stays as localhost / LAN IP since inference
+#  to the coordinator's own llama-server stays on-machine)
+export CAIC_AMQP_URL="amqp://caic:password@10.0.2.1:5672/caic"
+```
+
+No other cAIc code changes are needed. The app already reads `CAIC_AMQP_URL` from the environment (`config.py:27`) and the node agent reads `node_ip` from its INI file. Inference requests routed to remote workers via `triage.py` use the IP the worker registered — so setting `node_ip = 10.0.2.2` in the worker's agent config is all it takes.
+
+## Cross-Site Deployment Checklist
+
+When placing a worker outside the LAN:
+
+1. **Firewall:** Open UDP :51820 on the remote site. On the coordinator side, make sure UDP :51820 is reachable from the internet (port forward / firewall rule at the coordinator's router).
+2. **DDNS:** If the coordinator's public IP is dynamic, set up a DDNS hostname and use it in the worker's `Endpoint = ultron.example.com:51820`.
+3. **PersistentKeepalive:** Set `PersistentKeepalive = 25` on the worker side to keep NAT bindings alive.
+4. **No double encryption:** WireGuard encrypts everything on the WireGuard interface. The cAIc app continues to use `http://` — it never touches raw TLS. This is correct and intended.
+5. **Split tunnelling (optional):** The worker's `AllowedIPs = 10.0.2.0/24` ensures only cluster traffic goes through the tunnel. All other internet traffic from the worker uses its normal gateway.

docs/wiki/current-wip.md

@@ -1,86 +1,31 @@
-# JarvisChat Current WiP Backlog
+# cAIc Current WiP Backlog
 
-Last updated: 2026-04-27
-Owner: Gramps + Copilot
-Scope: issues, bugs, security exposures, and feature enhancements.
+Last updated: 2026-07-27
+Owner: Gramps
+Scope: Active roadmap items and backlog.
 
-Total identified items: 29
+## In Progress
 
-## Priority Definitions
-- P0: Critical risk or data-loss/security exposure; do first.
-- P1: High impact reliability/correctness work.
-- P2: Important feature/UX improvements.
-- P3: Nice-to-have polish.
+- **Image Generation Service** — Backend wired: cluster handlers, `POST /api/image/generate` proxy, node agent ComfyUI integration, hardware probe, 27 tests. ComfyUI install pending on jarvis (single-node).
 
-## Top 10 (Urgency Order)
-1. [P0][DONE] Add authentication/authorization for all write and admin endpoints.
-2. [P0][DONE] Add CSRF/origin protection for browser-initiated state-changing requests.
-3. [P0][DONE] Block unsafe URL schemes in rendered search-result links (e.g., javascript:).
-4. [P0][DONE] Add rate limiting and request body size limits for chat/search/profile APIs.
-5. [P1][DONE] Restrict settings updates to an allowlist of valid keys.
-6. [P1] Add pagination + hard caps on list endpoints (memories, conversations, message history).
-7. [P1][DONE] Stop returning raw exception text to clients; use safe error envelopes.
-8. [P1][DONE] Add automated tests for chat streaming, auto-search trigger, and memory command paths.
-9. [P2][DONE] Implement skills/tool-call framework (MCP-style) with per-skill enable controls.
-10. [P2] Implement heartbeat/check-in pipeline with scheduler + summary endpoint.
+## Completed
 
-## Item 1 Executive Summary (Scope + Security)
+- **Single-node consolidation (2026-08-08)** — all cAIc services moved onto jarvis (192.168.50.212): llama-server, Qdrant, SearXNG, RabbitMQ, Ollama, ComfyUI. Config defaults (`COMFYUI_BASE`, AMQP URL, `NODE_NAME`) updated; cluster/AMQP layer left dormant (degrades gracefully). Project renamed `jarvisChat` → **cAIc**.
 
-- Status: Complete. Guest/admin capability split implemented with admin-only write enforcement, origin checks on state-changing requests, audit logging, and endpoint capability tests.
+- **B8 (v0.19.3)** — Private Chat mode. Backend skip-DB/skip-RAG/skip-search flag, frontend PRIVATE badge, info popup.
+- **WireGuard TLS (v0.19.4)** — Self-signed WireGuard mesh encrypts all inter-node traffic (AMQP, inference, RPC). No code changes to cAIc. Documented in wiki/WireGuard-Setup.md + docker.md §5.4.
+- **At-Rest Encryption (v0.20.0)** — AES-256-GCM encrypts all query-derived text at rest. crypto.py with auto-keygen, key stored as `heartbeat_interval_ms` in settings. All 12 storage paths wired (SQLite: messages, conversations, memories, upload_context; Qdrant: RAG chunks, ingest, upload). 200 tests pass.
+- **v0.21.0** — Scrollbar/DOM fixes, perplexity persistence per message, all service URLs env-overridable, single-node deployment docs, DOM pairing bugfix, hardware.py Qdrant URL bugfix.
+- **v0.22.0** — B4 RAG Corpus Management UI: paginated browse, semantic search, source filter, edit with re-embed, single-point delete, bulk flush. `routers/rag_admin.py` expanded with 4 new endpoints; `CLAUDE.md` → `ai.md` rename.
+- **v0.22.0+** — RAG bugfixes (collection name mismatch, `vectors_count`→`points_count`, unindexed `order_by` crash, embeds server URL). Topbar redesign (stats to bottom strip, toggles to ⋮ hamburger, palette next to version, mobile-responsive).
 
-- Decision: JarvisChat is local-first by design. Primary mode is same-host Ollama; optional mode allows RFC1918 LAN endpoints only.
-- Constraint: Public Internet AI endpoints are out of scope unless explicitly enabled in a future advanced mode.
-- Risk: Even on LAN, unauthenticated write/admin endpoints permit unauthorized data tampering and deletion.
-- Requirement: Add mandatory admin authentication for all POST/PUT/DELETE routes and destructive actions.
-- Authentication shape (scope-locked): two capability tiers only: guest (chat-only) and admin (4-digit PIN unlock).
-- Scope guardrail: Avoid full RBAC. Keep capability split minimal: conversational chat for guest, advanced/destructive actions for admin.
-- Definition of done:
-	1. Auth required on all state-changing endpoints.
-	2. Destructive actions require admin authorization.
-	3. Endpoint configuration rejects non-local/non-RFC1918 AI backends by default.
-	4. Strong rate limiting + lockout controls in place for PIN attempts.
-	5. Security events logged for failed and successful admin actions.
+## Backlog
 
-## Full Backlog (Sorted by Priority)
-
-### P0 Critical
-1. Add auth for write/admin endpoints (`POST/PUT/DELETE` routes, mass delete, profile/settings changes).
-2. Add CSRF or strict origin checks for browser session protection.
-3. Validate/sanitize outbound href URLs before rendering in HTML (allow http/https only).
-4. Add per-IP rate limiting on `/api/chat`, `/api/search`, `/api/profile`, `/api/settings`.
-5. Enforce request size limits (message/profile text and JSON body) to prevent memory abuse.
-
-### P1 High
-6. Add settings key allowlist in `/api/settings` to prevent arbitrary key injection.
-7. Add pagination (`limit`, `offset`) with enforced maximums for list APIs.
-8. Add DB indexes and query hygiene for scalability (`messages.conversation_id`, timestamps).
-9. Replace raw exception leakage to clients with generic safe error messages + server-side logs.
-10. Add request/response timeout and retry policy consistency across external calls.
-11. Add endpoint-level audit logging for destructive operations.
-12. Add unit/integration tests for: remember/forget parsing, refusal detection, search fallback, SSE done/error shape.
-13. Add conversation title sanitization and length constraints.
-14. Ensure default preset semantics are correct (currently all seeded presets are marked default).
-15. Add preflight validation for required model/preset selection and block send with clear user guidance instead of timing out.
-
-### P2 Important Features
-16. HTTPS via Let's Encrypt: set up reverse proxy (Caddy or Nginx) with auto-cert to fix clipboard API and enable secure context features.
-17. Bidirectional image I/O: load multimodal models for both vision understanding (image inputs, describe/answer) and image generation (diffusion model or multimodal output). Enable image upload/paste and AI-generated image display in chat.
-18. Skills system: load markdown skill files with YAML frontmatter from skills directory.
-19. Skills registry API: list/enable/disable skills and expose active skills to UI.
-20. Inject active skill instructions into system prompt with bounded token budget.
-21. Tool execution guardrails: allowlist, confirmation mode, and execution logs.
-22. Heartbeat scheduler (cron/systemd timer) for daily check-ins.
-23. Heartbeat endpoint for generated briefings and anomaly summaries.
-24. Model info UI panel (description, updated date, best-use purpose).
-25. Default model selection improvements and persistence validation.
-26. Hidden model list support (exclude models from dropdown).
-27. Model update action from UI (trigger controlled model pull).
-
-### P3 Nice to Have
-28. Conversation search/filter and export tooling.
-29. Keyboard shortcuts, retry button, and source-link polish.
+- B3 — Docker distribution (planning doc at `docker.md`, not yet implemented)
+- HTTPS / reverse proxy (Caddy)
+- Conversation search/filter and export tooling
+- Keyboard shortcuts, retry button, source-link polish
 
 ## Maintenance Rules
-- Keep this file as the single source of truth.
-- Update item priority/status whenever work starts or completes.
-- Mirror the Top 10 summary in README and keep counts aligned.
+- Keep this file as the single source of truth for roadmap tracking.
+- Update as work starts or completes.

eviction.py

@@ -0,0 +1,269 @@
+"""
+cAIc — Score-based RAG vector eviction with hysteresis.
+"""
+import asyncio
+import logging
+from datetime import datetime, timezone, timedelta
+
+import httpx
+
+from config import (
+    QDRANT_URL, RAG_COLLECTION,
+    RAG_MAX_VECTORS, RAG_EVICTION_HIGH_WATER, RAG_EVICTION_LOW_WATER,
+    RAG_EVICTION_BATCH, RAG_PINNED_SOURCES, RAG_GRACE_HOURS,
+    RAG_ACCESS_WEIGHT, RAG_AGE_WEIGHT,
+)
+
+log = logging.getLogger("caic")
+
+eviction_lock = asyncio.Lock()
+EVICTION_LOG: list[dict] = []
+
+
+async def _update_retrieval_count(point_id: str, current_count: int = 0):
+    try:
+        async with httpx.AsyncClient() as client:
+            payload = {
+                "retrieval_count": current_count + 1,
+                "last_accessed": datetime.now(timezone.utc).isoformat(),
+            }
+            resp = await client.put(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/payload",
+                json={"points": [point_id], "payload": payload},
+                timeout=5.0,
+            )
+            if resp.status_code not in (200, 201):
+                log.warning(f"Failed to increment retrieval count for {point_id}: {resp.status_code}")
+    except Exception as e:
+        log.warning(f"Error incrementing retrieval count for {point_id}: {e}")
+
+
+async def get_collection_count() -> int:
+    try:
+        async with httpx.AsyncClient() as client:
+            resp = await client.get(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}",
+                timeout=10.0,
+            )
+            if resp.status_code == 200:
+                info = resp.json().get("result", {})
+                return info.get("points_count", info.get("vectors_count", 0))
+    except Exception as e:
+        log.warning(f"get_collection_count error: {e}")
+    return 0
+
+
+async def get_collection_stats() -> dict:
+    count = await get_collection_count()
+    high_water_pct = int(RAG_EVICTION_HIGH_WATER * 100)
+    low_water_pct = int(RAG_EVICTION_LOW_WATER * 100)
+    percent_full = round((count / RAG_MAX_VECTORS) * 100, 1) if RAG_MAX_VECTORS > 0 else 0
+    return {
+        "vector_count": count,
+        "max_vectors": RAG_MAX_VECTORS,
+        "high_water_mark": int(RAG_MAX_VECTORS * RAG_EVICTION_HIGH_WATER),
+        "low_water_mark": int(RAG_MAX_VECTORS * RAG_EVICTION_LOW_WATER),
+        "high_water_pct": high_water_pct,
+        "low_water_pct": low_water_pct,
+        "percent_full": percent_full,
+        "pinned_sources": list(RAG_PINNED_SOURCES),
+    }
+
+
+async def evict_batch(batch_size: int) -> int:
+    filter_conditions = {
+        "must_not": [
+            {"match": {"key": "source", "value": src}}
+            for src in RAG_PINNED_SOURCES
+        ]
+    }
+    try:
+        async with httpx.AsyncClient() as client:
+            scroll_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+                json={
+                    "filter": filter_conditions,
+                    "limit": min(batch_size * 10, 10000),
+                    "with_payload": True,
+                    "with_vector": False,
+                },
+                timeout=30.0,
+            )
+            if scroll_resp.status_code != 200:
+                log.warning(f"Eviction scroll failed: {scroll_resp.status_code}")
+                return 0
+
+            points = scroll_resp.json().get("result", {}).get("points", [])
+            if not points:
+                return 0
+
+            now = datetime.now(timezone.utc)
+            scored = []
+            for p in points:
+                payload = p.get("payload", {})
+                date_str = payload.get("ingest_date") or payload.get("upload_date", "")
+                if date_str:
+                    age_hours = (now - datetime.fromisoformat(date_str)).total_seconds() / 3600
+                else:
+                    age_hours = 999999
+
+                if age_hours < RAG_GRACE_HOURS:
+                    continue
+
+                retrieval_count = payload.get("retrieval_count", 0) or 0
+                score = retrieval_count * RAG_ACCESS_WEIGHT + age_hours * RAG_AGE_WEIGHT
+                last_accessed = payload.get("last_accessed", date_str)
+                scored.append((score, last_accessed, p["id"]))
+
+            if not scored:
+                log.warning("No evictable vectors found (all pinned or newborn)")
+                return 0
+
+            scored.sort(key=lambda x: (x[0], x[1]))
+            to_delete = [p[2] for p in scored[:batch_size]]
+            if not to_delete:
+                return 0
+
+            delete_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
+                json={"points": to_delete},
+                timeout=30.0,
+            )
+            if delete_resp.status_code not in (200, 201):
+                log.warning(f"Eviction delete failed: {delete_resp.status_code}")
+                return 0
+
+            return len(to_delete)
+    except Exception as e:
+        log.warning(f"evict_batch error: {e}")
+        return 0
+
+
+async def maybe_evict() -> int:
+    if RAG_MAX_VECTORS <= 0:
+        return 0
+    effective_batch = max(RAG_EVICTION_BATCH, 1)
+
+    async with eviction_lock:
+        count = await get_collection_count()
+        threshold_high = int(RAG_MAX_VECTORS * RAG_EVICTION_HIGH_WATER)
+        threshold_low = int(RAG_MAX_VECTORS * RAG_EVICTION_LOW_WATER)
+
+        if count < threshold_high:
+            return 0
+
+        total_evicted = 0
+        while count >= threshold_low:
+            if total_evicted > 0 and count < threshold_low:
+                break
+            deleted = await evict_batch(effective_batch)
+            if deleted == 0:
+                break
+            total_evicted += deleted
+            count -= deleted
+            if count < threshold_high and total_evicted > 0:
+                break
+            if count < threshold_low:
+                break
+
+        if total_evicted > 0:
+            entry = {
+                "timestamp": datetime.now(timezone.utc).isoformat(),
+                "count": total_evicted,
+                "remaining": count,
+            }
+            EVICTION_LOG.append(entry)
+            if len(EVICTION_LOG) > 1000:
+                EVICTION_LOG.pop(0)
+            log.info(f"Evicted {total_evicted} vectors ({count} remaining)")
+
+        return total_evicted
+
+
+async def get_rag_operational_stats() -> dict:
+    stats = await get_collection_stats()
+    now = datetime.now(timezone.utc)
+    cutoff_1m = now - timedelta(minutes=1)
+    cutoff_5m = now - timedelta(minutes=5)
+    cutoff_30m = now - timedelta(minutes=30)
+
+    eviction_1m = sum(
+        e["count"] for e in EVICTION_LOG
+        if datetime.fromisoformat(e["timestamp"]) > cutoff_1m
+    )
+    eviction_5m = sum(
+        e["count"] for e in EVICTION_LOG
+        if datetime.fromisoformat(e["timestamp"]) > cutoff_5m
+    )
+    eviction_30m = sum(
+        e["count"] for e in EVICTION_LOG
+        if datetime.fromisoformat(e["timestamp"]) > cutoff_30m
+    )
+
+    pinned_count = 0
+    avg_retrieval_count = 0.0
+    at_risk_count = 0
+
+    try:
+        async with httpx.AsyncClient() as client:
+            pinned_filter = {
+                "should": [
+                    {"match": {"key": "source", "value": src}}
+                    for src in RAG_PINNED_SOURCES
+                ]
+            }
+            pinned_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+                json={"filter": pinned_filter, "limit": 10000, "with_payload": True, "with_vector": False},
+                timeout=10.0,
+            )
+            if pinned_resp.status_code == 200:
+                pinned_count = len(pinned_resp.json().get("result", {}).get("points", []))
+
+            nonpinned_filter = {
+                "must_not": [
+                    {"match": {"key": "source", "value": src}}
+                    for src in RAG_PINNED_SOURCES
+                ]
+            }
+            np_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+                json={"filter": nonpinned_filter, "limit": 10000, "with_payload": True, "with_vector": False},
+                timeout=10.0,
+            )
+            if np_resp.status_code == 200:
+                points = np_resp.json().get("result", {}).get("points", [])
+                if points:
+                    retrievals = []
+                    scored = []
+                    for p in points:
+                        payload = p.get("payload", {})
+                        rc = payload.get("retrieval_count", 0) or 0
+                        retrievals.append(rc)
+                        date_str = payload.get("ingest_date") or payload.get("upload_date", "")
+                        if date_str:
+                            age_hours = (now - datetime.fromisoformat(date_str)).total_seconds() / 3600
+                        else:
+                            age_hours = 999999
+                        score = rc * RAG_ACCESS_WEIGHT + age_hours * RAG_AGE_WEIGHT
+                        last_accessed = payload.get("last_accessed", date_str)
+                        scored.append((score, last_accessed))
+
+                    avg_retrieval_count = round(sum(retrievals) / len(retrievals), 2)
+
+                    scored.sort(key=lambda x: (x[0], x[1]))
+                    at_risk_threshold = max(1, len(scored) // 10)
+                    at_risk_count = at_risk_threshold
+    except Exception as e:
+        log.warning(f"RAG operational stats scroll error: {e}")
+
+    stats.update({
+        "grace_hours": RAG_GRACE_HOURS,
+        "eviction_counts_last_1m": eviction_1m,
+        "eviction_counts_last_5m": eviction_5m,
+        "eviction_counts_last_30m": eviction_30m,
+        "pinned_count": pinned_count,
+        "avg_retrieval_count": avg_retrieval_count,
+        "at_risk_count": at_risk_count,
+    })
+    return stats

gpu.py

@@ -1,14 +1,50 @@
 """
-JarvisChat - AMD GPU stats via rocm-smi.
+cAIc - GPU stats: rocm-smi (AMD/Linux), system_profiler (Apple Silicon/macOS).
 """
 import json
 import logging
+import platform
+import re
 import subprocess
+import sys
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
 
-def get_gpu_stats() -> dict:
+def _parse_darwin_gpu_stats() -> dict:
+    try:
+        result = subprocess.run(
+            ["system_profiler", "SPDisplaysDataType"],
+            capture_output=True, text=True, timeout=10,
+        )
+        if result.returncode != 0:
+            return {}
+        text = result.stdout
+        gpu_model = ""
+        vram_mb = 0
+        for line in text.splitlines():
+            m = re.match(r"\s+Chipset Model:\s+(.+)", line)
+            if m:
+                gpu_model = m.group(1).strip()
+            m = re.match(r"\s+VRAM \(Dynamic, Max\):\s+(\d+)\s+GB", line)
+            if m:
+                vram_mb = int(m.group(1)) * 1024
+        if gpu_model:
+            return {
+                "gpu_percent": 0,
+                "vram_percent": 0,
+                "available": True,
+                "gpu_model": gpu_model,
+                "vram_total_mb": vram_mb,
+            }
+    except (subprocess.TimeoutExpired, FileNotFoundError):
+        pass
+    except Exception as e:
+        log.warning("Darwin GPU stats error: %s", e)
+    return {}
+
+
+def _parse_linux_gpu_stats() -> dict:
     try:
         result = subprocess.run(
             ["rocm-smi", "--showuse", "--showmemuse", "--json"],
@@ -27,5 +63,16 @@ def get_gpu_stats() -> dict:
     except (subprocess.TimeoutExpired, FileNotFoundError, json.JSONDecodeError):
         pass
     except Exception as e:
-        log.warning(f"GPU stats error: {e}")
+        log.warning("Linux GPU stats error: %s", e)
+    return {}
+
+
+def get_gpu_stats() -> dict:
+    if sys.platform == "darwin":
+        stats = _parse_darwin_gpu_stats()
+        if stats:
+            return stats
+    stats = _parse_linux_gpu_stats()
+    if stats:
+        return stats
     return {"gpu_percent": 0, "vram_percent": 0, "available": False}

hardware.py

@@ -0,0 +1,149 @@
+"""
+cAIc — Startup hardware self-assessment.
+"""
+import asyncio
+import json
+import logging
+import re
+import subprocess
+import sys
+from pathlib import Path
+
+import httpx
+import psutil
+
+from config import LLAMA_SERVER_BASE, SEARXNG_BASE, QDRANT_URL, HW_STATE_PATH, COMFYUI_BASE
+
+log = logging.getLogger("caic")
+
+HARDWARE_STATE_PATH = Path(HW_STATE_PATH)
+_TIMEOUT_EXPIRED = subprocess.TimeoutExpired
+
+
+def _get_vram_darwin() -> tuple[int, int]:
+    try:
+        result = subprocess.run(
+            ["system_profiler", "SPDisplaysDataType"],
+            capture_output=True, text=True, timeout=10,
+        )
+        if result.returncode != 0:
+            return 0, 0
+        vram_total_mb = 0
+        for line in result.stdout.splitlines():
+            m = re.match(r"\s+VRAM \(Dynamic, Max\):\s+(\d+)\s+GB", line)
+            if m:
+                vram_total_mb += int(m.group(1)) * 1024
+        return vram_total_mb, vram_total_mb  # free ~ total (unified memory)
+    except (FileNotFoundError, _TIMEOUT_EXPIRED):
+        log.warning("system_profiler not available — VRAM stats set to 0")
+    except Exception as e:
+        log.warning(f"Darwin VRAM error: {e}")
+    return 0, 0
+
+
+def _get_vram_linux() -> tuple[int, int]:
+    vram_total_mb = 0
+    vram_free_mb = 0
+    try:
+        result = subprocess.run(
+            ["rocm-smi", "--showmeminfo", "vram", "--json"],
+            capture_output=True, text=True, timeout=5,
+        )
+        if result.returncode == 0:
+            data = json.loads(result.stdout)
+            for card, info in data.items():
+                tot = info.get("VRAM Total (MB)", 0)
+                free = info.get("VRAM Free (MB)", None)
+                used = info.get("VRAM Used (MB)", 0)
+                if tot:
+                    vram_total_mb += int(tot)
+                if free is not None:
+                    vram_free_mb += int(free)
+                else:
+                    vram_free_mb += int(tot) - int(used)
+    except (FileNotFoundError, _TIMEOUT_EXPIRED, json.JSONDecodeError):
+        log.warning("rocm-smi not available or failed — VRAM stats set to 0")
+    except Exception as e:
+        log.warning(f"rocm-smi error: {e}")
+    return vram_total_mb, vram_free_mb
+
+
+async def assess_hardware() -> dict:
+    mem = psutil.virtual_memory()
+    ram_total_gb = round(mem.total / (1024 ** 3), 1)
+    ram_available_gb = round(mem.available / (1024 ** 3), 1)
+    cpu_count = psutil.cpu_count()
+
+    if sys.platform == "darwin":
+        vram_total_mb, vram_free_mb = _get_vram_darwin()
+    else:
+        vram_total_mb, vram_free_mb = _get_vram_linux()
+
+    llama_reachable = False
+    llama_models = []
+    try:
+        async with httpx.AsyncClient(timeout=3) as client:
+            resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models")
+            if resp.status_code == 200:
+                llama_reachable = True
+                data = resp.json()
+                llama_models = [m.get("id", "") for m in data.get("data", [])]
+    except Exception:
+        log.warning("llama-server not reachable")
+
+    qdrant_reachable = False
+    qdrant_collections = []
+    try:
+        async with httpx.AsyncClient(timeout=3) as client:
+            resp = await client.get(f"{QDRANT_URL}/collections")
+            if resp.status_code == 200:
+                qdrant_reachable = True
+                data = resp.json()
+                raw = data.get("result", {}).get("collections", [])
+                qdrant_collections = [c.get("name", "") for c in raw]
+    except Exception:
+        log.warning("Qdrant not reachable")
+
+    searxng_reachable = False
+    try:
+        async with httpx.AsyncClient(timeout=3) as client:
+            resp = await client.get(SEARXNG_BASE)
+            if resp.status_code == 200:
+                searxng_reachable = True
+    except Exception:
+        log.warning("SearXNG not reachable")
+
+    comfyui_reachable = False
+    comfyui_models = []
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            resp = await client.get(f"{COMFYUI_BASE}/object_info/CheckpointLoaderSimple")
+            if resp.status_code == 200:
+                comfyui_reachable = True
+                data = resp.json()
+                ckpt_info = data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {})
+                ckpt_list = ckpt_info.get("ckpt_name", [[]])[0]
+                comfyui_models = ckpt_list if isinstance(ckpt_list, list) else []
+    except Exception:
+        log.warning("ComfyUI not reachable")
+
+    state = {
+        "ram_total_gb": ram_total_gb,
+        "ram_available_gb": ram_available_gb,
+        "cpu_count": cpu_count,
+        "vram_total_mb": vram_total_mb,
+        "vram_free_mb": vram_free_mb,
+        "llama_reachable": llama_reachable,
+        "llama_models": llama_models,
+        "qdrant_reachable": qdrant_reachable,
+        "qdrant_collections": qdrant_collections,
+        "searxng_reachable": searxng_reachable,
+        "comfyui_reachable": comfyui_reachable,
+        "comfyui_models": comfyui_models,
+    }
+    HARDWARE_STATE_PATH.write_text(json.dumps(state, indent=2))
+    log.info(
+        f"HW: {ram_total_gb}GB RAM, {vram_total_mb}MB VRAM, "
+        f"llama={llama_reachable}, qdrant={qdrant_reachable}, searxng={searxng_reachable}, comfyui={comfyui_reachable}"
+    )
+    return state

memory.py

@@ -1,5 +1,5 @@
 """
-JarvisChat - FTS5 memory system.
+cAIc - FTS5 memory system.
 CRUD, search, remember/forget command processing, topic detection.
 """
 import logging
@@ -7,10 +7,11 @@ import re
 from datetime import datetime, timezone
 from typing import Optional
 
+from crypto import encrypt_text, decrypt_text
 from db import get_db
 from config import MAX_MEMORY_FACT_CHARS
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
 REMEMBER_PATTERNS = [
     (r"remember that (.+)", "explicit"),
@@ -27,6 +28,99 @@ FORGET_PATTERNS = [
 ]
 
 
+AUTO_FACT_PATTERNS = [
+    re.compile(r"\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b"),
+    re.compile(r"\b(?:systemd|nginx|docker|ssh|ufw|iptables|postgres(?:ql)?|redis|mosquitto|node_exporter|prometheus|grafana|qdrant|rabbitmq|searxng|llama-server)\b", re.IGNORECASE),
+    re.compile(r"/(?:etc|home|usr|var|opt|tmp|mnt)/\S+"),
+    re.compile(r"\b(?:Ryzen|RX\s*\d{4}|RTX\s*\d{4}|Radeon|AMD|NVIDIA|Core\s*i[579]|Threadripper)\b", re.IGNORECASE),
+    re.compile(r"\b(?:Qwen|Llama|Gemma|Phi|Mistral|DeepSeek)\S*\b", re.IGNORECASE),
+    re.compile(r"\b(?:systemd\.service|docker\s+(?:compose|container|service)|systemctl|journalctl)\b", re.IGNORECASE),
+]
+SOCIAL_TRIGGERS = {"hi", "hello", "hey", "yo", "sup", "howdy", "good morning", "good evening"}
+
+# Short filler words that shouldn't count as subject overlap between facts.
+_STOPWORDS = {
+    "with", "that", "have", "this", "from", "they", "what", "when", "where",
+    "which", "there", "your", "will", "would", "about", "these", "their",
+    "been", "into", "than", "then", "them", "were", "being", "more", "most",
+    "some", "other", "only", "still", "also", "after", "before", "during",
+    "because", "through", "without",
+}
+
+
+def _subject_words(text: str) -> set:
+    """Meaningful subject tokens for overlap comparison."""
+    words = re.findall(r"[A-Za-z0-9_]{4,}", text.lower())
+    return {w for w in words if w not in _STOPWORDS}
+
+
+def _is_social(text: str) -> bool:
+    t = text.strip().lower()
+    if t in SOCIAL_TRIGGERS or any(t.startswith(w) for w in ("thanks", "thank you", "ty")):
+        return True
+    return False
+
+
+def auto_detect_facts(user_message: str, assistant_message: str) -> list[str]:
+    """Extract environmental/factual content from a chat turn.
+
+    Returns a list of fact strings ready for storage. Empty list means
+    nothing worth persisting.
+    """
+    if _is_social(user_message):
+        return []
+    if len(assistant_message) < 40:
+        return []
+    if process_remember_command(user_message) is not None:
+        return []
+
+    found = []
+    for pat in AUTO_FACT_PATTERNS:
+        if pat.search(user_message):
+            found.append(user_message)
+            break
+
+    # Also capture when the user is reporting a change they made
+    change_match = re.search(
+        r"(?:I\s+)?(?:set|changed?|updated|installed|configured|enabled|disabled|added|removed|created|deleted|restarted|reloaded|switched|moved|copied|renamed|symlinked|mounted|unmounted)\s+(?:the\s+)?(.+)",
+        user_message, re.IGNORECASE,
+    )
+    if change_match and user_message not in found:
+        found.append(user_message)
+
+    seen = set()
+    deduped = []
+    for f in found:
+        key = f.strip().lower()
+        if key not in seen:
+            seen.add(key)
+            deduped.append(f.strip()[:MAX_MEMORY_FACT_CHARS])
+    return deduped
+
+
+def check_fact_conflicts(facts: list[str]) -> list[dict]:
+    """Search for existing memories that conflict with detected facts.
+
+    A conflict is reported only when the existing memory is about the same
+    subject (meaningful keyword overlap) but states something different —
+    unrelated hits that merely share an FTS keyword are not conflicts.
+
+    Returns list of {memory_id, old_fact, new_fact} for each conflict.
+    """
+    conflicts = []
+    for new_fact in facts:
+        related = search_memories(new_fact, limit=1)
+        if related:
+            old = related[0]["fact"]
+            if old.rstrip(".") != new_fact.rstrip(".") and (_subject_words(new_fact) & _subject_words(old)):
+                conflicts.append({
+                    "memory_id": related[0]["rowid"],
+                    "old_fact": old,
+                    "new_fact": new_fact,
+                })
+    return conflicts
+
+
 def detect_topic(fact: str) -> str:
     fact_lower = fact.lower()
     if any(w in fact_lower for w in ["prefer", "like", "hate", "always", "never", "favorite"]):
@@ -45,7 +139,7 @@ def add_memory(fact: str, topic: str = "general", source: str = "explicit") -> O
     now = datetime.now(timezone.utc).isoformat()
     cur = db.execute(
         "INSERT INTO memories (fact, topic, source, created_at) VALUES (?, ?, ?, ?)",
-        (fact, topic, source, now),
+        (encrypt_text(fact), topic, source, now),
     )
     db.commit()
     rowid = cur.lastrowid
@@ -57,31 +151,16 @@ def add_memory(fact: str, topic: str = "general", source: str = "explicit") -> O
 def search_memories(query: str, limit: int = 5) -> list:
     if not query.strip():
         return []
-    db = get_db()
-    words = re.findall(r"[A-Za-z0-9_]+", query)
-    if not words:
-        db.close()
-        return []
-    escaped = []
-    for word in words[:10]:
-        if word.upper() in {"AND", "OR", "NOT", "NEAR"}:
-            escaped.append(f'"{word}"*')
-        else:
-            escaped.append(word + "*")
-    safe_query = " OR ".join(escaped)
-    try:
-        rows = db.execute(
-            "SELECT rowid, fact, topic, source, created_at, bm25(memories) AS rank "
-            "FROM memories WHERE memories MATCH ? ORDER BY rank LIMIT ?",
-            (safe_query, limit),
-        ).fetchall()
-        results = [dict(row) for row in rows]
-        log.debug(f"Memory search '{query}' returned {len(results)} results")
-    except Exception as e:
-        log.warning(f"Memory search error: {e}")
-        results = []
-    db.close()
-    return results
+    all_mems = get_all_memories()
+    words = set(re.findall(r"[A-Za-z0-9_]+", query.lower()))
+    scored = []
+    for m in all_mems:
+        fact_lower = m["fact"].lower()
+        score = sum(1 for w in words if w in fact_lower)
+        if score > 0:
+            scored.append((score, m))
+    scored.sort(key=lambda x: -x[0])
+    return [m for _, m in scored[:limit]]
 
 
 def get_all_memories(topic: Optional[str] = None) -> list:
@@ -93,7 +172,12 @@ def get_all_memories(topic: Optional[str] = None) -> list:
     else:
         rows = db.execute("SELECT rowid, * FROM memories ORDER BY created_at DESC").fetchall()
     db.close()
-    return [dict(row) for row in rows]
+    result = []
+    for row in rows:
+        d = dict(row)
+        d["fact"] = decrypt_text(d["fact"])
+        result.append(d)
+    return result
 
 
 def delete_memory(rowid: int) -> bool:
@@ -109,7 +193,7 @@ def delete_memory(rowid: int) -> bool:
 
 def update_memory(rowid: int, fact: str) -> bool:
     db = get_db()
-    cur = db.execute("UPDATE memories SET fact = ? WHERE rowid = ?", (fact, rowid))
+    cur = db.execute("UPDATE memories SET fact = ? WHERE rowid = ?", (encrypt_text(fact), rowid))
     db.commit()
     updated = cur.rowcount > 0
     db.close()

model_pull.py

@@ -0,0 +1,80 @@
+"""
+cAIc — Model pull/download helper.
+
+Uses Ollama's pull API to download models that aren't available on the
+inference server. Runs synchronously during startup.
+"""
+import asyncio
+import json
+import logging
+
+import httpx
+
+from config import DEFAULT_MODEL, LLAMA_SERVER_BASE, OLLAMA_BASE
+
+log = logging.getLogger("caic")
+
+
+async def _model_available_on_llama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models")
+            if resp.status_code == 200:
+                models = resp.json().get("data", [])
+                return any(m.get("id") == model for m in models)
+    except Exception:
+        pass
+    return False
+
+
+async def _model_available_on_ollama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            resp = await client.post(f"{OLLAMA_BASE}/api/show", json={"name": model})
+            return resp.status_code == 200
+    except Exception:
+        pass
+    return False
+
+
+async def _pull_via_ollama(model: str) -> bool:
+    try:
+        async with httpx.AsyncClient(timeout=300) as client:
+            async with client.stream("POST", f"{OLLAMA_BASE}/api/pull", json={"name": model}) as resp:
+                if resp.status_code != 200:
+                    log.warning("ollama pull returned %s for %s", resp.status_code, model)
+                    return False
+                async for line in resp.aiter_lines():
+                    if line.strip():
+                        try:
+                            data = json.loads(line)
+                            status = data.get("status", "")
+                            if status:
+                                log.info("ollama pull %s: %s", model, status)
+                        except json.JSONDecodeError:
+                            pass
+                return True
+    except httpx.ConnectError:
+        log.warning("ollama not reachable at %s — cannot pull %s", OLLAMA_BASE, model)
+    except Exception as e:
+        log.warning("ollama pull error for %s: %s", model, e)
+    return False
+
+
+async def ensure_model(model: str = "") -> bool:
+    """Ensure *model* is available for inference. Pull via Ollama if needed."""
+    model = model or DEFAULT_MODEL
+    if await _model_available_on_llama(model):
+        log.info("model %s already available on llama-server", model)
+        return True
+    log.info("model %s not found on llama-server, checking Ollama", model)
+    if await _model_available_on_ollama(model):
+        log.info("model %s found on Ollama (available for embeddings)", model)
+        return True
+    log.info("model %s not found on Ollama either — pulling", model)
+    ok = await _pull_via_ollama(model)
+    if ok:
+        log.info("model %s pulled successfully", model)
+    else:
+        log.warning("model %s could not be pulled", model)
+    return ok

models/README.txt

@@ -0,0 +1,9 @@
+# Models
+Place .gguf model files in this directory.
+
+The filename must match the LLAMA_MODEL value in .env.
+For example, if LLAMA_MODEL=llama3.1-8b-instruct.Q4_K_M.gguf,
+place that file here.
+
+Download from HuggingFace:
+  https://huggingface.co/models?search=gguf

node_agent/agent.py

@@ -0,0 +1,600 @@
+"""
+cAIc — Worker node agent.
+
+Standalone AMQP client that registers with the cAIc coordinator,
+responds to pings, and handles model swap commands.
+
+## Config file: /etc/caic-node-agent.conf
+
+```ini
+[agent]
+# hostname — defaults to socket.gethostname()
+node_name = jarvis
+# LAN IP — defaults from socket
+node_ip = 192.168.50.212
+# "worker" (fixed)
+node_type = worker
+# comma-separated capability list
+capabilities = llm
+# RabbitMQ URL on coordinator
+amqp_url = amqp://caic:password@localhost:5672/caic
+# port llama-server listens on
+llama_port = 8081
+# path to GGUF model files
+models_dir = /var/lib/caic/models
+# currently active model filename
+active_model = llama3.1-latest-Q4_K_M.gguf
+```
+
+## systemd unit: /etc/systemd/system/caic-node-agent.service
+
+```ini
+[Unit]
+Description=cAIc Worker Node Agent
+After=network.target rabbitmq.service
+Wants=rabbitmq.service
+
+[Service]
+Type=simple
+User=root
+Group=root
+WorkingDirectory=/opt/caic
+ExecStart=/usr/bin/python3 /opt/caic/node_agent/agent.py
+Restart=always
+RestartSec=5
+
+[Install]
+WantedBy=multi-user.target
+```
+"""
+import asyncio
+import json
+import logging
+import os
+import re
+import socket
+import subprocess
+import sys
+import time
+from configparser import ConfigParser
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Optional
+
+try:
+    import psutil
+    HAS_PSUTIL = True
+except ImportError:
+    HAS_PSUTIL = False
+
+try:
+    import aio_pika
+    from aio_pika import DeliveryMode, ExchangeType
+    HAS_AIO_PIKA = True
+except ImportError:
+    HAS_AIO_PIKA = False
+
+try:
+    import httpx
+    HAS_HTTPX = True
+except ImportError:
+    HAS_HTTPX = False
+
+log = logging.getLogger("caic")
+CONFIG_PATH = "/etc/caic-node-agent.conf"
+
+# ── data types ──────────────────────────────────────────────────────────
+
+class AgentConfig:
+    def __init__(self):
+        self.node_name: str = socket.gethostname()
+        self.node_ip: str = "127.0.0.1"
+        self.node_type: str = "worker"
+        self.capabilities: list[str] = ["llm"]
+        self.amqp_url: str = "amqp://caic:password@localhost:5672/caic"
+        self.llama_port: int = 8081
+        self.comfyui_port: int = 8188
+        self.models_dir: str = "/var/lib/caic/models"
+        self.active_model: str = ""
+
+    @classmethod
+    def from_ini(cls, path: str = CONFIG_PATH) -> "AgentConfig":
+        cfg = cls()
+        parser = ConfigParser()
+        if not os.path.exists(path):
+            log.warning("config %s not found, using defaults", path)
+            return cfg
+        parser.read(path)
+        sec = "agent"
+        if parser.has_section(sec):
+            cfg.node_name = parser.get(sec, "node_name", fallback=cfg.node_name)
+            cfg.node_ip = parser.get(sec, "node_ip", fallback=cfg.node_ip)
+            cfg.node_type = parser.get(sec, "node_type", fallback=cfg.node_type)
+            raw_caps = parser.get(sec, "capabilities", fallback="llm")
+            cfg.capabilities = [c.strip() for c in raw_caps.split(",") if c.strip()]
+            cfg.amqp_url = parser.get(sec, "amqp_url", fallback=cfg.amqp_url)
+            cfg.llama_port = parser.getint(sec, "llama_port", fallback=cfg.llama_port)
+            cfg.comfyui_port = parser.getint(sec, "comfyui_port", fallback=cfg.comfyui_port)
+            cfg.models_dir = parser.get(sec, "models_dir", fallback=cfg.models_dir)
+            cfg.active_model = parser.get(sec, "active_model", fallback=cfg.active_model)
+        return cfg
+
+
+class ModelInfo:
+    def __init__(self, filename: str, name: str = "", version: str = "", quant: str = ""):
+        self.filename = filename
+        self.name = name
+        self.version = version
+        self.quant = quant
+        self.path = ""
+
+    def to_dict(self) -> dict:
+        return {
+            "name": self.name,
+            "version": self.version,
+            "quant": self.quant,
+            "filename": self.filename,
+        }
+
+
+# ── model discovery ─────────────────────────────────────────────────────
+
+_MODEL_PATTERN = None  # lazy compile
+
+
+def discover_models(models_dir: str) -> list[dict]:
+    import re
+    global _MODEL_PATTERN
+    if _MODEL_PATTERN is None:
+        _MODEL_PATTERN = re.compile(
+            r"^(?P<name>.+?)-(?P<version>[^-]+)-(?P<quant>Q\d+_K_[A-Z]+|IQ\d_[A-Z]+|fp\d+)\.gguf$"
+        )
+    root = Path(models_dir)
+    if not root.is_dir():
+        log.warning("models_dir %s not found", models_dir)
+        return []
+
+    results = []
+    for fpath in sorted(root.glob("*.gguf")):
+        m = _MODEL_PATTERN.match(fpath.name)
+        if m:
+            info = ModelInfo(
+                filename=fpath.name,
+                name=m.group("name"),
+                version=m.group("version"),
+                quant=m.group("quant"),
+            )
+            info.path = str(fpath)
+            results.append(info.to_dict())
+        else:
+            log.debug("skipping unrecognized model filename: %s", fpath.name)
+    return results
+
+
+# ── load reporting ──────────────────────────────────────────────────────
+
+def get_load() -> dict:
+    load = {}
+    if HAS_PSUTIL:
+        load["cpu_pct"] = round(psutil.cpu_percent(interval=0.5))
+        load["ram_pct"] = round(psutil.virtual_memory().percent)
+    try:
+        result = subprocess.run(
+            ["rocm-smi", "--showmeminfo", "vram"],
+            capture_output=True, text=True, timeout=3,
+        )
+        if result.returncode == 0:
+            total = 0
+            used = 0
+            for line in result.stdout.splitlines():
+                if "VRAM Total Used Memory (B)" in line:
+                    parts = line.split(":")
+                    if len(parts) >= 2:
+                        used = int(parts[-1].strip())
+                elif "VRAM Total Memory (B)" in line:
+                    parts = line.split(":")
+                    if len(parts) >= 2:
+                        total = int(parts[-1].strip())
+            if total > 0:
+                load["vram_pct"] = round(used / total * 100)
+    except (FileNotFoundError, subprocess.TimeoutExpired):
+        pass
+    # Darwin / Apple Silicon
+    if sys.platform == "darwin" and "vram_pct" not in load:
+        try:
+            result = subprocess.run(
+                ["system_profiler", "SPDisplaysDataType"],
+                capture_output=True, text=True, timeout=5,
+            )
+            if result.returncode == 0:
+                for line in result.stdout.splitlines():
+                    m = re.match(r"\s+VRAM \(Dynamic, Max\):\s+(\d+)\s+GB", line)
+                    if m:
+                        load["vram_pct"] = 50  # unified memory — best guess
+        except (FileNotFoundError, subprocess.TimeoutExpired):
+            pass
+    return load
+
+
+def detect_capabilities(cfg: AgentConfig) -> list[str]:
+    caps = list(cfg.capabilities)
+    if "image_gen" not in caps and HAS_HTTPX:
+        try:
+            resp = httpx.get(f"http://localhost:{cfg.comfyui_port}/system_stats", timeout=3)
+            if resp.status_code == 200:
+                caps.append("image_gen")
+                log.info("auto-detected image_gen capability (ComfyUI on port %d)", cfg.comfyui_port)
+        except Exception:
+            pass
+    return caps
+
+
+# ── AMQP helpers ────────────────────────────────────────────────────────
+
+async def declare_exchanges(channel) -> tuple:
+    admin = await channel.declare_exchange("jc.admin", ExchangeType.TOPIC, durable=True)
+    system = await channel.declare_exchange("jc.system", ExchangeType.TOPIC, durable=True)
+    return admin, system
+
+
+async def publish(channel, exchange, routing_key, payload):
+    body = json.dumps(payload).encode()
+    msg = aio_pika.Message(body, delivery_mode=DeliveryMode.PERSISTENT)
+    await exchange.publish(msg, routing_key)
+
+
+# ── registration ────────────────────────────────────────────────────────
+
+def build_registration_payload(cfg: AgentConfig, inventory: list[dict]) -> dict:
+    model_dict = None
+    if cfg.active_model:
+        for inv in inventory:
+            if inv["filename"] == cfg.active_model:
+                model_dict = {**inv, "port": cfg.llama_port}
+                break
+    return {
+        "node_name": cfg.node_name,
+        "node_type": cfg.node_type,
+        "ip": cfg.node_ip,
+        "capabilities": cfg.capabilities,
+        "active_model": model_dict,
+        "inventory": inventory,
+    }
+
+
+# ── ping / pong ─────────────────────────────────────────────────────────
+
+async def handle_ping(cfg: AgentConfig, channel, exchange, msg: aio_pika.IncomingMessage):
+    async with msg.process():
+        try:
+            payload = json.loads(msg.body.decode())
+        except json.JSONDecodeError:
+            return
+        correlation_id = payload.get("correlation_id")
+        if not correlation_id:
+            return
+
+        load = get_load()
+        now = datetime.now(timezone.utc).isoformat() + "Z"
+        pong = {
+            "node_name": cfg.node_name,
+            "type": "pong",
+            "correlation_id": correlation_id,
+            "status": "active",
+            "active_model": None,  # simplified; could read current
+            "load": load,
+            "timestamp": now,
+        }
+        await publish(channel, exchange, f"node.{cfg.node_name}.pong", pong)
+
+
+# ── model swap ──────────────────────────────────────────────────────────
+
+async def handle_swap_model(cfg: AgentConfig, channel, exchanges, msg: aio_pika.IncomingMessage):
+    admin_ex, system_ex = exchanges
+    async with msg.process():
+        try:
+            payload = json.loads(msg.body.decode())
+        except json.JSONDecodeError:
+            return
+
+        model_filename = payload.get("model_filename")
+        if not model_filename:
+            log.error("swap_model missing model_filename")
+            return
+
+        log.info("swapping model to %s", model_filename)
+
+        # 1. Stop current llama-server
+        log.info("stopping llama-server")
+        subprocess.run(["systemctl", "stop", "llama-server"], check=False)
+
+        # 2. Update config
+        _update_config_active_model(cfg, model_filename)
+
+        # 3. Start llama-server
+        log.info("starting llama-server")
+        subprocess.run(["systemctl", "start", "llama-server"], check=False)
+
+        # 4. Poll health endpoint
+        healthy = await _wait_for_llama(cfg.llama_port, timeout=120, interval=2)
+
+        now = datetime.now(timezone.utc).isoformat() + "Z"
+        if healthy:
+            result_payload = {
+                "node_name": cfg.node_name,
+                "type": "model_ready",
+                "active_model": model_filename,
+                "port": cfg.llama_port,
+                "timestamp": now,
+            }
+            log.info("model swap successful: %s", model_filename)
+        else:
+            result_payload = {
+                "node_name": cfg.node_name,
+                "type": "model_failed",
+                "active_model": model_filename,
+                "port": cfg.llama_port,
+                "error": "llama-server did not become healthy within 120s",
+                "timestamp": now,
+            }
+            log.error("model swap failed: %s", model_filename)
+
+        await publish(channel, system_ex, f"node.{cfg.node_name}.{result_payload['type']}", result_payload)
+
+
+def _update_config_active_model(cfg: AgentConfig, model_filename: str):
+    parser = ConfigParser()
+    if os.path.exists(CONFIG_PATH):
+        parser.read(CONFIG_PATH)
+    if not parser.has_section("agent"):
+        parser.add_section("agent")
+    parser.set("agent", "active_model", model_filename)
+    with open(CONFIG_PATH, "w") as f:
+        parser.write(f)
+    cfg.active_model = model_filename
+
+
+async def _wait_for_llama(port: int, timeout: int = 120, interval: int = 2) -> bool:
+    if not HAS_HTTPX:
+        log.warning("httpx not installed, skipping health check")
+        return True
+    deadline = time.time() + timeout
+    url = f"http://localhost:{port}/v1/models"
+    async with httpx.AsyncClient() as client:
+        while time.time() < deadline:
+            try:
+                resp = await client.get(url, timeout=5)
+                if resp.status_code == 200:
+                    return True
+            except (httpx.ConnectError, httpx.TimeoutException):
+                pass
+            await asyncio.sleep(interval)
+    return False
+
+
+# ── image generation ─────────────────────────────────────────────────────
+
+async def handle_image_generate(cfg: AgentConfig, channel, exchanges, msg: aio_pika.IncomingMessage):
+    admin_ex, system_ex = exchanges
+    async with msg.process():
+        try:
+            payload = json.loads(msg.body.decode())
+        except json.JSONDecodeError:
+            return
+
+        request_id = payload.get("request_id")
+        prompt = payload.get("prompt", "")
+        negative_prompt = payload.get("negative_prompt", "")
+        width = payload.get("width", 1024)
+        height = payload.get("height", 1024)
+        steps = payload.get("steps", 20)
+        seed = payload.get("seed", -1)
+        model = payload.get("model", "")
+
+        if not prompt:
+            log.error("image_generate missing prompt")
+            return
+
+        log.info("image generate: prompt=%s %dx%d steps=%d", prompt[:60], width, height, steps)
+
+        now = datetime.now(timezone.utc).isoformat() + "Z"
+        try:
+            image_data = await _comfyui_generate(
+                cfg, prompt, negative_prompt, width, height, steps, seed, model,
+            )
+            result_payload = {
+                "node_name": cfg.node_name,
+                "type": "image_generated",
+                "request_id": request_id,
+                "image_base64": image_data,
+                "timestamp": now,
+            }
+            log.info("image generate complete: request_id=%s", request_id)
+        except Exception as e:
+            result_payload = {
+                "node_name": cfg.node_name,
+                "type": "image_failed",
+                "request_id": request_id,
+                "error": str(e),
+                "timestamp": now,
+            }
+            log.error("image generate failed: %s", e)
+
+        await publish(channel, system_ex, f"node.{cfg.node_name}.{result_payload['type']}", result_payload)
+
+
+async def _comfyui_generate(
+    cfg: AgentConfig, prompt: str, negative_prompt: str,
+    width: int, height: int, steps: int, seed: int, model: str,
+) -> str:
+    import random
+    import uuid as _uuid
+
+    if not HAS_HTTPX:
+        raise RuntimeError("httpx not installed")
+
+    client_id = str(_uuid.uuid4())
+    if seed < 0:
+        seed = random.randint(0, 2**32 - 1)
+
+    checkpoint = model or "model.safetensors"
+
+    workflow = {
+        "3": {
+            "class_type": "KSampler",
+            "inputs": {
+                "seed": seed,
+                "steps": steps,
+                "cfg": 7.0,
+                "sampler_name": "euler",
+                "scheduler": "normal",
+                "denoise": 1.0,
+                "model": ["4", 0],
+                "positive": ["6", 0],
+                "negative": ["7", 0],
+                "latent_image": ["5", 0],
+            },
+        },
+        "4": {
+            "class_type": "CheckpointLoaderSimple",
+            "inputs": {"ckpt_name": checkpoint},
+        },
+        "5": {
+            "class_type": "EmptyLatentImage",
+            "inputs": {"width": width, "height": height, "batch_size": 1},
+        },
+        "6": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": prompt, "clip": ["4", 1]},
+        },
+        "7": {
+            "class_type": "CLIPTextEncode",
+            "inputs": {"text": negative_prompt or "blurry, low quality", "clip": ["4", 1]},
+        },
+        "8": {
+            "class_type": "VAEDecode",
+            "inputs": {"samples": ["3", 0], "vae": ["4", 2]},
+        },
+        "9": {
+            "class_type": "SaveImage",
+            "inputs": {"filename_prefix": f"caic_{client_id}", "images": ["8", 0]},
+        },
+    }
+
+    async with httpx.AsyncClient(timeout=120) as client:
+        resp = await client.post(
+            f"http://localhost:{cfg.comfyui_port}/prompt",
+            json={"prompt": workflow, "client_id": client_id},
+        )
+        if resp.status_code != 200:
+            raise RuntimeError(f"ComfyUI prompt failed: {resp.status_code} {resp.text}")
+
+        prompt_id = resp.json().get("prompt_id")
+        if not prompt_id:
+            raise RuntimeError("ComfyUI returned no prompt_id")
+
+        deadline = time.time() + 120
+        while time.time() < deadline:
+            resp = await client.get(f"http://localhost:{cfg.comfyui_port}/history/{prompt_id}")
+            if resp.status_code == 200:
+                history = resp.json().get(prompt_id, {})
+                outputs = history.get("outputs", {})
+                for node_id, node_output in outputs.items():
+                    images = node_output.get("images", [])
+                    if images:
+                        img_info = images[0]
+                        filename = img_info.get("filename")
+                        subfolder = img_info.get("subfolder", "")
+                        img_type = img_info.get("type", "output")
+                        img_resp = await client.get(
+                            f"http://localhost:{cfg.comfyui_port}/view",
+                            params={"filename": filename, "subfolder": subfolder, "type": img_type},
+                        )
+                        if img_resp.status_code == 200:
+                            import base64
+                            return base64.b64encode(img_resp.content).decode()
+            await asyncio.sleep(1)
+
+        raise RuntimeError("ComfyUI generation timed out after 120s")
+
+
+# ── main ────────────────────────────────────────────────────────────────
+
+async def amain():
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s caic[%(process)d]: %(levelname)s %(message)s",
+    )
+    log.info("cAIc node agent starting")
+
+    if not HAS_AIO_PIKA:
+        log.error("aio-pika not installed")
+        sys.exit(1)
+
+    cfg = AgentConfig.from_ini()
+    log.info("node_name=%s node_ip=%s", cfg.node_name, cfg.node_ip)
+
+    cfg.capabilities = detect_capabilities(cfg)
+    log.info("capabilities: %s", cfg.capabilities)
+
+    inventory = discover_models(cfg.models_dir)
+    log.info("discovered %d models", len(inventory))
+
+    # Connect to AMQP
+    conn = await aio_pika.connect_robust(cfg.amqp_url)
+    channel = await conn.channel()
+    admin_ex, system_ex = await declare_exchanges(channel)
+    log.info("connected to AMQP broker")
+
+    # Publish registration
+    reg_payload = build_registration_payload(cfg, inventory)
+    await publish(channel, admin_ex, f"node.{cfg.node_name}.register", reg_payload)
+    log.info("registration published")
+
+    # Wait for admission
+    response_queue = await channel.declare_queue("", exclusive=True)
+    await response_queue.bind(admin_ex, f"node.{cfg.node_name}.admitted")
+    await response_queue.bind(admin_ex, f"node.{cfg.node_name}.rejected")
+
+    admitted = False
+    async with response_queue.iterator() as iterator:
+        async for message in iterator:
+            async with message.process():
+                payload = json.loads(message.body.decode())
+                if payload.get("type") == "admitted":
+                    log.info("admitted to cluster")
+                    admitted = True
+                    break
+                else:
+                    log.error("rejected: %s", payload.get("reason"))
+                    sys.exit(1)
+
+    if not admitted:
+        log.error("no admission response received")
+        sys.exit(1)
+
+    # Set up ping consumer
+    ping_queue = await channel.declare_queue("", exclusive=True)
+    await ping_queue.bind(admin_ex, f"node.{cfg.node_name}.ping")
+    await ping_queue.consume(lambda msg: handle_ping(cfg, channel, admin_ex, msg))
+
+    # Set up swap consumer
+    swap_queue = await channel.declare_queue("", exclusive=True)
+    await swap_queue.bind(admin_ex, f"node.{cfg.node_name}.cmd.swap_model")
+    await swap_queue.consume(lambda msg: handle_swap_model(cfg, channel, (admin_ex, system_ex), msg))
+
+    # Set up image gen consumer
+    if "image_gen" in cfg.capabilities:
+        image_queue = await channel.declare_queue("", exclusive=True)
+        await image_queue.bind(admin_ex, f"node.{cfg.node_name}.cmd.image_generate")
+        await image_queue.consume(lambda msg: handle_image_generate(cfg, channel, (admin_ex, system_ex), msg))
+        log.info("image generation handler registered")
+
+    log.info("listening for pings and commands")
+    # Run forever
+    await asyncio.Event().wait()
+
+
+if __name__ == "__main__":
+    asyncio.run(amain())

node_agent/requirements.txt

@@ -0,0 +1,3 @@
+aio-pika>=9.0.0
+psutil>=5.9.0
+httpx>=0.27.0

rag.py

@@ -1,26 +1,132 @@
 """
-JarvisChat - RAG pipeline: Qdrant vector search + system prompt assembly.
+cAIc - RAG pipeline: Qdrant vector search + system prompt assembly.
 """
+import asyncio
 import logging
+import os
+import uuid
+from datetime import datetime, timezone
 
 import httpx
 
+from crypto import encrypt_text, decrypt_text
+from eviction import _update_retrieval_count
 from db import get_db, get_setting, list_skills_with_state, format_active_skills_prompt
 from memory import search_memories
-from config import MAX_SKILL_PROMPT_CHARS
+from config import MAX_SKILL_PROMPT_CHARS, QDRANT_URL, RAG_COLLECTION
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
-QDRANT_URL = "http://192.168.50.108:6333"
-EMBED_URL = "http://192.168.50.210:11434"
-EMBED_MODEL = "mxbai-embed-large"
-RAG_COLLECTION = "jarvis_rag"
+EMBED_URL = os.environ.get("CAIC_EMBED_URL", "http://localhost:11434")
+EMBED_MODEL = os.environ.get("CAIC_EMBED_MODEL", "mxbai-embed-large")
 RAG_SCORE_THRESHOLD = 0.25
 
+# Re-export eviction symbols for backward compatibility
+from eviction import (  # noqa: E402
+    maybe_evict, get_rag_operational_stats, EVICTION_LOG,
+    get_collection_count, get_collection_stats, evict_batch,
+)
 
-def chunk_text(text: str, chunk_size: int = 512, overlap: int = 128) -> list:
+
+async def _upsert_fact(fact: str, text: str, topic: str,
+                       client: httpx.AsyncClient) -> bool:
+    """Embed text and upsert a fact to Qdrant."""
+    chunks = chunk_text(text)
+    if not chunks:
+        return False
+    ts = datetime.now(timezone.utc).timestamp()
+    ok = False
+    for i, chunk in enumerate(chunks):
+        try:
+            er = await client.post(
+                f"{EMBED_URL}/api/embeddings",
+                json={"model": EMBED_MODEL, "prompt": chunk},
+                timeout=10.0,
+            )
+            if er.status_code != 200:
+                continue
+            vector = er.json()["embedding"]
+            pid = str(uuid.uuid5(uuid.NAMESPACE_DNS, f"auto-{ts}-{i}"))
+            payload = {
+                "text": encrypt_text(chunk), "source": "auto_fact", "fact": fact,
+                "ingest_date": datetime.now(timezone.utc).isoformat(),
+                "type": "auto_fact", "topic": topic,
+            }
+            r = await client.put(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
+                json={"points": [{"id": pid, "vector": vector, "payload": payload}]},
+                timeout=10.0,
+            )
+            if r.status_code in (200, 201):
+                ok = True
+        except Exception as e:
+            log.warning(f"Qdrant upsert error: {e}")
+    return ok
+
+
+async def ingest_auto_fact(facts: list[str], user_message: str,
+                           assistant_message: str) -> int:
+    """Persist pre-detected facts to memories + Qdrant.
+
+    Call this when no conflicts exist — silent ingest.
+    Returns the number of facts stored.
+    """
+    from memory import add_memory, detect_topic
+
+    ingested = 0
+    async with httpx.AsyncClient() as client:
+        for fact in facts:
+            topic = detect_topic(fact)
+            add_memory(fact, topic=topic, source="auto")
+            ingested += 1
+            text = f"Q: {user_message}\nA: {assistant_message}"
+            await _upsert_fact(fact, text, topic, client)
+    if ingested:
+        log.info(f"Auto-ingested {ingested} fact(s) from conversation")
+    return ingested
+
+
+async def confirm_fact_update(memory_id: int, old_fact: str, new_fact: str,
+                              user_message: str, assistant_message: str) -> bool:
+    """Confirm a user-accepted fact update: replace memory + Qdrant entry."""
+    from memory import update_memory, detect_topic
+
+    if not update_memory(memory_id, new_fact):
+        return False
+
+    topic = detect_topic(new_fact)
+    try:
+        async with httpx.AsyncClient() as client:
+            # scroll old points with matching fact and delete them
+            scroll_r = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+                json={
+                    "filter": {"must": [{"key": "fact", "match": {"value": old_fact}}]},
+                    "limit": 100,
+                    "with_payload": False,
+                },
+                timeout=10.0,
+            )
+            if scroll_r.status_code == 200:
+                ids = [p["id"] for p in scroll_r.json().get("result", [])]
+                if ids:
+                    await client.post(
+                        f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
+                        json={"points": ids},
+                        timeout=10.0,
+                    )
+
+            text = f"Q: {user_message}\nA: {assistant_message}"
+            await _upsert_fact(new_fact, text, topic, client)
+    except Exception as e:
+        log.warning(f"Fact update RAG error: {e}")
+
+    log.info(f"Fact updated [memory_id={memory_id}]: {new_fact}")
+    return True
+
+
+def chunk_text(text: str, chunk_size: int = 200, overlap: int = 64) -> list:
     words = text.split()
-    # Approximate token count as len(words) * 1.3
     target_words = int(chunk_size / 1.3)
     overlap_words = int(overlap / 1.3)
     if not words:
@@ -54,7 +160,14 @@ async def query_rag(query: str, limit: int = 3) -> list:
             )
             if search_resp.status_code != 200:
                 return []
-            return search_resp.json().get("result", [])
+            results = search_resp.json().get("result", [])
+            for r in results:
+                pid = r.get("id")
+                if pid:
+                    current = r.get("payload", {}).get("retrieval_count", 0) or 0
+                    # Fire-and-forget: update retrieval count without blocking the response
+                    asyncio.create_task(_update_retrieval_count(pid, current))
+            return results
     except Exception as e:
         log.warning(f"RAG query error: {e}")
         return []
@@ -80,7 +193,7 @@ async def build_system_prompt(db, extra_prompt: str = "", user_message: str = ""
         try:
             rag_results = await query_rag(user_message)
             if rag_results:
-                rag_lines = [r["payload"]["text"] for r in rag_results if r["score"] > RAG_SCORE_THRESHOLD]
+                rag_lines = [decrypt_text(r["payload"]["text"]) for r in rag_results if r["score"] > RAG_SCORE_THRESHOLD]
                 if rag_lines:
                     parts.append("## Retrieved Context\n" + "\n\n---\n\n".join(rag_lines))
                     log.info(f"RAG injected {len(rag_lines)} chunks into context")

requirements.txt

@@ -2,3 +2,8 @@ fastapi>=0.115.0
 uvicorn[standard]>=0.32.0
 httpx>=0.27.0
 pypdf>=5.0.0
+python-multipart>=0.0.9
+aio-pika>=9.0.0
+cryptography>=44.0.0
+psutil>=5.9.0
+jinja2>=3.1.0

routers/chat.py

@@ -1,4 +1,5 @@
-"""JarvisChat routers - /api/chat streaming endpoint."""
+"""cAIc routers - /api/chat streaming endpoint."""
+import asyncio
 import json
 import logging
 import uuid
@@ -9,18 +10,35 @@ from fastapi import APIRouter, HTTPException, Request
 from fastapi.responses import StreamingResponse
 
 from config import DEFAULT_MODEL, LLAMA_SERVER_BASE
+from crypto import encrypt_text, decrypt_text
 from db import get_db, get_upload_context
-from memory import process_remember_command
-from rag import build_system_prompt
+from memory import process_remember_command, auto_detect_facts, check_fact_conflicts
+from rag import build_system_prompt, ingest_auto_fact
 from search import (calculate_perplexity, is_uncertain, is_refusal,
                     clean_hedging, format_search_results, format_direct_answer,
                     extract_search_query, query_searxng)
 from security import read_json_body, log_incident, BODY_LIMIT_CHAT_BYTES
-from config import MAX_CHAT_MESSAGE_CHARS
+from config import MAX_CHAT_MESSAGE_CHARS, MODEL_CONTEXT_LENGTH
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
+# References to background auto-ingest tasks so they are never garbage-collected.
+_ingest_tasks: set = set()
+
+
+async def _safe_ingest(coro):
+    try:
+        await coro
+    except Exception as e:
+        log.warning("auto-ingest task failed: %s", e)
+
+
+def _spawn_ingest(coro):
+    task = asyncio.create_task(_safe_ingest(coro))
+    _ingest_tasks.add(task)
+    task.add_done_callback(_ingest_tasks.discard)
+
 
 def parse_llama_stream_chunk(line: str) -> tuple:
     if line.startswith("data: "):
@@ -45,6 +63,8 @@ def parse_llama_stream_chunk(line: str) -> tuple:
             if finish == "stop":
                 usage = chunk.get("usage", {})
                 stats["tokens_per_sec"] = usage.get("tokens_per_second", 0.0)
+                stats["completion_tokens"] = usage.get("completion_tokens", 0)
+                stats["prompt_tokens"] = usage.get("prompt_tokens", 0)
             return token, finish == "stop", stats, logprobs_list
         if "message" in chunk and "content" in chunk["message"]:
             token = chunk["message"]["content"]
@@ -54,6 +74,7 @@ def parse_llama_stream_chunk(line: str) -> tuple:
                 eval_count = chunk.get("eval_count", 0)
                 eval_duration = chunk.get("eval_duration", 0)
                 stats["tokens_per_sec"] = (eval_count / (eval_duration / 1e9)) if eval_duration > 0 else 0
+                stats["completion_tokens"] = eval_count
             return token, done, stats, []
     except json.JSONDecodeError:
         pass
@@ -70,6 +91,7 @@ async def chat(request: Request):
     model = body.get("model", DEFAULT_MODEL)
     preset_prompt = body.get("system_prompt", "")
     upload_context_id = body.get("upload_context_id")
+    private_chat = body.get("private_chat", False)
 
     if not user_message:
         raise HTTPException(status_code=400, detail="Empty message")
@@ -77,33 +99,52 @@ async def chat(request: Request):
     db = get_db()
     now = datetime.now(timezone.utc).isoformat()
     settings = {row["key"]: row["value"] for row in db.execute("SELECT key, value FROM settings").fetchall()}
-    search_enabled = settings.get("search_enabled", "true") == "true"
+    search_enabled = settings.get("search_enabled", "true") == "true" and not private_chat
 
     upload_doc = None
-    if upload_context_id:
+    if upload_context_id and not private_chat:
         ctx = get_upload_context(db, upload_context_id)
         if ctx:
             upload_doc = f"[ATTACHED DOCUMENT: {ctx['filename']}]\n{ctx['content']}\n[END DOCUMENT]"
         else:
             log.warning(f"upload_context_id {upload_context_id} not found or expired, continuing without it")
 
-    remember_response = process_remember_command(user_message)
+    remember_response = None if private_chat else process_remember_command(user_message)
 
+    if private_chat:
+        if not conv_id:
+            conv_id = str(uuid.uuid4())
+        system_prompt = ""
+        messages = []
+        if preset_prompt:
+            messages.append({"role": "system", "content": preset_prompt})
+        messages.append({"role": "user", "content": user_message})
+        history_rows = []
+        db.close()
+    else:
         if not conv_id:
             conv_id = str(uuid.uuid4())
             title = user_message[:80] + ("..." if len(user_message) > 80 else "")
             db.execute("INSERT INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
-                   (conv_id, title, model, now, now))
+                       (conv_id, encrypt_text(title), model, now, now))
         else:
+            # A client-supplied id may reference a conversation that no longer exists;
+            # recreate the row so the message insert satisfies the FK instead of 500ing.
+            title = user_message[:80] + ("..." if len(user_message) > 80 else "")
+            db.execute("INSERT OR IGNORE INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
+                       (conv_id, encrypt_text(title), model, now, now))
             db.execute("UPDATE conversations SET updated_at = ? WHERE id = ?", (now, conv_id))
 
-    db.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-               (conv_id, "user", user_message, now))
+        db.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                   (conv_id, "user", encrypt_text(user_message), now, None))
         db.commit()
 
-    history_rows = db.execute(
+        raw_rows = db.execute(
             "SELECT role, content FROM messages WHERE conversation_id = ? ORDER BY id ASC", (conv_id,)
         ).fetchall()
+        history_rows = []
+        for row in raw_rows:
+            history_rows.append({"role": row["role"], "content": decrypt_text(row["content"])})
         extra_prompt = preset_prompt
         if upload_doc:
             extra_prompt = (extra_prompt + "\n\n" + upload_doc) if extra_prompt else upload_doc
@@ -122,6 +163,9 @@ async def chat(request: Request):
         full_response = []
         all_logprobs = []
         tokens_per_sec = 0.0
+        completion_tokens = 0
+        prompt_tokens = 0
+        rag_update = None
 
         if remember_response:
             yield f"data: {json.dumps({'token': remember_response + chr(10) + chr(10), 'conversation_id': conv_id})}\n\n"
@@ -143,9 +187,13 @@ async def chat(request: Request):
                                 yield f"data: {json.dumps({'token': token, 'conversation_id': conv_id})}\n\n"
                             if done:
                                 tokens_per_sec = stats.get("tokens_per_sec", 0.0)
+                                completion_tokens = stats.get("completion_tokens", 0)
+                                prompt_tokens = stats.get("prompt_tokens", 0)
 
                 assistant_msg = "".join(full_response)
                 perplexity = calculate_perplexity(all_logprobs) if all_logprobs else 0.0
+                if not all_logprobs:
+                    log.warning("No logprobs received from inference server — perplexity auto-search unavailable")
                 should_search = is_uncertain(all_logprobs) or is_refusal(assistant_msg)
 
                 if search_enabled and should_search:
@@ -185,32 +233,50 @@ async def chat(request: Request):
                         if is_refusal(cleaned_response) or len(cleaned_response) < 20:
                             cleaned_response = format_direct_answer(user_message, search_results)
 
-                        yield f"data: {json.dumps({'token': cleaned_response, 'conversation_id': conv_id, 'augmented': True})}\n\n"
+                        yield f"data: {json.dumps({'token': cleaned_response, 'conversation_id': conv_id, 'augmented': True, 'reset': True})}\n\n"
 
+                        if not private_chat:
                             saved_msg = cleaned_response + "\n\n---\n*🔍 Enhanced with web search results*"
                             if remember_response:
                                 saved_msg = remember_response + "\n\n" + saved_msg
 
                             db2 = get_db()
-                        db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                                    (conv_id, "assistant", saved_msg, datetime.now(timezone.utc).isoformat()))
+                            db2.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                                        (conv_id, "assistant", encrypt_text(saved_msg), datetime.now(timezone.utc).isoformat(), round(perplexity, 2)))
                             db2.commit()
                             db2.close()
 
-                        yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1)})}\n\n"
+                            facts = auto_detect_facts(user_message, cleaned_response)
+                            if facts:
+                                conflicts = check_fact_conflicts(facts)
+                                if conflicts:
+                                    rag_update = {"conflicts": conflicts}
+                                else:
+                                    _spawn_ingest(ingest_auto_fact(facts, user_message, cleaned_response))
+
+                        yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
                         return
 
+                if not private_chat:
                     saved_msg = assistant_msg
                     if remember_response:
                         saved_msg = remember_response + "\n\n" + saved_msg
 
                     db2 = get_db()
-                db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                            (conv_id, "assistant", saved_msg, datetime.now(timezone.utc).isoformat()))
+                    db2.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                                (conv_id, "assistant", encrypt_text(saved_msg), datetime.now(timezone.utc).isoformat(), round(perplexity, 2)))
                     db2.commit()
                     db2.close()
 
-                yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1)})}\n\n"
+                    facts = auto_detect_facts(user_message, assistant_msg)
+                    if facts:
+                        conflicts = check_fact_conflicts(facts)
+                        if conflicts:
+                            rag_update = {"conflicts": conflicts}
+                        else:
+                            _spawn_ingest(ingest_auto_fact(facts, user_message, assistant_msg))
+
+                yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
 
             except httpx.RemoteProtocolError:
                 pass

routers/cluster.py

@@ -0,0 +1,23 @@
+"""cAIc routers - Cluster status API."""
+from fastapi import APIRouter
+
+import cluster
+
+router = APIRouter()
+
+
+@router.get("/api/cluster")
+async def cluster_status():
+    return {
+        "nodes": {name: _strip_internal(node) for name, node in cluster.CLUSTER_NODES.items()},
+        "node_count": len(cluster.CLUSTER_NODES),
+        "coordinator": cluster.CLUSTER_COORDINATOR,
+        "events": list(cluster.CLUSTER_EVENTS),
+    }
+
+
+def _strip_internal(node: dict) -> dict:
+    return {k: v for k, v in node.items() if k in {
+        "name", "type", "status", "capabilities", "active_model", "load",
+        "registered_at", "last_seen",
+    }}

routers/completions.py

@@ -1,11 +1,12 @@
 """
-JarvisChat - /v1/chat/completions router.
+cAIc - /v1/chat/completions router.
 OpenAI-compatible endpoint for IDE integration (Continue.dev, etc.).
 Runs all requests through the full jC pipeline: profile + RAG + memory injection.
 FIM (fill-in-the-middle) requests are proxied directly — not persisted.
 Chat-style requests are persisted to conversation history.
 Auth: static Bearer token via COMPLETIONS_API_KEY in config.
 """
+import hmac
 import json
 import logging
 import uuid
@@ -16,11 +17,12 @@ from fastapi import APIRouter, HTTPException, Request
 from fastapi.responses import StreamingResponse, JSONResponse
 
 from config import DEFAULT_MODEL, LLAMA_SERVER_BASE, COMPLETIONS_API_KEY
+from crypto import encrypt_text
 from db import get_db
 from rag import build_system_prompt
 from routers.chat import parse_llama_stream_chunk
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 
@@ -29,7 +31,7 @@ def _check_api_key(request: Request):
     if not auth.startswith("Bearer "):
         raise HTTPException(status_code=401, detail="Missing Bearer token")
     token = auth[7:].strip()
-    if token != COMPLETIONS_API_KEY:
+    if not hmac.compare_digest(token.encode(), COMPLETIONS_API_KEY.encode()):
         raise HTTPException(status_code=401, detail="Invalid API key")
 
 
@@ -86,6 +88,7 @@ def _build_openai_response(content: str, model: str, conv_id: str) -> dict:
 
 
 @router.post("/v1/chat/completions")
+@router.post("/v1/completions")
 async def chat_completions(request: Request):
     _check_api_key(request)
 
@@ -118,25 +121,27 @@ async def chat_completions(request: Request):
 
     # --- Persist conversation ---
     db = get_db()
+    try:
         now = datetime.now(timezone.utc).isoformat()
         conv_id = str(uuid.uuid4())
         title = f"[IDE] {user_message[:72]}{'...' if len(user_message) > 72 else ''}"
         db.execute(
             "INSERT INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
-        (conv_id, title, model, now, now),
+            (conv_id, encrypt_text(title), model, now, now),
         )
         for msg in messages:
             role = msg.get("role")
             content = msg.get("content", "")
             if role in ("user", "assistant"):
                 db.execute(
-                "INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                (conv_id, role, content, now),
+                    "INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                    (conv_id, role, encrypt_text(content), now, None),
                 )
         db.commit()
 
         # --- Build system prompt through full jC pipeline ---
         system_prompt = await build_system_prompt(db, "", user_message)
+    finally:
         db.close()
 
     # Assemble messages for upstream: inject jC system prompt, preserve history
@@ -193,8 +198,8 @@ async def _stream_chat(payload: dict, model: str, conv_id: str, request: Request
             if assistant_msg:
                 db = get_db()
                 db.execute(
-                    "INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                    (conv_id, "assistant", assistant_msg, datetime.now(timezone.utc).isoformat()),
+                    "INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                    (conv_id, "assistant", encrypt_text(assistant_msg), datetime.now(timezone.utc).isoformat(), None),
                 )
                 db.commit()
                 db.close()
@@ -238,8 +243,8 @@ async def _blocking_chat(payload: dict, model: str, conv_id: str, request: Reque
     if assistant_msg:
         db = get_db()
         db.execute(
-            "INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-            (conv_id, "assistant", assistant_msg, datetime.now(timezone.utc).isoformat()),
+            "INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+            (conv_id, "assistant", encrypt_text(assistant_msg), datetime.now(timezone.utc).isoformat(), None),
         )
         db.commit()
         db.close()
@@ -247,6 +252,79 @@ async def _blocking_chat(payload: dict, model: str, conv_id: str, request: Reque
     return JSONResponse(content=_build_openai_response(assistant_msg, model, conv_id))
 
 
+@router.post("/v1/fim/completions")
+@router.post("/fim/completions")
+async def fim_completions(request: Request):
+    _check_api_key(request)
+    try:
+        body = await request.json()
+    except Exception:
+        raise HTTPException(status_code=400, detail="Invalid JSON body")
+
+    prefix = body.get("prompt", "")
+    suffix = body.get("suffix", "")
+    stream = body.get("stream", True)
+    max_tokens = body.get("max_tokens", 128)
+
+    fim_prompt = f"<|fim_prefix|>{prefix}<|fim_suffix|>{suffix}<|fim_middle|>"
+
+    upstream = {
+        "prompt": fim_prompt,
+        "n_predict": max_tokens,
+        "temperature": body.get("temperature", 0),
+        "stop": body.get("stop", []),
+        "stream": True,
+        "cache_prompt": False,
+    }
+
+    async def _stream_fim():
+        async with httpx.AsyncClient() as client:
+            try:
+                async with client.stream(
+                    "POST", f"{LLAMA_SERVER_BASE}/completion",
+                    json=upstream,
+                    timeout=httpx.Timeout(30.0, connect=5.0),
+                ) as resp:
+                    async for line in resp.aiter_lines():
+                        if not line or not line.startswith("data: "):
+                            continue
+                        try:
+                            d = json.loads(line[6:])
+                            content = d.get("content", "")
+                            if content:
+                                chunk = {
+                                    "choices": [{"delta": {"content": content}, "index": 0}]
+                                }
+                                yield f"data: {json.dumps(chunk)}\n\n"
+                            if d.get("stop"):
+                                break
+                        except json.JSONDecodeError:
+                            continue
+                yield "data: [DONE]\n\n"
+            except httpx.ConnectError:
+                yield f"data: {json.dumps({'error': 'Cannot connect to inference server'})}\n\n"
+
+    if stream:
+        return StreamingResponse(_stream_fim(), media_type="text/event-stream")
+
+    # Non-streaming: accumulate and return
+    full = []
+    async for chunk in _stream_fim():
+        if chunk.startswith("data: [DONE]"):
+            break
+        try:
+            d = json.loads(chunk[6:])
+            content = d.get("choices", [{}])[0].get("delta", {}).get("content", "")
+            if content:
+                full.append(content)
+        except (json.JSONDecodeError, IndexError):
+            pass
+    return JSONResponse(content={
+        "choices": [{"text": "".join(full), "index": 0, "finish_reason": "stop"}],
+        "usage": {},
+    })
+
+
 async def _fim_passthrough(body: dict) -> JSONResponse:
     """
     Proxy FIM requests directly to llama-server without pipeline injection.
@@ -255,11 +333,20 @@ async def _fim_passthrough(body: dict) -> JSONResponse:
     async with httpx.AsyncClient() as client:
         try:
             resp = await client.post(
-                f"{LLAMA_SERVER_BASE}/v1/completions",
+                f"{LLAMA_SERVER_BASE}/completion",
                 json=body,
                 timeout=httpx.Timeout(30.0, connect=5.0),
             )
-            return JSONResponse(content=resp.json(), status_code=resp.status_code)
+            data = resp.json()
+            wrapped = {
+                "choices": [{
+                    "text": data.get("content", ""),
+                    "index": 0,
+                    "finish_reason": data.get("stop", False),
+                }],
+                "usage": {},
+            }
+            return JSONResponse(content=wrapped, status_code=resp.status_code)
         except httpx.ConnectError:
             raise HTTPException(status_code=503, detail="Cannot connect to inference server")
         except Exception as e:

routers/conversations.py

@@ -1,13 +1,14 @@
-"""JarvisChat routers - Conversation CRUD."""
+"""cAIc routers - Conversation CRUD."""
 import logging
 import uuid
 from datetime import datetime, timezone
 from fastapi import APIRouter, HTTPException, Request
 from db import get_db
+from crypto import encrypt_text, decrypt_text
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
 from config import DEFAULT_MODEL, MAX_CONVERSATION_TITLE_CHARS
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 
@@ -18,6 +19,7 @@ async def list_conversations():
     result = []
     for r in rows:
         c = dict(r)
+        c["title"] = decrypt_text(c["title"])
         attach_count = db.execute(
             "SELECT COUNT(*) FROM upload_context WHERE conversation_id = ?", (c["id"],)
         ).fetchone()[0]
@@ -36,7 +38,7 @@ async def create_conversation(request: Request):
     title = str(body.get("title", "New Chat"))[:MAX_CONVERSATION_TITLE_CHARS]
     db = get_db()
     db.execute("INSERT INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
-               (conv_id, title, model, now, now))
+               (conv_id, encrypt_text(title), model, now, now))
     db.commit()
     db.close()
     return {"id": conv_id, "title": title, "model": model, "created_at": now, "updated_at": now}
@@ -51,7 +53,14 @@ async def get_conversation(conv_id: str):
         raise HTTPException(status_code=404, detail="Conversation not found")
     messages = db.execute("SELECT * FROM messages WHERE conversation_id = ? ORDER BY id ASC", (conv_id,)).fetchall()
     db.close()
-    return {"conversation": dict(conv), "messages": [dict(m) for m in messages]}
+    conv_dict = dict(conv)
+    conv_dict["title"] = decrypt_text(conv_dict["title"])
+    msg_list = []
+    for m in messages:
+        md = dict(m)
+        md["content"] = decrypt_text(md["content"])
+        msg_list.append(md)
+    return {"conversation": conv_dict, "messages": msg_list}
 
 
 @router.put("/api/conversations/{conv_id}")
@@ -61,7 +70,7 @@ async def update_conversation(conv_id: str, request: Request):
     now = datetime.now(timezone.utc).isoformat()
     if "title" in body:
         db.execute("UPDATE conversations SET title = ?, updated_at = ? WHERE id = ?",
-                   (str(body["title"])[:MAX_CONVERSATION_TITLE_CHARS], now, conv_id))
+                   (encrypt_text(str(body["title"])[:MAX_CONVERSATION_TITLE_CHARS]), now, conv_id))
     if "model" in body:
         db.execute("UPDATE conversations SET model = ?, updated_at = ? WHERE id = ?",
                    (body["model"], now, conv_id))

routers/hardware.py

@@ -0,0 +1,15 @@
+"""cAIc routers — Hardware self-assessment endpoint."""
+import json
+
+from fastapi import APIRouter
+
+import hardware
+
+router = APIRouter()
+
+
+@router.get("/api/hardware")
+async def get_hardware_state():
+    if hardware.HARDWARE_STATE_PATH.exists():
+        return json.loads(hardware.HARDWARE_STATE_PATH.read_text())
+    return {"status": "not_ready", "message": "Hardware assessment not yet complete"}

routers/image.py

@@ -0,0 +1,70 @@
+"""cAIc routers — Image generation proxy endpoint."""
+import base64
+import logging
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import Response
+
+from cluster import CLUSTER_NODES, request_image_generate
+
+log = logging.getLogger("caic")
+router = APIRouter()
+
+
+def _find_image_node() -> str | None:
+    for name, node in CLUSTER_NODES.items():
+        if node.get("status") == "active" and "image_gen" in node.get("capabilities", []):
+            return name
+    return None
+
+
+@router.post("/api/image/generate")
+async def generate_image(request_body: dict):
+    prompt = (request_body.get("prompt") or "").strip()
+    if not prompt:
+        raise HTTPException(status_code=400, detail="Prompt is required")
+
+    negative_prompt = request_body.get("negative_prompt", "")
+    width = min(max(request_body.get("width", 1024), 256), 2048)
+    height = min(max(request_body.get("height", 1024), 256), 2048)
+    steps = min(max(request_body.get("steps", 20), 1), 50)
+    seed = request_body.get("seed", -1)
+    model = request_body.get("model", "")
+
+    node_name = _find_image_node()
+    if not node_name:
+        raise HTTPException(status_code=503, detail="No image generation service available")
+
+    log.info("image generate via %s: %s", node_name, prompt[:60])
+
+    image_b64 = await request_image_generate(
+        node_name=node_name,
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        width=width,
+        height=height,
+        steps=steps,
+        seed=seed,
+        model=model,
+    )
+
+    if image_b64 is None:
+        raise HTTPException(status_code=504, detail="Image generation timed out or failed")
+
+    image_bytes = base64.b64decode(image_b64)
+    return Response(content=image_bytes, media_type="image/png")
+
+
+@router.get("/api/image/status")
+async def image_status():
+    nodes = []
+    for name, node in CLUSTER_NODES.items():
+        caps = node.get("capabilities", [])
+        if "image_gen" in caps:
+            nodes.append({
+                "name": name,
+                "status": node.get("status"),
+                "load": node.get("load"),
+                "last_seen": node.get("last_seen"),
+            })
+    return {"available": len(nodes) > 0, "nodes": nodes}

routers/ingest.py

@@ -0,0 +1,75 @@
+"""cAIc routers - /api/ingest terminal command RAG hook."""
+import hashlib
+import hmac
+import logging
+import uuid
+from datetime import datetime, timezone
+
+import httpx
+from fastapi import APIRouter, HTTPException, Request
+from fastapi.responses import JSONResponse
+
+from config import COMPLETIONS_API_KEY
+from crypto import encrypt_text
+from eviction import maybe_evict
+from rag import chunk_text, QDRANT_URL, EMBED_URL, EMBED_MODEL, RAG_COLLECTION
+
+log = logging.getLogger("caic")
+router = APIRouter()
+
+
+def _check_api_key(request: Request):
+    auth = request.headers.get("Authorization", "")
+    if not auth.startswith("Bearer "):
+        raise HTTPException(status_code=401, detail="Missing Bearer token")
+    token = auth[7:].strip()
+    if not hmac.compare_digest(token.encode(), COMPLETIONS_API_KEY.encode()):
+        raise HTTPException(status_code=401, detail="Invalid API key")
+
+
+@router.post("/api/ingest")
+async def ingest_content(request: Request):
+    _check_api_key(request)
+    body = await request.json()
+    content = (body.get("content") or "").strip()
+    if not content:
+        raise HTTPException(status_code=422, detail="content is required")
+    source = str(body.get("source", "external")).strip() or "external"
+    metadata = body.get("metadata") or {}
+
+    chunks = chunk_text(content)
+    if not chunks:
+        raise HTTPException(status_code=422, detail="content produced no chunks")
+
+    ingested = 0
+    async with httpx.AsyncClient() as client:
+        for i, chunk in enumerate(chunks):
+            embed_resp = await client.post(
+                f"{EMBED_URL}/api/embeddings",
+                json={"model": EMBED_MODEL, "prompt": chunk},
+                timeout=30.0,
+            )
+            if embed_resp.status_code != 200:
+                log.warning(f"Ingest embedding failed for chunk {i}: {embed_resp.status_code}")
+                continue
+            vector = embed_resp.json()["embedding"]
+            chunk_hash = hashlib.md5(chunk.encode("utf-8")).hexdigest()[:12]
+            point_id = str(uuid.uuid5(uuid.NAMESPACE_DNS, f"ingest-{source}-{chunk_hash}-{i}"))
+            payload = {"text": encrypt_text(chunk), "source": source, "ingest_date": datetime.now(timezone.utc).isoformat(), "type": "ingest"}
+            payload.update(metadata)
+            upsert_resp = await client.put(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
+                json={"points": [{"id": point_id, "vector": vector, "payload": payload}]},
+                timeout=30.0,
+            )
+            if upsert_resp.status_code in (200, 201):
+                ingested += 1
+            else:
+                log.warning(f"Ingest Qdrant upsert failed for chunk {i}: {upsert_resp.status_code}")
+
+    if ingested > 0:
+        evicted = await maybe_evict()
+        if evicted:
+            log.info(f"Evicted {evicted} vectors after ingest")
+
+    return {"chunks_ingested": ingested, "source": source, "message": f"Ingested {ingested} chunks from {source}"}

routers/memories.py

@@ -1,9 +1,10 @@
-"""JarvisChat routers - Memory CRUD API."""
+"""cAIc routers - Memory CRUD API."""
 from fastapi import APIRouter, HTTPException, Request
 from typing import Optional
 
 from db import get_db
 from memory import add_memory, delete_memory, update_memory, get_all_memories, search_memories
+from rag import confirm_fact_update
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
 from config import MAX_MEMORY_FACT_CHARS
 
@@ -54,6 +55,22 @@ async def search_memories_api(q: str, limit: int = 10):
     return {"results": results, "count": len(results)}
 
 
+@router.post("/api/memories/confirm-update")
+async def confirm_memory_update(request: Request):
+    body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
+    memory_id = body.get("memory_id")
+    new_fact = str(body.get("new_fact", "")).strip()
+    old_fact = str(body.get("old_fact", "")).strip()
+    user_message = str(body.get("user_message", "")).strip()
+    assistant_message = str(body.get("assistant_message", "")).strip()
+    if not memory_id or not new_fact:
+        raise HTTPException(status_code=400, detail="memory_id and new_fact are required")
+    ok = await confirm_fact_update(memory_id, old_fact, new_fact, user_message, assistant_message)
+    if not ok:
+        raise HTTPException(status_code=404, detail="Memory not found")
+    return {"status": "ok"}
+
+
 @router.get("/api/memories/stats")
 async def memory_stats():
     db = get_db()

routers/models.py

@@ -1,5 +1,5 @@
 """
-JarvisChat routers - Model listing, system stats.
+cAIc routers - Model listing, system stats.
 """
 import logging
 from typing import Optional
@@ -12,7 +12,7 @@ from config import LLAMA_SERVER_BASE
 from gpu import get_gpu_stats
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 

routers/presets.py

@@ -1,4 +1,4 @@
-"""JarvisChat routers - System prompt presets."""
+"""cAIc routers - System prompt presets."""
 import uuid
 from datetime import datetime, timezone
 from fastapi import APIRouter, HTTPException, Request

routers/profile.py

@@ -1,4 +1,4 @@
-"""JarvisChat routers - Profile."""
+"""cAIc routers - Profile."""
 from datetime import datetime, timezone
 from fastapi import APIRouter, HTTPException, Request
 from db import get_db

routers/rag_admin.py

@@ -0,0 +1,249 @@
+"""cAIc routers — RAG corpus management admin endpoints."""
+import logging
+from datetime import datetime, timezone
+
+import httpx
+from fastapi import APIRouter, HTTPException, Query, Request
+from fastapi.responses import JSONResponse
+
+from crypto import decrypt_text, encrypt_text
+from eviction import get_rag_operational_stats, EVICTION_LOG
+from rag import QDRANT_URL, RAG_COLLECTION, EMBED_URL, EMBED_MODEL
+
+log = logging.getLogger("caic")
+router = APIRouter()
+
+
+def _normalise_date(payload: dict) -> str:
+    return payload.get("ingest_date") or payload.get("upload_date") or ""
+
+
+def _decrypt_payload(payload: dict) -> dict:
+    text = payload.get("text", "")
+    return {
+        "text": decrypt_text(text),
+        "source": payload.get("source"),
+        "type": payload.get("type"),
+        "date": _normalise_date(payload),
+        "retrieval_count": payload.get("retrieval_count", 0),
+        "topic": payload.get("topic"),
+        "fact": payload.get("fact"),
+        "filename": payload.get("filename"),
+        "last_accessed": payload.get("last_accessed"),
+    }
+
+
+@router.get("/api/rag/stats")
+async def rag_stats(request: Request):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+    stats = await get_rag_operational_stats()
+    stats["eviction_log_size"] = len(EVICTION_LOG)
+    return stats
+
+
+@router.get("/api/rag/points")
+async def rag_list_points(
+    request: Request,
+    limit: int = Query(20, ge=1, le=100),
+    offset: str = Query(None),
+    search: str = Query(None),
+    source: str = Query(None),
+    sort: str = Query("date"),
+    order: str = Query("desc"),
+):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+
+    async with httpx.AsyncClient() as client:
+        if search:
+            embed_resp = await client.post(
+                f"{EMBED_URL}/api/embeddings",
+                json={"model": EMBED_MODEL, "prompt": search},
+                timeout=10.0,
+            )
+            if embed_resp.status_code != 200:
+                return JSONResponse(status_code=502, content={"detail": "Embedding failed"})
+            vector = embed_resp.json()["embedding"]
+            search_body = {"vector": vector, "limit": limit, "with_payload": True}
+            if source:
+                search_body["filter"] = {"must": [{"match": {"key": "source", "value": source}}]}
+            sr = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/search",
+                json=search_body,
+                timeout=10.0,
+            )
+            if sr.status_code != 200:
+                return JSONResponse(status_code=502, content={"detail": "Qdrant search failed"})
+            results = sr.json().get("result", [])
+            points = []
+            for r in results:
+                p = _decrypt_payload(r.get("payload", {}))
+                p["id"] = r["id"]
+                p["score"] = r.get("score")
+                points.append(p)
+            return {"points": points, "total": len(points), "next_offset": None}
+
+        scroll_body = {
+            "limit": limit,
+            "with_payload": True,
+            "with_vector": False,
+        }
+        if offset:
+            scroll_body["offset"] = offset
+        if source:
+            scroll_body["filter"] = {"must": [{"match": {"key": "source", "value": source}}]}
+
+        sr = await client.post(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+            json=scroll_body,
+            timeout=10.0,
+        )
+        if sr.status_code != 200:
+            return JSONResponse(status_code=502, content={"detail": "Qdrant scroll failed"})
+        result = sr.json().get("result", {})
+        raw_points = result.get("points", [])
+        next_offset = result.get("next_page_offset")
+
+        info_resp = await client.get(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}",
+            timeout=5.0,
+        )
+        total = 0
+        if info_resp.status_code == 200:
+            info = info_resp.json().get("result", {})
+            total = info.get("points_count", info.get("vectors_count", 0))
+
+        points = []
+        for r in raw_points:
+            p = _decrypt_payload(r.get("payload", {}))
+            p["id"] = r["id"]
+            points.append(p)
+        return {"points": points, "total": total, "next_offset": next_offset}
+
+
+@router.get("/api/rag/point/{point_id}")
+async def rag_get_point(point_id: str, request: Request):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+
+    async with httpx.AsyncClient() as client:
+        resp = await client.get(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/{point_id}",
+            timeout=10.0,
+        )
+        if resp.status_code != 200:
+            raise HTTPException(status_code=404, detail="Point not found")
+        result = resp.json().get("result", {})
+        if not result:
+            raise HTTPException(status_code=404, detail="Point not found")
+        payload = result.get("payload", {})
+        point = _decrypt_payload(payload)
+        point["id"] = result["id"]
+        return point
+
+
+@router.delete("/api/rag/point/{point_id}")
+async def rag_delete_point(point_id: str, request: Request):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+
+    async with httpx.AsyncClient() as client:
+        resp = await client.post(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
+            json={"points": [point_id]},
+            timeout=10.0,
+        )
+        if resp.status_code not in (200, 201) and resp.status_code != 404:
+            return JSONResponse(status_code=502, content={"detail": "Qdrant delete failed"})
+        log.info(f"RAG point {point_id} deleted by admin")
+        return {"status": "deleted", "id": point_id}
+
+
+@router.patch("/api/rag/point/{point_id}")
+async def rag_update_point(point_id: str, request: Request):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+
+    body = await request.json()
+    new_text = (body.get("text") or "").strip()
+    if not new_text:
+        raise HTTPException(status_code=400, detail="text required")
+
+    async with httpx.AsyncClient() as client:
+        get_resp = await client.get(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/{point_id}",
+            timeout=10.0,
+        )
+        if get_resp.status_code != 200:
+            raise HTTPException(status_code=404, detail="Point not found")
+        existing = get_resp.json().get("result", {})
+        if not existing:
+            raise HTTPException(status_code=404, detail="Point not found")
+
+        old_payload = existing.get("payload", {})
+        embed_resp = await client.post(
+            f"{EMBED_URL}/api/embeddings",
+            json={"model": EMBED_MODEL, "prompt": new_text},
+            timeout=10.0,
+        )
+        if embed_resp.status_code != 200:
+            return JSONResponse(status_code=502, content={"detail": "Embedding failed"})
+        vector = embed_resp.json()["embedding"]
+
+        new_payload = dict(old_payload)
+        new_payload["text"] = encrypt_text(new_text)
+        date_field = "ingest_date" if "ingest_date" in old_payload else "upload_date"
+        new_payload[date_field] = datetime.now(timezone.utc).isoformat()
+
+        upsert_resp = await client.put(
+            f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
+            json={"points": [{"id": point_id, "vector": vector, "payload": new_payload}]},
+            timeout=10.0,
+        )
+        if upsert_resp.status_code not in (200, 201):
+            return JSONResponse(status_code=502, content={"detail": "Qdrant upsert failed"})
+
+        log.info(f"RAG point {point_id} updated by admin")
+        return {"status": "updated", "id": point_id}
+
+
+@router.post("/api/rag/flush")
+async def rag_flush(request: Request):
+    if getattr(request.state, "session_role", "none") != "admin":
+        raise HTTPException(status_code=403, detail="Admin PIN required for this action")
+    try:
+        async with httpx.AsyncClient() as client:
+            scroll_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
+                json={"limit": 10000, "with_payload": False, "with_vector": False},
+                timeout=30.0,
+            )
+            if scroll_resp.status_code != 200:
+                return JSONResponse(status_code=502, content={"detail": f"Qdrant scroll failed: {scroll_resp.status_code}"})
+
+            all_points = scroll_resp.json().get("result", {}).get("points", [])
+            point_ids = [p["id"] for p in all_points]
+
+            if not point_ids:
+                return {"deleted_count": 0, "collection": RAG_COLLECTION, "status": "flushed"}
+
+            delete_resp = await client.post(
+                f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
+                json={"points": point_ids},
+                timeout=30.0,
+            )
+            if delete_resp.status_code not in (200, 201):
+                return JSONResponse(status_code=502, content={"detail": f"Qdrant delete failed: {delete_resp.status_code}"})
+
+            EVICTION_LOG.clear()
+            log.warning(f"RAG collection '{RAG_COLLECTION}' flushed ({len(point_ids)} points deleted)")
+
+            return {
+                "deleted_count": len(point_ids),
+                "collection": RAG_COLLECTION,
+                "status": "flushed",
+            }
+    except Exception as e:
+        log.warning(f"RAG flush error: {e}")
+        return JSONResponse(status_code=502, content={"detail": f"RAG flush error: {e}"})

routers/search_route.py

@@ -1,4 +1,4 @@
-"""JarvisChat routers - /api/search explicit search endpoint."""
+"""cAIc routers - /api/search explicit search endpoint."""
 import json
 import logging
 import uuid
@@ -9,12 +9,13 @@ from fastapi import APIRouter, HTTPException, Request
 from fastapi.responses import StreamingResponse
 
 from config import DEFAULT_MODEL, LLAMA_SERVER_BASE, MAX_SEARCH_QUERY_CHARS
+from crypto import encrypt_text
 from db import get_db
 from search import query_searxng, format_search_results
 from routers.chat import parse_llama_stream_chunk
 from security import read_json_body, log_incident, BODY_LIMIT_CHAT_BYTES
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 
@@ -30,6 +31,10 @@ async def explicit_search(request: Request):
     if not query:
         raise HTTPException(status_code=400, detail="Empty query")
 
+    private_chat = body.get("private_chat", False)
+    if private_chat:
+        raise HTTPException(status_code=403, detail="Web search is disabled in private chat mode")
+
     db = get_db()
     now = datetime.now(timezone.utc).isoformat()
 
@@ -37,12 +42,15 @@ async def explicit_search(request: Request):
         conv_id = str(uuid.uuid4())
         title = query[:70] + "..." if len(query) > 70 else query
         db.execute("INSERT INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
-                   (conv_id, title, model, now, now))
+                   (conv_id, encrypt_text(title), model, now, now))
     else:
+        title = query[:70] + "..." if len(query) > 70 else query
+        db.execute("INSERT OR IGNORE INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
+                   (conv_id, title, model, now, now))
         db.execute("UPDATE conversations SET updated_at = ? WHERE id = ?", (now, conv_id))
 
-    db.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-               (conv_id, "user", query, now))
+    db.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+               (conv_id, "user", encrypt_text(query), now, None))
     db.commit()
     db.close()
 
@@ -55,8 +63,8 @@ async def explicit_search(request: Request):
             error_msg = "No search results found."
             yield f"data: {json.dumps({'token': error_msg, 'conversation_id': conv_id})}\n\n"
             db2 = get_db()
-            db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                        (conv_id, "assistant", error_msg, datetime.now(timezone.utc).isoformat()))
+            db2.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                        (conv_id, "assistant", encrypt_text(error_msg), datetime.now(timezone.utc).isoformat(), None))
             db2.commit()
             db2.close()
             yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id})}\n\n"
@@ -97,8 +105,8 @@ async def explicit_search(request: Request):
         saved_msg = f"{summary}\n\n---\n*🔍 Web search results*"
 
         db2 = get_db()
-        db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
-                    (conv_id, "assistant", saved_msg, datetime.now(timezone.utc).isoformat()))
+        db2.execute("INSERT INTO messages (conversation_id, role, content, created_at, perplexity) VALUES (?, ?, ?, ?, ?)",
+                    (conv_id, "assistant", encrypt_text(saved_msg), datetime.now(timezone.utc).isoformat(), None))
         db2.commit()
         db2.close()
 

routers/settings.py

@@ -1,4 +1,4 @@
-"""JarvisChat routers - Settings."""
+"""cAIc routers - Settings."""
 from fastapi import APIRouter, HTTPException, Request
 from db import get_db
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES

routers/skills.py

@@ -1,4 +1,4 @@
-"""JarvisChat routers - Skills."""
+"""cAIc routers - Skills."""
 from fastapi import APIRouter, HTTPException, Request
 from db import get_db, get_setting, list_skills_with_state, set_skill_enabled
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES

routers/upload.py

@@ -1,7 +1,8 @@
-"""JarvisChat routers - /api/upload file/document attachment endpoint."""
+"""cAIc routers - /api/upload file/document attachment endpoint."""
 import json
 import logging
 import os
+import uuid
 from datetime import datetime, timezone, timedelta
 
 import httpx
@@ -9,15 +10,17 @@ from fastapi import APIRouter, HTTPException, Request, UploadFile, File, Form
 from fastapi.responses import JSONResponse
 
 from config import UPLOAD_DIR, MAX_UPLOAD_BYTES, SUPPORTED_UPLOAD_TYPES, UPLOAD_CONTEXT_EXPIRY_HOURS
+from crypto import encrypt_text
 from db import get_db, insert_upload_context, list_upload_context_by_conversation, delete_upload_context_by_id
+from eviction import maybe_evict
 from rag import chunk_text, QDRANT_URL, EMBED_URL, EMBED_MODEL, RAG_COLLECTION
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 router = APIRouter()
 
 
 def _point_id(filename: str, chunk_idx: int) -> str:
-    return f"upload-{filename}-{chunk_idx}"
+    return str(uuid.uuid5(uuid.NAMESPACE_DNS, f"upload-{filename}-{chunk_idx}"))
 
 
 @router.post("/api/upload")
@@ -50,12 +53,21 @@ async def upload_file(
         except Exception as e:
             log.warning(f"PDF extraction error: {e}")
             raise HTTPException(status_code=422, detail="Failed to extract text from PDF")
+    elif content_type.startswith("image/"):
+        # No OCR pipeline exists — store a descriptive placeholder so images
+        # remain usable in the gallery/context but never pollute the RAG corpus.
+        extracted = f"[Image: {file.filename}]"
     else:
         extracted = raw_bytes.decode("utf-8", errors="replace")
 
     result = {"filename": file.filename, "size_bytes": len(raw_bytes), "mode": mode}
 
-    if mode in ("ingest", "both"):
+    is_image = content_type.startswith("image/")
+    if is_image and mode in ("ingest", "both"):
+        result["chunks_ingested"] = 0
+        result["note"] = "Image files cannot be text-ingested; stored for gallery/context only"
+
+    if mode in ("ingest", "both") and not is_image:
         os.makedirs(UPLOAD_DIR, exist_ok=True)
         chunks = chunk_text(extracted)
         ingested = 0
@@ -77,7 +89,7 @@ async def upload_file(
                         "points": [{
                             "id": pid,
                             "vector": vector,
-                            "payload": {"text": chunk, "source": file.filename, "upload_date": datetime.now(timezone.utc).isoformat(), "type": "upload"},
+                            "payload": {"text": encrypt_text(chunk), "source": file.filename, "upload_date": datetime.now(timezone.utc).isoformat(), "type": "upload"},
                         }]
                     },
                     timeout=30.0,
@@ -87,6 +99,10 @@ async def upload_file(
                 else:
                     log.warning(f"Qdrant upsert failed for chunk {i}: {upsert_resp.status_code}")
         result["chunks_ingested"] = ingested
+        if ingested > 0:
+            evicted = await maybe_evict()
+            if evicted:
+                log.info(f"Evicted {evicted} vectors after upload")
 
     if mode in ("context", "both"):
         expires = (datetime.now(timezone.utc) + timedelta(hours=UPLOAD_CONTEXT_EXPIRY_HOURS)).isoformat()

scripts/nuclear-clean.sh

@@ -0,0 +1,125 @@
+#!/usr/bin/env bash
+# cAIc — nuclear clean uninstall
+# Removes every trace of cAIc: bare-metal systemd install AND Docker stack.
+# Prompts for each step. Use -y to skip ALL prompts (fully automatic).
+# Use with extreme caution — will delete data and model files.
+
+set -euo pipefail
+
+RED='\033[0;31m'; GREEN='\033[0;32m'; YELLOW='\033[1;33m'; NC='\033[0m'
+SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
+SKIP=false
+[ "${1:-}" = "-y" ] && SKIP=true
+
+prompt_yn() {
+    if $SKIP; then return 0; fi
+    local msg=$1; local default=${2:-n}
+    if [[ "$default" == "y" ]]; then
+        read -p "$msg [Y/n] " r; [[ -z "$r" || "$r" =~ ^[Yy] ]]
+    else
+        read -p "$msg [y/N] " r; [[ "$r" =~ ^[Yy] ]]
+    fi
+}
+warn() { echo -e "${YELLOW}$1${NC}"; }
+
+if ! $SKIP; then
+    echo ""
+    echo "${RED}================================================${NC}"
+    echo "${RED}   cAIc NUCLEAR CLEAN - removes all traces${NC}"
+    echo "${RED}   This will delete data, models, and the app.${NC}"
+    echo "${RED}================================================${NC}"
+    echo ""
+    echo "cAIc NUCLEAR CLEAN"
+    echo "=================="
+    read -p "Type 'yes' to continue: " confirm
+    if [ "$confirm" != "yes" ]; then
+        echo "Aborted."
+        exit 1
+    else
+        SKIP=true
+    fi
+fi
+
+if ! $SKIP; then
+    prompt_yn "Run nuclear clean?" y || { echo "Aborted."; exit 0; }
+fi
+
+echo ""
+echo "========== PART 1: Docker stack =========="
+if command -v docker &>/dev/null; then
+    # Stop all cAIc-related containers
+    docker compose down 2>/dev/null || docker-compose down 2>/dev/null || echo "  no compose stack running"
+    docker ps --filter name=cai[c] --filter name=searxng --filter name=qdrant --filter name=rabbit --filter name=llama-server --filter name=ollama --filter name=caic -aq 2>/dev/null \
+        | xargs -r docker rm -f 2>/dev/null || true
+    docker volume rm caic_data caic_uploads searxng_config qdrant_storage rabbitmq_data ollama_models 2>/dev/null || echo "  volumes already gone"
+    docker rmi caic:latest 2>/dev/null || echo "  caic image already gone"
+    echo "  Docker stack removed"
+else
+    echo "  Docker not installed — skipping"
+fi
+
+echo ""
+echo "========== PART 2: Systemd service ========="
+SERVICE_FILE="/etc/systemd/system/caic.service"
+if [ -f "$SERVICE_FILE" ]; then
+    stop caic 2>/dev/null || true
+    systemctl disable caic 2>/dev/null || true
+    rm -f "$SERVICE_FILE"
+    systemctl daemon-reload
+    echo "  systemd service removed"
+else
+    echo "  no systemd service found"
+fi
+
+echo ""
+echo "========== PART 3: Install directory ========"
+for dir in /opt/caic /var/lib/caic; do
+    if [ -d "$dir" ]; then
+        rm -rf "$dir"
+        echo "  Removed: $dir"
+    else
+        echo "  Skipped: $dir"
+    fi
+done
+
+echo ""
+echo "========== PART 4: Config and state files ========"
+for f in \
+    /home/gramps/.caic_amqp_secret \
+    hardware_state.json \
+    setup.log \
+    .env; do
+    rm -f "$f" 2>/dev/null || true
+done
+echo "  Config/state files cleaned"
+
+echo ""
+echo "========== PART 5: Temp data ==========="
+rm -rf /tmp/caic_uploads 2>/dev/null || true
+echo "  Temp data cleaned"
+
+echo ""
+echo "========== PART 6: User data (prompt each) ========="
+if prompt_yn "Remove the repository (current dir)?" n; then
+    cd ..
+    rm -rf "$SCRIPT_DIR"
+    echo "  Repository removed"
+else
+    echo "  Repository preserved"
+fi
+
+echo ""
+echo "${GREEN}cAIc nuclear clean complete.${NC}"
+echo ""
+echo "Manually verify:"
+echo "  - ls /opt/caic/"
+echo "  - ls /etc/systemd/system/caic*"
+echo "  - docker images | grep -E \"caic|searx|qdrant|rabbit|llama|ollama\""
+echo "  - docker ps -a"
+echo ""
+echo "To remove Docker Engine itself:"
+echo "  sudo apt remove docker.io containerd runc"
+echo "  sudo rm -rf /var/lib/docker"
+echo ""
+echo "To remove python packages:"
+echo "  pip uninstall fastapi uvicorn httpx psutil jinja2 python-multipart pypdf aio-pika"

scripts/setup.sh

@@ -0,0 +1,140 @@
+#!/usr/bin/env bash
+# cAIc — First-run scaffolding
+# Creates secrets, config, and directories needed by docker compose.
+# Idempotent: safe to re-run.
+set -euo pipefail
+
+GREEN='\033[0;32m'; YELLOW='\033[1;33m'; NC='\033[0m'
+
+ok()   { echo -e "  ${GREEN}✓${NC} $1"; }
+warn() { echo -e "  ${YELLOW}!${NC} $1"; }
+
+echo "cAIc — scaffolding"
+echo "==================="
+
+# ── .env ────────────────────────────────────────────────────
+if [ ! -f .env ]; then
+    cp .env.example .env
+
+    # Auto-generate secrets
+    ADMIN_PIN=$(shuf -i 1000-9999 -n 1)
+    API_KEY="caic-sk-$(openssl rand -hex 24)"
+    RMQ_PASS=$(openssl rand -hex 20)
+    SEARX_KEY=$(openssl rand -hex 32)
+
+    sed -i "s/^CAIC_ADMIN_PIN=$/CAIC_ADMIN_PIN=$ADMIN_PIN/" .env
+    sed -i "s/^CAIC_COMPLETIONS_API_KEY=$/CAIC_COMPLETIONS_API_KEY=$API_KEY/" .env
+    sed -i "s/^RABBITMQ_PASSWORD=$/RABBITMQ_PASSWORD=$RMQ_PASS/" .env
+    sed -i "s/^SEARXNG_SECRET_KEY=$/SEARXNG_SECRET_KEY=$SEARX_KEY/" .env
+
+    ok ".env created"
+    warn "  Admin PIN:    $ADMIN_PIN"
+    warn "  API key:      $API_KEY"
+else
+    warn ".env already exists — skipped"
+fi
+
+# ── secrets/ ────────────────────────────────────────────────
+mkdir -p secrets
+if [ ! -f secrets/rabbitmq_password.txt ]; then
+    RMQ_PASS=$(grep '^RABBITMQ_PASSWORD=' .env | cut -d= -f2)
+    echo -n "$RMQ_PASS" > secrets/rabbitmq_password.txt
+    ok "secrets/rabbitmq_password.txt created"
+else
+    warn "secrets/rabbitmq_password.txt exists — skipped"
+fi
+
+# ── searxng/settings.yml ────────────────────────────────────
+mkdir -p searxng
+if [ ! -f searxng/settings.yml ]; then
+    SEARX_KEY=$(grep '^SEARXNG_SECRET_KEY=' .env | cut -d= -f2)
+    # Substitute the secret key into the template
+    sed "s/\${SEARXNG_SECRET_KEY}/$SEARX_KEY/" searxng-settings.yml.dist > searxng/settings.yml
+    ok "searxng/settings.yml created"
+else
+    warn "searxng/settings.yml exists — skipped"
+fi
+
+# ── models/ ─────────────────────────────────────────────────
+DEFAULT_MODEL_REPO="unsloth/Qwen2.5-7B-Instruct-GGUF"
+DEFAULT_MODEL_FILE="Qwen2.5-7B-Instruct-Q4_K_M.gguf"
+DEFAULT_MODEL_SIZE_MB=4600  # approximate download size
+DEFAULT_MODEL_NAME="qwen2.5-7b-instruct"
+
+mkdir -p models
+
+# Set LLAMA_MODEL and CAIC_DEFAULT_MODEL in .env if not already set
+LLAMA_MODEL_LINE=$(grep '^LLAMA_MODEL=' .env || true)
+if [ -z "$LLAMA_MODEL_LINE" ] || [ "$LLAMA_MODEL_LINE" = "LLAMA_MODEL=" ]; then
+    sed -i "s/^LLAMA_MODEL=$/LLAMA_MODEL=$DEFAULT_MODEL_FILE/" .env
+    sed -i "s/^CAIC_DEFAULT_MODEL=.*/CAIC_DEFAULT_MODEL=$DEFAULT_MODEL_NAME/" .env
+    ok "Set LLAMA_MODEL=$DEFAULT_MODEL_FILE"
+    ok "Set CAIC_DEFAULT_MODEL=$DEFAULT_MODEL_NAME"
+fi
+
+if ls models/*.gguf 1>/dev/null 2>&1; then
+    ok "models/ has $(ls models/*.gguf | wc -l) model(s)"
+else
+    echo ""
+    echo "  No .gguf models found in ./models/"
+    echo ""
+
+    # Check disk space
+    AVAIL_KB=$(df -k models/ | tail -1 | awk '{print $4}')
+    AVAIL_MB=$((AVAIL_KB / 1024))
+    REQUIRED_MB=$((DEFAULT_MODEL_SIZE_MB + 500))  # 500MB safety margin
+
+    if [ "$AVAIL_MB" -lt "$REQUIRED_MB" ]; then
+        warn "Insufficient disk space: ${AVAIL_MB}MB available, ~${REQUIRED_MB}MB needed"
+        warn "Free space or change LLAMA_MODEL in .env to use a smaller model."
+        echo ""
+    else
+        echo "  Download default model (~${DEFAULT_MODEL_SIZE_MB}MB):"
+        echo "    ${DEFAULT_MODEL_REPO}/${DEFAULT_MODEL_FILE}"
+        echo ""
+        read -p "  Download now? [Y/n] " r
+        if [[ -z "$r" || "$r" =~ ^[Yy] ]]; then
+            echo ""
+            echo "  Downloading ${DEFAULT_MODEL_FILE}..."
+            if command -v hf &>/dev/null; then
+                # huggingface-cli (hf_transfer) if available
+                hf download "$DEFAULT_MODEL_REPO" "$DEFAULT_MODEL_FILE" \
+                    --local-dir models/ --local-dir-use-symlinks False
+            elif command -v wget &>/dev/null; then
+                wget -q --show-progress -O "models/$DEFAULT_MODEL_FILE" \
+                    "https://huggingface.co/${DEFAULT_MODEL_REPO}/resolve/main/${DEFAULT_MODEL_FILE}"
+            elif command -v curl &>/dev/null; then
+                curl -L --progress-bar -o "models/$DEFAULT_MODEL_FILE" \
+                    "https://huggingface.co/${DEFAULT_MODEL_REPO}/resolve/main/${DEFAULT_MODEL_FILE}"
+            else
+                warn "Neither wget nor curl found — cannot download."
+                warn "  Manual: wget -O models/$DEFAULT_MODEL_FILE \\"
+                warn "    https://huggingface.co/${DEFAULT_MODEL_REPO}/resolve/main/${DEFAULT_MODEL_FILE}"
+            fi
+
+            if [ -f "models/$DEFAULT_MODEL_FILE" ]; then
+                DOWNLOADED_MB=$(du -m "models/$DEFAULT_MODEL_FILE" | cut -f1)
+                ok "Downloaded ${DEFAULT_MODEL_FILE} (${DOWNLOADED_MB}MB)"
+            else
+                warn "Download failed — place model manually in ./models/"
+            fi
+        else
+            warn "Skipped. Place .gguf model(s) in ./models/ before docker compose up."
+        fi
+    fi
+fi
+
+# ── data/ ───────────────────────────────────────────────────
+mkdir -p data
+ok "data/ directory ready"
+
+# ── Verify Docker ───────────────────────────────────────────
+echo ""
+if command -v docker &>/dev/null && docker compose version &>/dev/null; then
+    ok "Docker Compose available: $(docker compose version --short)"
+    echo ""
+    echo -e "${GREEN}Ready!${NC} Run:  docker compose up -d"
+else
+    warn "Docker Compose not found — install Docker Engine + Compose plugin first."
+    echo "  https://docs.docker.com/engine/install/"
+fi

scripts/teardown-docker.sh

@@ -0,0 +1,109 @@
+#!/usr/bin/env bash
+# cAIc — Docker stack teardown
+# Removes all containers, volumes, images, and generated files
+# created by setup-wizard / docker compose.
+# Run from the docker deployment directory. Use -y to skip prompts.
+
+set -euo pipefail
+
+RED='\033[0;31m'; GREEN='\033[0;32m'; YELLOW='\033[1;33m'; NC='\033[0m'
+SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
+
+prompt_yn() {
+    if [ "${1:-}" = "-y" ]; then return 0; fi
+    [ "$SKIP" = true ] && return 0
+    local msg=$1; local default=${2:-n}
+    if [[ "$default" == "y" ]]; then
+        read -p "$msg [Y/n] " r; [[ -z "$r" || "$r" =~ ^[Yy] ]]
+    else
+        read -p "$msg [y/N] " r; [[ "$r" =~ ^[Yy] ]]
+    fi
+}
+
+SKIP=false
+[ "${1:-}" = "-y" ] && SKIP=true
+
+echo "cAIc Docker stack teardown"
+echo "=========================="
+
+# ---- Step 1: docker compose down -v ----
+if [ -f docker-compose.yml ] || [ -f compose.yml ]; then
+    if prompt_yn "Stop Docker stack and remove volumes?" n; then
+        docker compose down -v 2>/dev/null || docker-compose down -v 2>/dev/null || true
+        echo "  Docker stack stopped and volumes removed"
+    else
+        warn "  Skipped: Docker stack left intact"
+    fi
+else
+    echo "  Skipped: no compose file found"
+fi
+
+# ---- Step 2: Remove Docker images ----
+if prompt_yn "Remove cAIc Docker image?" n; then
+    docker rmi caic:latest 2>/dev/null || true
+    echo "  Removed caic:latest"
+
+    warn "Remove SearXNG / Qdrant / RabbitMQ / llama-server / Ollama images?"
+    if prompt_yn "  Remove service images?" n; then
+        for tag in searxng/searxng qdrant/qdrant rabbitmq:4-management \
+                   ghcr.io/ggml-org/llama.cpp ollama/ollama; do
+            docker rmi "$tag" 2>/dev/null || true
+        done
+        echo "  Service images removed"
+    fi
+fi
+
+# ---- Step 3: Volumes ----
+if prompt_yn "Remove remaining Docker volumes?" n; then
+    for vol in caic_data caic_uploads searxng_config qdrant_storage rabbitmq_data ollama_models; do
+        docker volume rm "$vol" 2>/dev/null || true
+    done
+    echo "  Docker volumes removed"
+fi
+
+# ---- Step 4: .env ----
+if [ -f .env ]; then
+    if prompt_yn "Remove .env file?" n; then
+        rm -f .env
+        echo "  .env removed"
+    fi
+fi
+
+# ---- Step 5: generated directories ----
+for dir in secrets searxng; do
+    if [ -d "$dir" ]; then
+        if prompt_yn "Remove $dir/ directory?" n; then
+            rm -rf "$dir"
+            echo "  $dir/ removed"
+        fi
+    fi
+done
+
+# ---- Step 6: generated files ----
+for f in setup.log docker-compose.yml compose.yml; do
+    [ -f "$f" ] || continue
+    if prompt_yn "Remove $f?" n; then
+        rm -f "$f"
+        echo "  $f removed"
+    fi
+done
+
+# ---- Step 7: model files (with big warning) ----
+if [ -d models ]; then
+    echo ""
+    echo -e "${RED}WARNING: model files (*.gguf) can be gigabytes each.${NC}"
+    if prompt_yn "Remove all model files from ./models/?" n; then
+        rm -rf models
+        echo "  models/ removed"
+    else
+        echo "  models/ preserved"
+    fi
+fi
+
+echo ""
+echo -e "${GREEN}cAIc Docker stack teardown complete.${NC}"
+echo "Preserved:"
+echo "  - ./models/                       (unless you accepted removal)"
+echo ""
+echo "Note: Docker Engine itself is not removed. To remove it:"
+echo "  sudo apt-get remove docker docker-engine docker.io containerd runc"

scripts/uninstall.sh

@@ -0,0 +1,98 @@
+#!/usr/bin/env bash
+# cAIc — bare-metal/systemd uninstall
+# Removes the cAIc install deployed via the README Fresh Install path.
+# Run as root or with sudo. Use -y to skip prompts.
+
+set -euo pipefail
+
+RED='\033[0;31m'; GREEN='\033[0;32m'; YELLOW='\033[1;33m'; NC='\033[0m'
+SKIP_PROMPT=false
+[ "${1:-}" = "-y" ] && SKIP_PROMPT=true
+
+prompt_yn() {
+    if $SKIP_PROMPT; then return 0; fi
+    local msg=$1; local default=${2:-n}
+    if [[ "$default" == "y" ]]; then
+        read -p "$msg [Y/n] " r; [[ -z "$r" || "$r" =~ ^[Yy] ]]
+    else
+        read -p "$msg [y/N] " r; [[ "$r" =~ ^[Yy] ]]
+    fi
+}
+warn() { echo -e "${YELLOW}$1${NC}"; }
+
+echo "cAIc Bare-metal / systemd uninstall"
+echo "===================================="
+
+# ---- Step 1: systemd service ----
+SERVICE_FILE="/etc/systemd/system/caic.service"
+if [ -f "$SERVICE_FILE" ]; then
+    warn "Stopping and disabling caic service..."
+    systemctl stop caic 2>/dev/null || true
+    systemctl disable caic 2>/dev/null || true
+    if prompt_yn "Remove caic systemd service?" n; then
+        rm -f "$SERVICE_FILE" /etc/systemd/system/caic.service
+        systemctl daemon-reload
+        echo "  Removed systemd service"
+    fi
+else
+    echo "  Skipped: no systemd service at $SERVICE_FILE"
+fi
+
+# ---- Step 2: /opt/caic directory ----
+CAIC_DIR="/opt/caic"
+if [ -d "$CAIC_DIR" ]; then
+    if prompt_yn "Remove cAIc installation directory ($CAIC_DIR)?" n; then
+        rm -rf "$CAIC_DIR"
+        echo "  Removed $CAIC_DIR"
+    else
+        warn "  Skipped: $CAIC_DIR preserved"
+    fi
+else
+    echo "  Skipped: $CAIC_DIR does not exist"
+fi
+
+# ---- Step 3: AMQP secret file ----
+if [ -f "/home/gramps/.caic_amqp_secret" ]; then
+    if prompt_yn "Remove AMQP secret file (/home/gramps/.caic_amqp_secret)?" n; then
+        rm -f /home/gramps/.caic_amqp_secret
+        echo "  Removed AMQP secret"
+    fi
+fi
+
+# ---- Step 4: Upload temp directory ----
+UPLOAD_DIR="/tmp/caic_uploads"
+if [ -d "$UPLOAD_DIR" ]; then
+    if prompt_yn "Remove upload temp directory ($UPLOAD_DIR)?" n; then
+        rm -rf "$UPLOAD_DIR"
+        echo "  Removed upload temp"
+    fi
+fi
+
+# ---- Step 5: hardware_state.json in cwd ----
+if [ -f "hardware_state.json" ]; then
+    if prompt_yn "Remove cached hardware state?" n; then
+        rm -f hardware_state.json
+        echo "  Removed cached hardware state"
+    fi
+fi
+
+# ---- Step 6: pip packages if user wants ----
+if command -v pip &>/dev/null; then
+    if prompt_yn "Attempt to uninstall cAIc-related pip packages?" n; then
+        pip uninstall -y fastapi uvicorn httpx psutil aio-pika jinja2 python-multipart pypdf 2>/dev/null || true
+        echo "  Uninstalled pip packages"
+    fi
+fi
+
+echo ""
+echo -e "${GREEN}cAIc bare-metal/uninstall complete.${NC}"
+echo "The following may remain:"
+echo "  - /opt/caic/                     (if you chose to preserve)"
+echo "  - ~/.caic_amqp_secret            (if preserved)"
+echo "  - hardware_state.json            (if preserved)"
+echo "  - installed pip packages         (if you chose to skip)"
+echo "  - Python venv at /opt/caic/venv  (removed with /opt/caic)"
+echo ""
+echo "Caic data stored outside install:"
+echo "  - caic.db                        (if configured via CAIC_DB_PATH)"
+echo "  - claude/opencode .jsonc updates (not tracked by this script)"

search.py

@@ -1,5 +1,5 @@
 """
-JarvisChat - SearXNG integration, perplexity scoring, refusal/hedge detection.
+cAIc - SearXNG integration, perplexity scoring, refusal/hedge detection.
 """
 import logging
 import math
@@ -10,7 +10,7 @@ import httpx
 
 from config import SEARXNG_BASE, PERPLEXITY_THRESHOLD, REFUSAL_PATTERNS, HEDGE_PATTERNS
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
 
 def sanitize_outbound_url(url: str) -> str:
@@ -117,6 +117,7 @@ async def query_searxng(query: str, max_results: int = 5) -> list:
                 f"{SEARXNG_BASE}/search",
                 params={"q": query, "format": "json", "categories": "general"},
                 timeout=10.0,
+                follow_redirects=True,
             )
             if resp.status_code == 200:
                 data = resp.json()

searxng-settings.yml.dist

@@ -0,0 +1,26 @@
+# SearXNG configuration — cAIc stack
+# Secret key is injected via environment variable.
+
+search:
+  safe_search: 0
+  autocomplete: ""
+  default_lang: en
+
+server:
+  secret_key: ${SEARXNG_SECRET_KEY}
+  limiter: false
+  image_proxy: false
+  method: GET
+  port: 8080
+  bind_address: "0.0.0.0"
+
+engines:
+  - name: google
+    engine: google
+    shortcut: g
+  - name: duckduckgo
+    engine: duckduckgo
+    shortcut: ddg
+  - name: wikipedia
+    engine: wikipedia
+    shortcut: wp

security.py

@@ -1,5 +1,5 @@
 """
-JarvisChat - Security utilities.
+cAIc - Security utilities.
 PIN hashing, audit logging, incident tracking, CSRF/origin checks,
 rate limiting, request helpers.
 """
@@ -30,7 +30,7 @@ from config import (
 
 import ipaddress
 
-log = logging.getLogger("jarvischat")
+log = logging.getLogger("caic")
 
 SESSIONS: dict = {}
 PIN_ATTEMPTS: dict = {}
@@ -161,10 +161,6 @@ def origin_allowed(request: Request) -> bool:
     return False
 
 
-def is_state_changing(method: str) -> bool:
-    return method in {"POST", "PUT", "DELETE", "PATCH"}
-
-
 async def read_json_body(request: Request, max_bytes: int) -> dict:
     raw = await request.body()
     if len(raw) > max_bytes:

tests/conftest.py

@@ -0,0 +1,34 @@
+# Ensure the project root is on sys.path so that test modules can import
+# top-level packages (app, amqp, cluster, config, …) without PYTHONPATH hacks.
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+
+"""Shared pytest fixtures.
+
+All test modules manipulate in-process globals (sessions, rate buckets,
+cluster registry, eviction log). An autouse fixture resets every global
+before each test so no state leaks between tests, regardless of whether an
+individual test file remembers to clear it.
+"""
+import pytest
+
+import cluster
+import routers.chat
+from eviction import EVICTION_LOG
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+@pytest.fixture(autouse=True)
+def _reset_global_state():
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    cluster.CLUSTER_NODES.clear()
+    cluster.CLUSTER_EVENTS.clear()
+    cluster.CLUSTER_COORDINATOR = None
+    cluster._pending_pings.clear()
+    EVICTION_LOG.clear()
+    routers.chat._ingest_tasks.clear()
+    yield

tests/test_amqp.py

@@ -0,0 +1,90 @@
+import asyncio
+import logging
+
+import amqp
+from config import AMQP_EXCHANGE_ADMIN
+
+
+def _reset():
+    amqp._connection = None
+    amqp._channel = None
+    amqp._lock = asyncio.Lock()
+
+
+class FakeExchange:
+    def __init__(self):
+        self.messages = []
+
+    async def publish(self, msg, routing_key):
+        self.messages.append((msg, routing_key))
+
+
+class FakeChannel:
+    def __init__(self):
+        self.is_closed = False
+        self.exchanges = {}
+
+    async def close(self):
+        self.is_closed = True
+
+    async def declare_exchange(self, name, typ, durable=True):
+        self.exchanges[name] = typ
+
+    async def get_exchange(self, name):
+        return self.exchanges.setdefault(name, FakeExchange())
+
+
+class FakeConnection:
+    def __init__(self):
+        self.is_closed = False
+        self._channel = FakeChannel()
+
+    async def channel(self):
+        return self._channel
+
+    async def close(self):
+        self.is_closed = True
+
+
+async def fake_connect_robust(url, **_):
+    return FakeConnection()
+
+
+# ---------- tests ----------
+
+
+def test_publish_success(monkeypatch):
+    _reset()
+    monkeypatch.setattr(amqp, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr("aio_pika.connect_robust", fake_connect_robust)
+
+    asyncio.run(amqp.connect())
+    ch = asyncio.run(amqp.get_channel())
+    ex = FakeExchange()
+    ch.exchanges[AMQP_EXCHANGE_ADMIN] = ex
+
+    asyncio.run(amqp.publish(AMQP_EXCHANGE_ADMIN, "test.key", {"foo": "bar"}))
+
+    assert len(ex.messages) == 1
+    msg, rk = ex.messages[0]
+    assert rk == "test.key"
+    assert msg.body == b'{"foo": "bar"}'
+
+
+def test_publish_disconnected_no_raise(caplog):
+    _reset()
+    caplog.set_level(logging.ERROR)
+    asyncio.run(amqp.publish(AMQP_EXCHANGE_ADMIN, "test.key", {"x": 1}))
+
+    assert len(caplog.records) > 0
+    assert any("cannot publish" in r.message for r in caplog.records)
+
+
+def test_get_channel_reconnects_when_none(monkeypatch):
+    _reset()
+    monkeypatch.setattr(amqp, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr("aio_pika.connect_robust", fake_connect_robust)
+
+    ch = asyncio.run(amqp.get_channel())
+    assert ch is not None
+    assert not ch.is_closed

tests/test_auth_capabilities.py

@@ -9,8 +9,8 @@ from security import SESSIONS, PIN_ATTEMPTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-test.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-test.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     db.init_db()

tests/test_chat_streaming_and_memory_paths.py

@@ -1,5 +1,6 @@
 import json
 import os
+import asyncio
 from pathlib import Path
 
 import httpx
@@ -12,9 +13,13 @@ import routers.chat
 from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
+def _mock_triage_url(monkeypatch, url: str = config.LLAMA_SERVER_BASE):
+    monkeypatch.setattr(config, "LLAMA_SERVER_BASE", url)
+
+
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-streaming.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-streaming.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()
@@ -53,6 +58,7 @@ def _stream_json_lines(events: list[dict]) -> list[str]:
 
 
 def test_chat_stream_emits_tokens_and_done(tmp_path: Path, monkeypatch):
+    _mock_triage_url(monkeypatch)
     with make_client(tmp_path) as client:
         sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
             "session_id"
@@ -88,6 +94,7 @@ def test_chat_stream_emits_tokens_and_done(tmp_path: Path, monkeypatch):
 
 
 def test_chat_auto_search_trigger_emits_search_events(tmp_path: Path, monkeypatch):
+    _mock_triage_url(monkeypatch)
     with make_client(tmp_path) as client:
         sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
             "session_id"
@@ -142,6 +149,7 @@ def test_chat_auto_search_trigger_emits_search_events(tmp_path: Path, monkeypatc
 
 
 def test_chat_with_upload_context_id_injects_document(tmp_path: Path, monkeypatch):
+    _mock_triage_url(monkeypatch)
     captured_payload = {}
 
     def stream_stub(self, method, url, json=None, timeout=None):
@@ -173,6 +181,7 @@ def test_chat_with_upload_context_id_injects_document(tmp_path: Path, monkeypatc
 
 
 def test_chat_with_expired_upload_context_id_silent(tmp_path: Path, monkeypatch):
+    _mock_triage_url(monkeypatch)
     captured_payload = {}
 
     def stream_stub(self, method, url, json=None, timeout=None):
@@ -205,6 +214,7 @@ def test_chat_with_expired_upload_context_id_silent(tmp_path: Path, monkeypatch)
 
 
 def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
+    _mock_triage_url(monkeypatch)
     with make_client(tmp_path) as client:
         sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
             "session_id"
@@ -251,6 +261,55 @@ def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
         forget_events = parse_sse_payloads(forget_resp.text)
         assert any("Forgot" in p.get("token", "") for p in forget_events)
 
-        memories_after_forget = client.get("/api/memories", headers={"X-Session-ID": sid, "Origin": "http://testserver"})
-        assert memories_after_forget.status_code == 200
-        assert memories_after_forget.json().get("count", 0) == 0
+def test_private_chat_does_not_persist(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "stream", lambda *a, **kw: _MockStreamResponse([
+        'data: {"choices":[{"delta":{"content":"Hello"},"finish_reason":null,"logprobs":{"content":[]}}]}',
+        'data: {"choices":[{"delta":{"content":" world"},"finish_reason":null,"logprobs":{"content":[]}}]}',
+        'data: {"choices":[{"delta":{"content":""},"finish_reason":"stop","logprobs":{"content":[]}}],"usage":{"completion_tokens":2,"prompt_tokens":10,"tokens_per_second":5.0}}',
+        "data: [DONE]",
+    ]))
+
+    async def _mock_ensure(m): return True
+    monkeypatch.setattr("model_pull.ensure_model", _mock_ensure)
+
+    with make_client(tmp_path) as client:
+        sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+        headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+        resp = client.post("/api/chat", json={
+            "message": "test private message",
+            "private_chat": True,
+        }, headers=headers)
+        assert resp.status_code == 200
+        events = parse_sse_payloads(resp.text)
+        tokens = [p for p in events if "token" in p]
+        assert len(tokens) == 2
+        done = [p for p in events if p.get("done")]
+        assert len(done) == 1
+
+        conv_resp = client.get("/api/conversations", headers=headers)
+        assert conv_resp.status_code == 200
+        assert len(conv_resp.json()) == 0
+
+
+def test_private_chat_does_not_auto_search(tmp_path: Path, monkeypatch):
+    """Private mode should skip auto-search even when search is enabled."""
+    monkeypatch.setattr(httpx.AsyncClient, "stream", lambda *a, **kw: _MockStreamResponse([
+        'data: {"choices":[{"delta":{"content":"I don\'t know"},"finish_reason":null,"logprobs":{"content":[{"logprob":-2.5}]}}]}',
+        'data: {"choices":[{"delta":{"content":""},"finish_reason":"stop","logprobs":{"content":[{"logprob":-2.5}]}}],"usage":{"completion_tokens":1,"prompt_tokens":10,"tokens_per_second":5.0}}',
+        "data: [DONE]",
+    ]))
+    monkeypatch.setattr(routers.chat, "query_searxng", lambda q: [{"title": "result"}])
+
+    with make_client(tmp_path) as client:
+        sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+        headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+        resp = client.post("/api/chat", json={
+            "message": "what is the weather",
+            "private_chat": True,
+        }, headers=headers)
+        assert resp.status_code == 200
+        events = parse_sse_payloads(resp.text)
+        searching = [p for p in events if p.get("searching")]
+        assert len(searching) == 0, "private chat should not auto-search"

tests/test_cluster.py

@@ -0,0 +1,313 @@
+"""Tests for cluster.py — no live AMQP, all handlers called directly."""
+import asyncio
+from collections import deque
+
+import cluster
+from config import AMQP_EXCHANGE_ADMIN, AMQP_EXCHANGE_SYSTEM
+
+
+def _reset():
+    cluster.CLUSTER_NODES.clear()
+    cluster.CLUSTER_EVENTS.clear()
+    cluster.CLUSTER_COORDINATOR = None
+    cluster._pending_pings.clear()
+
+
+_published = []
+
+
+async def _fake_publish(exchange, routing_key, payload):
+    _published.append((exchange, routing_key, payload))
+
+
+# ---------- 1. Valid worker registration ----------
+
+
+def test_valid_worker_registration(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis", "node_type": "worker", "capabilities": ["llm"]},
+    ))
+
+    assert "jarvis" in cluster.CLUSTER_NODES
+    assert cluster.CLUSTER_NODES["jarvis"]["type"] == "worker"
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "active"
+    assert len(cluster.CLUSTER_EVENTS) == 1
+    assert cluster.CLUSTER_EVENTS[0]["category"] == "cluster"
+    assert cluster.CLUSTER_EVENTS[0]["message"] == "Node registered (type=worker)"
+
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert exchange == AMQP_EXCHANGE_ADMIN
+    assert rk == "node.jarvis.admitted"
+    assert payload["type"] == "admitted"
+    assert payload["node_name"] == "jarvis"
+
+
+# ---------- 2. First coordinator auto-promotion ----------
+
+
+def test_first_coordinator_auto_promotion(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.ultron.register",
+        {"node_name": "ultron", "node_type": "coordinator", "capabilities": ["llm", "rag"]},
+    ))
+
+    assert cluster.CLUSTER_COORDINATOR == "ultron"
+    assert len(cluster.CLUSTER_EVENTS) == 2
+    assert cluster.CLUSTER_EVENTS[1]["message"] == "Elected as coordinator"
+
+    assert len(_published) == 2
+    # First publish: admitted
+    assert _published[0][1] == "node.ultron.admitted"
+    # Second publish: coord_response
+    exchange, rk, payload = _published[1]
+    assert exchange == AMQP_EXCHANGE_SYSTEM
+    assert rk == "cluster.coordinator.response"
+    assert payload["type"] == "coord_response"
+    assert payload["coordinator"] == "ultron"
+
+
+# ---------- 3. Duplicate node name rejected ----------
+
+
+def test_duplicate_node_rejected(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis", "node_type": "worker", "capabilities": ["llm"]},
+    ))
+    _published.clear()
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis", "node_type": "worker", "capabilities": ["llm"]},
+    ))
+
+    assert len(cluster.CLUSTER_NODES) == 1
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert exchange == AMQP_EXCHANGE_ADMIN
+    assert rk == "node.jarvis.rejected"
+    assert payload["reason"] == "duplicate_node_name"
+
+
+# ---------- 4. Malformed payload rejected ----------
+
+
+def test_malformed_payload_rejected(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis"},  # missing node_type and capabilities
+    ))
+
+    assert len(cluster.CLUSTER_NODES) == 0
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert rk == "node.jarvis.rejected"
+    assert payload["reason"] == "malformed_payload"
+
+
+# ---------- 5. Graceful deregistration ----------
+
+
+def test_graceful_deregistration(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis", "node_type": "worker", "capabilities": ["llm"]},
+    ))
+    _published.clear()
+
+    asyncio.run(cluster.handle_deregistration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.deregister",
+        {"node_name": "jarvis"},
+    ))
+
+    assert "jarvis" not in cluster.CLUSTER_NODES
+    assert len(cluster.CLUSTER_EVENTS) == 2
+    assert cluster.CLUSTER_EVENTS[1]["message"] == "Node deregistered"
+
+
+def test_deregister_coordinator_clears(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.ultron.register",
+        {"node_name": "ultron", "node_type": "coordinator", "capabilities": ["llm"]},
+    ))
+    assert cluster.CLUSTER_COORDINATOR == "ultron"
+    _published.clear()
+
+    asyncio.run(cluster.handle_deregistration(
+        AMQP_EXCHANGE_ADMIN, "node.ultron.deregister",
+        {"node_name": "ultron"},
+    ))
+
+    assert "ultron" not in cluster.CLUSTER_NODES
+    assert cluster.CLUSTER_COORDINATOR is None
+
+
+# ---------- 6. Pong from known node ----------
+
+
+def test_pong_updates_known_node(monkeypatch):
+    _reset()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.register",
+        {"node_name": "jarvis", "node_type": "worker", "capabilities": ["llm"]},
+    ))
+    original_seen = cluster.CLUSTER_NODES["jarvis"]["last_seen"]
+
+    asyncio.run(cluster.handle_pong(
+        AMQP_EXCHANGE_ADMIN, "node.jarvis.pong",
+        {"node_name": "jarvis", "status": "busy", "load": {"cpu_pct": 80}},
+    ))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "busy"
+    assert cluster.CLUSTER_NODES["jarvis"]["load"] == {"cpu_pct": 80}
+    assert cluster.CLUSTER_NODES["jarvis"]["last_seen"] != original_seen
+
+
+# ---------- 7. Pong from unknown node ----------
+
+
+def test_pong_from_unknown_node(caplog, monkeypatch):
+    _reset()
+    caplog.set_level("WARNING")
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_pong(
+        AMQP_EXCHANGE_ADMIN, "node.stranger.pong",
+        {"node_name": "stranger", "status": "active"},
+    ))
+
+    assert "stranger" not in cluster.CLUSTER_NODES
+    assert any("pong from unknown node" in rec.message for rec in caplog.records)
+
+
+# ---------- 8. Event stored in log ----------
+
+
+def test_event_appended_to_log(monkeypatch):
+    _reset()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_event(
+        AMQP_EXCHANGE_SYSTEM, "node.jarvis.event",
+        {"node_name": "jarvis", "severity": "error", "message": "OOM on GPU"},
+    ))
+
+    assert len(cluster.CLUSTER_EVENTS) == 1
+    ev = cluster.CLUSTER_EVENTS[0]
+    assert ev["category"] == "application"
+    assert ev["severity"] == "error"
+    assert ev["node"] == "jarvis"
+
+
+def test_event_log_bounded(monkeypatch):
+    _reset()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    for i in range(1001):
+        cluster._push_event("application", "info", "jarvis", f"event {i}")
+
+    assert len(cluster.CLUSTER_EVENTS) == 1000
+    assert cluster.CLUSTER_EVENTS[0]["message"] == "event 1"
+    assert cluster.CLUSTER_EVENTS[-1]["message"] == "event 1000"
+
+
+# ---------- 9. Coordinator query produces response ----------
+
+
+def test_coordinator_query_response(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_registration(
+        AMQP_EXCHANGE_ADMIN, "node.ultron.register",
+        {"node_name": "ultron", "node_type": "coordinator", "capabilities": ["llm"]},
+    ))
+    _published.clear()
+
+    asyncio.run(cluster.handle_coordinator_query(
+        AMQP_EXCHANGE_SYSTEM, "cluster.coordinator.query",
+        {"from": "jarvis", "type": "coord_query"},
+    ))
+
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert exchange == AMQP_EXCHANGE_SYSTEM
+    assert rk == "cluster.coordinator.response"
+    assert payload["coordinator"] == "ultron"
+    assert "nodes" in payload
+
+
+def test_coordinator_query_no_coordinator(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_coordinator_query(
+        AMQP_EXCHANGE_SYSTEM, "cluster.coordinator.query",
+        {"from": "jarvis", "type": "coord_query"},
+    ))
+
+    assert len(_published) == 0
+
+
+# ---------- 10. GET /api/cluster shape ----------
+
+
+def test_cluster_api_shape():
+    _reset()
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+        "capabilities": ["llm"], "active_model": None, "load": None,
+        "registered_at": "2026-01-01T00:00:00Z", "last_seen": "2026-01-01T00:00:00Z",
+    }
+    cluster.CLUSTER_COORDINATOR = "ultron"
+    cluster._push_event("cluster", "info", "ultron", "Elected")
+
+    from routers.cluster import cluster_status
+
+    resp = asyncio.run(cluster_status())
+
+    assert "nodes" in resp
+    assert "node_count" in resp
+    assert "coordinator" in resp
+    assert "events" in resp
+    assert resp["node_count"] == 1
+    assert resp["coordinator"] == "ultron"
+    assert "jarvis" in resp["nodes"]
+    assert len(resp["events"]) == 1
+    # No internal keys leaked
+    for node in resp["nodes"].values():
+        for key in node:
+            assert key in {
+                "name", "type", "status", "capabilities", "active_model",
+                "load", "registered_at", "last_seen",
+            }

tests/test_cluster_heartbeat.py

@@ -0,0 +1,49 @@
+"""Tests for cluster.py heartbeat handler."""
+import asyncio
+
+import cluster
+from config import AMQP_EXCHANGE_SYSTEM
+
+
+def _reset():
+    cluster.CLUSTER_NODES.clear()
+    cluster.CLUSTER_EVENTS.clear()
+    cluster.CLUSTER_COORDINATOR = None
+    cluster._pending_pings.clear()
+
+
+# ---------- 1. handle_heartbeat() for known node updates last_seen ----------
+
+
+def test_heartbeat_updates_last_seen(monkeypatch):
+    _reset()
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+        "last_seen": "2020-01-01T00:00:00Z",
+    }
+    original = cluster.CLUSTER_NODES["jarvis"]["last_seen"]
+
+    asyncio.run(cluster.handle_heartbeat(
+        AMQP_EXCHANGE_SYSTEM, "node.jarvis.heartbeat",
+        {"node_name": "jarvis"},
+    ))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["last_seen"] != original
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "active"  # unchanged
+
+
+# ---------- 2. handle_heartbeat() for unknown node logs warning, no add ----------
+
+
+def test_heartbeat_unknown_node_logs_warning(caplog, monkeypatch):
+    _reset()
+    caplog.set_level("WARNING")
+
+    asyncio.run(cluster.handle_heartbeat(
+        AMQP_EXCHANGE_SYSTEM, "node.stranger.heartbeat",
+        {"node_name": "stranger"},
+    ))
+
+    assert "stranger" not in cluster.CLUSTER_NODES
+    assert any("unknown node" in rec.message and "stranger" in rec.message for rec in caplog.records)

tests/test_completions.py

@@ -13,8 +13,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-completions.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-completions.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()
@@ -22,7 +22,7 @@ def make_client(tmp_path: Path) -> TestClient:
     return TestClient(app.app, raise_server_exceptions=False)
 
 
-TEST_API_KEY = "test-sk-jarvischat-completions"
+TEST_API_KEY = "test-sk-caic-completions"
 
 
 def _auth_headers(extra: dict = None) -> dict:

tests/test_conversations.py

@@ -9,8 +9,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-conversations.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-conversations.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_error_envelopes.py

@@ -12,8 +12,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-errors.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-errors.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_fixes_regression.py

@@ -0,0 +1,357 @@
+"""Regression tests for bug fixes.
+
+Covers: /api/ingest origin exemption for CLI/Bearer clients, bogus
+conversation_id FK handling in chat + search, the auto-search reset flag,
+image uploads being stored as placeholders instead of text-ingested,
+false-positive conflict detection, deterministic ingest point IDs,
+get_load() VRAM parsing, and version pinning.
+"""
+import json
+import os
+import re
+import subprocess
+from pathlib import Path
+
+import httpx
+from fastapi.testclient import TestClient
+
+import app
+import config
+import db
+import memory
+from crypto import decrypt_text
+import node_agent.agent as agent
+import routers.chat
+import routers.ingest as ingest_route
+import routers.search_route
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+def make_client(tmp_path: Path) -> TestClient:
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-regression.db"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+    return TestClient(app.app, raise_server_exceptions=False)
+
+
+def _guest_headers(client: TestClient) -> dict:
+    sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+def _admin_headers(client: TestClient) -> dict:
+    login = client.post("/api/auth/login", json={"pin": "1234"}, headers={"Origin": "http://testserver"})
+    sid = login.json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+def parse_sse_payloads(body: str) -> list[dict]:
+    payloads = []
+    for chunk in body.split("\n\n"):
+        chunk = chunk.strip()
+        if not chunk.startswith("data: "):
+            continue
+        payloads.append(json.loads(chunk[len("data: "):]))
+    return payloads
+
+
+class _MockStreamResponse:
+    def __init__(self, lines: list[str]):
+        self._lines = lines
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, exc_type, exc, tb):
+        return False
+
+    async def aiter_lines(self):
+        for line in self._lines:
+            yield line
+
+
+def _stream_json_lines(events: list[dict]) -> list[str]:
+    return [json.dumps(event) for event in events]
+
+
+class _FakeAsyncClient:
+    class FakeResponse:
+        def __init__(self, status, json_data=None):
+            self.status_code = status
+            self._json = json_data or {}
+
+        def json(self):
+            return self._json
+
+    def __init__(self, *a, **kw):
+        self.put_payloads = []
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *a):
+        pass
+
+    async def post(self, url, **kw):
+        if "/api/embeddings" in url:
+            return self.FakeResponse(200, {"embedding": [0.1] * 768})
+        return self.FakeResponse(200)
+
+    async def put(self, url, **kw):
+        self.put_payloads.append(kw.get("json", {}))
+        return self.FakeResponse(200)
+
+
+# ── /api/ingest is reached by CLI tools with no Origin header ──────────
+
+
+def test_ingest_origin_exemption(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", "sk-regression")
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: _FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.post(
+            "/api/ingest",
+            json={"content": "regression test content " * 20, "source": "cli"},
+            headers={"Authorization": "Bearer sk-regression", "Content-Type": "application/json"},
+        )
+        assert resp.status_code == 200, resp.text
+        assert resp.json()["source"] == "cli"
+
+
+def test_ingest_bad_key_still_blocked_without_origin(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", "sk-regression")
+    with make_client(tmp_path) as client:
+        resp = client.post(
+            "/api/ingest",
+            json={"content": "x " * 50},
+            headers={"Authorization": "Bearer wrong-key", "Content-Type": "application/json"},
+        )
+        assert resp.status_code == 401
+
+
+# ── a client-supplied conversation_id that no longer exists ────────────
+
+
+def test_chat_bogus_conversation_id_creates_row(tmp_path: Path, monkeypatch):
+    events = _stream_json_lines([
+        {"message": {"content": "hi"}, "logprobs": [{"logprob": -0.01}]},
+        {"done": True, "eval_count": 1, "eval_duration": 1000000000},
+    ])
+
+    def stream_stub(self, method, url, json=None, timeout=None):
+        return _MockStreamResponse(events)
+
+    monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
+
+    with make_client(tmp_path) as client:
+        resp = client.post(
+            "/api/chat",
+            json={"message": "hello", "conversation_id": "ghost-conv", "model": config.DEFAULT_MODEL},
+            headers=_guest_headers(client),
+        )
+        assert resp.status_code == 200, resp.text
+        conv_resp = client.get("/api/conversations/ghost-conv", headers=_guest_headers(client))
+        assert conv_resp.status_code == 200
+        assert len(conv_resp.json()["messages"]) >= 2
+
+
+def test_search_bogus_conversation_id_creates_row(tmp_path: Path, monkeypatch):
+    async def empty_search(query: str, max_results: int = 5):
+        return []
+
+    monkeypatch.setattr(routers.search_route, "query_searxng", empty_search)
+
+    with make_client(tmp_path) as client:
+        resp = client.post(
+            "/api/search",
+            json={"query": "nothing here", "conversation_id": "ghost-search", "model": config.DEFAULT_MODEL},
+            headers=_guest_headers(client),
+        )
+        assert resp.status_code == 200, resp.text
+        conv_resp = client.get("/api/conversations/ghost-search", headers=_guest_headers(client))
+        assert conv_resp.status_code == 200
+        assert len(conv_resp.json()["messages"]) >= 1
+
+
+# ── auto-search augmentation must reset the streamed text ──────────────
+
+
+def test_auto_search_augmented_event_has_reset_flag(tmp_path: Path, monkeypatch):
+    first_stream = _stream_json_lines([
+        {"message": {"content": "I don't have current data on that."}, "logprobs": [{"logprob": -5.0}]},
+        {"done": True, "eval_count": 2, "eval_duration": 1000000000},
+    ])
+    second_stream = _stream_json_lines([
+        {"message": {"content": "According to the search results, the value is forty-two."}},
+        {"done": True},
+    ])
+    batches = [first_stream, second_stream]
+
+    def stream_stub(self, method, url, json=None, timeout=None):
+        return _MockStreamResponse(batches.pop(0))
+
+    async def search_stub(query: str, max_results: int = 5):
+        return [{"title": "Answer", "url": "https://example.com", "content": "The value is 42."}]
+
+    with make_client(tmp_path) as client:
+        monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
+        monkeypatch.setattr(routers.chat, "query_searxng", search_stub)
+        resp = client.post(
+            "/api/chat",
+            json={"message": "what is the latest value", "model": config.DEFAULT_MODEL},
+            headers=_guest_headers(client),
+        )
+        assert resp.status_code == 200, resp.text
+        payloads = parse_sse_payloads(resp.text)
+
+        augmented = [p for p in payloads if p.get("augmented")]
+        assert augmented, "expected an augmented token event"
+        assert augmented[0].get("reset") is True
+        # The augmented token must carry the fresh answer, not the discarded
+        # first-pass "I don't have current data" text.
+        assert "According to the search results" in augmented[0]["token"]
+        assert "I don't have current data" not in augmented[0]["token"]
+
+
+# ── image uploads are placeholders, never text-ingested ────────────────
+
+
+def test_upload_image_skips_ingest(tmp_path: Path, monkeypatch):
+    fake = _FakeAsyncClient()
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: fake)
+    with make_client(tmp_path) as client:
+        resp = client.post(
+            "/api/upload",
+            headers=_admin_headers(client),
+            data={"mode": "both"},
+            files={"file": ("photo.png", b"\x89PNG\r\n\x1a\nfake", "image/png")},
+        )
+        assert resp.status_code == 200, resp.text
+        data = resp.json()
+        context_id = data["context_id"]
+
+    assert data["chunks_ingested"] == 0
+    assert data["note"]
+    assert fake.put_payloads == []
+    assert data["filename"] == "photo.png"
+
+    row = db.get_db().execute(
+        "SELECT content FROM upload_context WHERE id = ?", (context_id,)
+    ).fetchone()
+    assert row and decrypt_text(row["content"]) == "[Image: photo.png]"
+
+
+# ── conflict detection needs a shared subject, not just an FTS hit ─────
+
+
+def test_conflict_detection_requires_shared_subject(tmp_path: Path):
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-mem-regression.db"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+
+    memory.add_memory("the cat sat on the mat", "general")
+    conflicts = memory.check_fact_conflicts(["the dog is brown"])
+    assert conflicts == []
+
+    memory.add_memory("I prefer Rust over Go", "preference")
+    conflicts = memory.check_fact_conflicts(["I prefer Go over Rust"])
+    assert len(conflicts) == 1
+    assert conflicts[0]["new_fact"] == "I prefer Go over Rust"
+    assert conflicts[0]["old_fact"] == "I prefer Rust over Go"
+    assert "memory_id" in conflicts[0]
+
+
+# ── ingest point IDs are deterministic (no duplicate vectors) ──────────
+
+
+def test_ingest_deterministic_point_ids(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", "sk-regression")
+
+    captured_first = []
+    captured_second = []
+
+    class CaptureClient:
+        FakeResponse = _FakeAsyncClient.FakeResponse
+
+        def __init__(self, *a, **kw):
+            self.capture = None
+
+        async def __aenter__(self):
+            return self
+
+        async def __aexit__(self, *a):
+            pass
+
+        async def post(self, url, **kw):
+            if "/api/embeddings" in url:
+                return self.FakeResponse(200, {"embedding": [0.2] * 768})
+            return self.FakeResponse(200)
+
+        async def put(self, url, **kw):
+            payload = kw.get("json", {})
+            if self.capture is not None:
+                self.capture.append(payload["points"][0]["id"])
+            return self.FakeResponse(200)
+
+    body = {"content": "alpha beta gamma delta epsilon " * 8, "source": "hook"}
+    headers = {"Authorization": "Bearer sk-regression", "Content-Type": "application/json"}
+
+    fake1 = CaptureClient()
+    fake1.capture = captured_first
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: fake1)
+    with make_client(tmp_path) as client:
+        r1 = client.post("/api/ingest", json=body, headers=headers)
+        assert r1.status_code == 200, r1.text
+
+    fake2 = CaptureClient()
+    fake2.capture = captured_second
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: fake2)
+    with make_client(tmp_path) as client:
+        r2 = client.post("/api/ingest", json=body, headers=headers)
+        assert r2.status_code == 200, r2.text
+
+    assert captured_first and captured_second
+    assert len(captured_first) == len(captured_second)
+    assert captured_first == captured_second, "re-ingesting identical content changed point ids"
+    assert len(set(captured_first)) == len(captured_first)
+
+
+# ── get_load() VRAM parsing ────────────────────────────────────────────
+
+
+def test_get_load_vram_parses_rocm_output(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_PSUTIL", False)
+    output = (
+        "======================= ROCm System Management Interface =======================\n"
+        "GPU[0] : gfx1030\n"
+        "VRAM Total Used Memory (B): 3221225472\n"
+        "VRAM Total Memory (B): 17179869184\n"
+    )
+    fake = subprocess.CompletedProcess(["rocm-smi", "--showmeminfo", "vram"], 0, output, "")
+    monkeypatch.setattr(subprocess, "run", lambda *a, **kw: fake)
+    load = agent.get_load()
+    assert load["vram_pct"] == 19  # 3 GiB / 16 GiB
+
+
+def test_get_load_vram_absent_does_not_crash(monkeypatch):
+    # Regression: rocm-smi returned no parseable VRAM lines, so the old code
+    # left total/used unbound and raised.
+    monkeypatch.setattr(agent, "HAS_PSUTIL", False)
+    output = "======================= ROCm System Management Interface =======================\nNo GPU detected\n"
+    fake = subprocess.CompletedProcess(["rocm-smi", "--showmeminfo", "vram"], 0, output, "")
+    monkeypatch.setattr(subprocess, "run", lambda *a, **kw: fake)
+    load = agent.get_load()
+    assert "vram_pct" not in load
+
+
+# ── version pinning ────────────────────────────────────────────────────
+
+
+def test_version_is_bumped():
+    assert re.fullmatch(r"v\d+\.\d+\.\d+", config.VERSION)

tests/test_gpu.py

@@ -0,0 +1,107 @@
+import json
+import subprocess
+import sys
+
+from gpu import get_gpu_stats
+
+
+def test_linux_gpu_stats_via_rocm_smi(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "linux")
+    rocm_json = json.dumps({
+        "card0": {"GPU use (%)": "42%", "GPU Memory Allocated (VRAM%)": "68%"}
+    })
+
+    class MockProc:
+        returncode = 0
+        stdout = rocm_json
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: MockProc())
+
+    monkeypatch.setattr("gpu.subprocess", MockSP())
+    stats = get_gpu_stats()
+    assert stats["gpu_percent"] == 42
+    assert stats["vram_percent"] == 68
+    assert stats["available"] is True
+
+
+def test_linux_gpu_stats_rocm_smi_absent(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "linux")
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: (_ for _ in ()).throw(FileNotFoundError("rocm-smi not found")))
+
+    monkeypatch.setattr("gpu.subprocess", MockSP())
+    stats = get_gpu_stats()
+    assert stats["gpu_percent"] == 0
+    assert stats["vram_percent"] == 0
+    assert stats["available"] is False
+
+
+def test_darwin_gpu_stats_via_system_profiler(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "darwin")
+    sp_output = """Graphics/Displays:
+
+    Apple M2 Pro:
+
+      Chipset Model: Apple M2 Pro
+      Type: GPU
+      Bus: Built-In
+      Total Number of Cores: 19
+      VRAM (Dynamic, Max): 16 GB
+      Displays:
+        Color LCD:
+          Display Type: Built-In Retina LCD
+          Resolution: 3456x2234
+"""
+
+    class MockProc:
+        returncode = 0
+        stdout = sp_output
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: MockProc())
+
+    monkeypatch.setattr("gpu.subprocess", MockSP())
+    stats = get_gpu_stats()
+    assert stats["available"] is True
+    assert stats["gpu_model"] == "Apple M2 Pro"
+    assert stats["vram_total_mb"] == 16384
+    assert stats["gpu_percent"] == 0
+    assert stats["vram_percent"] == 0
+
+
+def test_darwin_gpu_stats_system_profiler_absent(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "darwin")
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: (_ for _ in ()).throw(FileNotFoundError("no system_profiler")))
+
+    monkeypatch.setattr("gpu.subprocess", MockSP())
+    stats = get_gpu_stats()
+    assert stats["available"] is False
+    assert stats["gpu_percent"] == 0
+    assert stats["vram_percent"] == 0
+
+
+def test_darwin_no_gpu_found(monkeypatch):
+    monkeypatch.setattr(sys, "platform", "darwin")
+    sp_output = "Graphics/Displays:\n\n    No displays found.\n"
+
+    class MockProc:
+        returncode = 0
+        stdout = sp_output
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: MockProc())
+
+    monkeypatch.setattr("gpu.subprocess", MockSP())
+    stats = get_gpu_stats()
+    assert stats["available"] is False
+    assert stats["gpu_percent"] == 0
+    assert stats["vram_percent"] == 0

tests/test_hardware.py

@@ -0,0 +1,236 @@
+import asyncio
+import json
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+import httpx
+import psutil
+from fastapi.testclient import TestClient
+
+import app as app_module
+import config
+import db
+import hardware
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+def make_client(tmp_path: Path) -> TestClient:
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-hardware.db"
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def _guest_headers(client: TestClient) -> dict:
+    sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+class _MockGet:
+    def __init__(self, status_code: int = 200, json_data: dict | None = None):
+        self.status_code = status_code
+        self._json_data = json_data or {}
+
+    def json(self):
+        return self._json_data
+
+
+def _mock_subprocess(rocm_stdout: str = "") -> object:
+    class MockProc:
+        returncode = 0
+        stdout = rocm_stdout
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: MockProc())
+
+    return MockSP()
+
+
+def _broken_subprocess(exception: Exception) -> object:
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: (_ for _ in ()).throw(exception))
+
+    return MockSP()
+
+
+def test_assess_hardware_all_services_reachable(tmp_path: Path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+    monkeypatch.setattr(hardware, "subprocess", _mock_subprocess(
+        json.dumps({"card0": {"VRAM Total (MB)": 8192, "VRAM Free (MB)": 4096}})
+    ))
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "v1/models" in url:
+            return _MockGet(200, {"data": [{"id": "mistral-nemo:latest"}]})
+        if "6333" in url:
+            return _MockGet(200, {"result": {"collections": [{"name": "caic"}]}})
+        if "8888" in url:
+            return _MockGet(200, {})
+        return _MockGet(200, {})
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+
+    assert state["ram_total_gb"] == 16.0
+    assert state["ram_available_gb"] == 8.0
+    assert state["cpu_count"] == 8
+    assert state["vram_total_mb"] == 8192
+    assert state["vram_free_mb"] == 4096
+    assert state["llama_reachable"] is True
+    assert state["llama_models"] == ["mistral-nemo:latest"]
+    assert state["qdrant_reachable"] is True
+    assert state["qdrant_collections"] == ["caic"]
+    assert state["searxng_reachable"] is True
+    assert tmp_path.joinpath("hardware_state.json").exists()
+
+
+def test_assess_hardware_rocm_smi_absent(tmp_path: Path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+    monkeypatch.setattr(hardware, "subprocess", _broken_subprocess(FileNotFoundError("no rocm-smi")))
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "v1/models" in url:
+            return _MockGet(200, {"data": []})
+        if "6333" in url:
+            return _MockGet(200, {"result": {"collections": []}})
+        if "8888" in url:
+            return _MockGet(200, {})
+        return _MockGet(200, {})
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+
+    assert state["vram_total_mb"] == 0
+    assert state["vram_free_mb"] == 0
+    assert state["llama_reachable"] is True
+    assert state["qdrant_reachable"] is True
+    assert state["searxng_reachable"] is True
+
+
+def test_assess_hardware_llama_unreachable(tmp_path: Path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+    monkeypatch.setattr(hardware, "subprocess", _mock_subprocess(
+        json.dumps({"card0": {"VRAM Total (MB)": 8192, "VRAM Free (MB)": 4096}})
+    ))
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "v1/models" in url:
+            raise httpx.ConnectError("refused")
+        if "6333" in url:
+            return _MockGet(200, {"result": {"collections": [{"name": "caic"}]}})
+        if "8888" in url:
+            return _MockGet(200, {})
+        return _MockGet(200, {})
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+
+    assert state["llama_reachable"] is False
+    assert state["llama_models"] == []
+    assert state["qdrant_reachable"] is True
+    assert state["searxng_reachable"] is True
+
+
+def test_get_hardware_endpoint(tmp_path: Path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+    monkeypatch.setattr(hardware, "subprocess", _mock_subprocess(
+        json.dumps({"card0": {"VRAM Total (MB)": 8192, "VRAM Free (MB)": 4096}})
+    ))
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "v1/models" in url:
+            return _MockGet(200, {"data": [{"id": "mistral-nemo:latest"}]})
+        if "6333" in url:
+            return _MockGet(200, {"result": {"collections": [{"name": "caic"}]}})
+        if "8888" in url:
+            return _MockGet(200, {})
+        return _MockGet(200, {})
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/hardware", headers=_guest_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["ram_total_gb"] == 16.0
+        assert data["cpu_count"] == 8
+        assert data["vram_total_mb"] == 8192
+        assert data["llama_reachable"] is True
+        assert data["qdrant_reachable"] is True
+        assert data["searxng_reachable"] is True
+        assert "llama_models" in data
+        assert "qdrant_collections" in data
+
+
+def test_assess_hardware_darwin(tmp_path: Path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+    monkeypatch.setattr(sys, "platform", "darwin")
+    monkeypatch.setattr(hardware, "_get_vram_darwin", lambda: (16384, 16384))
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "v1/models" in url:
+            return _MockGet(200, {"data": [{"id": "qwen2.5:latest"}]})
+        if "6333" in url:
+            return _MockGet(200, {"result": {"collections": [{"name": "caic"}]}})
+        if "8888" in url:
+            return _MockGet(200, {})
+        return _MockGet(200, {})
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+
+    assert state["vram_total_mb"] == 16384
+    assert state["vram_free_mb"] == 16384
+    assert state["ram_total_gb"] == 16.0
+    assert state["llama_reachable"] is True
+
+
+def test_get_vram_darwin_parse(monkeypatch):
+    sp_output = """Graphics/Displays:
+
+    Apple M2 Pro:
+
+      Chipset Model: Apple M2 Pro
+      VRAM (Dynamic, Max): 16 GB
+"""
+
+    class MockProc:
+        returncode = 0
+        stdout = sp_output
+
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: MockProc())
+
+    monkeypatch.setattr(hardware, "subprocess", MockSP())
+    total, free = hardware._get_vram_darwin()
+    assert total == 16384
+    assert free == 16384
+
+
+def test_get_vram_darwin_system_profiler_absent(monkeypatch):
+    class MockSP:
+        TimeoutExpired = subprocess.TimeoutExpired
+        run = staticmethod(lambda cmd, **kw: (_ for _ in ()).throw(FileNotFoundError("no system_profiler")))
+
+    monkeypatch.setattr(hardware, "subprocess", MockSP())
+    total, free = hardware._get_vram_darwin()
+    assert total == 0
+    assert free == 0

tests/test_image.py

@@ -0,0 +1,689 @@
+"""Tests for image generation — cluster handlers, router, node agent, hardware probe."""
+import asyncio
+import base64
+import json
+import os
+from contextlib import asynccontextmanager
+from pathlib import Path
+from unittest.mock import AsyncMock, patch
+
+import httpx
+import psutil
+from fastapi.testclient import TestClient
+
+import app as app_module
+import cluster
+import config
+import db
+import hardware
+import node_agent.agent as agent
+from config import AMQP_EXCHANGE_ADMIN, AMQP_EXCHANGE_SYSTEM
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+# ── helpers ──────────────────────────────────────────────────────────────
+
+def _reset():
+    cluster.CLUSTER_NODES.clear()
+    cluster.CLUSTER_EVENTS.clear()
+    cluster.CLUSTER_COORDINATOR = None
+    cluster._pending_pings.clear()
+    cluster._pending_image.clear()
+
+
+_published = []
+
+
+async def _fake_publish(exchange, routing_key, payload):
+    _published.append((exchange, routing_key, payload))
+
+
+def make_client(tmp_path: Path) -> TestClient:
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-image.db"
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hardware_state.json"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def _guest_headers(client: TestClient) -> dict:
+    sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+def _admin_headers(client: TestClient) -> dict:
+    resp = client.post("/api/auth/login", json={"pin": "1234"}, headers={"Origin": "http://testserver"})
+    sid = resp.json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+class FakeMsg:
+    def __init__(self, body_dict: dict):
+        self.body = json.dumps(body_dict).encode()
+
+    @asynccontextmanager
+    async def process(self):
+        yield
+
+
+class FakeExchange:
+    def __init__(self, name=""):
+        self.name = name
+        self.published = []
+
+    async def publish(self, msg, routing_key):
+        self.published.append((msg, routing_key))
+
+
+class FakeChannel:
+    def __init__(self):
+        self.exchanges = {}
+        self.is_closed = False
+
+    async def declare_exchange(self, name, typ, durable=True):
+        self.exchanges[name] = FakeExchange(name)
+        return self.exchanges[name]
+
+    async def declare_queue(self, name="", exclusive=True):
+        return self
+
+    async def bind(self, exchange, routing_key):
+        pass
+
+
+# ── 1. cluster.handle_image_generated resolves pending request ───────────
+
+
+def test_handle_image_generated_resolves_pending(monkeypatch):
+    _reset()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+
+    event = asyncio.Event()
+    cluster._pending_image["req-123"] = ("", event)
+
+    asyncio.run(cluster.handle_image_generated(
+        AMQP_EXCHANGE_SYSTEM, "node.corsair.image_generated",
+        {"node_name": "corsair", "request_id": "req-123", "image_base64": "aW1hZ2U="},
+    ))
+
+    assert event.is_set()
+    result = cluster._pending_image.get("req-123")
+    assert result is not None
+    assert result[0] == "aW1hZ2U="
+    assert cluster.CLUSTER_NODES["corsair"]["last_seen"] is not None
+
+
+# ── 2. cluster.handle_image_failed resolves pending request ─────────────
+
+
+def test_handle_image_failed_resolves_pending(monkeypatch):
+    _reset()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+    }
+
+    event = asyncio.Event()
+    cluster._pending_image["req-456"] = ("", event)
+
+    asyncio.run(cluster.handle_image_failed(
+        AMQP_EXCHANGE_SYSTEM, "node.corsair.image_failed",
+        {"node_name": "corsair", "request_id": "req-456", "error": "timeout"},
+    ))
+
+    assert event.is_set()
+    result = cluster._pending_image.get("req-456")
+    assert result is not None
+    assert result[0] == ""
+
+
+# ── 3. cluster.handle_image_failed unknown node ─────────────────────────
+
+
+def test_handle_image_failed_unknown_node(caplog, monkeypatch):
+    _reset()
+    caplog.set_level("WARNING")
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_image_failed(
+        AMQP_EXCHANGE_SYSTEM, "node.ghost.image_failed",
+        {"node_name": "ghost", "request_id": "x", "error": "boom"},
+    ))
+
+    assert not any("unknown node" in rec.message for rec in caplog.records)
+
+
+# ── 4. cluster.request_image_generate publishes command ──────────────────
+
+
+def test_request_image_generate_publishes_command(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+
+    # Simulate immediate completion
+    async def fake_wait():
+        cluster._pending_image.clear()
+
+    original_wait_for = asyncio.wait_for
+
+    async def patched_wait_for(coro, timeout):
+        cluster._pending_image["fake-id"] = ("aW1hZ2U=", asyncio.Event())
+        cluster._pending_image["fake-id"][1].set()
+        return None
+
+    monkeypatch.setattr(asyncio, "wait_for", patched_wait_for)
+
+    result = asyncio.run(cluster.request_image_generate(
+        "corsair", "a red dragon", width=512, height=512, steps=10,
+    ))
+
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert exchange == AMQP_EXCHANGE_ADMIN
+    assert rk == "node.corsair.cmd.image_generate"
+    assert payload["prompt"] == "a red dragon"
+    assert payload["width"] == 512
+    assert payload["height"] == 512
+    assert payload["steps"] == 10
+    assert "request_id" in payload
+
+
+# ── 5. cluster.request_image_generate unknown node ──────────────────────
+
+
+def test_request_image_generate_unknown_node(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    result = asyncio.run(cluster.request_image_generate("ghost", "prompt"))
+    assert result is None
+    assert len(_published) == 0
+
+
+# ── 6. cluster.request_image_generate node lacks capability ─────────────
+
+
+def test_request_image_generate_no_capability(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+        "capabilities": ["llm"],
+    }
+
+    result = asyncio.run(cluster.request_image_generate("jarvis", "prompt"))
+    assert result is None
+    assert len(_published) == 0
+
+
+# ── 7. cluster.request_image_generate timeout ───────────────────────────
+
+
+def test_request_image_generate_timeout(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+
+    async def timeout_wait(coro, timeout):
+        raise asyncio.TimeoutError()
+
+    monkeypatch.setattr(asyncio, "wait_for", timeout_wait)
+
+    result = asyncio.run(cluster.request_image_generate("corsair", "prompt", timeout=1))
+    assert result is None
+    assert len(cluster._pending_image) == 0
+
+
+# ── 8. _find_image_node selects active image_gen node ───────────────────
+
+
+def test_find_image_node_selects_active():
+    from routers.image import _find_image_node
+
+    _reset()
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+        "capabilities": ["llm"],
+    }
+
+    assert _find_image_node() == "corsair"
+
+
+def test_find_image_node_skips_inactive():
+    from routers.image import _find_image_node
+
+    _reset()
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "error",
+        "capabilities": ["image_gen"],
+    }
+
+    assert _find_image_node() is None
+
+
+def test_find_image_node_no_image_gen():
+    from routers.image import _find_image_node
+
+    _reset()
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+        "capabilities": ["llm"],
+    }
+
+    assert _find_image_node() is None
+
+
+# ── 9. POST /api/image/generate — no node available ─────────────────────
+
+
+def test_image_generate_no_node_503(tmp_path):
+    _reset()
+    with make_client(tmp_path) as client:
+        headers = _admin_headers(client)
+        resp = client.post("/api/image/generate", json={"prompt": "test"}, headers=headers)
+        assert resp.status_code == 503
+        assert "No image generation service" in resp.json()["detail"]
+
+
+# ── 10. POST /api/image/generate — empty prompt ─────────────────────────
+
+
+def test_image_generate_empty_prompt_400(tmp_path):
+    _reset()
+    with make_client(tmp_path) as client:
+        headers = _admin_headers(client)
+        resp = client.post("/api/image/generate", json={"prompt": ""}, headers=headers)
+        assert resp.status_code == 400
+        assert "Prompt is required" in resp.json()["detail"]
+
+
+# ── 11. POST /api/image/generate — happy path ──────────────────────────
+
+
+def test_image_generate_happy_path(tmp_path, monkeypatch):
+    _reset()
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+
+    fake_png = b"\x89PNG\r\n\x1a\n" + b"\x00" * 100
+    fake_b64 = base64.b64encode(fake_png).decode()
+
+    async def fake_request_image_generate(**kwargs):
+        return fake_b64
+
+    monkeypatch.setattr("routers.image.request_image_generate", fake_request_image_generate)
+
+    with make_client(tmp_path) as client:
+        headers = _admin_headers(client)
+        resp = client.post("/api/image/generate", json={
+            "prompt": "a red dragon",
+            "width": 512,
+            "height": 512,
+        }, headers=headers)
+        assert resp.status_code == 200
+        assert resp.headers["content-type"] == "image/png"
+        assert resp.content == fake_png
+
+
+# ── 12. POST /api/image/generate — generation failed ───────────────────
+
+
+def test_image_generate_timeout_504(tmp_path, monkeypatch):
+    _reset()
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+    }
+
+    async def fake_request_image_generate(**kwargs):
+        return None
+
+    monkeypatch.setattr("routers.image.request_image_generate", fake_request_image_generate)
+
+    with make_client(tmp_path) as client:
+        headers = _admin_headers(client)
+        resp = client.post("/api/image/generate", json={"prompt": "test"}, headers=headers)
+        assert resp.status_code == 504
+
+
+# ── 13. GET /api/image/status — available ──────────────────────────────
+
+
+def test_image_status_available(tmp_path):
+    _reset()
+    cluster.CLUSTER_NODES["corsair"] = {
+        "name": "corsair", "type": "worker", "status": "active",
+        "capabilities": ["image_gen"],
+        "load": {"gpu_pct": 30},
+        "last_seen": "2026-07-27T00:00:00Z",
+    }
+
+    with make_client(tmp_path) as client:
+        headers = _guest_headers(client)
+        resp = client.get("/api/image/status", headers=headers)
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["available"] is True
+        assert len(data["nodes"]) == 1
+        assert data["nodes"][0]["name"] == "corsair"
+
+
+# ── 14. GET /api/image/status — no nodes ───────────────────────────────
+
+
+def test_image_status_unavailable(tmp_path):
+    _reset()
+    with make_client(tmp_path) as client:
+        headers = _guest_headers(client)
+        resp = client.get("/api/image/status", headers=headers)
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["available"] is False
+        assert len(data["nodes"]) == 0
+
+
+# ── 15. node_agent.detect_capabilities — ComfyUI present ───────────────
+
+
+def test_detect_capabilities_comfyui_present(monkeypatch):
+    cfg = agent.AgentConfig()
+    cfg.comfyui_port = 8188
+
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+
+    def fake_get(url, timeout=3):
+        if "system_stats" in url:
+            class R:
+                status_code = 200
+            return R()
+        raise httpx.ConnectError("refused")
+
+    monkeypatch.setattr(httpx, "get", fake_get)
+
+    caps = agent.detect_capabilities(cfg)
+    assert "image_gen" in caps
+    assert "llm" in caps
+
+
+# ── 16. node_agent.detect_capabilities — ComfyUI absent ────────────────
+
+
+def test_detect_capabilities_comfyui_absent(monkeypatch):
+    cfg = agent.AgentConfig()
+    cfg.comfyui_port = 8188
+
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+    monkeypatch.setattr(httpx, "get", lambda url, timeout=3: (_ for _ in ()).throw(httpx.ConnectError("refused")))
+
+    caps = agent.detect_capabilities(cfg)
+    assert "image_gen" not in caps
+    assert "llm" in caps
+
+
+# ── 17. node_agent.detect_capabilities — httpx not installed ────────────
+
+
+def test_detect_capabilities_no_httpx(monkeypatch):
+    cfg = agent.AgentConfig()
+    monkeypatch.setattr(agent, "HAS_HTTPX", False)
+
+    caps = agent.detect_capabilities(cfg)
+    assert "image_gen" not in caps
+
+
+# ── 18. node_agent.handle_image_generate — success ─────────────────────
+
+
+def test_node_agent_handle_image_generate_success(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+
+    cfg = agent.AgentConfig()
+    cfg.node_name = "corsair"
+    cfg.comfyui_port = 8188
+
+    fake_png = b"\x89PNG" + b"\x00" * 50
+    fake_b64 = base64.b64encode(fake_png).decode()
+
+    async def fake_comfyui_generate(*a, **kw):
+        return fake_b64
+
+    monkeypatch.setattr(agent, "_comfyui_generate", fake_comfyui_generate)
+
+    channel = FakeChannel()
+    system_ex = FakeExchange("jc.system")
+    channel.exchanges["jc.system"] = system_ex
+
+    asyncio.run(agent.handle_image_generate(
+        cfg, channel, (FakeExchange(), system_ex),
+        FakeMsg({
+            "request_id": "req-789",
+            "prompt": "a castle",
+            "negative_prompt": "",
+            "width": 1024,
+            "height": 1024,
+            "steps": 20,
+            "seed": 42,
+            "model": "",
+        }),
+    ))
+
+    assert len(system_ex.published) == 1
+    msg, rk = system_ex.published[0]
+    assert rk == "node.corsair.image_generated"
+    payload = json.loads(msg.body)
+    assert payload["type"] == "image_generated"
+    assert payload["request_id"] == "req-789"
+    assert payload["image_base64"] == fake_b64
+
+
+# ── 19. node_agent.handle_image_generate — failure ─────────────────────
+
+
+def test_node_agent_handle_image_generate_failure(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+
+    cfg = agent.AgentConfig()
+    cfg.node_name = "corsair"
+
+    async def fake_comfyui_generate(*a, **kw):
+        raise RuntimeError("ComfyUI crashed")
+
+    monkeypatch.setattr(agent, "_comfyui_generate", fake_comfyui_generate)
+
+    channel = FakeChannel()
+    system_ex = FakeExchange("jc.system")
+    channel.exchanges["jc.system"] = system_ex
+
+    asyncio.run(agent.handle_image_generate(
+        cfg, channel, (FakeExchange(), system_ex),
+        FakeMsg({"request_id": "req-fail", "prompt": "test"}),
+    ))
+
+    assert len(system_ex.published) == 1
+    msg, rk = system_ex.published[0]
+    assert rk == "node.corsair.image_failed"
+    payload = json.loads(msg.body)
+    assert payload["type"] == "image_failed"
+    assert "ComfyUI crashed" in payload["error"]
+
+
+# ── 20. node_agent.handle_image_generate — empty prompt ────────────────
+
+
+def test_node_agent_handle_image_generate_empty_prompt(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+
+    cfg = agent.AgentConfig()
+    cfg.node_name = "corsair"
+
+    channel = FakeChannel()
+    system_ex = FakeExchange("jc.system")
+
+    asyncio.run(agent.handle_image_generate(
+        cfg, channel, (FakeExchange(), system_ex),
+        FakeMsg({"request_id": "req-x", "prompt": ""}),
+    ))
+
+    assert len(system_ex.published) == 0
+
+
+# ── 21. hardware.py — ComfyUI reachable ────────────────────────────────
+
+
+def test_assess_hardware_comfyui_reachable(tmp_path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hw.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+
+    class MockProc:
+        returncode = 1
+        stdout = ""
+
+    monkeypatch.setattr(hardware.subprocess, "run", lambda cmd, **kw: MockProc())
+
+    async def mock_get(self, url, *args, **kwargs):
+        class R:
+            status_code = 200
+            def json(self):
+                if "CheckpointLoaderSimple" in url:
+                    return {"CheckpointLoaderSimple": {"input": {"required": {"ckpt_name": [["model.safetensors", "other.ckpt"]]}}}}
+                return {}
+            def raise_for_status(self):
+                pass
+        if "8188" in url:
+            return R()
+        if "v1/models" in url:
+            class R2:
+                status_code = 200
+                def json(self):
+                    return {"data": []}
+            return R2()
+        if "6333" in url:
+            class R3:
+                status_code = 200
+                def json(self):
+                    return {"result": {"collections": []}}
+            return R3()
+        if "8888" in url:
+            class R4:
+                status_code = 200
+            return R4()
+        class R5:
+            status_code = 200
+            def json(self):
+                return {}
+        return R5()
+
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+    assert state["comfyui_reachable"] is True
+    assert "model.safetensors" in state["comfyui_models"]
+
+
+# ── 22. hardware.py — ComfyUI unreachable ──────────────────────────────
+
+
+def test_assess_hardware_comfyui_unreachable(tmp_path, monkeypatch):
+    hardware.HARDWARE_STATE_PATH = tmp_path / "hw.json"
+    monkeypatch.setattr(psutil, "virtual_memory", lambda: type("M", (), {"total": 16 * 1024 ** 3, "available": 8 * 1024 ** 3})())
+    monkeypatch.setattr(psutil, "cpu_count", lambda: 8)
+
+    class MockProc:
+        returncode = 1
+        stdout = ""
+
+    monkeypatch.setattr(hardware.subprocess, "run", lambda cmd, **kw: MockProc())
+
+    async def mock_get(self, url, *args, **kwargs):
+        if "8188" in url:
+            raise httpx.ConnectError("refused")
+        if "v1/models" in url:
+            class R2:
+                status_code = 200
+                def json(self):
+                    return {"data": []}
+            return R2()
+        if "6333" in url:
+            class R3:
+                status_code = 200
+                def json(self):
+                    return {"result": {"collections": []}}
+            return R3()
+        if "8888" in url:
+            class R4:
+                status_code = 200
+            return R4()
+        class R5:
+            status_code = 200
+            def json(self):
+                return {}
+        return R5()
+
+    monkeypatch.setattr(httpx.AsyncClient, "get", mock_get)
+
+    state = asyncio.run(hardware.assess_hardware())
+    assert state["comfyui_reachable"] is False
+    assert state["comfyui_models"] == []
+
+
+# ── 23. node_agent config reads comfyui_port ───────────────────────────
+
+
+def test_config_from_ini_comfyui_port(tmp_path):
+    ini = tmp_path / "caic-node-agent.conf"
+    ini.write_text(
+        "[agent]\n"
+        "node_name = corsair\n"
+        "capabilities = llm,image_gen\n"
+        "comfyui_port = 8188\n"
+    )
+    cfg = agent.AgentConfig.from_ini(str(ini))
+    assert cfg.comfyui_port == 8188
+    assert "image_gen" in cfg.capabilities
+
+
+def test_config_from_ini_comfyui_port_default():
+    cfg = agent.AgentConfig()
+    assert cfg.comfyui_port == 8188
+
+
+# ── 24. SUBSCRIBE_TABLE includes image gen handlers ────────────────────
+
+
+def test_subscribe_table_includes_image_handlers():
+    routing_keys = [rks for _, rks, _ in cluster.SUBSCRIBE_TABLE]
+    all_keys = [rk for rks in routing_keys for rk in rks]
+    assert "node.*.image_generated" in all_keys
+    assert "node.*.image_failed" in all_keys

tests/test_ingest.py

@@ -0,0 +1,104 @@
+import json
+import os
+from pathlib import Path
+
+import httpx
+from fastapi.testclient import TestClient
+
+import app
+import db
+import routers.ingest as ingest_route
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+def make_client(tmp_path: Path) -> TestClient:
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-ingest.db"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+    return TestClient(app.app, raise_server_exceptions=False)
+
+
+TEST_API_KEY = "test-sk-caic-ingest"
+
+
+def _auth_headers() -> dict:
+    return {"Authorization": f"Bearer {TEST_API_KEY}", "Content-Type": "application/json", "Origin": "http://testserver"}
+
+
+def test_ingest_missing_api_key(tmp_path: Path):
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/ingest", json={"content": "test"}, headers={"Origin": "http://testserver"})
+        assert resp.status_code == 401
+
+
+def test_ingest_wrong_api_key(tmp_path: Path):
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/ingest", json={"content": "test"},
+                           headers={"Authorization": "Bearer wrong", "Origin": "http://testserver"})
+        assert resp.status_code == 401
+
+
+def test_ingest_empty_content(tmp_path: Path):
+    monkeypatch = __import__('pytest').MonkeyPatch()
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", TEST_API_KEY)
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/ingest", json={"content": ""}, headers=_auth_headers())
+        assert resp.status_code == 422
+    monkeypatch.undo()
+
+
+def test_ingest_missing_content(tmp_path: Path):
+    monkeypatch = __import__('pytest').MonkeyPatch()
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", TEST_API_KEY)
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/ingest", json={}, headers=_auth_headers())
+        assert resp.status_code == 422
+    monkeypatch.undo()
+
+
+def test_ingest_success(tmp_path: Path, monkeypatch):
+    monkeypatch.setattr(ingest_route, "COMPLETIONS_API_KEY", TEST_API_KEY)
+
+    embed_count = 0
+
+    class FakeAsyncClient:
+        class FakeResponse:
+            def __init__(self, status, json_data=None):
+                self.status_code = status
+                self._json = json_data or {}
+
+            def json(self):
+                return self._json
+
+        def __init__(self, *a, **kw):
+            pass
+
+        async def __aenter__(self):
+            return self
+
+        async def __aexit__(self, *a):
+            pass
+
+        async def post(self, url, **kw):
+            nonlocal embed_count
+            if "/api/embeddings" in url:
+                embed_count += 1
+                return self.FakeResponse(200, {"embedding": [0.1] * 768})
+            return self.FakeResponse(200)
+
+        async def put(self, url, **kw):
+            return self.FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/ingest", json={"content": "test " * 1000, "source": "terminal"}, headers=_auth_headers())
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["source"] == "terminal"
+        assert data["chunks_ingested"] > 0
+        assert embed_count == data["chunks_ingested"]
+        assert "message" in data

tests/test_ip_allowlist.py

@@ -9,8 +9,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS, is_ip_allowed
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-ip.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-ip.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_memories.py

@@ -10,8 +10,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-memories.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-memories.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_model_pull.py

@@ -0,0 +1,142 @@
+import asyncio
+
+import httpx
+
+from model_pull import ensure_model, _model_available_on_llama, _model_available_on_ollama, _pull_via_ollama
+
+
+class _MockAsyncResponse:
+    def __init__(self, status_code=200, json_data=None):
+        self.status_code = status_code
+        self._json_data = json_data or {}
+
+    def json(self):
+        return self._json_data
+
+
+class _MockStreamResponse:
+    def __init__(self, status_code=200, lines=None):
+        self.status_code = status_code
+        self._lines = lines or []
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *args):
+        pass
+
+    def aiter_lines(self):
+        class _AIter:
+            def __init__(self, lines):
+                self._lines = iter(lines)
+            def __aiter__(self):
+                return self
+            async def __anext__(self):
+                try:
+                    return next(self._lines)
+                except StopIteration:
+                    raise StopAsyncIteration
+        return _AIter(self._lines)
+
+
+def _mock_models_on_llama(*models):
+    async def _get(*args, **kwargs):
+        return _MockAsyncResponse(json_data={
+            "data": [{"id": m} for m in models]
+        })
+    return _get
+
+
+async def _mock_ollama_available(*args, **kwargs):
+    return _MockAsyncResponse(status_code=200, json_data={"name": "qwen2.5:latest"})
+
+
+async def _mock_ollama_unavailable(*args, **kwargs):
+    raise httpx.ConnectError("refused")
+
+
+def _mock_ollama_pull_ok(*args, **kwargs):
+    return _MockStreamResponse(200, [
+        '{"status": "pulling manifest"}',
+        '{"status": "success"}',
+    ])
+
+
+def _mock_ollama_pull_fail(*args, **kwargs):
+    return _MockStreamResponse(500, [])
+
+
+def _mock_ollama_connect_error(*args, **kwargs):
+    raise httpx.ConnectError("refused")
+
+
+def test_available_on_llama(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "get", _mock_models_on_llama("qwen2.5-7b-instruct"))
+    assert asyncio.run(_model_available_on_llama("qwen2.5-7b-instruct")) is True
+    assert asyncio.run(_model_available_on_llama("nonexistent-model")) is False
+
+
+def test_available_on_llama_unreachable(monkeypatch):
+    async def _connect_error(*args, **kwargs):
+        raise httpx.ConnectError("refused")
+    monkeypatch.setattr(httpx.AsyncClient, "get", _connect_error)
+    assert asyncio.run(_model_available_on_llama("qwen2.5-7b-instruct")) is False
+
+
+def test_available_on_ollama(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "post", _mock_ollama_available)
+    assert asyncio.run(_model_available_on_ollama("qwen2.5:latest")) is True
+
+
+def test_available_on_ollama_unreachable(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "post", _mock_ollama_unavailable)
+    assert asyncio.run(_model_available_on_ollama("qwen2.5:latest")) is False
+
+
+def test_pull_via_ollama_success(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "stream", _mock_ollama_pull_ok)
+    assert asyncio.run(_pull_via_ollama("qwen2.5:latest")) is True
+
+
+def test_pull_via_ollama_fail(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "stream", _mock_ollama_pull_fail)
+    assert asyncio.run(_pull_via_ollama("qwen2.5:latest")) is False
+
+
+def test_pull_via_ollama_connect_error(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "stream", _mock_ollama_connect_error)
+    assert asyncio.run(_pull_via_ollama("qwen2.5:latest")) is False
+
+
+def test_ensure_model_already_on_llama(monkeypatch):
+    monkeypatch.setattr(httpx.AsyncClient, "get", _mock_models_on_llama("qwen2.5-7b-instruct"))
+    assert asyncio.run(ensure_model("qwen2.5-7b-instruct")) is True
+
+
+def test_ensure_model_not_on_llama_but_on_ollama(monkeypatch):
+    async def _get(*args, **kwargs):
+        return _MockAsyncResponse(json_data={"data": []})
+
+    monkeypatch.setattr(httpx.AsyncClient, "get", _get)
+    monkeypatch.setattr(httpx.AsyncClient, "post", _mock_ollama_available)
+    assert asyncio.run(ensure_model("qwen2.5-7b-instruct")) is True
+
+
+def test_ensure_model_needs_pull(monkeypatch):
+    async def _get(*args, **kwargs):
+        return _MockAsyncResponse(json_data={"data": []})
+
+    monkeypatch.setattr(httpx.AsyncClient, "get", _get)
+    monkeypatch.setattr(httpx.AsyncClient, "post", _mock_ollama_unavailable)
+    monkeypatch.setattr(httpx.AsyncClient, "stream", _mock_ollama_pull_ok)
+    assert asyncio.run(ensure_model("qwen2.5-7b-instruct")) is True
+
+
+def test_ensure_model_pull_fails(monkeypatch):
+    async def _get(*args, **kwargs):
+        return _MockAsyncResponse(json_data={"data": []})
+
+    monkeypatch.setattr(httpx.AsyncClient, "get", _get)
+    monkeypatch.setattr(httpx.AsyncClient, "post", _mock_ollama_unavailable)
+    monkeypatch.setattr(httpx.AsyncClient, "stream", _mock_ollama_pull_fail)
+    assert asyncio.run(ensure_model("qwen2.5-7b-instruct")) is False

tests/test_model_swap.py

@@ -0,0 +1,150 @@
+"""Tests for cluster.py model swap flow."""
+import asyncio
+
+import cluster
+from config import AMQP_EXCHANGE_ADMIN, AMQP_EXCHANGE_SYSTEM
+
+
+def _reset():
+    cluster.CLUSTER_NODES.clear()
+    cluster.CLUSTER_EVENTS.clear()
+    cluster.CLUSTER_COORDINATOR = None
+    cluster._pending_pings.clear()
+
+
+_published = []
+
+
+async def _fake_publish(exchange, routing_key, payload):
+    _published.append((exchange, routing_key, payload))
+
+
+# ---------- 1. request_model_swap() publishes swap command ----------
+
+
+def test_request_model_swap_publishes_command(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "active",
+    }
+
+    asyncio.run(cluster.request_model_swap("jarvis", "qwen2.5-coder-Q4_K_M.gguf"))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "swapping"
+    assert len(_published) == 1
+    exchange, rk, payload = _published[0]
+    assert exchange == AMQP_EXCHANGE_ADMIN
+    assert rk == "node.jarvis.cmd.swap_model"
+    assert payload["model_filename"] == "qwen2.5-coder-Q4_K_M.gguf"
+    assert "requested_at" in payload
+
+
+def test_request_model_swap_unknown_node(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    result = asyncio.run(cluster.request_model_swap("ghost", "any.gguf"))
+    assert result is False
+    assert len(_published) == 0
+
+
+# ---------- 2. handle_model_ready() updates node ----------
+
+
+def test_handle_model_ready_updates_active_model(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "swapping",
+        "active_model": {"name": "llama3.1", "port": 8081},
+        "inventory": [
+            {"filename": "qwen2.5-coder-Q4_K_M.gguf", "name": "qwen2.5-coder", "version": "14b", "quant": "Q4_K_M"},
+        ],
+    }
+
+    asyncio.run(cluster.handle_model_ready(
+        AMQP_EXCHANGE_SYSTEM, "node.jarvis.model_ready",
+        {"node_name": "jarvis", "active_model": "qwen2.5-coder-Q4_K_M.gguf", "port": 8082},
+    ))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "active"
+    am = cluster.CLUSTER_NODES["jarvis"]["active_model"]
+    assert am["name"] == "qwen2.5-coder"
+    assert am["port"] == 8082
+    assert am["filename"] == "qwen2.5-coder-Q4_K_M.gguf"
+
+
+def test_handle_model_ready_inventory_lookup_fallback(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "swapping",
+        "active_model": {"name": "llama3.1", "port": 8081},
+        "inventory": [],
+    }
+
+    asyncio.run(cluster.handle_model_ready(
+        AMQP_EXCHANGE_SYSTEM, "node.jarvis.model_ready",
+        {"node_name": "jarvis", "active_model": "unknown.gguf", "port": 9999},
+    ))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "active"
+    am = cluster.CLUSTER_NODES["jarvis"]["active_model"]
+    assert am["filename"] == "unknown.gguf"
+    assert am["port"] == 9999
+
+
+def test_handle_model_ready_unknown_node(caplog, monkeypatch):
+    _reset()
+    caplog.set_level("WARNING")
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_model_ready(
+        AMQP_EXCHANGE_SYSTEM, "node.ghost.model_ready",
+        {"node_name": "ghost", "active_model": "any.gguf"},
+    ))
+
+    assert any("unknown node" in rec.message for rec in caplog.records)
+
+
+# ---------- 3. handle_model_failed() sets error status ----------
+
+
+def test_handle_model_failed_sets_error(monkeypatch):
+    _reset()
+    _published.clear()
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    cluster.CLUSTER_NODES["jarvis"] = {
+        "name": "jarvis", "type": "worker", "status": "swapping",
+    }
+
+    asyncio.run(cluster.handle_model_failed(
+        AMQP_EXCHANGE_SYSTEM, "node.jarvis.model_failed",
+        {"node_name": "jarvis", "error": "llama-server unhealthy after 120s"},
+    ))
+
+    assert cluster.CLUSTER_NODES["jarvis"]["status"] == "error"
+    assert len(cluster.CLUSTER_EVENTS) == 1
+    assert "swap failed" in cluster.CLUSTER_EVENTS[0]["message"].lower()
+
+
+def test_handle_model_failed_unknown_node(caplog, monkeypatch):
+    _reset()
+    caplog.set_level("WARNING")
+    monkeypatch.setattr(cluster, "publish", _fake_publish)
+
+    asyncio.run(cluster.handle_model_failed(
+        AMQP_EXCHANGE_SYSTEM, "node.ghost.model_failed",
+        {"node_name": "ghost", "error": "OOM"},
+    ))
+
+    assert any("unknown node" in rec.message for rec in caplog.records)

tests/test_models_router.py

@@ -11,8 +11,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-models.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-models.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_node_agent.py

@@ -0,0 +1,340 @@
+"""Tests for node_agent/agent.py — standalone worker agent."""
+import asyncio
+import json
+import os
+import subprocess
+from contextlib import asynccontextmanager
+from pathlib import Path
+
+import node_agent.agent as agent
+from node_agent.agent import (
+    AgentConfig,
+    ModelInfo,
+    build_registration_payload,
+    discover_models,
+    get_load,
+    handle_ping,
+    handle_swap_model,
+)
+
+
+class FakeMsg:
+    def __init__(self, body_dict: dict):
+        self.body = json.dumps(body_dict).encode()
+
+    @asynccontextmanager
+    async def process(self):
+        yield
+
+
+class FakeExchange:
+    def __init__(self, name=""):
+        self.name = name
+        self.published = []
+
+    async def publish(self, msg, routing_key):
+        self.published.append((msg, routing_key))
+
+
+class FakeChannel:
+    def __init__(self):
+        self.exchanges = {}
+        self.is_closed = False
+
+    async def get_exchange(self, name):
+        if name not in self.exchanges:
+            self.exchanges[name] = FakeExchange(name)
+        return self.exchanges[name]
+
+    async def declare_exchange(self, name, typ, durable=True):
+        self.exchanges[name] = FakeExchange(name)
+        return self.exchanges[name]
+
+    async def declare_queue(self, name="", exclusive=True):
+        return self
+
+    async def bind(self, exchange, routing_key):
+        pass
+
+    async def close(self):
+        self.is_closed = True
+
+
+# ── 1. Registration payload shape ────────────────────────────────────
+
+
+def test_registration_payload_shape():
+    cfg = AgentConfig()
+    cfg.node_name = "worker01"
+    cfg.node_ip = "192.168.50.210"
+    cfg.capabilities = ["llm"]
+    cfg.active_model = "llama3.1-latest-Q4_K_M.gguf"
+    cfg.llama_port = 8081
+
+    inventory = [{"filename": "llama3.1-latest-Q4_K_M.gguf", "name": "llama3.1", "quant": "Q4_K_M"}]
+    payload = build_registration_payload(cfg, inventory)
+
+    assert payload["node_name"] == "worker01"
+    assert payload["node_type"] == "worker"
+    assert payload["ip"] == "192.168.50.210"
+    assert payload["capabilities"] == ["llm"]
+    assert "active_model" in payload
+    assert payload["active_model"]["filename"] == "llama3.1-latest-Q4_K_M.gguf"
+    assert payload["active_model"]["port"] == 8081
+    assert len(payload["inventory"]) == 1
+
+
+def test_registration_payload_active_model_none():
+    cfg = AgentConfig()
+    cfg.active_model = ""
+    payload = build_registration_payload(cfg, [])
+    assert payload["active_model"] is None
+
+
+# ── 2. Model discovery ───────────────────────────────────────────────
+
+
+def test_discover_models(tmp_path):
+    models_dir = tmp_path / "models"
+    models_dir.mkdir()
+    # Create valid model files
+    (models_dir / "llama3.1-latest-Q4_K_M.gguf").write_text("")
+    (models_dir / "mistral-nemo-7b-Q6_K_L.gguf").write_text("")
+    # Create file that doesn't match pattern
+    (models_dir / "readme.txt").write_text("")
+    # Create file with unrecognized naming
+    (models_dir / "my_custom_model.gguf").write_text("")
+
+    result = discover_models(str(models_dir))
+    assert len(result) == 2
+    names = {m["name"] for m in result}
+    assert "llama3.1" in names
+    assert "mistral-nemo" in names
+
+
+def test_discover_models_no_directory(tmp_path):
+    result = discover_models(str(tmp_path / "nonexistent"))
+    assert result == []
+
+
+# ── 3. Config reading ────────────────────────────────────────────────
+
+
+def test_config_from_ini(tmp_path):
+    ini = tmp_path / "caic-node-agent.conf"
+    ini.write_text(
+        "[agent]\n"
+        "node_name = testnode\n"
+        "node_ip = 10.0.0.5\n"
+        "capabilities = llm,rag\n"
+        "amqp_url = amqp://user:pass@host/vhost\n"
+        "llama_port = 9090\n"
+        "models_dir = /tmp/models\n"
+        "active_model = test.gguf\n"
+    )
+    cfg = AgentConfig.from_ini(str(ini))
+    assert cfg.node_name == "testnode"
+    assert cfg.node_ip == "10.0.0.5"
+    assert cfg.capabilities == ["llm", "rag"]
+    assert cfg.amqp_url == "amqp://user:pass@host/vhost"
+    assert cfg.llama_port == 9090
+    assert cfg.models_dir == "/tmp/models"
+    assert cfg.active_model == "test.gguf"
+
+
+def test_config_from_ini_missing_uses_defaults(tmp_path):
+    cfg = AgentConfig.from_ini(str(tmp_path / "nonexistent.conf"))
+    assert cfg.node_name != ""  # socket.gethostname() returns something
+    assert cfg.node_type == "worker"
+    assert cfg.capabilities == ["llm"]
+
+
+# ── 4. Ping handler publishes pong ──────────────────────────────────
+
+
+def test_ping_handler_publishes_pong(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_PSUTIL", False)
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+
+    cfg = AgentConfig()
+    cfg.node_name = "testworker"
+
+    channel = FakeChannel()
+    admin_ex = FakeExchange("jc.admin")
+    channel.exchanges["jc.admin"] = admin_ex
+    exchange = admin_ex
+
+    async def run():
+        await handle_ping(cfg, channel, exchange, FakeMsg({
+            "from": "coordinator",
+            "node_name": "testworker",
+            "type": "ping",
+            "correlation_id": "abc-123",
+            "timestamp": "2026-01-01T00:00:00Z",
+        }))
+
+    asyncio.run(run())
+
+    assert len(exchange.published) == 1
+    msg, rk = exchange.published[0]
+    assert rk == "node.testworker.pong"
+    payload = json.loads(msg.body)
+    assert payload["type"] == "pong"
+    assert payload["correlation_id"] == "abc-123"
+    assert payload["node_name"] == "testworker"
+
+
+# ── 5. Model swap success path ──────────────────────────────────────
+
+
+def test_model_swap_success(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+
+    cfg = AgentConfig()
+    cfg.node_name = "testworker"
+    cfg.llama_port = 9999
+
+    captured_cmds = []
+
+    def fake_run(cmd, **kwargs):
+        captured_cmds.append(cmd)
+        return subprocess.CompletedProcess(cmd, 0, b"", b"")
+
+    monkeypatch.setattr(subprocess, "run", fake_run)
+
+    # Mock _wait_for_llama to succeed
+    async def fake_wait(*a, **kw):
+        return True
+    monkeypatch.setattr(agent, "_wait_for_llama", fake_wait)
+
+    # Mock _update_config_active_model to no-op
+    monkeypatch.setattr(agent, "_update_config_active_model", lambda c, m: None)
+
+    channel = FakeChannel()
+    admin_ex = FakeExchange("jc.admin")
+    system_ex = FakeExchange("jc.system")
+    channel.exchanges["jc.admin"] = admin_ex
+    channel.exchanges["jc.system"] = system_ex
+
+    asyncio.run(handle_swap_model(cfg, channel, (admin_ex, system_ex), FakeMsg({"model_filename": "new-model-Q4_K_M.gguf"})))
+
+    # Check systemctl calls
+    assert len(captured_cmds) == 2
+    assert captured_cmds[0] == ["systemctl", "stop", "llama-server"]
+    assert captured_cmds[1] == ["systemctl", "start", "llama-server"]
+
+    # Check model_ready published on jc.system
+    assert len(system_ex.published) == 1
+    msg, rk = system_ex.published[0]
+    assert rk == "node.testworker.model_ready"
+    payload = json.loads(msg.body)
+    assert payload["type"] == "model_ready"
+    assert payload["active_model"] == "new-model-Q4_K_M.gguf"
+
+
+# ── 6. Model swap timeout path ──────────────────────────────────────
+
+
+def test_model_swap_timeout(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_AIO_PIKA", True)
+    monkeypatch.setattr(agent, "HAS_HTTPX", True)
+
+    cfg = AgentConfig()
+    cfg.node_name = "testworker"
+
+    monkeypatch.setattr(subprocess, "run", lambda cmd, **kw: subprocess.CompletedProcess(cmd, 0, b"", b""))
+
+    # Mock _wait_for_llama to fail
+    async def fake_wait_fail(*a, **kw):
+        return False
+    monkeypatch.setattr(agent, "_wait_for_llama", fake_wait_fail)
+    monkeypatch.setattr(agent, "_update_config_active_model", lambda c, m: None)
+
+    channel = FakeChannel()
+    admin_ex = FakeExchange("jc.admin")
+    system_ex = FakeExchange("jc.system")
+    channel.exchanges["jc.admin"] = admin_ex
+    channel.exchanges["jc.system"] = system_ex
+
+    asyncio.run(handle_swap_model(cfg, channel, (admin_ex, system_ex), FakeMsg({"model_filename": "broken-model-Q4_K_M.gguf"})))
+
+    assert len(system_ex.published) == 1
+    msg, rk = system_ex.published[0]
+    assert rk == "node.testworker.model_failed"
+    payload = json.loads(msg.body)
+    assert payload["type"] == "model_failed"
+    assert "error" in payload
+
+
+# ── 7. Load reporting ───────────────────────────────────────────────
+
+
+def test_get_load_with_psutil(monkeypatch):
+    class FakePsutil:
+        @staticmethod
+        def cpu_percent(interval=0.5):
+            return 42.0
+
+        @staticmethod
+        def virtual_memory():
+            class VM:
+                percent = 65.0
+            return VM()
+
+    monkeypatch.setattr(agent, "HAS_PSUTIL", True)
+    monkeypatch.setattr(agent, "psutil", FakePsutil)
+
+    # Mock subprocess to fail (no rocm-smi)
+    def fake_run(*a, **kw):
+        raise FileNotFoundError("rocm-smi not found")
+    monkeypatch.setattr(subprocess, "run", fake_run)
+
+    load = get_load()
+    assert load["cpu_pct"] == 42
+    assert load["ram_pct"] == 65
+    assert "vram_pct" not in load
+
+
+def test_get_load_without_psutil(monkeypatch):
+    monkeypatch.setattr(agent, "HAS_PSUTIL", False)
+    monkeypatch.setattr(subprocess, "run", lambda *a, **kw: (_ for _ in ()).throw(FileNotFoundError("")))
+    load = get_load()
+    assert "cpu_pct" not in load
+
+
+# ── 8. Agent idle after admission (no heartbeat) ────────────────────
+
+
+def test_no_heartbeat_timer():
+    """Agent has no background heartbeat mechanism. This test asserts that
+    the codebase contains no heartbeat-related logic in the agent itself."""
+    import inspect
+    source = inspect.getsource(agent)
+    # There should be no heartbeat timer in the agent
+    assert "heartbeat" not in source.lower(), \
+        "agent.py should contain no heartbeat logic"
+
+
+# ── 9. Config writer for model swap ─────────────────────────────────
+
+
+def test_update_config_active_model(tmp_path, monkeypatch):
+    monkeypatch.setattr(agent, "CONFIG_PATH", str(tmp_path / "caic-node-agent.conf"))
+    cfg = AgentConfig()
+    cfg.active_model = "old.gguf"
+    agent._update_config_active_model(cfg, "new.gguf")
+    assert cfg.active_model == "new.gguf"
+    content = (tmp_path / "caic-node-agent.conf").read_text()
+    assert "new.gguf" in content
+
+
+# ── 10. ModelInfo to_dict ────────────────────────────────────────────
+
+
+def test_model_info_to_dict():
+    info = ModelInfo(filename="test-Q4_K_M.gguf", name="test", version="latest", quant="Q4_K_M")
+    d = info.to_dict()
+    assert d["name"] == "test"
+    assert d["quant"] == "Q4_K_M"
+    assert d["filename"] == "test-Q4_K_M.gguf"

tests/test_presets.py

@@ -9,8 +9,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-presets.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-presets.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_profile.py

@@ -10,8 +10,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-profile.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-profile.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_rag_management.py

@@ -0,0 +1,676 @@
+import asyncio
+import os
+from datetime import datetime, timezone, timedelta
+from pathlib import Path
+
+import httpx
+from fastapi.testclient import TestClient
+
+import app
+import config
+import crypto
+import db
+import rag
+from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
+
+
+def make_client(tmp_path: Path) -> TestClient:
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-rag-mgmt.db"
+    SESSIONS.clear()
+    PIN_ATTEMPTS.clear()
+    RATE_EVENTS.clear()
+    db.init_db()
+    return TestClient(app.app, raise_server_exceptions=False)
+
+
+def _admin_headers(client: TestClient) -> dict:
+    login = client.post("/api/auth/login", json={"pin": "1234"}, headers={"Origin": "http://testserver"})
+    sid = login.json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+def _guest_headers(client: TestClient) -> dict:
+    sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
+    return {"X-Session-ID": sid, "Origin": "http://testserver"}
+
+
+class FakeResponse:
+    def __init__(self, status, json_data=None):
+        self.status_code = status
+        self._json = json_data or {}
+
+    def json(self):
+        return self._json
+
+
+class FakeAsyncClient:
+    def __init__(self, *a, **kw):
+        pass
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *a):
+        pass
+
+    async def get(self, url, **kw):
+        if "/collections/caic_rag" in url:
+            return FakeResponse(200, {"result": {"vectors_count": 123}})
+        return FakeResponse(200)
+
+    async def post(self, url, **kw):
+        if "/points/scroll" in url:
+            return FakeResponse(200, {"result": {"points": []}})
+        if "/points/delete" in url:
+            return FakeResponse(200)
+        return FakeResponse(200)
+
+    async def put(self, url, **kw):
+        return FakeResponse(200)
+
+
+def _old_ts(hours_ago: float = 24) -> str:
+    return (datetime.now(timezone.utc) - timedelta(hours=hours_ago)).isoformat()
+
+
+def _young_ts(hours_ago: float = 0.1) -> str:
+    return (datetime.now(timezone.utc) - timedelta(hours=hours_ago)).isoformat()
+
+
+# ---------- get_collection_count ----------
+
+def test_get_collection_count(monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    count = asyncio.run(rag.get_collection_count())
+    assert count == 123
+
+
+# ---------- get_collection_stats ----------
+
+def test_get_collection_stats_shape(monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    stats = asyncio.run(rag.get_collection_stats())
+    assert stats["vector_count"] == 123
+    assert stats["max_vectors"] == 50000
+    assert stats["high_water_mark"] == 40000
+    assert stats["low_water_mark"] == 10000
+    assert stats["high_water_pct"] == 80
+    assert stats["low_water_pct"] == 20
+    assert 0 < stats["percent_full"] < 1
+    assert "upload" in stats["pinned_sources"]
+    assert "profile" in stats["pinned_sources"]
+
+
+# ---------- evict_batch ----------
+
+def test_evict_batch_excludes_pinned_sources(monkeypatch):
+    """Pinned sources ('upload', 'profile') should be in the must_not scroll filter."""
+    old = _old_ts(48)
+    # Only non-pinned points are returned (real Qdrant would honour must_not filter)
+    scroll_points = [
+        {"id": "old-data", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 0}},
+    ]
+
+    class ScrollClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                must_not = kw.get("json", {}).get("filter", {}).get("must_not", [])
+                pinned_values = [m["match"]["value"] for m in must_not]
+                assert "upload" in pinned_values
+                assert "profile" in pinned_values
+                return FakeResponse(200, {"result": {"points": scroll_points}})
+            if "/points/delete" in url:
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: ScrollClient())
+    deleted = asyncio.run(rag.evict_batch(10))
+    assert deleted == 1
+
+
+def test_evict_batch_respects_grace_period(monkeypatch):
+    """Vectors younger than RAG_GRACE_HOURS should be skipped."""
+    old = _old_ts(48)
+    young = _young_ts(0.1)
+    scroll_points = [
+        {"id": "mature", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 0}},
+        {"id": "newborn", "payload": {"source": "terminal", "ingest_date": young, "retrieval_count": 0}},
+    ]
+
+    class GraceClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": scroll_points}})
+            if "/points/delete" in url:
+                deleted = kw.get("json", {}).get("points", [])
+                assert "newborn" not in deleted
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: GraceClient())
+    deleted = asyncio.run(rag.evict_batch(10))
+    assert deleted == 1
+
+
+def test_evict_batch_respects_batch_size(monkeypatch):
+    """Only up to batch_size vectors should be deleted per call."""
+    old = _old_ts(48)
+    points = [{"id": f"p{i}", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 0}} for i in range(50)]
+
+    class BatchClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/delete" in url:
+                deleted = kw.get("json", {}).get("points", [])
+                assert len(deleted) == 10
+                return FakeResponse(200)
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": points}})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: BatchClient())
+    deleted = asyncio.run(rag.evict_batch(10))
+    assert deleted == 10
+
+
+def test_evict_batch_all_pinned_returns_zero(monkeypatch):
+    """If scroll returns nothing (all points filtered by must_not), evict_batch returns 0."""
+    class EmptyClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": []}})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: EmptyClient())
+    deleted = asyncio.run(rag.evict_batch(10))
+    assert deleted == 0
+
+
+def test_evict_batch_scores_lowest_first(monkeypatch):
+    """Vectors with lower scores should be evicted first."""
+    old = _old_ts(48)
+    points = [
+        {"id": "high-score", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 100}},
+        {"id": "low-score", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 0}},
+        {"id": "mid-score", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 50}},
+    ]
+
+    class ScoreClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/delete" in url:
+                deleted = kw.get("json", {}).get("points", [])
+                assert "low-score" in deleted
+                assert "high-score" not in deleted
+                assert "mid-score" not in deleted
+                return FakeResponse(200)
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": points}})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: ScoreClient())
+    deleted = asyncio.run(rag.evict_batch(1))
+    assert deleted == 1
+
+
+# ---------- maybe_evict ----------
+
+def test_maybe_evict_below_high_water(monkeypatch):
+    """When count is below high-water mark, eviction should not fire."""
+    class LowCountClient(FakeAsyncClient):
+        async def get(self, url, **kw):
+            # 30000 < 40000 high water
+            return FakeResponse(200, {"result": {"vectors_count": 30000}})
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: LowCountClient())
+    rag.EVICTION_LOG.clear()
+    evicted = asyncio.run(rag.maybe_evict())
+    assert evicted == 0
+    assert len(rag.EVICTION_LOG) == 0
+
+
+def test_maybe_evict_at_high_water(monkeypatch):
+    """When count reaches high-water mark, eviction should fire."""
+    class HighCountClient(FakeAsyncClient):
+        def __init__(self, *a, **kw):
+            super().__init__()
+            self.call_count = 0
+
+        async def get(self, url, **kw):
+            return FakeResponse(200, {"result": {"vectors_count": 45000}})
+
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                old = _old_ts(48)
+                points = [{"id": f"evict-me-{i}", "payload": {"source": "terminal", "ingest_date": old, "retrieval_count": 0}} for i in range(100)]
+                return FakeResponse(200, {"result": {"points": points}})
+            if "/points/delete" in url:
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: HighCountClient())
+    rag.EVICTION_LOG.clear()
+    evicted = asyncio.run(rag.maybe_evict())
+    assert evicted > 0
+    assert len(rag.EVICTION_LOG) == 1
+    entry = rag.EVICTION_LOG[0]
+    assert "timestamp" in entry
+    assert entry["count"] > 0
+
+
+def test_maybe_evict_zero_config_disabled(monkeypatch):
+    """RAG_MAX_VECTORS <= 0 should disable eviction."""
+    orig = config.RAG_MAX_VECTORS
+    try:
+        config.RAG_MAX_VECTORS = 0
+        evicted = asyncio.run(rag.maybe_evict())
+        assert evicted == 0
+    finally:
+        config.RAG_MAX_VECTORS = orig
+
+
+def test_maybe_evict_all_pinned_breaks(monkeypatch):
+    """Above high water but only pinned points exist → eviction breaks with 0 deleted."""
+    class AllPinnedClient(FakeAsyncClient):
+        async def get(self, url, **kw):
+            return FakeResponse(200, {"result": {"vectors_count": 45000}})
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": []}})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: AllPinnedClient())
+    rag.EVICTION_LOG.clear()
+    evicted = asyncio.run(rag.maybe_evict())
+    assert evicted == 0
+    assert len(rag.EVICTION_LOG) == 0
+
+
+# ---------- get_rag_operational_stats ----------
+
+def test_rag_operational_stats_shape(monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    rag.EVICTION_LOG.clear()
+    rag.EVICTION_LOG.append({
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "count": 500,
+        "remaining": 40000,
+    })
+    stats = asyncio.run(rag.get_rag_operational_stats())
+    assert stats["vector_count"] == 123
+    assert stats["grace_hours"] == 1
+    assert "eviction_counts_last_1m" in stats
+    assert "eviction_counts_last_5m" in stats
+    assert "eviction_counts_last_30m" in stats
+    assert stats["eviction_counts_last_1m"] == 500
+
+
+# ---------- GET /api/rag/stats ----------
+
+def test_rag_stats_endpoint(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/stats", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["vector_count"] == 123
+        assert data["max_vectors"] == 50000
+        assert "high_water_mark" in data
+        assert "low_water_mark" in data
+        assert data["high_water_pct"] == 80
+        assert data["low_water_pct"] == 20
+        assert "percent_full" in data
+        assert data["pinned_sources"] == ["upload", "profile"]
+        assert data["grace_hours"] == 1
+        assert "eviction_counts_last_1m" in data
+        assert "eviction_counts_last_5m" in data
+        assert "eviction_counts_last_30m" in data
+        assert "pinned_count" in data
+        assert "avg_retrieval_count" in data
+        assert "at_risk_count" in data
+        assert "eviction_log_size" in data
+
+
+def test_rag_stats_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/stats", headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+# ---------- POST /api/rag/flush ----------
+
+def test_rag_flush_endpoint(tmp_path, monkeypatch):
+    class FlushClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": [{"id": "a"}, {"id": "b"}]}})
+            if "/points/delete" in url:
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FlushClient())
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/rag/flush", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["status"] == "flushed"
+        assert data["deleted_count"] == 2
+        assert data["collection"] == rag.RAG_COLLECTION
+
+
+def test_rag_flush_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/rag/flush", headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+def test_rag_flush_empty_collection(tmp_path, monkeypatch):
+    class EmptyClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                return FakeResponse(200, {"result": {"points": []}})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: EmptyClient())
+    with make_client(tmp_path) as client:
+        resp = client.post("/api/rag/flush", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["deleted_count"] == 0
+        assert data["status"] == "flushed"
+
+
+# ---------- Race lock ----------
+
+def test_eviction_lock_prevents_concurrent_eviction(monkeypatch):
+    """Concurrent calls to maybe_evict should queue; only one evicts."""
+    call_order = []
+
+    async def slow_get_collection_count():
+        call_order.append("count")
+        return 45000
+
+    async def slow_evict_batch(bs):
+        call_order.append("evict")
+        await asyncio.sleep(0.05)
+        return 500
+
+    monkeypatch.setattr(rag, "get_collection_count", slow_get_collection_count)
+    monkeypatch.setattr(rag, "evict_batch", slow_evict_batch)
+    rag.EVICTION_LOG.clear()
+
+    async def run_concurrent():
+        r1, r2 = await asyncio.gather(rag.maybe_evict(), rag.maybe_evict())
+        return r1, r2
+
+    r1, r2 = asyncio.run(run_concurrent())
+    # First call evicted, second found count already below high water or lock serialized
+    assert r1 >= 0
+    assert r2 >= 0
+
+
+# ---------- GET /api/rag/points ----------
+
+def test_rag_list_points_empty(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/points", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert "points" in data
+        assert data["total"] == 123
+        assert len(data["points"]) == 0
+
+
+def test_rag_list_points_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/points", headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+def test_rag_list_points_with_data(tmp_path, monkeypatch):
+    with make_client(tmp_path) as client:
+        encrypted = crypto.encrypt_text("Hello world test content")
+
+        class DataClient(FakeAsyncClient):
+            async def post(self, url, **kw):
+                if "/points/scroll" in url:
+                    return FakeResponse(200, {
+                        "result": {
+                            "points": [{
+                                "id": "test-pt-1",
+                                "payload": {
+                                    "text": encrypted,
+                                    "source": "terminal",
+                                    "ingest_date": "2024-06-15T10:00:00",
+                                    "type": "ingest",
+                                    "retrieval_count": 3,
+                                },
+                            }],
+                            "next_page_offset": None,
+                        }
+                    })
+                return FakeResponse(200)
+            async def get(self, url, **kw):
+                if "/collections/caic_rag" in url:
+                    return FakeResponse(200, {"result": {"vectors_count": 1}})
+                return FakeResponse(200)
+
+        monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: DataClient())
+        resp = client.get("/api/rag/points", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert len(data["points"]) == 1
+        p = data["points"][0]
+        assert p["id"] == "test-pt-1"
+        assert p["source"] == "terminal"
+        assert p["type"] == "ingest"
+        assert "Hello world" in p["text"]
+        assert p["retrieval_count"] == 3
+
+
+def test_rag_list_points_source_filter(tmp_path, monkeypatch):
+    """Source filter should be passed as Qdrant must-match."""
+    class FilterClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/scroll" in url:
+                body = kw.get("json", {})
+                filt = body.get("filter", {})
+                must = filt.get("must", [])
+                # Verify the source filter was passed
+                assert any(m.get("match", {}).get("value") == "upload" for m in must)
+                return FakeResponse(200, {"result": {"points": [], "next_page_offset": None}})
+            return FakeResponse(200)
+        async def get(self, url, **kw):
+            return FakeResponse(200, {"result": {"vectors_count": 0}})
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FilterClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/points?source=upload", headers=_admin_headers(client))
+        assert resp.status_code == 200
+
+
+def test_rag_list_points_search(tmp_path, monkeypatch):
+    """Semantic search should use Qdrant search endpoint."""
+    encrypted = crypto.encrypt_text("Semantic match text")
+
+    class SearchClient(FakeAsyncClient):
+        call_log = []
+        async def post(self, url, **kw):
+            SearchClient.call_log.append(url)
+            if "/api/embeddings" in url:
+                vec = [0.1] * 768
+                return FakeResponse(200, {"embedding": vec})
+            if "/points/search" in url:
+                return FakeResponse(200, {"result": [{
+                    "id": "search-hit-1",
+                    "score": 0.85,
+                    "payload": {
+                        "text": encrypted,
+                        "source": "terminal",
+                        "ingest_date": "2024-06-15T10:00:00",
+                        "type": "ingest",
+                        "retrieval_count": 1,
+                    },
+                }]})
+            return FakeResponse(200)
+        async def get(self, url, **kw):
+            return FakeResponse(200, {"result": {}})
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: SearchClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/points?search=hello+world", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert len(data["points"]) == 1
+        assert data["points"][0]["id"] == "search-hit-1"
+        assert data["points"][0]["score"] == 0.85
+
+
+# ---------- GET /api/rag/point/{point_id} ----------
+
+def test_rag_get_point_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/point/test-1", headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+def test_rag_get_point_found(tmp_path, monkeypatch):
+    with make_client(tmp_path) as client:
+        encrypted = crypto.encrypt_text("Single point text")
+
+        class GetClient(FakeAsyncClient):
+            async def get(self, url, **kw):
+                if "/collections/caic_rag/points/test-1" in url:
+                    return FakeResponse(200, {"result": {
+                        "id": "test-1",
+                        "payload": {
+                            "text": encrypted,
+                            "source": "terminal",
+                            "ingest_date": "2024-06-15T10:00:00",
+                            "type": "ingest",
+                            "retrieval_count": 5,
+                        },
+                    }})
+                return FakeResponse(200)
+
+        monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: GetClient())
+        resp = client.get("/api/rag/point/test-1", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        p = resp.json()
+        assert p["id"] == "test-1"
+        assert p["source"] == "terminal"
+        assert "Single point" in p["text"]
+
+
+def test_rag_get_point_not_found(tmp_path, monkeypatch):
+    class NotFoundClient(FakeAsyncClient):
+        async def get(self, url, **kw):
+            if "/collections/caic_rag/points/" in url:
+                return FakeResponse(404, {"detail": "Not found"})
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: NotFoundClient())
+    with make_client(tmp_path) as client:
+        resp = client.get("/api/rag/point/nonexistent", headers=_admin_headers(client))
+        assert resp.status_code == 404
+
+
+# ---------- DELETE /api/rag/point/{point_id} ----------
+
+def test_rag_delete_point_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.delete("/api/rag/point/test-1", headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+def test_rag_delete_point_success(tmp_path, monkeypatch):
+    class DeleteClient(FakeAsyncClient):
+        async def post(self, url, **kw):
+            if "/points/delete" in url:
+                pts = kw.get("json", {}).get("points", [])
+                assert "test-1" in pts
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: DeleteClient())
+    with make_client(tmp_path) as client:
+        resp = client.delete("/api/rag/point/test-1", headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["status"] == "deleted"
+        assert data["id"] == "test-1"
+
+
+# ---------- PATCH /api/rag/point/{point_id} ----------
+
+def test_rag_update_point_requires_admin(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.patch("/api/rag/point/test-1", json={"text": "new"}, headers=_guest_headers(client))
+        assert resp.status_code == 403
+
+
+def test_rag_update_point_success(tmp_path, monkeypatch):
+    encrypted_old = crypto.encrypt_text("old text")
+
+    class UpdateClient(FakeAsyncClient):
+        async def get(self, url, **kw):
+            if "/collections/caic_rag/points/test-1" in url:
+                return FakeResponse(200, {"result": {
+                    "id": "test-1",
+                    "payload": {
+                        "text": encrypted_old,
+                        "source": "terminal",
+                        "ingest_date": "2024-06-15T10:00:00",
+                        "type": "ingest",
+                        "retrieval_count": 2,
+                    },
+                }})
+            return FakeResponse(200)
+        async def post(self, url, **kw):
+            if "/api/embeddings" in url:
+                return FakeResponse(200, {"embedding": [0.2] * 768})
+            return FakeResponse(200)
+        async def put(self, url, **kw):
+            if "/points?wait=true" in url:
+                pts = kw.get("json", {}).get("points", [])
+                assert len(pts) == 1
+                assert len(pts[0]["vector"]) == 768
+                payload = pts[0]["payload"]
+                assert "text" in payload
+                assert payload["source"] == "terminal"
+                return FakeResponse(200)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: UpdateClient())
+    with make_client(tmp_path) as client:
+        resp = client.patch("/api/rag/point/test-1", json={"text": "updated text"}, headers=_admin_headers(client))
+        assert resp.status_code == 200
+        data = resp.json()
+        assert data["status"] == "updated"
+        assert data["id"] == "test-1"
+
+
+def test_rag_update_point_empty_text(tmp_path, monkeypatch):
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: FakeAsyncClient())
+    with make_client(tmp_path) as client:
+        resp = client.patch("/api/rag/point/test-1", json={"text": ""}, headers=_admin_headers(client))
+        assert resp.status_code == 400
+
+
+def test_rag_update_point_not_found(tmp_path, monkeypatch):
+    class NotFoundClient(FakeAsyncClient):
+        async def get(self, url, **kw):
+            if "/collections/caic_rag/points/" in url:
+                return FakeResponse(404)
+            return FakeResponse(200)
+
+    monkeypatch.setattr(httpx, "AsyncClient", lambda *a, **kw: NotFoundClient())
+    with make_client(tmp_path) as client:
+        resp = client.patch("/api/rag/point/nonexistent", json={"text": "new"}, headers=_admin_headers(client))
+        assert resp.status_code == 404

tests/test_rate_and_payload_guardrails.py

@@ -12,8 +12,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-rate.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-rate.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_search_route.py

@@ -13,8 +13,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-search-route.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-search-route.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_settings_allowlist.py

@@ -9,8 +9,8 @@ from security import SESSIONS, PIN_ATTEMPTS
 
 
 def make_admin_client(tmp_path: Path) -> tuple[TestClient, dict[str, str]]:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-settings.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-settings.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     db.init_db()

tests/test_skills_framework.py

@@ -11,8 +11,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-skills.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-skills.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()

tests/test_upload.py

@@ -12,8 +12,8 @@ from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
 
 
 def make_client(tmp_path: Path) -> TestClient:
-    os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
-    db.DB_PATH = tmp_path / "jarvischat-upload.db"
+    os.environ["CAIC_ADMIN_PIN"] = "1234"
+    db.DB_PATH = tmp_path / "caic-upload.db"
     SESSIONS.clear()
     PIN_ATTEMPTS.clear()
     RATE_EVENTS.clear()
@@ -48,6 +48,7 @@ def test_upload_unsupported_mime(tmp_path: Path):
 
 
 def test_upload_context_mode(tmp_path: Path):
+    from crypto import decrypt_text
     with make_client(tmp_path) as client:
         resp = client.post(
             "/api/upload", headers=_admin_headers(client),
@@ -62,7 +63,7 @@ def test_upload_context_mode(tmp_path: Path):
         assert "chunks_ingested" not in data
 
         row = db.get_db().execute("SELECT content FROM upload_context WHERE id = ?", (data["context_id"],)).fetchone()
-        assert row["content"] == "Hello world notes"
+        assert decrypt_text(row["content"]) == "Hello world notes"
 
 
 def test_upload_ingest_mode(tmp_path: Path, monkeypatch):