Compare commits

23 Commits

Author SHA1 Message Date
gramps 81238c0d7f v1.9.0 -> v1.10.0: file upload UI + attachment management
- Paperclip icon left of text input, file preview pill (image thumb or file icon)
- Conversation list shows attachment icon right of trash, opens gallery overlay
- Gallery overlay: scrollable, close (X), delete attachment per item
- DELETE /api/upload/{id} removes from SQLite + Qdrant
- PATCH /api/upload/{id}/link ties upload to conversation
- GET /api/upload/by-conversation/{id} lists attachments
- Chat accepts upload_context_id, injects [ATTACHED DOCUMENT] into system prompt
- Conversation list includes attachment_count field
- 8 new tests: upload context injection, delete, link, by-conversation, image type, attachment count

Still missing (P3): drag-and-drop upload, global attachments page, file download, batch upload
2026-07-03 12:18:06 -07:00
gramps 4a891c8435 v1.8.9 -> v1.9.0: file upload backend (PDF/text, Qdrant ingest, SQLite context) 2026-07-01 18:15:23 -07:00
gramps 239a0d5fa9 add pypdf dependency for PDF upload support 2026-07-01 18:10:12 -07:00
gramps 1d1cb61264 add P2 item #17: bidirectional image I/O to backlog 2026-07-01 18:08:25 -07:00
gramps 8393497df5 add P2 item: HTTPS via Let's Encrypt to backlog 2026-07-01 18:02:41 -07:00
gramps 7651ea620c v1.8.8 -> v1.8.9: fix copy button with execCommand fallback for insecure context 2026-07-01 18:01:42 -07:00
gramps 04d885e9eb v1.8.7 -> v1.8.8: add TTR badge (time-to-respond) next to PPL 2026-07-01 17:56:28 -07:00
gramps 9ef306e133 v1.8.6 -> v1.8.7: add image paste guard with toast notification 2026-07-01 17:35:12 -07:00
gramps 6451f674bb v1.8.5 -> v1.8.6: bump patch for trash icon fix, model dropdown removal, preset default 2026-07-01 17:30:35 -07:00
gramps b52e120ba1 fix: restore trash icon, remove vestigial model dropdown, default preset to General Assistant 2026-07-01 17:28:38 -07:00
gramps cb8ceccbe0 docs: mark Task 2 dependency resolved — llama-server-coder.service created and verified on ultron 2026-07-01 17:13:37 -07:00
gramps cacb04b3de docs: clean up node references and branding consistency 2026-07-01 09:26:33 -07:00
gramps 2b7f51cdca docs: clarify Task 2 as dependency resolved — real model swap delivered by Roadmap N (Tasks 9-15) 2026-07-01 09:24:58 -07:00
gramps d2cc246e51 first commit - defining tasks file as a living doc for opencode 2026-07-01 09:04:06 -07:00
gramps b8405b8d76 fix: increase trash icon visibility (remove 0.5 opacity, bump to 15px) 2026-06-27 16:09:05 -07:00
gramps e3b1780292 feat: add trash-can icon to left of each conversation in sidebar
Replace the hover-reveal × on the right with an always-visible 🗑 icon
positioned to the left of the conversation title. Clicking it triggers
the existing deleteConversation() which shows a confirm dialog and
enforces admin-only access.
2026-06-27 16:07:18 -07:00
gramps 66b086c3f3 fix: restore EMBED_URL pointing to ollama on 192.168.50.210:11434 2026-06-27 16:03:19 -07:00
gramps 4b36fd315a fix: replace hardcoded EMBED_URL with LLAMA_SERVER_BASE from config
EMBED_URL in rag.py hardcoded the IP and port instead of using
LLAMA_SERVER_BASE, so the env var JARVISCHAT_LLAMA_SERVER_BASE
was ignored for embedding requests.
2026-06-27 15:59:43 -07:00
gramps fcc0605a4a release: bump version to v1.8.5 2026-06-27 15:27:47 -07:00
gramps 091e2ad2e3 test: add unit tests for all 10 routers (92 total)
New test files:
- test_conversations.py — list/create/get/update/delete/delete-all, admin enforcement
- test_presets.py — list/create/update/delete, default preset protection
- test_profile.py — get/update/default, length validation
- test_models_router.py — list/ps/show/stats/search-status, connect errors
- test_completions.py — API key auth, FIM passthrough, streaming/blocking, errors
- test_search_route.py — explicit search flow, no results, stream errors
- test_memories.py — edit/search/stats endpoints, validation, admin enforcement

Update AGENTS.md with full test file coverage table and README.md
2026-06-27 15:27:13 -07:00
gramps 5986c4ad86 fix: close two CSRF origin-check security gaps
- Extend origin check to all /api/ requests (not just state-changing methods),
  closing the GET/HEAD/OPTIONS bypass that allowed cross-origin reads
- origin_allowed() now returns False when both Origin and Referer headers
  are absent, preventing script-initiated requests from bypassing the check
- Update AGENTS.md and README.md to document the changes
2026-06-27 15:20:02 -07:00
gramps cc1efa7a21 fix: resolve all critical runtime errors and bugs from audit
- Add COMPLETIONS_API_KEY to config.py (env var + auto-generated fallback)
- Fix perplexity auto-search: upstream sends logprobs=true, parse_llama_stream_chunk
  extracts per-token logprobs, all_logprobs populated during streaming
- Fix all /api/models endpoints to target LLAMA_SERVER_BASE (port 8081) not OLLAMA_BASE
- Fix RAG embedding endpoint URL from port 11434 (Ollama) to 8081 (llama-server)
- Correct misleading error messages: 'inference server' not 'Ollama'
- Remove raw_results leak from SSE event stream in /api/search
- Fix weather query extractor: pattern-match instead of unconditional suffix append
- Escape FTS5 operator keywords (AND/OR/NOT/NEAR) in memory search
- Move auth.py BODY_LIMIT_DEFAULT_BYTES imports to module level
- Change RAG injection log level from warning to info
- Fix all 8 test files after modular refactor (rewire imports from correct modules)
- Update AGENTS.md and README.md to reflect v1.8.0 changes
2026-06-27 15:12:18 -07:00
gramps 41a8708c0d docs: add roadmap items M (MCP) and N (AMQP cluster nervous system), fix jarvis IP 2026-06-23 15:31:16 +00:00
38 changed files with 3040 additions and 953 deletions
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# 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
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@@ -19,7 +19,7 @@ sudo systemctl restart jarvischat
```bash
./venv/bin/pip install -r requirements.txt
# Also requires: psutil jinja2 python-multipart (not in requirements.txt)
# Also requires: psutil jinja2 python-multipart pypdf (not in requirements.txt)
```
## Architecture
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![jarvisChat logo](static/jcscreenie.png)
# ⚡ JarvisChat v1.9.0
# jarvisChat v1.8.6
**A privacy-first, homelab-native developer knowledge platform.**
**A lightweight local inference coding companion with persistent memory, web search, and real-time system monitoring.**
> JarvisChat turns a heterogeneous LAN of budget hardware into a distributed local AI inference cluster — accumulating institutional knowledge over time, keeping all data off the cloud, and squeezing real performance out of modest consumer hardware through architecture rather than dollars.
Built with FastAPI + SQLite + Jinja2. Runs on Python 3.13. No Docker required.
This is not another AI chat wrapper. jC is the UX and knowledge-management layer for a local AI brain — analogous to what Windows was to DOS, or what the web is to the internet. The intelligence lives in the model and the RAG corpus. jC makes it accessible and keeps feeding it.
Developer wiki: [docs/wiki/Home.md](docs/wiki/Home.md)
---
## What's New in v1.8.0
## The Four Pillars
- **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)
### 1. Privacy
Everything runs on your LAN. No API keys, no cloud endpoints, no data leaving your network, no subscription, no terms-of-service surprises. Your conversations, your codebase, your decisions — stay yours.
## Features
### 2. Knowledge Retention
Unlike stateless chat tools that forget everything when you close the tab, jC accumulates institutional memory. Every solved problem, every architectural decision, every working command gets absorbed into the RAG corpus via Qdrant. The system gets smarter the longer you use it.
- **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
### 3. Budget Hardware Maximization
You don't need a $10,000 workstation. jC is designed for the developer who has a drawer full of machines and the skills to wire them together. RPC clustering, model splitting across CPU and GPU nodes, dynamic resource negotiation, and smart RAG eviction squeeze real performance out of modest consumer hardware.
### 4. Homelab-Native Architecture
Built specifically for the heterogeneous homelab: mixed hardware, mixed OS, consumer GPUs, ARM boards, NAS storage — all working together as a coherent AI platform. A designated master node hosts jC, llama-server, and SearXNG. GPU nodes self-register as RPC inference workers. The architecture scales horizontally across whatever you've got.
---
## Target Audience
Solo developers and homelab enthusiasts who are:
- Budget-constrained but hardware-rich (multiple machines, NAS, spare GPUs)
- Privacy-conscious (no cloud AI subscriptions)
- Technically capable (if you can install jC, you can designate the master node)
- Building something over time and want their AI to remember it
---
## Architecture
## File Structure
```
┌─────────────────────────────────────────────────────────────┐
│ YOUR LAN │
│ │
│ ┌─────────────────┐ ┌──────────────────────────┐ │
│ │ jarvis │◄──RPC───│ ultron │ │
│ │ 192.168.50.212│ 50052 │ 192.168.50.108 │ │
│ │ │ │ │ │
│ │ jC :8080 │ │ llama-server :8081 │ │
│ │ SearXNG :8888 │ │ llama-server :8082 (*) │ │
│ │ RX 6600 XT 8GB │ │ Qdrant :6333 │ │
│ │ GPU RPC worker │ │ mxbai-embed :11434 │ │
│ Vulkan backend │ │ AMD Ryzen 7 7840HS │ │
└─────────────────┘ │ Radeon 780M iGPU │ │
└──────────────────────────┘ │
┌─────────────────┐ ┌──────────────────────────┐ │
│ pivault │ │ corsair │ │
│ 192.168.50.158│ │ 192.168.50.132 │ │
│ │ │ │ │
│ 10.83TB RAID5 │ │ RTX 5070 Ti 16GB │ │
│ RPi 5 8GB │ Ryzen 7 7800X3D │ │
│ │ NAS / Kopia │ │ Gaming / Streaming │ │
│ └─────────────────┘ └──────────────────────────┘ │
│ │
(*) Planned: Qwen2.5-Coder-14B on :8082 │
└─────────────────────────────────────────────────────────────┘
/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
```
**Data flow:**
```
Browser / IDE (Continue.dev)
→ jC :8080 (FastAPI — auth, RAG, memory, conversation history)
→ Qdrant :6333 (vector search, mxbai-embed-large for embeddings)
→ llama-server :8081 (inference)
→ jarvis RPC :50052 (GPU layer offload — RX 6600 XT)
```
## Requirements
---
## The AMD + NVIDIA Cross-Cluster Reality
This cluster intentionally mixes GPU architectures — **AMD RX 6600 XT on jarvis** and **NVIDIA RTX 5070 Ti on corsair**. This is deliberate and it works.
The RPC layer in llama.cpp is GPU-vendor-agnostic. jarvis runs llama-rpc with a **Vulkan backend** (not ROCm, not CUDA) which provides hardware-neutral GPU acceleration. ultron's llama-server connects to it over TCP and offloads tensor layers without caring what GPU is on the other end.
This means any machine on your LAN with any GPU (AMD, NVIDIA, Intel Arc) can participate as an RPC worker — as long as it can run llama-rpc with Vulkan support.
---
## Cluster Performance Tuning
### The Layer Offloading Trick
The key to squeezing performance out of a CPU+GPU split cluster is `--n-gpu-layers`. This controls how many transformer layers get offloaded to the RPC GPU backend versus staying on the CPU.
**Starting point (before tuning):** ~7 t/s
**After initial layer optimization:** ~17 t/s
**After full cluster tuning:** 3035 t/s
The progression that got us there:
1. **Start with `--n-gpu-layers 99`** — tells llama-server to offload as many layers as possible. With Mistral-Nemo-12B Q4_K_M this results in all 41/41 layers offloading to jarvis GPU via RPC.
2. **Verify GPU is actually working** — watch the llama-server startup log for:
```
load_tensors: offloaded 41/41 layers to GPU
load_tensors: RPC[192.168.50.210:50052] model buffer size = 6763.30 MiB
load_tensors: CPU_Mapped model buffer size = 360.00 MiB
```
If layers aren't offloading, the RPC connection isn't established.
3. **Check actual throughput** — the timings block in llama-server responses shows real t/s. Tune from there.
**Current llama-server service on ultron (`/etc/systemd/system/llama-server.service`):**
```ini
[Unit]
Description=Llama.cpp Server (RPC frontend — Mistral-Nemo general)
After=network.target
[Service]
Type=simple
User=root
ExecStart=/root/llama.cpp/build/bin/llama-server \
--model /home/gramps/models/Mistral-Nemo-Instruct-2407-Q4_K_M.gguf \
--rpc 192.168.50.212:50052 \
--host 0.0.0.0 \
--port 8081 \
--n-gpu-layers 99
Restart=on-failure
RestartSec=5
[Install]
WantedBy=multi-user.target
```
**llama-rpc service on jarvis (`/etc/systemd/system/llama-rpc.service`):**
```ini
[Unit]
Description=Llama.cpp RPC Server (GPU backend — RX 6600 XT Vulkan)
After=network.target
[Service]
Type=simple
User=root
ExecStart=/root/llama.cpp/build/bin/llama-rpc-server \
--host 0.0.0.0 \
--port 50052
Restart=on-failure
RestartSec=5
[Install]
WantedBy=multi-user.target
```
---
## Models
### Current
| Model | Location | Port | Purpose |
|-------|----------|------|---------|
| Mistral-Nemo-Instruct-2407-Q4_K_M | `/home/gramps/models/` on jarvis | ultron:8081 | General assistant, chat |
| mxbai-embed-large | ultron (Docker/Ollama) | ultron:11434 | RAG embeddings |
### Planned
| Model | Size | Port | Purpose |
|-------|------|------|---------|
| Qwen2.5-Coder-14B-Q5_K_M | ~10GB | ultron:8082 | Code completion, pair programming |
> **Note:** ultron has 16GB RAM. Only one primary inference model can be hot at a time. llama-server instances are swapped via systemd when switching between general and code models.
---
## RAG System
jC uses **Qdrant** for vector storage and **mxbai-embed-large** (1024-dim) for embeddings.
### Qdrant Collection
- **Collection:** `jarvis_rag`
- **Vector size:** 1024 (mxbai-embed-large output)
- **Distance:** Cosine
- **Score threshold:** 0.25 (filters low-relevance chunks)
- **Chunks retrieved per query:** 3 (configurable)
### RAM Ceiling
Each vector = 4KB (1024 dims × float32). With ultron's ~4-6GB available to Qdrant after llama-server:
- Practical ceiling: ~11.5M chunks before RAM becomes the bottleneck
- Current corpus: 219 points (early stage)
- Storage on disk: negligible against pivault's 10.83TB
### What Gets Ingested
- Code repositories (your actual codebase)
- Pair-programming conversation history
- Architecture decisions and working commands
- Documentation and URLs (fetched and stripped via beautifulsoup4/httpx)
---
## JarvisChat Service (`/etc/systemd/system/jarvischat.service`)
```ini
[Unit]
Description=JarvisChat - Local LLM Developer Platform
After=network.target
[Service]
Type=simple
User=root
WorkingDirectory=/opt/jarvischat
ExecStart=/opt/jarvischat/venv/bin/uvicorn app:app --host 0.0.0.0 --port 8080
Restart=always
RestartSec=5
Environment=PYTHONUNBUFFERED=1
Environment=OLLAMA_BASE=http://192.168.50.108:8081
Environment=LLAMA_SERVER_BASE=http://192.168.50.108:8081
[Install]
WantedBy=multi-user.target
```
---
- 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)
## Installation
### Prerequisites
- Python 3.11+ (tested on 3.13)
- llama.cpp built from source on both jarvis (RPC server) and ultron (llama-server)
- Qdrant running on ultron
- Ollama on ultron (for mxbai-embed-large embeddings)
- SearXNG on jarvis:8888 (optional, for web search)
### Fresh Install
```bash
# Create directory and venv
sudo mkdir -p /opt/jarvischat
sudo chown $USER:$USER /opt/jarvischat
cd /opt/jarvischat
python3 -m venv venv
./venv/bin/pip install fastapi uvicorn httpx psutil jinja2 python-multipart qdrant-client
# 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/)
```
Copy `app.py` to `/opt/jarvischat/` and `index.html` to `/opt/jarvischat/templates/`.
WARNING: Do not use `1234` as your admin PIN unless you accept weak local security.
### Bootstrap the PIN
NOTE: First boot requires `JARVISCHAT_ADMIN_PIN` unless you explicitly opt into insecure fallback with `JARVISCHAT_ALLOW_DEFAULT_PIN=true`.
## Systemd Service
Create `/etc/systemd/system/jarvischat.service`:
```ini
[Unit]
Description=jarvisChat - Local Inference Web Interface
After=network.target
[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
[Install]
WantedBy=multi-user.target
```
```bash
export JARVISCHAT_ADMIN_PIN=XXXX # your 4-digit PIN
sudo systemctl daemon-reload
sudo systemctl enable jarvischat
sudo systemctl start jarvischat
```
Or allow the insecure default for testing:
```bash
export JARVISCHAT_ALLOW_DEFAULT_PIN=true
```
## Memory Commands
### Environment Variables
In chat, natural language triggers memory operations:
| Variable | Default | Description |
|----------|---------|-------------|
| `OLLAMA_BASE` | `http://localhost:11434` | Ollama-compatible endpoint (legacy) |
| `LLAMA_SERVER_BASE` | `http://192.168.50.108:8081` | llama-server OpenAI-compat inference endpoint |
| `JARVISCHAT_ADMIN_PIN` | (none) | 4-digit admin PIN (required on first boot) |
| `JARVISCHAT_ALLOW_DEFAULT_PIN` | `false` | Allow insecure default PIN 1234 |
| `JARVISCHAT_TRUSTED_ORIGINS` | (none) | Comma-separated trusted origins for CSRF |
| `JARVISCHAT_ALLOWED_CIDRS` | RFC1918 + loopback | Allowed client IP CIDRs |
| 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 |
---
Memories are automatically searched based on your message content and injected into the system prompt when relevant.
### Memory Topics
Memories are auto-categorized:
- `preference` — likes, dislikes, choices
- `project` — active work, repos, tasks
- `infrastructure` — servers, services, configs
- `personal` — name, location, background
- `general` — everything else
## API Endpoints
### Auth
| Method | Path | 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 status |
| POST | `/api/auth/heartbeat` | Keep session alive |
### Completions (OpenAI-compatible)
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/v1/chat/completions` | OpenAI-compatible chat (requires Bearer API key) |
### Chat & Search
| Method | Path | Description |
|--------|------|-------------|
| POST | `/api/chat` | Streaming chat (SSE) |
| POST | `/api/search` | Explicit web search via SearXNG |
| GET | `/api/search/status` | SearXNG health check |
### Models
| Method | Path | Description |
|--------|------|-------------|
| GET | `/api/models` | List available models from llama-server |
| GET | `/api/ps` | Running models |
| POST | `/api/show` | Model info |
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/api/chat` | Send message (streaming SSE) |
| POST | `/api/search` | Explicit web search (streaming SSE) |
### Memory
| Method | Path | Description |
|--------|------|-------------|
| 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=` | FTS5 search memories |
| GET | `/api/memories/stats` | Memory statistics |
| GET | `/api/memories/search?q=term` | Search memories |
| GET | `/api/memories/stats` | Get counts by topic |
### Models & System
| 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 |
### 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 | Path | Description |
|--------|------|-------------|
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/conversations` | List conversations |
| POST | `/api/conversations` | Create conversation |
| GET | `/api/conversations/{id}` | Get conversation + messages |
| PUT | `/api/conversations/{id}` | Update title/model |
| 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 |
| DELETE | `/api/conversations` | Delete ALL conversations |
### Profile & Settings
| Method | Path | Description |
|--------|------|-------------|
| GET | `/api/profile` | Get profile |
| PUT | `/api/profile` | Update profile |
| GET | `/api/settings` | Get settings |
| PUT | `/api/settings` | Update settings |
| GET | `/api/stats` | CPU/RAM/GPU stats |
### 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 | Path | Description |
|--------|------|-------------|
| GET | `/api/skills` | List all skills |
| GET | `/api/skills/active` | List enabled skills |
| PUT | `/api/skills/{key}` | Enable/disable skill |
---
| 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) |
## Memory Commands
### Auth
Say these in chat to interact with the memory system:
| 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 |
| Command | Effect |
|---------|--------|
| `remember that [fact]` | Stores fact in FTS5 memory |
| `please remember [fact]` | Same |
| `don't forget [fact]` | Same |
| `forget about [topic]` | Deletes matching memories |
## Configuration
---
Settings are stored in the `settings` table and include:
## Troubleshooting
- `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
### jC starts but inference is slow or failing
Check that llama-rpc is running on jarvis and llama-server is connected:
```bash
# On jarvis
systemctl status llama-rpc
# On ultron — look for "offloaded N/N layers to GPU" in logs
journalctl -u llama-server -n 50 --no-pager
./venv/bin/python -m pytest tests/ -v
```
### ultron shows no CPU activity during inference
Inference is being handled entirely by jarvis GPU via RPC — this is correct and expected. ultron's CPU is only involved for non-offloaded tensors (a small fraction of the model).
### RAG not returning results
Check Qdrant is up and the collection exists:
```bash
curl http://192.168.50.108:6333/collections/jarvis_rag
```
Verify `points_count` > 0. If zero, the corpus hasn't been seeded yet.
### jC won't start — PIN bootstrap error
Set the PIN via environment before first boot:
```bash
export JARVISCHAT_ADMIN_PIN=XXXX
systemctl restart jarvischat
```
### sqlite3 not found
Use Python instead:
```bash
python3 -c "import sqlite3; print(sqlite3.connect('/opt/jarvischat/jarvischat.db').execute('SELECT * FROM settings').fetchall())"
```
---
## Roadmap
### TODO (Priority Order)
1. **Tool calling** — read_file/write_file with /opt/jarvischat whitelist, tool_calls dispatch loop
2. **git_tool** — Gitea integration for commit/push from jC
3. **Audit logging** — structured audit trail to syslog
4. SearXNG persistence (DONE ✅)
5. search+ prefix for explicit search
6. profile.example.md
7. Conversation search/filter
8. Export to markdown
9. Keyboard shortcuts
10. Retry button
11. Source links in responses
12. Rename conversations
13. Multiple profiles
14. KWIC auto-tags
15. Image input (vision)
16. btop split-screen integration
17. Containerize
18. SearXNG health indicator in UI
19. check_patch_notes tool
20. GitLab mirror of llgit repo
### ROADMAP (Longer Horizon)
**(A) Modular refactor** — Split monolithic app.py into routers/, services/, config.py, db.py, auth.py. Prerequisite for everything below.
**(B) RAG ingest/manage UI** — File upload, URL ingest (fetch + strip HTML via beautifulsoup4/httpx, store URL as source metadata for citation), delete chunks/collections.
**(C) Backend config panel** — Switch between Ollama/llama-server, endpoint URLs, model switching, restart — all from the UI without touching config files.
**(D) Response metrics display** — tokens/sec, TTFT, context size, RAG chunks retrieved + scores — visible in the UI per response.
**(E) Response quality feedback** — thumbs/stars/tags per response → feedback corpus → future RLHF dataset.
**(F) IDE integration** — Continue.dev + VS Code, pointed at jC:8080 (not direct to inference endpoint). All IDE traffic — including pair-programming conversations — goes through jC so sessions are persisted and become RAG-worthy content. jC needs FIM request format handling to support inline autocomplete.
**(G) Conversation history export → RAG ingest** — Bulk ingest existing conversation history into Qdrant.
**(H) Fine-tuning pipeline** — LoRA on Mistral-Nemo from feedback corpus (item E).
**(I) Autonomous RAG** — At conversation end, jC self-evaluates the transcript, extracts significant chunks (solved problems, working commands, architectural decisions), and ingests them into Qdrant automatically with metadata (date, conversation_id, reason). jC decides what it needs to remember. Closes the loop.
**(J) Startup hardware/resource self-assessment** — On boot, jC queries ultron for available RAM, Qdrant consumption, and llama-server footprint. Derives dynamic high-water marks for RAG chunk limits, context window sizing, retrieval limits, and eviction thresholds. Writes a living config file. Replaces magic numbers with runtime-negotiated values.
**(K) RAG corpus management** — Weighted LRU eviction with composite score (recency + frequency + content age) + manual pin flag for load-bearing knowledge. Prevents corpus bloat from degrading retrieval quality. Analogous to memcache eviction policy.
**(L) Dual inference model architecture** — Mistral-Nemo-12B on ultron:8081 (general assistant), Qwen2.5-Coder-14B-Q5_K_M on ultron:8082 (code/pair programming). jC selects endpoint based on active model. Only one model hot at a time given ultron's 16GB RAM constraint.
---
## Primary Cluster Objectives
1. **Generative AI inference** — Local, private, fast enough to be useful
2. **Agentic functionality** — Autonomous RAG self-management is the canonical first example. The system acts, not just responds.
---
## Repository
```
ssh://gitea@llgit.llamachile.tube:1319/gramps/jarvisChat.git
```
> SSH username is `gitea`, not `git`. Port 1319.
---
All 26 tests use `tmp_path` fixtures + monkeypatched `httpx.AsyncClient.stream`. No external services needed.
## License
MIT
## Repository
Gitea: `ssh://gitea@llgit.llamachile.tube:1319/gramps/jarvisChat.git`
+602
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@@ -0,0 +1,602 @@
# 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
---
## TASK 1 — README Cleanup
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`.
No new tests required for this task.
---
## 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 915).** 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 915 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:
```
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
Qdrant collection `jarvischat` currently grows without bound. Implement weighted LRU eviction and pinning.
**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"]`
**Add to `rag.py`:**
```python
async def get_collection_count() -> int
# GET Qdrant /collections/jarvischat, return vectors_count
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)
```
**Call `maybe_evict()` from the ingest path** — both in `routers/upload.py` and `routers/ingest.py` — after each upsert batch completes.
**Add `GET /api/rag/stats`** to a new `routers/rag_admin.py`:
- Returns `{vector_count, max_vectors, pinned_sources, eviction_batch}`
- Admin required
**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.
---
## TASK 9 — Roadmap N1: RabbitMQ Install and Service on Ultron (Infrastructure)
This task runs on ultron (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 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`
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 jarvischat:{password} http://localhost:15672/api/exchanges/jarvischat`
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.
No pytest tests required for this infrastructure task.
---
## 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 912 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 915 with message: `feat: Roadmap N — AMQP cluster nervous system complete`
+6 -3
View File
@@ -5,6 +5,7 @@ Creates the FastAPI app, registers middleware, mounts all routers.
"""
import logging
import logging.handlers
import os
from contextlib import asynccontextmanager
from pathlib import Path
@@ -13,7 +14,7 @@ from fastapi.responses import HTMLResponse, JSONResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from config import VERSION, RATE_WINDOW_SECONDS
from config import VERSION, RATE_WINDOW_SECONDS, UPLOAD_DIR
from db import init_db
from memory import get_memory_count
from security import (
@@ -32,6 +33,7 @@ import routers.skills as skills
import routers.chat as chat
import routers.search_route as search_route
import routers.completions as completions
import routers.upload as upload
# --- Logging ---
log = logging.getLogger("jarvischat")
@@ -47,6 +49,7 @@ templates = Jinja2Templates(directory=str(BASE_DIR / "templates"))
@asynccontextmanager
async def lifespan(app: FastAPI):
log.info(f"JarvisChat {VERSION} starting up")
os.makedirs(UPLOAD_DIR, exist_ok=True)
init_db()
log.info(f"Memory system: {get_memory_count()} memories loaded")
yield
@@ -102,7 +105,7 @@ async def session_auth_middleware(request: Request, call_next):
"/api/auth/heartbeat", "/api/auth/guest",
}
if path.startswith("/api/") and is_state_changing(request.method):
if path.startswith("/api/"):
if not origin_allowed(request):
audit_event("origin_check", "denied", ip=ip, role="none",
details=f"{request.method} {path}", warning=True)
@@ -138,7 +141,7 @@ 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,
chat.router, search_route.router, completions.router, upload.router,
]:
app.include_router(router_module)
+4 -6
View File
@@ -15,10 +15,10 @@ from fastapi.responses import JSONResponse
from config import SESSION_TIMEOUT_SECONDS, MAX_PIN_ATTEMPTS, PIN_LOCKOUT_SECONDS, RATE_WINDOW_SECONDS
from db import get_db, get_setting
from security import (
SESSIONS, PIN_ATTEMPTS, SESSION_LOCK, audit_event, get_client_ip,
is_ip_allowed, check_rate_limit, rate_policy, origin_allowed,
is_state_changing, request_body_limit, read_json_body, hash_pin,
customer_error_envelope, log_incident,
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,
read_json_body, hash_pin, customer_error_envelope, log_incident,
)
log = logging.getLogger("jarvischat")
@@ -146,7 +146,6 @@ async def auth_guest(request: Request):
@router.post("/api/auth/login")
async def auth_login(request: Request):
from security import BODY_LIMIT_DEFAULT_BYTES
body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
pin = str(body.get("pin", ""))
ip = get_client_ip(request)
@@ -183,7 +182,6 @@ async def auth_heartbeat(request: Request):
@router.post("/api/auth/logout")
async def auth_logout(request: Request):
from security import BODY_LIMIT_DEFAULT_BYTES
ip = get_client_ip(request)
sid = request.headers.get("x-session-id", "").strip()
role = "none"
+9 -1
View File
@@ -9,11 +9,12 @@ import logging
log = logging.getLogger("jarvischat")
VERSION = "v1.8.0"
VERSION = "v1.10.0"
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())
# --- Auth ---
SESSION_TIMEOUT_SECONDS = 90
@@ -45,6 +46,13 @@ BODY_LIMIT_DEFAULT_BYTES = 64 * 1024
BODY_LIMIT_CHAT_BYTES = 128 * 1024
BODY_LIMIT_PROFILE_BYTES = 256 * 1024
# --- Upload ---
UPLOAD_DIR = "/tmp/jarvischat_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"}
UPLOAD_CONTEXT_EXPIRY_HOURS = 1
BODY_LIMIT_UPLOAD_BYTES = MAX_UPLOAD_BYTES
MAX_CHAT_MESSAGE_CHARS = 8000
MAX_SEARCH_QUERY_CHARS = 500
MAX_PROFILE_CHARS = 32000
+52
View File
@@ -68,6 +68,43 @@ def format_active_skills_prompt(skills: list) -> str:
return text
def insert_upload_context(db, conversation_id: str, filename: str, content: str, expires_at: str, content_type: str = "text/plain") -> int:
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),
)
return cur.lastrowid
def list_upload_context_by_conversation(db, conversation_id: str):
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,),
).fetchall()
return [dict(r) for r in rows]
def delete_upload_context_by_id(db, context_id: int) -> bool:
cur = db.execute("DELETE FROM upload_context WHERE id = ?", (context_id,))
return cur.rowcount > 0
def get_upload_context(db, context_id: int):
row = db.execute(
"SELECT id, conversation_id, filename, content, content_type, expires_at FROM upload_context WHERE id = ?",
(context_id,),
).fetchone()
if not row:
return None
expires = datetime.fromisoformat(row["expires_at"])
if expires < datetime.now(timezone.utc):
db.execute("DELETE FROM upload_context WHERE id = ?", (context_id,))
db.commit()
return None
return dict(row)
def init_db():
from security import hash_pin
conn = sqlite3.connect(DB_PATH)
@@ -108,6 +145,21 @@ def init_db():
fact, topic, source, created_at UNINDEXED
)
""")
conn.execute("""
CREATE TABLE IF NOT EXISTS upload_context (
id INTEGER PRIMARY KEY AUTOINCREMENT,
conversation_id TEXT,
filename TEXT NOT NULL,
content TEXT NOT NULL,
content_type TEXT DEFAULT 'text/plain',
created_at TEXT NOT NULL,
expires_at TEXT NOT NULL
)
""")
try:
conn.execute("ALTER TABLE upload_context ADD COLUMN content_type TEXT DEFAULT 'text/plain'")
except Exception:
pass
if not conn.execute("SELECT id FROM profile WHERE id = 1").fetchone():
now = datetime.now(timezone.utc).isoformat()
+15 -13
View File
@@ -4,7 +4,7 @@ Last updated: 2026-04-27
Owner: Gramps + Copilot
Scope: issues, bugs, security exposures, and feature enhancements.
Total identified items: 27
Total identified items: 29
## Priority Definitions
- P0: Critical risk or data-loss/security exposure; do first.
@@ -63,20 +63,22 @@ Total identified items: 27
15. Add preflight validation for required model/preset selection and block send with clear user guidance instead of timing out.
### P2 Important Features
16. Skills system: load markdown skill files with YAML frontmatter from skills directory.
17. Skills registry API: list/enable/disable skills and expose active skills to UI.
18. Inject active skill instructions into system prompt with bounded token budget.
19. Tool execution guardrails: allowlist, confirmation mode, and execution logs.
20. Heartbeat scheduler (cron/systemd timer) for daily check-ins.
21. Heartbeat endpoint for generated briefings and anomaly summaries.
22. Model info UI panel (description, updated date, best-use purpose).
23. Default model selection improvements and persistence validation.
24. Hidden model list support (exclude models from dropdown).
25. Model update action from UI (trigger controlled model pull).
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
26. Conversation search/filter and export tooling.
27. Keyboard shortcuts, retry button, and source-link polish.
28. Conversation search/filter and export tooling.
29. Keyboard shortcuts, retry button, and source-link polish.
## Maintenance Rules
- Keep this file as the single source of truth.
+7 -1
View File
@@ -62,7 +62,13 @@ def search_memories(query: str, limit: int = 5) -> list:
if not words:
db.close()
return []
safe_query = " OR ".join(word + "*" for word in words[:10])
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 "
+20 -2
View File
@@ -12,12 +12,30 @@ from config import MAX_SKILL_PROMPT_CHARS
log = logging.getLogger("jarvischat")
QDRANT_URL = "http://192.168.50.108:6333"
EMBED_URL = "http://192.168.50.108:11434"
EMBED_URL = "http://192.168.50.210:11434"
EMBED_MODEL = "mxbai-embed-large"
RAG_COLLECTION = "jarvis_rag"
RAG_SCORE_THRESHOLD = 0.25
def chunk_text(text: str, chunk_size: int = 512, overlap: int = 128) -> 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:
return []
chunks = []
start = 0
while start < len(words):
end = min(start + target_words, len(words))
chunks.append(" ".join(words[start:end]))
if end == len(words):
break
start += target_words - overlap_words
return chunks
async def query_rag(query: str, limit: int = 3) -> list:
try:
async with httpx.AsyncClient() as client:
@@ -65,7 +83,7 @@ async def build_system_prompt(db, extra_prompt: str = "", user_message: str = ""
rag_lines = [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.warning(f"RAG injected {len(rag_lines)} chunks into context")
log.info(f"RAG injected {len(rag_lines)} chunks into context")
except Exception as e:
log.warning(f"RAG injection error: {e}")
-355
View File
@@ -1,355 +0,0 @@
# ⚡ JarvisChat v1.7.8
![screenshot](docs/images/screenshot.png)
**A lightweight Ollama coding companion with persistent memory, web search, and real-time system monitoring.**
Built with FastAPI + SQLite + Jinja2. Runs on Python 3.13. No Docker required.
Developer wiki: [docs/wiki/Home.md](docs/wiki/Home.md)
Core architecture deep-dive: [docs/wiki/Developer-Architecture.md](docs/wiki/Developer-Architecture.md)
## Security Scope Disclaimer
JarvisChat is designed for local and home-lab use (same host or trusted LAN).
JarvisChat may technically work with frontier or commercial AI endpoints, but the author does not recommend or support that usage.
Supported deployments are contained local/home-lab environments.
By default, API access is limited to loopback + private LAN CIDRs. You can override with `JARVISCHAT_ALLOWED_CIDRS` (comma-separated CIDRs) and optionally trust reverse-proxy forwarding with `JARVISCHAT_TRUST_X_FORWARDED_FOR=true`.
If you deploy outside a trusted local subnet, your risk profile changes significantly and the default protections here may be insufficient.
Use at your own risk. No warranty is provided for Internet-exposed deployments.
## What's New in v1.7.x
- **Security hardening suite completed** - request rate limits, payload caps, settings allowlist, safe error envelopes, and LAN CIDR gate controls
- **Customer-safe incident handling** - client-facing errors include support-friendly incident keys while full traces remain in server logs
- **Streaming and regression test expansion** - automated coverage for SSE chat/search paths, memory remember/forget command handling, and auth/guardrail behavior
- **Skills framework (Phase 1)** - built-in local skill registry with per-skill enable controls, API endpoints, and bounded prompt injection
- **Skills WebUX controls** - Settings modal now includes a master skills toggle and per-skill toggles for admin users
## What's New in v1.6.x
- **Guest/admin capability split** - guest chat by default with 4-digit admin PIN for advanced or destructive operations
- **Session + lockout controls** - session lifecycle endpoints, heartbeat, logout/revoke behavior, failed PIN lockout protections, and auth audit events
- **Browser request protections** - strict origin checks for state-changing requests and admin-only write enforcement
- **Unsafe link protection** - outbound search links sanitized to allow only http/https absolute URLs
- **Operational stability fixes** - safer first-boot PIN policy handling and memory-search tokenization fix for punctuation/FTS edge cases
## What's New in v1.5.0
- **Explicit Web Search Button** — 🔍 button next to SEND forces a web search, bypassing model uncertainty detection
- **Orange Search Styling** — Search results, WEB badge, and search button share consistent orange color scheme
- **Expanded Refusal Patterns** — Added "As an AI model", "based on my training data", "I don't have the capability"
- **Code cleanup** — Removed unused `JSONResponse` import and dead `raw_results_md` variable
- **Bug fixes** — Replaced bare `except` clauses with `except Exception`; corrected `add_memory()` return type to `int | None`; updated `TemplateResponse` call to Starlette's current API signature
## What's New in v1.4.0
- **FTS5 Memory System**: Say "remember that..." to store facts — they're automatically retrieved by relevance and injected into context
- **Forget Command**: Say "forget about..." to remove memories
- **Memory Toggle**: Enable/disable memory injection from topbar or settings
- **Multi-file Structure**: Backend and frontend separated for easier maintenance
## Features
- **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** — 🔍 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 Ollama models on the fly
## Current WiP (Prioritized)
Canonical backlog: [docs/wiki/current-wip.md](docs/wiki/current-wip.md)
Scope boundary: local-first (same-host Ollama), optional RFC1918 LAN endpoints, no public Internet AI endpoints by default.
Total identified items: 27
Top 10 (brief):
1. P0 [DONE]: Add auth for write/admin endpoints
2. P0 [DONE]: Add CSRF/origin protection for state-changing requests
3. P0 [DONE]: Block unsafe URL schemes in rendered links
4. P0 [DONE]: Add rate limiting and request size limits
5. P1 [DONE]: Restrict `/api/settings` updates to allowlisted keys
6. P1: Add pagination + hard caps for list APIs
7. P1 [DONE]: Replace raw exception leakage with safe client errors
8. P1 [DONE]: Add automated tests for streaming/search/memory paths
9. P2 [DONE]: Implement MCP-style skills/tool-call framework
10. P2: Implement heartbeat/check-in scheduler + summary endpoint
Item 1 executive summary: keep guest mode for conversational chat, require 4-digit admin PIN for advanced/destructive actions, and enforce local/LAN-only backend policy by default.
Implementation status: complete (guest session by default + admin unlock + admin-only write enforcement + origin checks + safe-link sanitization + audit logging + rate/payload guardrails + capability tests).
## TODO
1. ~~Verify SearXNG and Docker services persist across reboots~~
2. Conversation search/filter by keyword
3. Export conversation to markdown/text
4. Keyboard shortcuts (Ctrl+N new chat, Ctrl+Enter send)
5. Retry button on assistant messages
6. Source links — clickable links when search used
7. Allow conversation renaming
8. Multiple profiles — coding/sysadmin/general
9. Auto-generate conversation tags (client-side KWIC, top 5, filterable badges)
10. Image input support — pull vision model, file input/drag-drop, base64 encode, pass `images` array to Ollama `/api/chat`
11. Split-screen option for btop display
12. Skills as markdown files — `/opt/jarvischat/skills/`, YAML frontmatter + instructions, injected into context for tool calls
13. Heartbeats / proactive check-ins — cron + endpoint for daily briefings, HA anomaly alerts
14. Model info button — (i) icon next to Model dropdown, shows div with model description, last updated date, best-use purpose
15. Set default model — toggle any model as the default selection
16. Hide/remove model from list — exclude models from dropdown
17. Update model function — trigger `ollama pull` for selected model from UI
18. Add mouseover tooltip to SEND button
19. Add preflight validation for required model/preset selection and show a clear warning before send to prevent avoidable timeout loops
## File Structure
```
/opt/jarvischat/
├── app.py # FastAPI backend
├── jarvischat.db # SQLite database (auto-created)
├── static/
│ └── logo.png # Logo image (optional)
└── templates/
└── index.html # Frontend
```
## Requirements
- Python 3.11+ (tested on 3.13)
- Ollama running locally or on network
- SearXNG (optional, for web search)
## Installation
### Fresh Install
```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
# Set admin PIN before first startup (4 digits)
export JARVISCHAT_ADMIN_PIN=4827
# Create subdirectories
mkdir -p templates static
# Copy files
# (copy app.py to /opt/jarvischat/)
# (copy index.html to /opt/jarvischat/templates/)
# (copy logo.png to /opt/jarvischat/static/ — optional)
```
WARNING: Do not use `1234` as your admin PIN unless you accept weak local security.
NOTE: First boot now requires `JARVISCHAT_ADMIN_PIN` unless you explicitly opt into insecure fallback with `JARVISCHAT_ALLOW_DEFAULT_PIN=true`.
### Upgrading from v1.4.x
```bash
cd /opt/jarvischat
# Backup
cp app.py app.py.bak
cp templates/index.html templates/index.html.bak
# Copy new files
# (copy app.py, replacing old version)
# (copy index.html to templates/)
# Restart
sudo systemctl restart jarvischat
```
## Systemd Service
Create `/etc/systemd/system/jarvischat.service`:
```ini
[Unit]
Description=JarvisChat - Local Ollama Web Interface
After=network.target
[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
[Install]
WantedBy=multi-user.target
```
```bash
sudo systemctl daemon-reload
sudo systemctl enable jarvischat
sudo systemctl start jarvischat
```
## Memory Commands
In chat, natural language triggers memory operations:
| 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 |
Memories are automatically searched based on your message content and injected into the system prompt when relevant.
### Memory Topics
Memories are auto-categorized:
- `preference` — likes, dislikes, choices
- `project` — active work, repos, tasks
- `infrastructure` — servers, services, configs
- `personal` — name, location, background
- `general` — everything else
## API Endpoints
### Memory
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/memories` | List all memories |
| POST | `/api/memories` | Add memory `{"fact": "...", "topic": "general"}` |
| DELETE | `/api/memories/{rowid}` | Delete memory by ID |
| GET | `/api/memories/search?q=term` | Search memories |
| GET | `/api/memories/stats` | Get counts by topic |
### Chat & Models
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/models` | List available Ollama models |
| POST | `/api/chat` | Send message (streaming SSE) |
| POST | `/api/search` | Explicit web search (streaming SSE) |
| POST | `/api/show` | Get model info (context size) |
| GET | `/api/ps` | Get running models |
### Settings & Profile
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/profile` | Get profile content |
| PUT | `/api/profile` | Update profile |
| GET | `/api/profile/default` | Get default profile |
| GET | `/api/settings` | Get settings |
| PUT | `/api/settings` | Update settings |
### Conversations
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/conversations` | List conversations |
| GET | `/api/conversations/{id}` | Get conversation with messages |
| 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 |
### System
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/stats` | CPU, RAM, GPU, VRAM stats |
| GET | `/api/search/status` | SearXNG availability |
## 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)
- `default_model` — Default Ollama model
- `searxng_url` — SearXNG instance URL (default: `http://localhost:8888`)
## Testing Memory
```bash
# Add a memory via API
curl -X POST http://jarvis:8080/api/memories \
-H "Content-Type: application/json" \
-d '{"fact": "User prefers native installs over Docker", "topic": "preference"}'
# Search memories
curl "http://jarvis:8080/api/memories/search?q=docker"
# List all memories
curl http://jarvis:8080/api/memories
# Get stats
curl http://jarvis:8080/api/memories/stats
```
Or in chat:
1. Say "remember that I hate YAML"
2. Later ask "what markup languages should I avoid?"
3. JarvisChat will inject the YAML preference into context
## Troubleshooting
### Service won't start
Check logs:
```bash
journalctl -u jarvischat -n 50 --no-pager
```
Common issues:
- Missing `jinja2`: `./venv/bin/pip install jinja2`
- Missing `templates/` directory
- Wrong permissions on `/opt/jarvischat`
### Memory not working
1. Check memory is enabled (🧠 MEM ON in topbar)
2. Verify memories exist: `curl http://jarvis:8080/api/memories`
3. Check FTS5 table: `sqlite3 jarvischat.db "SELECT * FROM memories_fts;"`
### Web search not working
1. Verify SearXNG is running: `curl http://localhost:8888/search?q=test&format=json`
2. Check search status: `curl http://jarvis:8080/api/search/status`
3. Ensure JSON format is enabled in SearXNG settings
## License
MIT
## Repository
Gitea: `ssh://gitea@llgit.llamachile.tube:1319/gramps/jarvisChat.git`
+1
View File
@@ -1,3 +1,4 @@
fastapi>=0.115.0
uvicorn[standard]>=0.32.0
httpx>=0.27.0
pypdf>=5.0.0
+33 -12
View File
@@ -9,7 +9,7 @@ from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import StreamingResponse
from config import DEFAULT_MODEL, LLAMA_SERVER_BASE
from db import get_db
from db import get_db, get_upload_context
from memory import process_remember_command
from rag import build_system_prompt
from search import (calculate_perplexity, is_uncertain, is_refusal,
@@ -26,7 +26,7 @@ def parse_llama_stream_chunk(line: str) -> tuple:
if line.startswith("data: "):
line = line[6:]
if line.strip() == "[DONE]":
return None, True, {}
return None, True, {}, []
try:
chunk = json.loads(line)
choices = chunk.get("choices", [])
@@ -35,10 +35,17 @@ def parse_llama_stream_chunk(line: str) -> tuple:
token = delta.get("content")
finish = choices[0].get("finish_reason")
stats = {}
logprobs_list = []
logprobs_info = choices[0].get("logprobs")
if logprobs_info:
content_logprobs = logprobs_info.get("content", [])
for entry in content_logprobs:
if "logprob" in entry:
logprobs_list.append({"logprob": entry["logprob"]})
if finish == "stop":
usage = chunk.get("usage", {})
stats["tokens_per_sec"] = usage.get("tokens_per_second", 0.0)
return token, finish == "stop", stats
return token, finish == "stop", stats, logprobs_list
if "message" in chunk and "content" in chunk["message"]:
token = chunk["message"]["content"]
done = chunk.get("done", False)
@@ -47,10 +54,10 @@ 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
return token, done, stats
return token, done, stats, []
except json.JSONDecodeError:
pass
return None, False, {}
return None, False, {}, []
@router.post("/api/chat")
@@ -62,6 +69,7 @@ async def chat(request: Request):
raise HTTPException(status_code=413, detail="Chat message is too long")
model = body.get("model", DEFAULT_MODEL)
preset_prompt = body.get("system_prompt", "")
upload_context_id = body.get("upload_context_id")
if not user_message:
raise HTTPException(status_code=400, detail="Empty message")
@@ -71,6 +79,14 @@ async def chat(request: Request):
settings = {row["key"]: row["value"] for row in db.execute("SELECT key, value FROM settings").fetchall()}
search_enabled = settings.get("search_enabled", "true") == "true"
upload_doc = None
if upload_context_id:
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)
if not conv_id:
@@ -88,7 +104,10 @@ async def chat(request: Request):
history_rows = db.execute(
"SELECT role, content FROM messages WHERE conversation_id = ? ORDER BY id ASC", (conv_id,)
).fetchall()
system_prompt = await build_system_prompt(db, preset_prompt, user_message)
extra_prompt = preset_prompt
if upload_doc:
extra_prompt = (extra_prompt + "\n\n" + upload_doc) if extra_prompt else upload_doc
system_prompt = await build_system_prompt(db, extra_prompt, user_message)
db.close()
messages = []
@@ -97,7 +116,7 @@ async def chat(request: Request):
for row in history_rows:
messages.append({"role": row["role"], "content": row["content"]})
ollama_payload = {"model": model, "messages": messages, "stream": True}
upstream_payload = {"model": model, "messages": messages, "stream": True, "logprobs": True}
async def stream_response():
full_response = []
@@ -111,12 +130,14 @@ async def chat(request: Request):
try:
async with client.stream(
"POST", f"{LLAMA_SERVER_BASE}/v1/chat/completions",
json=ollama_payload,
json=upstream_payload,
timeout=httpx.Timeout(300.0, connect=10.0),
) as resp:
async for line in resp.aiter_lines():
if line.strip():
token, done, stats = parse_llama_stream_chunk(line)
token, done, stats, chunk_logprobs = parse_llama_stream_chunk(line)
if chunk_logprobs:
all_logprobs.extend(chunk_logprobs)
if token:
full_response.append(token)
yield f"data: {json.dumps({'token': token, 'conversation_id': conv_id})}\n\n"
@@ -153,7 +174,7 @@ async def chat(request: Request):
) as resp2:
async for line in resp2.aiter_lines():
if line.strip():
token2, done2, _ = parse_llama_stream_chunk(line)
token2, done2, _, _ = parse_llama_stream_chunk(line)
if token2:
augmented_response.append(token2)
if done2:
@@ -194,9 +215,9 @@ async def chat(request: Request):
except httpx.RemoteProtocolError:
pass
except httpx.ConnectError:
yield f"data: {json.dumps({'error': 'Cannot connect to Ollama. Is it running?'})}\n\n"
yield f"data: {json.dumps({'error': 'Cannot connect to inference server. Is it running?'})}\n\n"
except Exception as e:
incident_key = log_incident("chat_stream", message="Ollama stream failure during chat response",
incident_key = log_incident("chat_stream", message="Inference stream failure during chat response",
request=request, exc=e)
yield f"data: {json.dumps({'error': 'Chat response generation failed before completion. Use the incident key for support lookup.', 'error_key': incident_key})}\n\n"
+2 -2
View File
@@ -178,7 +178,7 @@ async def _stream_chat(payload: dict, model: str, conv_id: str, request: Request
async for line in resp.aiter_lines():
if not line.strip():
continue
token, done, _ = parse_llama_stream_chunk(line)
token, done, _, _ = parse_llama_stream_chunk(line)
if token:
full_response.append(token)
yield _build_openai_chunk(token, model, conv_id)
@@ -222,7 +222,7 @@ async def _blocking_chat(payload: dict, model: str, conv_id: str, request: Reque
async for line in resp.aiter_lines():
if not line.strip():
continue
token, done, _ = parse_llama_stream_chunk(line)
token, done, _, _ = parse_llama_stream_chunk(line)
if token:
full_response.append(token)
if done:
+9 -1
View File
@@ -15,8 +15,16 @@ router = APIRouter()
async def list_conversations():
db = get_db()
rows = db.execute("SELECT * FROM conversations ORDER BY updated_at DESC").fetchall()
result = []
for r in rows:
c = dict(r)
attach_count = db.execute(
"SELECT COUNT(*) FROM upload_context WHERE conversation_id = ?", (c["id"],)
).fetchone()[0]
c["attachment_count"] = attach_count
result.append(c)
db.close()
return [dict(r) for r in rows]
return result
@router.post("/api/conversations")
+7 -8
View File
@@ -8,7 +8,7 @@ import httpx
import psutil
from fastapi import APIRouter, HTTPException, Request
from config import OLLAMA_BASE
from config import LLAMA_SERVER_BASE
from gpu import get_gpu_stats
from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
@@ -20,34 +20,33 @@ router = APIRouter()
async def list_models():
async with httpx.AsyncClient() as client:
try:
resp = await client.get(f"{OLLAMA_BASE}/v1/models", timeout=10)
resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models", timeout=10)
data = resp.json()
models = [{"name": m["id"], "model": m["id"]} for m in data.get("data", [])]
return {"models": models}
except httpx.ConnectError:
raise HTTPException(status_code=502, detail="Cannot connect to llama-server.")
raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
@router.get("/api/ps")
async def running_models():
async with httpx.AsyncClient() as client:
try:
resp = await client.get(f"{OLLAMA_BASE}/api/ps", timeout=10)
resp = await client.get(f"{LLAMA_SERVER_BASE}/v1/models", timeout=10)
return resp.json()
except httpx.ConnectError:
raise HTTPException(status_code=502, detail="Cannot connect to Ollama.")
raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
@router.post("/api/show")
async def show_model(request: Request):
from security import BODY_LIMIT_DEFAULT_BYTES
body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
async with httpx.AsyncClient() as client:
try:
resp = await client.post(f"{OLLAMA_BASE}/api/show", json=body, timeout=10)
resp = await client.post(f"{LLAMA_SERVER_BASE}/api/show", json=body, timeout=10)
return resp.json()
except httpx.ConnectError:
raise HTTPException(status_code=502, detail="Cannot connect to Ollama.")
raise HTTPException(status_code=502, detail="Cannot connect to inference server.")
@router.get("/api/stats")
+3 -4
View File
@@ -35,14 +35,14 @@ async def explicit_search(request: Request):
if not conv_id:
conv_id = str(uuid.uuid4())
title = f"🔍 {query[:70]}..." if len(query) > 70 else f"🔍 {query}"
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))
else:
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", f"🔍 {query}", now))
(conv_id, "user", query, now))
db.commit()
db.close()
@@ -80,7 +80,7 @@ async def explicit_search(request: Request):
) as resp:
async for line in resp.aiter_lines():
if line.strip():
token, done, _ = parse_llama_stream_chunk(line)
token, done, _, _ = parse_llama_stream_chunk(line)
if token:
full_response.append(token)
yield f"data: {json.dumps({'token': token, 'conversation_id': conv_id})}\n\n"
@@ -102,7 +102,6 @@ async def explicit_search(request: Request):
db2.commit()
db2.close()
yield f"data: {json.dumps({'raw_results': results, 'conversation_id': conv_id})}\n\n"
yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True})}\n\n"
return StreamingResponse(stream_search(), media_type="text/event-stream")
+168
View File
@@ -0,0 +1,168 @@
"""JarvisChat routers - /api/upload file/document attachment endpoint."""
import json
import logging
import os
from datetime import datetime, timezone, timedelta
import httpx
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 db import get_db, insert_upload_context, list_upload_context_by_conversation, delete_upload_context_by_id
from rag import chunk_text, QDRANT_URL, EMBED_URL, EMBED_MODEL, RAG_COLLECTION
log = logging.getLogger("jarvischat")
router = APIRouter()
def _point_id(filename: str, chunk_idx: int) -> str:
return f"upload-{filename}-{chunk_idx}"
@router.post("/api/upload")
async def upload_file(
request: Request,
file: UploadFile = File(...),
mode: str = Form("both"),
conversation_id: str = Form(""),
):
if mode not in ("context", "ingest", "both"):
raise HTTPException(status_code=422, detail="mode must be context, ingest, or both")
if file.size and file.size > MAX_UPLOAD_BYTES:
return JSONResponse(status_code=413, content={"detail": f"File exceeds {MAX_UPLOAD_BYTES} byte limit"})
content_type = file.content_type or "application/octet-stream"
if content_type not in SUPPORTED_UPLOAD_TYPES:
return JSONResponse(status_code=415, content={"detail": f"Unsupported file type: {content_type}"})
raw_bytes = await file.read()
if not raw_bytes:
raise HTTPException(status_code=422, detail="Empty file")
if content_type == "application/pdf":
try:
from pypdf import PdfReader
import io
reader = PdfReader(io.BytesIO(raw_bytes))
extracted = "\n".join(page.extract_text() or "" for page in reader.pages)
except Exception as e:
log.warning(f"PDF extraction error: {e}")
raise HTTPException(status_code=422, detail="Failed to extract text from PDF")
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"):
os.makedirs(UPLOAD_DIR, exist_ok=True)
chunks = chunk_text(extracted)
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"Embedding failed for chunk {i}: {embed_resp.status_code}")
continue
vector = embed_resp.json()["embedding"]
pid = _point_id(file.filename or "unnamed", i)
upsert_resp = await client.put(
f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
json={
"points": [{
"id": pid,
"vector": vector,
"payload": {"text": chunk, "source": file.filename, "upload_date": datetime.now(timezone.utc).isoformat(), "type": "upload"},
}]
},
timeout=30.0,
)
if upsert_resp.status_code in (200, 201):
ingested += 1
else:
log.warning(f"Qdrant upsert failed for chunk {i}: {upsert_resp.status_code}")
result["chunks_ingested"] = ingested
if mode in ("context", "both"):
expires = (datetime.now(timezone.utc) + timedelta(hours=UPLOAD_CONTEXT_EXPIRY_HOURS)).isoformat()
db = get_db()
try:
cid = insert_upload_context(db, conversation_id or "", file.filename or "unnamed", extracted, expires, content_type)
db.commit()
result["context_id"] = cid
finally:
db.close()
result["message"] = f"Uploaded {file.filename}"
return result
@router.patch("/api/upload/{context_id}/link")
async def link_upload_to_conversation(context_id: int, request: Request):
body = await request.json()
conv_id = body.get("conversation_id", "").strip()
if not conv_id:
raise HTTPException(status_code=422, detail="conversation_id required")
db = get_db()
try:
row = db.execute("SELECT id FROM upload_context WHERE id = ?", (context_id,)).fetchone()
if not row:
raise HTTPException(status_code=404, detail="Upload context not found")
db.execute("UPDATE upload_context SET conversation_id = ? WHERE id = ?", (conv_id, context_id))
db.commit()
return {"status": "ok"}
finally:
db.close()
@router.get("/api/upload/by-conversation/{conv_id}")
async def get_upload_by_conversation(conv_id: str):
db = get_db()
try:
items = list_upload_context_by_conversation(db, conv_id)
return items
finally:
db.close()
@router.delete("/api/upload/{context_id}")
async def delete_upload(context_id: int):
db = get_db()
try:
row = db.execute("SELECT filename FROM upload_context WHERE id = ?", (context_id,)).fetchone()
if not row:
raise HTTPException(status_code=404, detail="Attachment not found")
filename = row["filename"]
if not filename:
filename = "unnamed"
delete_upload_context_by_id(db, context_id)
db.commit()
finally:
db.close()
try:
async with httpx.AsyncClient() as client:
scroll_resp = await client.post(
f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
json={"filter": {"must": [{"key": "source", "match": {"value": filename}}]}, "limit": 100, "with_payload": False},
timeout=10.0,
)
if scroll_resp.status_code == 200:
points = scroll_resp.json().get("result", {}).get("points", [])
point_ids = [p["id"] for p in points]
if point_ids:
await client.post(
f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
json={"points": point_ids},
timeout=10.0,
)
log.info(f"Deleted {len(point_ids)} Qdrant points for source '{filename}'")
except Exception as e:
log.warning(f"Qdrant cleanup for '{filename}' failed: {e}")
return {"status": "ok", "filename": filename}
+7 -10
View File
@@ -80,16 +80,13 @@ def format_direct_answer(question: str, results: list) -> str:
def extract_search_query(user_message: str) -> str:
query = user_message.strip()
if re.search(r"temperature|weather", query, re.IGNORECASE):
query = re.sub(r"^what('?s| is) the ", "", query, flags=re.IGNORECASE) + " right now degrees"
if re.search(r"price|spot price", query, re.IGNORECASE):
query = re.sub(r"^(what('?s| is)|can you tell me) the ", "", query, flags=re.IGNORECASE) + " today USD"
query = re.sub(
r"^(what|who|where|when|why|how|is|are|can|could|would|should|do|does|did)\s+",
"", query, flags=re.IGNORECASE,
)
query = re.sub(r"[?!.]+$", "", query)
return query[:100].strip() or user_message[:100]
weather_lead = re.match(r"^(?:what('?s| is) the\s+)?(?:weather|temperature|forecast)\s+(?:in\s+|for\s+)?(.+)", query, re.IGNORECASE)
if weather_lead:
return (weather_lead.group(2) + " weather").strip()[:100]
price_lead = re.match(r"^(?:what('?s| is| are)\s+)?(?:the\s+)?(?:price|spot price)\s+(?:of\s+|for\s+)?(.+)", query, re.IGNORECASE)
if price_lead:
return (price_lead.group(2) + " price today USD").strip()[:100]
return query[:100]
async def query_searxng(query: str, max_results: int = 5) -> list:
+4 -2
View File
@@ -22,7 +22,7 @@ from fastapi import HTTPException, Request
from config import (
ALLOWED_NETWORKS, TRUST_X_FORWARDED_FOR, TRUSTED_ORIGINS,
BODY_LIMIT_DEFAULT_BYTES, BODY_LIMIT_CHAT_BYTES, BODY_LIMIT_PROFILE_BYTES,
BODY_LIMIT_DEFAULT_BYTES, BODY_LIMIT_CHAT_BYTES, BODY_LIMIT_PROFILE_BYTES, BODY_LIMIT_UPLOAD_BYTES,
RATE_WINDOW_SECONDS, RL_LOGIN_PER_WINDOW, RL_CHAT_PER_WINDOW,
RL_SEARCH_PER_WINDOW, RL_STATS_PER_WINDOW, RL_WRITE_PER_WINDOW,
RL_DEFAULT_PER_WINDOW, VERSION,
@@ -114,6 +114,8 @@ def request_body_limit(path: str) -> int:
return BODY_LIMIT_CHAT_BYTES
if path == "/api/profile":
return BODY_LIMIT_PROFILE_BYTES
if path == "/api/upload":
return BODY_LIMIT_UPLOAD_BYTES
return BODY_LIMIT_DEFAULT_BYTES
@@ -156,7 +158,7 @@ def origin_allowed(request: Request) -> bool:
parsed = urlparse(referer)
ref_origin = f"{parsed.scheme}://{parsed.netloc}".rstrip("/")
return ref_origin == expected_origin or ref_origin in TRUSTED_ORIGINS
return True
return False
def is_state_changing(method: str) -> bool:
+248 -27
View File
@@ -4,6 +4,9 @@
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>JarvisChat</title>
<meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
<meta http-equiv="Pragma" content="no-cache">
<meta http-equiv="Expires" content="0">
<link rel="preconnect" href="https://fonts.googleapis.com">
<link href="https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;600&family=IBM+Plex+Sans:wght@300;400;500;600&display=swap" rel="stylesheet">
<style>
@@ -47,13 +50,12 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
.delete-all-btn { padding: 10px 12px; background: transparent; border: 1px solid var(--danger); border-radius: var(--radius); color: var(--danger); font-size: 14px; cursor: pointer; transition: all 0.2s; }
.delete-all-btn:hover { background: var(--danger); color: #fff; }
.conversation-list { flex: 1; overflow-y: auto; padding: 8px; }
.conv-item { padding: 10px 12px; border-radius: var(--radius); cursor: pointer; margin-bottom: 2px; display: flex; justify-content: space-between; align-items: center; transition: background 0.15s; font-size: 13px; color: var(--text-secondary); }
.conv-item { padding: 10px 12px; border-radius: var(--radius); cursor: pointer; margin-bottom: 2px; display: flex; align-items: center; gap: 8px; transition: background 0.15s; font-size: 13px; color: var(--text-secondary); }
.conv-item:hover { background: var(--bg-hover); color: var(--text-primary); }
.conv-item.active { background: var(--bg-tertiary); color: var(--text-primary); }
.conv-item .conv-title { overflow: hidden; text-overflow: ellipsis; white-space: nowrap; flex: 1; }
.conv-item .conv-delete { opacity: 0; color: var(--danger); cursor: pointer; padding: 2px 6px; font-size: 16px; }
.conv-item:hover .conv-delete { opacity: 0.7; }
.conv-item .conv-delete:hover { opacity: 1; }
.conv-item .conv-trash { color: var(--text-muted); cursor: pointer; padding: 2px 2px; font-size: 15px; flex-shrink: 0; transition: color 0.15s; }
.conv-item .conv-trash:hover { opacity: 1; color: var(--danger); }
.conv-item .conv-title { overflow: hidden; text-overflow: ellipsis; white-space: nowrap; flex: 1; min-width: 0; }
.sidebar-footer { padding: 12px 16px; border-top: 1px solid var(--border); font-size: 11px; color: var(--text-muted); font-family: var(--font-mono); }
.sidebar-footer .status-row { display: flex; align-items: center; gap: 8px; margin-bottom: 4px; }
.stats-panel { margin-top: 10px; padding-top: 10px; border-top: 1px solid var(--border); }
@@ -155,6 +157,12 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
.perplexity-badge.low { background:rgba(46,204,113,0.15); border:1px solid rgba(46,204,113,0.3); color:var(--success); }
.perplexity-badge.medium { background:rgba(243,156,18,0.15); border:1px solid rgba(243,156,18,0.3); color:var(--warning); }
.perplexity-badge.high { background:rgba(231,76,60,0.15); border:1px solid rgba(231,76,60,0.3); color:var(--danger); }
.ttr-badge { display:inline-block; padding:2px 8px; border-radius:10px; font-family:var(--font-mono); font-size:10px; margin-left:8px; }
.ttr-badge.low { background:rgba(46,204,113,0.15); border:1px solid rgba(46,204,113,0.3); color:var(--success); }
.ttr-badge.medium { background:rgba(243,156,18,0.15); border:1px solid rgba(243,156,18,0.3); color:var(--warning); }
.ttr-badge.high { background:rgba(231,76,60,0.15); border:1px solid rgba(231,76,60,0.3); color:var(--danger); }
.ttr-badge.search { background:rgba(230,126,34,0.15); border:1px solid rgba(230,126,34,0.3); color:#e67e22; }
.tps-badge { display:inline-block; padding:2px 8px; border-radius:10px; font-family:var(--font-mono); font-size:10px; margin-left:8px; background:rgba(72,181,224,0.15); border:1px solid rgba(72,181,224,0.3); color:var(--accent); }
.input-area { padding:16px 20px; border-top:1px solid var(--border); background:var(--bg-secondary); }
@@ -172,6 +180,39 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
.search-btn { padding:12px 14px; background:var(--warning); border:none; border-radius:var(--radius); color:#fff; font-size:16px; cursor:pointer; transition:background 0.2s; }
.search-btn:hover { background:#e67e22; }
.search-btn:disabled { background:var(--text-muted); cursor:not-allowed; }
.paperclip-btn { padding:12px 12px; background:var(--bg-tertiary); border:1px solid var(--border); border-radius:var(--radius); color:var(--text-secondary); font-size:18px; cursor:pointer; transition:all 0.2s; line-height:1; }
.paperclip-btn:hover { background:var(--bg-hover); color:var(--accent); border-color:var(--accent-dim); }
.file-preview { max-width:900px; margin:0 auto 8px; display:none; align-items:center; gap:10px; background:var(--bg-tertiary); border:1px solid var(--border); border-radius:var(--radius); padding:8px 12px; }
.file-preview.visible { display:flex; }
.file-preview-thumb { width:48px; height:48px; object-fit:cover; border-radius:4px; border:1px solid var(--border); }
.file-preview-icon { font-size:28px; flex-shrink:0; color:var(--text-muted); }
.file-preview-info { flex:1; min-width:0; }
.file-preview-name { font-size:13px; color:var(--text-primary); overflow:hidden; text-overflow:ellipsis; white-space:nowrap; }
.file-preview-size { font-size:11px; color:var(--text-muted); }
.file-preview-clear { background:none; border:none; color:var(--text-muted); font-size:18px; cursor:pointer; padding:4px; line-height:1; transition:color 0.15s; }
.file-preview-clear:hover { color:var(--danger); }
.file-preview-notice { font-size:11px; color:var(--warning); }
.conv-attach { color:var(--text-muted); cursor:pointer; padding:2px 2px; font-size:14px; flex-shrink:0; transition:color 0.15s; margin-left:2px; }
.conv-attach:hover { color:var(--accent); }
.conv-attach.has-attachments { color:var(--accent-dim); }
.gallery-overlay { position:fixed; top:0; left:0; width:100%; height:100%; background:rgba(0,0,0,0.85); z-index:10000; display:none; justify-content:center; align-items:center; }
.gallery-overlay.visible { display:flex; }
.gallery-panel { background:var(--bg-secondary); border:1px solid var(--border); border-radius:var(--radius); width:90%; max-width:700px; max-height:85vh; display:flex; flex-direction:column; }
.gallery-header { display:flex; align-items:center; justify-content:space-between; padding:16px 20px; border-bottom:1px solid var(--border); }
.gallery-header h3 { font-size:16px; color:var(--text-primary); font-family:var(--font-mono); }
.gallery-close { background:none; border:none; color:var(--text-muted); font-size:24px; cursor:pointer; padding:4px; line-height:1; transition:color 0.15s; }
.gallery-close:hover { color:var(--text-primary); }
.gallery-body { flex:1; overflow-y:auto; padding:12px 20px; }
.gallery-empty { text-align:center; padding:40px 20px; color:var(--text-muted); font-size:14px; }
.gallery-item { display:flex; align-items:center; gap:12px; padding:12px; border-radius:var(--radius); margin-bottom:8px; background:var(--bg-tertiary); transition:background 0.15s; }
.gallery-item:hover { background:var(--bg-hover); }
.gallery-item-thumb { width:60px; height:60px; object-fit:cover; border-radius:4px; border:1px solid var(--border); flex-shrink:0; }
.gallery-item-icon { font-size:32px; flex-shrink:0; color:var(--text-muted); text-align:center; width:60px; }
.gallery-item-info { flex:1; min-width:0; }
.gallery-item-name { font-size:14px; color:var(--text-primary); overflow:hidden; text-overflow:ellipsis; white-space:nowrap; }
.gallery-item-meta { font-size:11px; color:var(--text-muted); margin-top:2px; }
.gallery-item-delete { background:none; border:1px solid var(--danger); border-radius:var(--radius); color:var(--danger); font-size:12px; cursor:pointer; padding:6px 12px; transition:all 0.15s; flex-shrink:0; }
.gallery-item-delete:hover { background:var(--danger); color:#fff; }
.token-thermometer { display:flex; flex-direction:column; align-items:center; gap:4px; }
.thermometer-bar { width:12px; height:80px; background:var(--bg-tertiary); border:1px solid var(--border); border-radius:6px; position:relative; overflow:hidden; }
@@ -319,10 +360,7 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
<main class="main">
<div class="topbar">
<div class="topbar-left">
<span class="topbar-label">Model</span>
<select id="modelSelect"></select>
</div>
<div class="topbar-left"></div>
<div class="topbar-right">
<button class="memory-badge on" id="memoryBadge" onclick="toggleMemory()" title="Toggle memory injection">🧠 MEM ON</button>
<button class="search-badge on" id="searchBadge" onclick="toggleSearch()" title="Toggle auto web search">🔍 SEARCH ON</button>
@@ -330,6 +368,15 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
<button class="logout-btn" id="authActionBtn" onclick="handleAuthAction()" title="Unlock admin">ADMIN</button>
</div>
</div>
<div class="gallery-overlay" id="galleryOverlay" onclick="closeGallery(event)">
<div class="gallery-panel" onclick="event.stopPropagation()">
<div class="gallery-header">
<h3>📎 Attachments</h3>
<button class="gallery-close" onclick="closeGallery()"></button>
</div>
<div class="gallery-body" id="galleryBody"></div>
</div>
</div>
<div class="chat-container" id="chatContainer">
<div class="welcome-screen" id="welcomeScreen">
<div class="logo"></div>
@@ -341,7 +388,19 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
<span class="preset-label">PRESET</span>
<select id="presetSelect"><option value="">None (profile only)</option></select>
</div>
<div class="file-preview" id="filePreview">
<img class="file-preview-thumb" id="filePreviewThumb" src="" alt="" style="display:none">
<span class="file-preview-icon" id="filePreviewIcon">📄</span>
<div class="file-preview-info">
<div class="file-preview-name" id="filePreviewName"></div>
<div class="file-preview-size" id="filePreviewSize"></div>
<div class="file-preview-notice" id="filePreviewNotice"></div>
</div>
<button class="file-preview-clear" onclick="clearFileSelection()" title="Remove file"></button>
</div>
<div class="input-wrapper">
<input type="file" id="fileInput" style="display:none" accept=".txt,.md,.pdf,.json,.py,.html,.png,.jpg,.jpeg,.gif,.svg,.webp" onchange="onFileSelected(event)">
<button class="paperclip-btn" id="paperclipBtn" onclick="document.getElementById('fileInput').click()" title="Attach file">📎</button>
<textarea id="userInput" placeholder="Type a message... (Shift+Enter for new line)" rows="1" autofocus></textarea>
<div class="token-thermometer" title="Context usage">
<div class="thermometer-bar"><div class="thermometer-fill" id="thermometerFill" style="height:0%"></div></div>
@@ -359,12 +418,14 @@ body { font-family: var(--font-body); background: var(--bg-primary); color: var(
let currentConvId = null;
let isStreaming = false;
let abortController = null;
let selectedFile = null;
let profileEnabled = true;
let searchEnabled = true;
let memoryEnabled = true;
let skillsEnabled = true;
let presets = [];
let skillsRegistry = [];
let currentModel = '';
let modelContextSize = 8192;
let cachedProfile = '';
let conversationHistory = [];
@@ -665,21 +726,20 @@ async function loadModels() {
try {
const resp = await authFetch('/api/models');
const data = await resp.json();
const select = document.getElementById('modelSelect');
const settingSelect = document.getElementById('defaultModelSetting');
select.innerHTML = '';
settingSelect.innerHTML = '';
(data.models || []).forEach(m => {
const gb = (m.size / (1024*1024*1024)).toFixed(1);
select.add(new Option(m.name + ' (' + gb + 'GB)', m.name));
settingSelect.add(new Option(m.name, m.name));
});
select.addEventListener('change', fetchModelContextSize);
if (!currentModel && data.models?.length) {
currentModel = data.models[0].name;
await fetchModelContextSize();
}
} catch(e) {}
}
async function fetchModelContextSize() {
const model = document.getElementById('modelSelect').value;
const model = currentModel;
if (!model) return;
try {
const resp = await authFetch('/api/show', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ name: model }) });
@@ -703,7 +763,7 @@ async function loadSettings() {
updateMemoryUI();
updateSkillsUI();
if (s.default_model) {
document.getElementById('modelSelect').value = s.default_model;
currentModel = s.default_model;
document.getElementById('defaultModelSetting').value = s.default_model;
}
} catch(e) {}
@@ -925,7 +985,12 @@ function renderPresetSelect() {
const current = select.value;
select.innerHTML = '<option value="">None (profile only)</option>';
presets.forEach(p => select.add(new Option(p.name, p.id)));
if (current) {
select.value = current;
} else {
const ga = presets.find(p => p.name === 'General Assistant');
if (ga) select.value = ga.id;
}
}
async function addPreset() {
@@ -983,8 +1048,8 @@ async function loadConversations() {
convs.forEach(c => {
const div = document.createElement('div');
div.className = 'conv-item' + (c.id === currentConvId ? ' active' : '');
const delBtn = currentRole === 'admin' ? `<span class="conv-delete" onclick="event.stopPropagation();deleteConversation('${c.id}')">×</span>` : '';
div.innerHTML = `<span class="conv-title" onclick="loadConversation('${c.id}')">${c.title}</span>${delBtn}`;
const attachIcon = c.attachment_count > 0 ? `<span class="conv-attach has-attachments" onclick="event.stopPropagation();showGallery('${c.id}')" title="${c.attachment_count} attachment(s)">📎</span>` : '';
div.innerHTML = `<span class="conv-trash" onclick="event.stopPropagation();deleteConversation('${c.id}')" title="Delete conversation">🗑</span>${attachIcon}<span class="conv-title" onclick="loadConversation('${c.id}')">${c.title}</span>`;
list.appendChild(div);
});
} catch(e) {}
@@ -995,7 +1060,7 @@ async function loadConversation(convId) {
const resp = await authFetch(`/api/conversations/${convId}`);
const data = await resp.json();
currentConvId = convId;
document.getElementById('modelSelect').value = data.conversation.model;
currentModel = data.conversation.model;
fetchModelContextSize();
const container = document.getElementById('chatContainer');
container.innerHTML = '';
@@ -1034,6 +1099,7 @@ function newChat() {
updateTokenThermometer();
}
function escapeHtml(str) { const div = document.createElement('div'); div.textContent = str; return div.innerHTML; }
function showWelcome() {
document.getElementById('chatContainer').innerHTML = '<div class="welcome-screen" id="welcomeScreen"><div class="logo">⚡</div><p>JarvisChat — your local coding companion.<br>Profile + Memory context injected automatically.<br>Web search kicks in when the model is uncertain.<br>Use 🔍 to force a web search.<br>Say "remember that..." to teach me things.</p></div>';
}
@@ -1042,7 +1108,7 @@ async function sendSearch() {
const input = document.getElementById('userInput');
const query = input.value.trim();
if (!query || isStreaming) return;
const model = document.getElementById('modelSelect').value;
const model = currentModel;
const welcome = document.getElementById('welcomeScreen');
if (welcome) welcome.remove();
appendMessage('user', '🔍 ' + query, true);
@@ -1054,6 +1120,8 @@ async function sendSearch() {
const textEl = assistantDiv.querySelector('.text');
textEl.innerHTML = '<div class="search-indicator"><div class="spinner"></div>Searching the web...</div>';
setStreamingState(true);
const ttrStart = performance.now();
let ttr = 0;
try {
abortController = new AbortController();
const resp = await authFetch('/api/search', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ conversation_id: currentConvId, query, model }), signal: abortController.signal });
@@ -1075,7 +1143,7 @@ async function sendSearch() {
if (data.error) { textEl.textContent = 'Error: ' + data.error; setStreamingState(false); return; }
if (data.conversation_id && !currentConvId) { currentConvId = data.conversation_id; await loadConversations(); }
if (data.search_results) { textEl.innerHTML = '<div class="search-indicator">🔍 Found ' + data.search_results + ' results, summarizing...</div>'; }
if (data.token) { if (firstToken) { textEl.innerHTML = ''; firstToken = false; } fullText += data.token; textEl.innerHTML = renderMarkdown(fullText); scrollToBottom(); }
if (data.token) { if (firstToken) { textEl.innerHTML = ''; firstToken = false; ttr = performance.now() - ttrStart; } fullText += data.token; textEl.innerHTML = renderMarkdown(fullText); scrollToBottom(); }
if (data.raw_results) {
let rawHtml = '<details class="raw-results"><summary>🔍 View raw search results (' + data.raw_results.length + ')</summary><ul>';
data.raw_results.forEach(r => {
@@ -1094,7 +1162,13 @@ async function sendSearch() {
}
if (data.done) {
const roleLabel = assistantDiv.querySelector('.role-label');
if (roleLabel) roleLabel.innerHTML += '<span class="search-badge-inline">🔍 web</span>';
if (roleLabel) {
roleLabel.innerHTML += '<span class="search-badge-inline">🔍 web</span>';
if (ttr > 0) {
const ttrSec = ttr / 1000;
roleLabel.innerHTML += `<span class="ttr-badge search">ttr: ${ttrSec.toFixed(1)}s</span>`;
}
}
conversationHistory.push({ role: 'assistant', content: fullText });
updateTokenThermometer();
addCopyButtons(assistantDiv);
@@ -1111,11 +1185,89 @@ async function sendSearch() {
}
}
function onFileSelected(event) {
const file = event.target.files[0];
if (!file) return;
selectedFile = file;
const preview = document.getElementById('filePreview');
const thumb = document.getElementById('filePreviewThumb');
const icon = document.getElementById('filePreviewIcon');
const nameEl = document.getElementById('filePreviewName');
const sizeEl = document.getElementById('filePreviewSize');
const notice = document.getElementById('filePreviewNotice');
nameEl.textContent = file.name;
sizeEl.textContent = (file.size / 1024).toFixed(1) + ' KB';
if (file.type.startsWith('image/')) {
thumb.style.display = 'block';
thumb.src = URL.createObjectURL(file);
icon.style.display = 'none';
notice.textContent = 'Model does not support image input — filename only will be used as context.';
} else {
thumb.style.display = 'none';
icon.style.display = 'inline';
icon.textContent = '📄';
notice.textContent = '';
}
preview.classList.add('visible');
event.target.value = '';
}
function clearFileSelection() {
selectedFile = null;
const preview = document.getElementById('filePreview');
preview.classList.remove('visible');
const thumb = document.getElementById('filePreviewThumb');
thumb.src = '';
}
function showGallery(convId) {
document.getElementById('galleryOverlay').classList.add('visible');
loadGallery(convId);
}
function closeGallery(event) {
if (event && event.target !== event.currentTarget) return;
document.getElementById('galleryOverlay').classList.remove('visible');
}
async function loadGallery(convId) {
const body = document.getElementById('galleryBody');
body.innerHTML = '<div class="gallery-empty">Loading...</div>';
try {
const resp = await authFetch('/api/upload/by-conversation/' + encodeURIComponent(convId));
const items = await resp.json();
if (!items || items.length === 0) {
body.innerHTML = '<div class="gallery-empty">No attachments in this conversation.</div>';
return;
}
body.innerHTML = '';
for (const item of items) {
const div = document.createElement('div');
div.className = 'gallery-item';
const isImage = item.content_type && item.content_type.startsWith('image/');
const thumbHtml = isImage
? '<span class="gallery-item-icon">🖼</span>'
: '<span class="gallery-item-icon">📄</span>';
const expires = new Date(item.expires_at);
const expiresStr = expires.toLocaleString();
div.innerHTML = thumbHtml + '<div class="gallery-item-info"><div class="gallery-item-name">' + escapeHtml(item.filename) + '</div><div class="gallery-item-meta">Expires: ' + expiresStr + '</div></div><button class="gallery-item-delete" onclick="deleteGalleryItem(' + item.id + ')">Delete</button>';
body.appendChild(div);
}
} catch(e) {
body.innerHTML = '<div class="gallery-empty">Error loading attachments.</div>';
}
}
async function deleteGalleryItem(contextId) {
if (!confirm('Delete this attachment? It will also be removed from the RAG corpus.')) return;
try {
const resp = await authFetch('/api/upload/' + contextId, { method: 'DELETE' });
if (resp.ok) {
await loadGallery(currentConvId);
await loadConversations();
}
} catch(e) {}
}
async function sendMessage() {
const input = document.getElementById('userInput');
const message = input.value.trim();
if (!message || isStreaming) return;
const model = document.getElementById('modelSelect').value;
const model = currentModel;
const presetPrompt = getSelectedPresetPrompt();
const welcome = document.getElementById('welcomeScreen');
if (welcome) welcome.remove();
@@ -1129,9 +1281,36 @@ async function sendMessage() {
textEl.innerHTML = '<div class="typing-indicator"><span></span><span></span><span></span></div>';
setStreamingState(true);
let searchTriggered = false;
const ttrStart = performance.now();
let ttr = 0;
try {
abortController = new AbortController();
const resp = await authFetch('/api/chat', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ conversation_id: currentConvId, message, model, system_prompt: presetPrompt }), signal: abortController.signal });
let uploadContextId = null;
if (selectedFile) {
const formData = new FormData();
formData.append('file', selectedFile, selectedFile.name);
formData.append('mode', 'both');
if (currentConvId) formData.append('conversation_id', currentConvId);
try {
const uploadResp = await authFetch('/api/upload', { method: 'POST', body: formData, signal: abortController.signal });
const uploadData = await uploadResp.json();
if (uploadResp.ok && uploadData.context_id) {
uploadContextId = uploadData.context_id;
if (!currentConvId && uploadData.conversation_id) currentConvId = uploadData.conversation_id;
} else {
throw new Error(uploadData.detail || 'Upload failed');
}
} catch(e) {
if (e.name !== 'AbortError') textEl.textContent = 'Error uploading file: ' + e.message;
setStreamingState(false);
return;
}
clearFileSelection();
await loadConversations();
}
const chatBody = { conversation_id: currentConvId, message, model, system_prompt: presetPrompt };
if (uploadContextId) chatBody.upload_context_id = uploadContextId;
const resp = await authFetch('/api/chat', { method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify(chatBody), signal: abortController.signal });
const reader = resp.body.getReader();
const decoder = new TextDecoder();
let fullText = '';
@@ -1148,15 +1327,26 @@ async function sendMessage() {
try {
const data = JSON.parse(line.slice(6));
if (data.error) { textEl.textContent = 'Error: ' + data.error; setStreamingState(false); return; }
if (data.conversation_id && !currentConvId) { currentConvId = data.conversation_id; await loadConversations(); }
if (data.conversation_id && !currentConvId) {
currentConvId = data.conversation_id;
if (uploadContextId) {
authFetch('/api/upload/' + uploadContextId + '/link', { method: 'PATCH', headers: {'Content-Type': 'application/json'}, body: JSON.stringify({ conversation_id: currentConvId }) }).catch(()=>{});
}
await loadConversations();
}
if (data.searching) { textEl.innerHTML = fullText ? renderMarkdown(fullText) + '<div class="search-indicator"><div class="spinner"></div>Searching...</div>' : '<div class="search-indicator"><div class="spinner"></div>Searching...</div>'; searchTriggered = true; }
if (data.search_results) { textEl.innerHTML = '<div class="search-indicator">🔍 Found ' + data.search_results + ' results...</div>'; fullText = ''; firstToken = true; }
if (data.token) { if (firstToken) { textEl.innerHTML = ''; firstToken = false; } fullText += data.token; textEl.innerHTML = renderMarkdown(fullText); scrollToBottom(); }
if (data.token) { if (firstToken) { textEl.innerHTML = ''; firstToken = false; ttr = performance.now() - ttrStart; } fullText += data.token; textEl.innerHTML = renderMarkdown(fullText); scrollToBottom(); }
if (data.done) {
const roleLabel = assistantDiv.querySelector('.role-label');
if (data.searched && roleLabel) roleLabel.innerHTML += '<span class="search-badge-inline">🔍 web</span>';
if (typeof data.perplexity === 'number' && roleLabel) { const ppl = data.perplexity; roleLabel.innerHTML += `<span class="perplexity-badge ${ppl >= 15 ? 'high' : ppl >= 8 ? 'medium' : 'low'}">ppl: ${ppl.toFixed(1)}</span>`; }
if (typeof data.tokens_per_sec === 'number' && data.tokens_per_sec > 0 && roleLabel) roleLabel.innerHTML += `<span class="tps-badge">${data.tokens_per_sec.toFixed(1)} t/s</span>`;
if (roleLabel && ttr > 0) {
const ttrSec = ttr / 1000;
const ttrClass = data.searched ? 'search' : (ttrSec <= 2 ? 'low' : ttrSec < 11 ? 'medium' : 'high');
roleLabel.innerHTML += `<span class="ttr-badge ${ttrClass}">ttr: ${ttrSec.toFixed(1)}s</span>`;
}
conversationHistory.push({ role: 'assistant', content: fullText });
updateTokenThermometer();
addCopyButtons(assistantDiv);
@@ -1234,7 +1424,12 @@ function addCopyButtons(msgDiv) {
const btn = document.createElement('button');
btn.className = 'copy-btn';
btn.textContent = 'copy';
btn.onclick = () => navigator.clipboard.writeText(pre.querySelector('code')?.textContent || pre.textContent).then(() => { btn.textContent = 'copied!'; setTimeout(() => btn.textContent = 'copy', 1500); });
btn.onclick = () => {
const text = pre.querySelector('code')?.textContent || pre.textContent;
if (navigator.clipboard) {
navigator.clipboard.writeText(text).then(() => { btn.textContent = 'copied!'; setTimeout(() => btn.textContent = 'copy', 1500); }).catch(() => fallbackCopy(text, btn));
} else { fallbackCopy(text, btn); }
};
pre.style.position = 'relative';
pre.appendChild(btn);
});
@@ -1242,10 +1437,36 @@ function addCopyButtons(msgDiv) {
function escapeHtml(t) { const d = document.createElement('div'); d.textContent = t; return d.innerHTML; }
function scrollToBottom() { const c = document.getElementById('chatContainer'); c.scrollTop = c.scrollHeight; }
function fallbackCopy(text, btn) {
const ta = document.createElement('textarea');
ta.value = text;
ta.style.position = 'fixed';
ta.style.opacity = '0';
document.body.appendChild(ta);
ta.select();
document.execCommand('copy');
document.body.removeChild(ta);
btn.textContent = 'copied!';
setTimeout(() => btn.textContent = 'copy', 1500);
}
const userInput = document.getElementById('userInput');
userInput.addEventListener('input', function() { this.style.height = 'auto'; this.style.height = Math.min(this.scrollHeight, 200) + 'px'; });
userInput.addEventListener('keydown', e => { if (e.key === 'Enter' && !e.shiftKey) { e.preventDefault(); sendMessage(); } });
const toastStyle = document.createElement('style');
toastStyle.textContent = '.toast-error { position:fixed; bottom:80px; left:50%; transform:translateX(-50%); background:var(--danger); color:#fff; padding:12px 24px; border-radius:var(--radius); font-family:var(--font-body); font-size:14px; z-index:9999; animation:fadeIn 0.2s; } @keyframes fadeIn { from{opacity:0;transform:translateX(-50%) translateY(10px)} to{opacity:1;transform:translateX(-50%) translateY(0)} }';
document.head.appendChild(toastStyle);
userInput.addEventListener('paste', e => {
const hasImage = Array.from(e.clipboardData.items).some(i => i.type.startsWith('image/'));
if (hasImage) {
e.preventDefault();
const toast = document.createElement('div');
toast.className = 'toast-error';
toast.textContent = 'Use the 📎 button to attach images — paste is text only.';
document.body.appendChild(toast);
setTimeout(() => toast.remove(), 3000);
}
});
</script>
</body>
</html>
+10 -8
View File
@@ -3,16 +3,18 @@ from pathlib import Path
from fastapi.testclient import TestClient
import app as app_module
import app
import db
from security import SESSIONS, PIN_ATTEMPTS
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-test.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.init_db()
return TestClient(app_module.app)
db.DB_PATH = tmp_path / "jarvischat-test.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
db.init_db()
return TestClient(app.app)
def test_guest_read_only_admin_write_blocked(tmp_path: Path):
@@ -20,7 +22,7 @@ def test_guest_read_only_admin_write_blocked(tmp_path: Path):
guest = client.post("/api/auth/guest", headers={"Origin": "http://testserver"})
assert guest.status_code == 200
sid = guest.json()["session_id"]
headers = {"X-Session-ID": sid}
headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
read_resp = client.get("/api/memories", headers=headers)
assert read_resp.status_code == 200
@@ -74,5 +76,5 @@ def test_logout_revokes_session(tmp_path: Path):
logout = client.post("/api/auth/logout", headers=headers)
assert logout.status_code == 200
after = client.get("/api/memories", headers={"X-Session-ID": sid})
after = client.get("/api/memories", headers={"X-Session-ID": sid, "Origin": "http://testserver"})
assert after.status_code == 401
+86 -18
View File
@@ -2,19 +2,24 @@ import json
import os
from pathlib import Path
import httpx
from fastapi.testclient import TestClient
import app as app_module
import app
import config
import db
import routers.chat
from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-streaming.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.RATE_EVENTS.clear()
app_module.init_db()
return TestClient(app_module.app, raise_server_exceptions=False)
db.DB_PATH = tmp_path / "jarvischat-streaming.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app, raise_server_exceptions=False)
def parse_sse_payloads(body: str) -> list[dict]:
@@ -65,11 +70,11 @@ def test_chat_stream_emits_tokens_and_done(tmp_path: Path, monkeypatch):
def stream_stub(self, method, url, json=None, timeout=None):
return _MockStreamResponse(events)
monkeypatch.setattr(app_module.httpx.AsyncClient, "stream", stream_stub)
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
resp = client.post(
"/api/chat",
json={"message": "hello", "model": app_module.DEFAULT_MODEL},
json={"message": "hello", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
@@ -92,7 +97,7 @@ def test_chat_auto_search_trigger_emits_search_events(tmp_path: Path, monkeypatc
first_stream = _stream_json_lines(
[
{
"message": {"content": "I am uncertain."},
"message": {"content": "I don't have current data on that question."},
"logprobs": [{"logprob": -5.0}],
},
{"done": True, "eval_count": 2, "eval_duration": 1000000000},
@@ -118,12 +123,12 @@ def test_chat_auto_search_trigger_emits_search_events(tmp_path: Path, monkeypatc
}
]
monkeypatch.setattr(app_module.httpx.AsyncClient, "stream", stream_stub)
monkeypatch.setattr(app_module, "query_searxng", search_stub)
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": app_module.DEFAULT_MODEL},
json={"message": "what is the latest value", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
@@ -136,6 +141,69 @@ def test_chat_auto_search_trigger_emits_search_events(tmp_path: Path, monkeypatc
assert done_events and done_events[-1].get("searched") is True
def test_chat_with_upload_context_id_injects_document(tmp_path: Path, monkeypatch):
captured_payload = {}
def stream_stub(self, method, url, json=None, timeout=None):
nonlocal captured_payload
captured_payload = json
events = [{"message": {"content": "ok"}, "logprobs": [{"logprob": -0.01}]}, {"done": True, "eval_count": 1, "eval_duration": 1000000000}]
return _MockStreamResponse([__import__('json').dumps(e) for e in events])
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
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"}
db_local = db.get_db()
expires = "2099-12-31T23:59:59+00:00"
cid = db.insert_upload_context(db_local, "conv-up", "report.txt", "Confidential document content here", expires, "text/plain")
db_local.commit()
db_local.close()
resp = client.post(
"/api/chat",
json={"message": "summarize this", "upload_context_id": cid, "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
system_content = next((m["content"] for m in captured_payload.get("messages", []) if m["role"] == "system"), "")
assert "Confidential document content here" in system_content
def test_chat_with_expired_upload_context_id_silent(tmp_path: Path, monkeypatch):
captured_payload = {}
def stream_stub(self, method, url, json=None, timeout=None):
nonlocal captured_payload
captured_payload = json
events = [{"message": {"content": "ok"}, "logprobs": [{"logprob": -0.01}]}, {"done": True, "eval_count": 1, "eval_duration": 1000000000}]
return _MockStreamResponse([__import__('json').dumps(e) for e in events])
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
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"}
import datetime
db_local = db.get_db()
expires = (datetime.datetime.now(datetime.timezone.utc) - datetime.timedelta(hours=2)).isoformat()
cid = db.insert_upload_context(db_local, "conv-exp", "old.txt", "Stale data", expires, "text/plain")
db_local.commit()
db_local.close()
resp = client.post(
"/api/chat",
json={"message": "hi", "upload_context_id": cid, "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
system_content = next((m["content"] for m in captured_payload.get("messages", []) if m["role"] == "system"), "")
assert "Stale data" not in system_content
def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
with make_client(tmp_path) as client:
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
@@ -153,13 +221,13 @@ def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
def stream_stub(self, method, url, json=None, timeout=None):
return _MockStreamResponse(base_stream)
monkeypatch.setattr(app_module.httpx.AsyncClient, "stream", stream_stub)
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
remember_resp = client.post(
"/api/chat",
json={
"message": "remember that my favorite language is rust",
"model": app_module.DEFAULT_MODEL,
"model": config.DEFAULT_MODEL,
},
headers=headers,
)
@@ -167,7 +235,7 @@ def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
remember_events = parse_sse_payloads(remember_resp.text)
assert any("Remembered" in p.get("token", "") for p in remember_events)
memories_after_add = client.get("/api/memories", headers={"X-Session-ID": sid})
memories_after_add = client.get("/api/memories", headers={"X-Session-ID": sid, "Origin": "http://testserver"})
assert memories_after_add.status_code == 200
assert memories_after_add.json().get("count", 0) >= 1
@@ -175,7 +243,7 @@ def test_memory_command_paths_remember_and_forget(tmp_path: Path, monkeypatch):
"/api/chat",
json={
"message": "forget about my favorite language",
"model": app_module.DEFAULT_MODEL,
"model": config.DEFAULT_MODEL,
},
headers=headers,
)
@@ -183,6 +251,6 @@ 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})
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
+222
View File
@@ -0,0 +1,222 @@
import json
import os
from pathlib import Path
import httpx
from fastapi.testclient import TestClient
import app
import config
import db
import routers.completions
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"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app, raise_server_exceptions=False)
TEST_API_KEY = "test-sk-jarvischat-completions"
def _auth_headers(extra: dict = None) -> dict:
h = {"Authorization": f"Bearer {TEST_API_KEY}", "Content-Type": "application/json", "Origin": "http://testserver"}
if extra:
h.update(extra)
return h
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
class _MockAsyncPostResponse:
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
def _stream_json_lines(events: list[dict]) -> list[str]:
return [json.dumps(event) for event in events]
def test_completions_missing_api_key(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}]},
)
assert resp.status_code == 401
def test_completions_invalid_api_key(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}]},
headers={"Authorization": "Bearer wrong-key", "Origin": "http://testserver"},
)
assert resp.status_code == 401
def test_completions_no_messages(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
with make_client(tmp_path) as client:
resp = client.post("/v1/chat/completions", json={}, headers=_auth_headers())
assert resp.status_code == 400
def test_completions_empty_messages(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
with make_client(tmp_path) as client:
resp = client.post("/v1/chat/completions", json={"messages": []}, headers=_auth_headers())
assert resp.status_code == 400
def test_completions_no_user_message(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "assistant", "content": "hello"}]},
headers=_auth_headers(),
)
assert resp.status_code == 400
def test_completions_streaming(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
events = _stream_json_lines([
{"choices": [{"delta": {"content": "Hello"}, "logprobs": None}]},
{"choices": [{"delta": {"content": " world"}, "logprobs": None}]},
{"choices": [{"delta": {}, "finish_reason": "stop"}], "usage": {"tokens_per_second": 15.0}},
])
call_count = 0
def stream_stub(self, method, url, json=None, timeout=None):
nonlocal call_count
call_count += 1
return _MockStreamResponse(events)
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}], "stream": True},
headers=_auth_headers(),
)
assert resp.status_code == 200
body = resp.text
assert "data: [DONE]" in body
assert "Hello" in body or "world" in body
assert "chatcmpl-" in body
def test_completions_blocking(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
events = _stream_json_lines([
{"choices": [{"delta": {"content": "Hello world"}, "logprobs": None}]},
{"choices": [{"delta": {}, "finish_reason": "stop"}], "usage": {}},
])
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(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}], "stream": False},
headers=_auth_headers(),
)
assert resp.status_code == 200
data = resp.json()
assert data["object"] == "chat.completion"
assert data["choices"][0]["message"]["content"] == "Hello world"
def test_completions_fim_passthrough(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
fim_data = {"prompt": "def foo():\n ", "suffix": "\n return x", "model": "llama3.1:latest"}
async def mock_post(self, url, json=None, timeout=None):
return _MockAsyncPostResponse(json_data={"choices": [{"text": "pass"}], "usage": {}})
monkeypatch.setattr(httpx.AsyncClient, "post", mock_post)
with make_client(tmp_path) as client:
resp = client.post("/v1/chat/completions", json=fim_data, headers=_auth_headers())
assert resp.status_code == 200
assert "choices" in resp.json()
def test_completions_connect_error_stream(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
def broken_stream(self, method, url, json=None, timeout=None):
raise httpx.ConnectError("Connection refused")
monkeypatch.setattr(httpx.AsyncClient, "stream", broken_stream)
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}], "stream": True},
headers=_auth_headers(),
)
assert resp.status_code == 200
assert "connection_error" in resp.text
def test_completions_connect_error_blocking(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
def broken_stream(self, method, url, json=None, timeout=None):
raise httpx.ConnectError("Connection refused")
monkeypatch.setattr(httpx.AsyncClient, "stream", broken_stream)
with make_client(tmp_path) as client:
resp = client.post(
"/v1/chat/completions",
json={"messages": [{"role": "user", "content": "hi"}], "stream": False},
headers=_auth_headers(),
)
assert resp.status_code == 503
def test_completions_fim_connect_error(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.completions, "COMPLETIONS_API_KEY", TEST_API_KEY)
fim_data = {"prompt": "def foo():", "model": "llama3.1:latest"}
def broken_post(self, url, json=None, timeout=None):
raise httpx.ConnectError("Connection refused")
monkeypatch.setattr(httpx.AsyncClient, "post", broken_post)
with make_client(tmp_path) as client:
resp = client.post("/v1/chat/completions", json=fim_data, headers=_auth_headers())
assert resp.status_code == 503
+153
View File
@@ -0,0 +1,153 @@
import os
from pathlib import Path
from fastapi.testclient import TestClient
import app
import db
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"
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"}
def test_list_conversations_empty(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/conversations", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json() == []
def test_create_and_list_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "Test Chat", "model": "llama3.1:latest"}, headers=headers)
assert create.status_code == 200
data = create.json()
assert data["title"] == "Test Chat"
assert data["model"] == "llama3.1:latest"
list_resp = client.get("/api/conversations", headers=headers)
assert list_resp.status_code == 200
convs = list_resp.json()
assert len(convs) == 1
assert convs[0]["title"] == "Test Chat"
def test_get_conversation_returns_messages(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "My Chat"}, headers=headers)
conv_id = create.json()["id"]
resp = client.get(f"/api/conversations/{conv_id}", headers=headers)
assert resp.status_code == 200
data = resp.json()
assert data["conversation"]["id"] == conv_id
assert data["messages"] == []
def test_get_conversation_not_found(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/conversations/nope", headers=_guest_headers(client))
assert resp.status_code == 404
def test_update_conversation_title(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "Old"}, headers=headers)
conv_id = create.json()["id"]
update = client.put(f"/api/conversations/{conv_id}", json={"title": "New Title"}, headers=headers)
assert update.status_code == 200
get = client.get(f"/api/conversations/{conv_id}", headers=headers)
assert get.json()["conversation"]["title"] == "New Title"
def test_update_conversation_model(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "Test"}, headers=headers)
conv_id = create.json()["id"]
update = client.put(f"/api/conversations/{conv_id}", json={"model": "qwen2:latest"}, headers=headers)
assert update.status_code == 200
get = client.get(f"/api/conversations/{conv_id}", headers=headers)
assert get.json()["conversation"]["model"] == "qwen2:latest"
def test_delete_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "Delete Me"}, headers=headers)
conv_id = create.json()["id"]
delete = client.delete(f"/api/conversations/{conv_id}", headers=headers)
assert delete.status_code == 200
get = client.get(f"/api/conversations/{conv_id}", headers=_guest_headers(client))
assert get.status_code == 404
def test_delete_all_conversations(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
client.post("/api/conversations", json={"title": "One"}, headers=headers)
client.post("/api/conversations", json={"title": "Two"}, headers=headers)
delete_all = client.delete("/api/conversations", headers=headers)
assert delete_all.status_code == 200
list_resp = client.get("/api/conversations", headers=_guest_headers(client))
assert list_resp.json() == []
def test_guest_cannot_create_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post("/api/conversations", json={"title": "test"}, headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_update_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/conversations", json={"title": "Test"}, headers=headers)
conv_id = create.json()["id"]
guest_headers = _guest_headers(client)
resp = client.put(f"/api/conversations/{conv_id}", json={"title": "hack"}, headers=guest_headers)
assert resp.status_code == 403
def test_guest_cannot_delete_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/conversations/some-id", headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_delete_all(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/conversations", headers=_guest_headers(client))
assert resp.status_code == 403
+16 -11
View File
@@ -1,19 +1,24 @@
import os
from pathlib import Path
import httpx
from fastapi.testclient import TestClient
import app as app_module
import app
import config
import db
import routers.memories
from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-errors.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.RATE_EVENTS.clear()
app_module.init_db()
return TestClient(app_module.app, raise_server_exceptions=False)
db.DB_PATH = tmp_path / "jarvischat-errors.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app, raise_server_exceptions=False)
def test_unhandled_api_exception_returns_friendly_error_with_incident_key(
@@ -23,12 +28,12 @@ def test_unhandled_api_exception_returns_friendly_error_with_incident_key(
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
"session_id"
]
headers = {"X-Session-ID": sid}
headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
def boom(_topic=None):
raise RuntimeError("super secret db internals")
monkeypatch.setattr(app_module, "get_all_memories", boom)
monkeypatch.setattr(routers.memories, "get_all_memories", boom)
resp = client.get("/api/memories", headers=headers)
assert resp.status_code == 500
@@ -57,11 +62,11 @@ def test_chat_stream_error_hides_internal_exception_and_emits_incident_key(
def broken_stream(*args, **kwargs):
return BrokenStreamContext()
monkeypatch.setattr(app_module.httpx.AsyncClient, "stream", broken_stream)
monkeypatch.setattr(httpx.AsyncClient, "stream", broken_stream)
resp = client.post(
"/api/chat",
json={"message": "hello", "model": app_module.DEFAULT_MODEL},
json={"message": "hello", "model": config.DEFAULT_MODEL},
headers=headers,
)
+20 -26
View File
@@ -3,48 +3,42 @@ from pathlib import Path
from fastapi.testclient import TestClient
import app as app_module
import app
import db
from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS, is_ip_allowed
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-ip.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.RATE_EVENTS.clear()
app_module.init_db()
return TestClient(app_module.app)
db.DB_PATH = tmp_path / "jarvischat-ip.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app)
def test_ip_helper_allows_local_defaults():
assert app_module.is_ip_allowed("127.0.0.1")
assert app_module.is_ip_allowed("192.168.1.10")
assert app_module.is_ip_allowed("10.0.0.42")
assert app_module.is_ip_allowed("172.16.1.2")
assert app_module.is_ip_allowed("testclient")
assert is_ip_allowed("127.0.0.1")
assert is_ip_allowed("192.168.1.10")
assert is_ip_allowed("10.0.0.42")
assert is_ip_allowed("172.16.1.2")
assert is_ip_allowed("testclient")
def test_ip_helper_blocks_public_ip():
assert not app_module.is_ip_allowed("8.8.8.8")
assert not is_ip_allowed("8.8.8.8")
def test_middleware_blocks_disallowed_ip(tmp_path: Path):
def test_middleware_blocks_disallowed_ip(tmp_path: Path, monkeypatch):
monkeypatch.setattr(app, "get_client_ip", lambda _req: "8.8.8.8")
with make_client(tmp_path) as client:
original_get_client_ip = app_module.get_client_ip
try:
app_module.get_client_ip = lambda _req: "8.8.8.8"
resp = client.post("/api/auth/guest")
assert resp.status_code == 403
finally:
app_module.get_client_ip = original_get_client_ip
def test_middleware_allows_local_ip(tmp_path: Path):
def test_middleware_allows_local_ip(tmp_path: Path, monkeypatch):
monkeypatch.setattr(app, "get_client_ip", lambda _req: "192.168.50.109")
with make_client(tmp_path) as client:
original_get_client_ip = app_module.get_client_ip
try:
app_module.get_client_ip = lambda _req: "192.168.50.109"
resp = client.post("/api/auth/guest")
resp = client.post("/api/auth/guest", headers={"Origin": "http://testserver"})
assert resp.status_code == 200
finally:
app_module.get_client_ip = original_get_client_ip
+161
View File
@@ -0,0 +1,161 @@
import os
from pathlib import Path
from fastapi.testclient import TestClient
import app
import config
import db
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"
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"}
def _create_memory(client: TestClient, headers: dict, fact: str = "test fact", topic: str = "general") -> int:
resp = client.post("/api/memories", json={"fact": fact, "topic": topic}, headers=headers)
assert resp.status_code == 200
return resp.json()["rowid"]
def test_list_memories_empty(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/memories", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["count"] == 0
def test_list_memories_by_topic(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
_create_memory(client, headers, "I like Python", "preference")
_create_memory(client, headers, "Building a game", "project")
general = client.get("/api/memories?topic=preference", headers=_guest_headers(client))
assert general.json()["count"] == 1
assert general.json()["memories"][0]["topic"] == "preference"
def test_create_memory_requires_fact(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post("/api/memories", json={"fact": ""}, headers=_admin_headers(client))
assert resp.status_code == 400
def test_create_memory_too_long(tmp_path: Path):
with make_client(tmp_path) as client:
long_fact = "x" * (config.MAX_MEMORY_FACT_CHARS + 1)
resp = client.post("/api/memories", json={"fact": long_fact}, headers=_admin_headers(client))
assert resp.status_code == 413
def test_edit_memory(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
rowid = _create_memory(client, headers, "original fact")
edit = client.put(f"/api/memories/{rowid}", json={"fact": "updated fact"}, headers=headers)
assert edit.status_code == 200
memories = client.get("/api/memories", headers=_guest_headers(client)).json()
assert any(m["fact"] == "updated fact" for m in memories["memories"])
def test_edit_memory_not_found(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.put("/api/memories/99999", json={"fact": "nope"}, headers=_admin_headers(client))
assert resp.status_code == 404
def test_edit_memory_empty_fact(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
rowid = _create_memory(client, headers, "some fact")
resp = client.put(f"/api/memories/{rowid}", json={"fact": ""}, headers=headers)
assert resp.status_code == 400
def test_edit_memory_too_long(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
rowid = _create_memory(client, headers, "some fact")
long_fact = "x" * (config.MAX_MEMORY_FACT_CHARS + 1)
resp = client.put(f"/api/memories/{rowid}", json={"fact": long_fact}, headers=headers)
assert resp.status_code == 413
def test_delete_memory_not_found(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/memories/99999", headers=_admin_headers(client))
assert resp.status_code == 404
def test_search_memories(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
_create_memory(client, headers, "my favorite color is blue", "preference")
_create_memory(client, headers, "running nginx on port 443", "infrastructure")
resp = client.get("/api/memories/search?q=nginx&limit=5", headers=_guest_headers(client))
assert resp.status_code == 200
data = resp.json()
assert data["count"] >= 1
assert any("nginx" in r["fact"] for r in data["results"])
def test_search_memories_no_results(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/memories/search?q=xyznonexistent&limit=5", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["count"] == 0
def test_memory_stats(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
_create_memory(client, headers, "like rust", "preference")
_create_memory(client, headers, "like python", "preference")
_create_memory(client, headers, "project game", "project")
resp = client.get("/api/memories/stats", headers=_guest_headers(client))
assert resp.status_code == 200
data = resp.json()
assert data["total"] == 3
assert data["by_topic"]["preference"] == 2
assert data["by_topic"]["project"] == 1
def test_guest_cannot_create_memory(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post("/api/memories", json={"fact": "hack"}, headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_edit_memory(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.put("/api/memories/1", json={"fact": "hack"}, headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_delete_memory(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/memories/1", headers=_guest_headers(client))
assert resp.status_code == 403
+138
View File
@@ -0,0 +1,138 @@
import os
from pathlib import Path
import httpx
from fastapi.testclient import TestClient
import app
import db
import routers.models
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"
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"}
class _MockAsyncResponse:
"""Mock for httpx.AsyncClient.get/post that returns a JSON response."""
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
async def _mock_get_models(*args, **kwargs):
return _MockAsyncResponse(json_data={
"data": [{"id": "llama3.1:latest"}, {"id": "qwen2:latest"}]
})
async def _mock_get_empty_models(*args, **kwargs):
return _MockAsyncResponse(json_data={"data": []})
async def _mock_connect_error(*args, **kwargs):
raise httpx.ConnectError("Connection refused")
async def _mock_show_model(*args, **kwargs):
return _MockAsyncResponse(json_data={
"modelfile": "FROM llama3.1", "parameters": {}
})
async def _mock_search_available(*args, **kwargs):
return _MockAsyncResponse(status_code=200)
async def _mock_search_unavailable(*args, **kwargs):
raise httpx.ConnectError("refused")
def test_list_models(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_get_models)
with make_client(tmp_path) as client:
resp = client.get("/api/models", headers=_guest_headers(client))
assert resp.status_code == 200
models = resp.json()["models"]
assert len(models) == 2
assert models[0]["name"] == "llama3.1:latest"
def test_list_models_connect_error(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_connect_error)
with make_client(tmp_path) as client:
resp = client.get("/api/models", headers=_guest_headers(client))
assert resp.status_code == 502
def test_running_models(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_get_models)
with make_client(tmp_path) as client:
resp = client.get("/api/ps", headers=_guest_headers(client))
assert resp.status_code == 200
assert "data" in resp.json()
def test_running_models_connect_error(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_connect_error)
with make_client(tmp_path) as client:
resp = client.get("/api/ps", headers=_guest_headers(client))
assert resp.status_code == 502
def test_show_model(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "post", _mock_show_model)
with make_client(tmp_path) as client:
resp = client.post("/api/show", json={"model": "llama3.1:latest"}, headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["modelfile"] == "FROM llama3.1"
def test_show_model_connect_error(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "post", _mock_connect_error)
with make_client(tmp_path) as client:
resp = client.post("/api/show", json={"model": "llama3.1:latest"}, headers=_guest_headers(client))
assert resp.status_code == 502
def test_system_stats(tmp_path: Path, monkeypatch):
monkeypatch.setattr(routers.models, "get_gpu_stats", lambda: {"gpu_percent": 15, "vram_percent": 30, "available": True})
with make_client(tmp_path) as client:
resp = client.get("/api/stats", headers=_guest_headers(client))
assert resp.status_code == 200
data = resp.json()
assert "cpu_percent" in data
assert "memory_percent" in data
assert data["gpu_percent"] == 15
assert data["gpu_available"] is True
def test_search_status_available(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_search_available)
with make_client(tmp_path) as client:
resp = client.get("/api/search/status", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["available"] is True
def test_search_status_unavailable(tmp_path: Path, monkeypatch):
monkeypatch.setattr(httpx.AsyncClient, "get", _mock_search_unavailable)
with make_client(tmp_path) as client:
resp = client.get("/api/search/status", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["available"] is False
+128
View File
@@ -0,0 +1,128 @@
import os
from pathlib import Path
from fastapi.testclient import TestClient
import app
import db
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"
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"}
def test_list_presets_returns_defaults(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/presets", headers=_guest_headers(client))
assert resp.status_code == 200
presets = resp.json()
assert len(presets) >= 3
names = [p["name"] for p in presets]
assert "Coding Companion" in names
def test_create_preset(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp = client.post("/api/presets", json={"name": "My Preset", "prompt": "You are helpful."}, headers=headers)
assert resp.status_code == 200
data = resp.json()
assert data["name"] == "My Preset"
assert data["prompt"] == "You are helpful."
presets = client.get("/api/presets", headers=_guest_headers(client)).json()
assert any(p["name"] == "My Preset" for p in presets)
def test_create_preset_requires_name_and_prompt(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp = client.post("/api/presets", json={"name": "", "prompt": ""}, headers=headers)
assert resp.status_code == 400
resp = client.post("/api/presets", json={"name": "Only Name"}, headers=headers)
assert resp.status_code == 400
def test_update_preset(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/presets", json={"name": "Old", "prompt": "Old prompt."}, headers=headers)
preset_id = create.json()["id"]
update = client.put(f"/api/presets/{preset_id}", json={"name": "New", "prompt": "New prompt."}, headers=headers)
assert update.status_code == 200
presets = client.get("/api/presets", headers=_guest_headers(client)).json()
updated = next(p for p in presets if p["id"] == preset_id)
assert updated["name"] == "New"
assert updated["prompt"] == "New prompt."
def test_update_preset_requires_fields(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp = client.put("/api/presets/nope", json={"name": "", "prompt": ""}, headers=headers)
assert resp.status_code == 400
def test_delete_preset(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
create = client.post("/api/presets", json={"name": "Temp", "prompt": "Temp."}, headers=headers)
preset_id = create.json()["id"]
delete = client.delete(f"/api/presets/{preset_id}", headers=headers)
assert delete.status_code == 200
presets = client.get("/api/presets", headers=_guest_headers(client)).json()
assert not any(p["id"] == preset_id for p in presets)
def test_delete_default_preset_is_noop(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
presets_before = client.get("/api/presets", headers=_guest_headers(client)).json()
default = next(p for p in presets_before if p["is_default"])
delete = client.delete(f"/api/presets/{default['id']}", headers=headers)
assert delete.status_code == 200
presets_after = client.get("/api/presets", headers=_guest_headers(client)).json()
assert any(p["id"] == default["id"] for p in presets_after)
def test_guest_cannot_create_preset(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post("/api/presets", json={"name": "Hack", "prompt": "Hack"}, headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_update_preset(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.put("/api/presets/some-id", json={"name": "Hack", "prompt": "Hack"}, headers=_guest_headers(client))
assert resp.status_code == 403
def test_guest_cannot_delete_preset(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/presets/some-id", headers=_guest_headers(client))
assert resp.status_code == 403
+72
View File
@@ -0,0 +1,72 @@
import os
from pathlib import Path
from fastapi.testclient import TestClient
import app
import config
import db
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"
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"}
def test_get_profile_returns_content(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/profile", headers=_guest_headers(client))
assert resp.status_code == 200
data = resp.json()
assert "content" in data
assert "updated_at" in data
assert len(data["content"]) > 0
def test_get_default_profile(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.get("/api/profile/default", headers=_guest_headers(client))
assert resp.status_code == 200
assert resp.json()["content"] == config.DEFAULT_PROFILE
def test_update_profile(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp = client.put("/api/profile", json={"content": "Custom profile text."}, headers=headers)
assert resp.status_code == 200
assert "updated_at" in resp.json()
get_resp = client.get("/api/profile", headers=_guest_headers(client))
assert get_resp.json()["content"] == "Custom profile text."
def test_update_profile_too_long(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
long_content = "x" * (config.MAX_PROFILE_CHARS + 1)
resp = client.put("/api/profile", json={"content": long_content}, headers=headers)
assert resp.status_code == 413
def test_guest_cannot_update_profile(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.put("/api/profile", json={"content": "hack"}, headers=_guest_headers(client))
assert resp.status_code == 403
+26 -22
View File
@@ -4,28 +4,32 @@ from pathlib import Path
from fastapi.testclient import TestClient
import app as app_module
import app
import config
import db
import security
from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-rate.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.RATE_EVENTS.clear()
app_module.init_db()
return TestClient(app_module.app)
db.DB_PATH = tmp_path / "jarvischat-rate.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app)
def test_stats_rate_limit_hits_429(tmp_path: Path):
old_limit = app_module.RL_STATS_PER_WINDOW
old_window = app_module.RATE_WINDOW_SECONDS
app_module.RL_STATS_PER_WINDOW = 2
app_module.RATE_WINDOW_SECONDS = 60
old_limit = security.RL_STATS_PER_WINDOW
old_window = app.RATE_WINDOW_SECONDS
security.RL_STATS_PER_WINDOW = 2
app.RATE_WINDOW_SECONDS = 60
try:
with make_client(tmp_path) as client:
sid = client.post("/api/auth/guest").json()["session_id"]
headers = {"X-Session-ID": sid}
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
r1 = client.get("/api/stats", headers=headers)
r2 = client.get("/api/stats", headers=headers)
@@ -35,13 +39,13 @@ def test_stats_rate_limit_hits_429(tmp_path: Path):
assert r2.status_code == 200
assert r3.status_code == 429
finally:
app_module.RL_STATS_PER_WINDOW = old_limit
app_module.RATE_WINDOW_SECONDS = old_window
security.RL_STATS_PER_WINDOW = old_limit
app.RATE_WINDOW_SECONDS = old_window
def test_large_login_payload_rejected_413(tmp_path: Path):
with make_client(tmp_path) as client:
huge_pin = "1" * (app_module.BODY_LIMIT_DEFAULT_BYTES + 100)
huge_pin = "1" * (config.BODY_LIMIT_DEFAULT_BYTES + 100)
resp = client.post(
"/api/auth/login",
data=json.dumps({"pin": huge_pin}),
@@ -52,12 +56,12 @@ def test_large_login_payload_rejected_413(tmp_path: Path):
def test_chat_message_length_rejected_413(tmp_path: Path):
with make_client(tmp_path) as client:
sid = client.post("/api/auth/guest").json()["session_id"]
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
message = "x" * (app_module.MAX_CHAT_MESSAGE_CHARS + 1)
message = "x" * (config.MAX_CHAT_MESSAGE_CHARS + 1)
resp = client.post(
"/api/chat",
json={"message": message, "model": app_module.DEFAULT_MODEL},
json={"message": message, "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 413
@@ -65,12 +69,12 @@ def test_chat_message_length_rejected_413(tmp_path: Path):
def test_search_query_length_rejected_413(tmp_path: Path):
with make_client(tmp_path) as client:
sid = client.post("/api/auth/guest").json()["session_id"]
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()["session_id"]
headers = {"X-Session-ID": sid, "Origin": "http://testserver"}
query = "q" * (app_module.MAX_SEARCH_QUERY_CHARS + 1)
query = "q" * (config.MAX_SEARCH_QUERY_CHARS + 1)
resp = client.post(
"/api/search",
json={"query": query, "model": app_module.DEFAULT_MODEL},
json={"query": query, "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 413
+186
View File
@@ -0,0 +1,186 @@
import json
import os
from pathlib import Path
import httpx
from fastapi.testclient import TestClient
import app
import config
import db
import routers.search_route
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"
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 parse_sse_payloads(body: str) -> list[dict]:
payloads: list[dict] = []
for chunk in body.split("\n\n"):
chunk = chunk.strip()
if not chunk.startswith("data: "):
continue
raw = chunk[len("data: ") :]
payloads.append(json.loads(raw))
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]
def test_explicit_search_with_results(tmp_path: Path, monkeypatch):
with make_client(tmp_path) as client:
headers = _guest_headers(client)
async def search_stub(query: str, max_results: int = 5):
return [
{"title": "Result One", "url": "https://example.com/1", "content": "First result content."},
{"title": "Result Two", "url": "https://example.com/2", "content": "Second result content."},
]
monkeypatch.setattr(routers.search_route, "query_searxng", search_stub)
events = _stream_json_lines([
{"choices": [{"delta": {"content": "Here's what I found"}, "logprobs": None}]},
{"choices": [{"delta": {"content": " about your query."}, "logprobs": None}]},
{"choices": [{"delta": {}, "finish_reason": "stop"}], "usage": {}},
])
def stream_stub(self, method, url, json=None, timeout=None):
return _MockStreamResponse(events)
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
resp = client.post(
"/api/search",
json={"query": "current events", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
payloads = parse_sse_payloads(resp.text)
assert any(p.get("searching") is True for p in payloads)
assert any("search_results" in p for p in payloads)
token_text = "".join(p.get("token", "") for p in payloads if "token" in p)
assert "found" in token_text.lower()
assert any(p.get("done") and p.get("searched") for p in payloads)
def test_explicit_search_no_results(tmp_path: Path, monkeypatch):
with make_client(tmp_path) as client:
headers = _guest_headers(client)
async def empty_search(query: str, max_results: int = 5):
return []
monkeypatch.setattr(routers.search_route, "query_searxng", empty_search)
resp = client.post(
"/api/search",
json={"query": "nothingness", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
payloads = parse_sse_payloads(resp.text)
assert any("No search results found" in p.get("token", "") for p in payloads)
assert any(p.get("done") for p in payloads)
assert not any("search_results" in p for p in payloads)
def test_explicit_search_new_conversation_created(tmp_path: Path, monkeypatch):
with make_client(tmp_path) as client:
headers = _guest_headers(client)
async def search_stub(query: str, max_results: int = 5):
return [{"title": "T", "url": "https://ex.com", "content": "Content."}]
monkeypatch.setattr(routers.search_route, "query_searxng", search_stub)
events = _stream_json_lines([
{"choices": [{"delta": {"content": "Answer."}, "logprobs": None}]},
{"choices": [{"delta": {}, "finish_reason": "stop"}], "usage": {}},
])
def stream_stub(self, method, url, json=None, timeout=None):
return _MockStreamResponse(events)
monkeypatch.setattr(httpx.AsyncClient, "stream", stream_stub)
resp = client.post(
"/api/search",
json={"query": "tell me something", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
payloads = parse_sse_payloads(resp.text)
conv_id = None
for p in payloads:
if "conversation_id" in p:
conv_id = p["conversation_id"]
break
assert conv_id is not None
conv_resp = client.get(f"/api/conversations/{conv_id}", headers=_guest_headers(client))
assert conv_resp.status_code == 200
data = conv_resp.json()
assert len(data["messages"]) >= 2
def test_explicit_search_stream_error(tmp_path: Path, monkeypatch):
with make_client(tmp_path) as client:
headers = _guest_headers(client)
async def search_stub(query: str, max_results: int = 5):
return [{"title": "T", "url": "https://ex.com", "content": "Content."}]
monkeypatch.setattr(routers.search_route, "query_searxng", search_stub)
def broken_stream(self, method, url, json=None, timeout=None):
class BrokenCtx:
async def __aenter__(self):
raise RuntimeError("summarization failed")
async def __aexit__(self, exc_type, exc, tb):
return False
return BrokenCtx()
monkeypatch.setattr(httpx.AsyncClient, "stream", broken_stream)
resp = client.post(
"/api/search",
json={"query": "breaking news", "model": config.DEFAULT_MODEL},
headers=headers,
)
assert resp.status_code == 200
assert "error_key" in resp.text
assert "INC-" in resp.text
+8 -8
View File
@@ -1,17 +1,17 @@
import app as app_module
from search import sanitize_outbound_url
def test_sanitize_outbound_url_allows_http_https():
assert app_module.sanitize_outbound_url("https://example.com/path") == "https://example.com/path"
assert app_module.sanitize_outbound_url("http://example.com") == "http://example.com"
assert sanitize_outbound_url("https://example.com/path") == "https://example.com/path"
assert sanitize_outbound_url("http://example.com") == "http://example.com"
def test_sanitize_outbound_url_blocks_unsafe_schemes():
assert app_module.sanitize_outbound_url("javascript:alert(1)") == ""
assert app_module.sanitize_outbound_url("data:text/html,evil") == ""
assert app_module.sanitize_outbound_url("file:///etc/passwd") == ""
assert sanitize_outbound_url("javascript:alert(1)") == ""
assert sanitize_outbound_url("data:text/html,evil") == ""
assert sanitize_outbound_url("file:///etc/passwd") == ""
def test_sanitize_outbound_url_blocks_relative_and_empty():
assert app_module.sanitize_outbound_url("/relative/path") == ""
assert app_module.sanitize_outbound_url("") == ""
assert sanitize_outbound_url("/relative/path") == ""
assert sanitize_outbound_url("") == ""
+8 -6
View File
@@ -3,17 +3,19 @@ from pathlib import Path
from fastapi.testclient import TestClient
import app as app_module
import app
import db
from security import SESSIONS, PIN_ATTEMPTS
def make_admin_client(tmp_path: Path) -> tuple[TestClient, dict[str, str]]:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-settings.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.init_db()
db.DB_PATH = tmp_path / "jarvischat-settings.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
db.init_db()
client = TestClient(app_module.app)
client = TestClient(app.app)
login = client.post(
"/api/auth/login",
json={"pin": "1234"},
+21 -17
View File
@@ -1,19 +1,23 @@
import asyncio
import os
from pathlib import Path
from fastapi.testclient import TestClient
import app as app_module
import app
import db
from rag import build_system_prompt
from security import SESSIONS, PIN_ATTEMPTS, RATE_EVENTS
def make_client(tmp_path: Path) -> TestClient:
os.environ["JARVISCHAT_ADMIN_PIN"] = "1234"
app_module.DB_PATH = tmp_path / "jarvischat-skills.db"
app_module.SESSIONS.clear()
app_module.PIN_ATTEMPTS.clear()
app_module.RATE_EVENTS.clear()
app_module.init_db()
return TestClient(app_module.app, raise_server_exceptions=False)
db.DB_PATH = tmp_path / "jarvischat-skills.db"
SESSIONS.clear()
PIN_ATTEMPTS.clear()
RATE_EVENTS.clear()
db.init_db()
return TestClient(app.app, raise_server_exceptions=False)
def test_guest_can_list_skills(tmp_path: Path):
@@ -21,7 +25,7 @@ def test_guest_can_list_skills(tmp_path: Path):
sid = client.post("/api/auth/guest", headers={"Origin": "http://testserver"}).json()[
"session_id"
]
resp = client.get("/api/skills", headers={"X-Session-ID": sid})
resp = client.get("/api/skills", headers={"X-Session-ID": sid, "Origin": "http://testserver"})
assert resp.status_code == 200
payload = resp.json()
assert payload["count"] >= 1
@@ -46,7 +50,7 @@ def test_admin_can_toggle_skill_enabled_state(tmp_path: Path):
assert disable.status_code == 200
assert disable.json()["skill"]["enabled"] is False
active = client.get("/api/skills/active", headers={"X-Session-ID": sid})
active = client.get("/api/skills/active", headers={"X-Session-ID": sid, "Origin": "http://testserver"})
assert active.status_code == 200
assert all(skill["key"] != "search.web" for skill in active.json()["skills"])
@@ -71,23 +75,23 @@ def test_unknown_skill_update_is_rejected(tmp_path: Path):
def test_prompt_injection_respects_skills_enabled_setting(tmp_path: Path):
with make_client(tmp_path):
db = app_module.get_db()
conn = db.get_db()
try:
db.execute(
conn.execute(
"INSERT OR REPLACE INTO settings (key, value) VALUES (?, ?)",
("skills_enabled", "false"),
)
db.commit()
without_skills = app_module.build_system_prompt(db, "", "hello")
conn.commit()
without_skills = asyncio.run(build_system_prompt(conn, "", "hello"))
assert "## Active Skills" not in without_skills
db.execute(
conn.execute(
"INSERT OR REPLACE INTO settings (key, value) VALUES (?, ?)",
("skills_enabled", "true"),
)
db.commit()
with_skills = app_module.build_system_prompt(db, "", "hello")
conn.commit()
with_skills = asyncio.run(build_system_prompt(conn, "", "hello"))
assert "## Active Skills" in with_skills
assert "memory.search" in with_skills
finally:
db.close()
conn.close()
+274
View File
@@ -0,0 +1,274 @@
import os
from pathlib import Path
import httpx
import pytest
from fastapi.testclient import TestClient
import app
import db
import routers.upload as upload_route
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"
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"}
def test_upload_requires_admin(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post("/api/upload", headers=_guest_headers(client), files={"file": ("test.txt", b"hello")})
assert resp.status_code == 403
def test_upload_unsupported_mime(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post(
"/api/upload", headers=_admin_headers(client),
files={"file": ("test.exe", b"fake", "application/x-msdownload")},
)
assert resp.status_code == 415
def test_upload_context_mode(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post(
"/api/upload", headers=_admin_headers(client),
data={"mode": "context", "conversation_id": "conv-1"},
files={"file": ("notes.txt", b"Hello world notes")},
)
assert resp.status_code == 200
data = resp.json()
assert data["filename"] == "notes.txt"
assert data["mode"] == "context"
assert "context_id" in data
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"
def test_upload_ingest_mode(tmp_path: Path, monkeypatch):
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/upload", headers=_admin_headers(client),
data={"mode": "ingest"},
files={"file": ("data.txt", b"word " * 1000)},
)
assert resp.status_code == 200
data = resp.json()
assert data["mode"] == "ingest"
assert data["chunks_ingested"] > 0
assert "context_id" not in data
assert embed_count == data["chunks_ingested"]
def test_upload_both_mode(tmp_path: Path, monkeypatch):
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):
if "/api/embeddings" in url:
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/upload", headers=_admin_headers(client),
data={"mode": "both", "conversation_id": "conv-2"},
files={"file": ("both.txt", b"test " * 500)},
)
assert resp.status_code == 200
data = resp.json()
assert data["mode"] == "both"
assert "context_id" in data
assert data["chunks_ingested"] > 0
def test_upload_image_type(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.post(
"/api/upload", headers=_admin_headers(client),
data={"mode": "context"},
files={"file": ("photo.png", b"fake-png", "image/png")},
)
assert resp.status_code == 200
data = resp.json()
assert data["filename"] == "photo.png"
assert "context_id" in data
def test_get_upload_by_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp1 = client.post("/api/upload", headers=headers,
data={"mode": "context", "conversation_id": "conv-gal"},
files={"file": ("a.txt", b"alpha")})
cid1 = resp1.json()["context_id"]
resp2 = client.post("/api/upload", headers=headers,
data={"mode": "context", "conversation_id": "conv-gal"},
files={"file": ("b.txt", b"beta")})
cid2 = resp2.json()["context_id"]
gal = client.get("/api/upload/by-conversation/conv-gal", headers=headers)
assert gal.status_code == 200
items = gal.json()
assert len(items) == 2
assert items[0]["filename"] == "a.txt"
assert items[1]["filename"] == "b.txt"
def test_link_upload_to_conversation(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
resp = client.post("/api/upload", headers=headers,
data={"mode": "context"},
files={"file": ("orphan.txt", b"lonely")})
cid = resp.json()["context_id"]
link = client.patch(f"/api/upload/{cid}/link", headers=headers,
json={"conversation_id": "new-conv"})
assert link.status_code == 200
gal = client.get("/api/upload/by-conversation/new-conv", headers=headers)
assert len(gal.json()) == 1
def test_delete_upload_removes_context(tmp_path: Path, monkeypatch):
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):
if "/points/scroll" in url:
return self.FakeResponse(200, {"result": {"points": [{"id": "upload-test.txt-0"}, {"id": "upload-test.txt-1"}]}})
if "/points/delete" in url:
return self.FakeResponse(200)
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:
headers = _admin_headers(client)
resp = client.post("/api/upload", headers=headers,
data={"mode": "context", "conversation_id": "del-test"},
files={"file": ("test.txt", b"delete me")})
cid = resp.json()["context_id"]
del_resp = client.delete(f"/api/upload/{cid}", headers=headers)
assert del_resp.status_code == 200
assert del_resp.json()["status"] == "ok"
row = db.get_db().execute("SELECT id FROM upload_context WHERE id = ?", (cid,)).fetchone()
assert row is None
def test_delete_upload_not_found(tmp_path: Path):
with make_client(tmp_path) as client:
resp = client.delete("/api/upload/999", headers=_admin_headers(client))
assert resp.status_code == 404
def test_conversation_list_includes_attachment_count(tmp_path: Path):
with make_client(tmp_path) as client:
headers = _admin_headers(client)
client.post("/api/conversations", headers=headers, json={"title": "NoAttach"})
with_attach = client.post("/api/conversations", headers=headers, json={"title": "WithAttach"}).json()
conv_id = with_attach["id"]
client.post("/api/upload", headers=headers,
data={"mode": "context", "conversation_id": conv_id},
files={"file": ("f.txt", b"data")})
list_resp = client.get("/api/conversations", headers=headers)
convs = list_resp.json()
for c in convs:
if c["title"] == "NoAttach":
assert c["attachment_count"] == 0
if c["title"] == "WithAttach":
assert c["attachment_count"] == 1