v0.17.2: auto-fact detection with conflict-alert flow
- auto_detect_facts() scans chat turns for factual content (IPs, paths, services, config changes, hardware refs) using pattern matching - check_fact_conflicts() cross-references detected facts against stored FTS5 memories — when a contradiction exists (same topic, diff value) the system surfaces a rag_update_suggestion in the done SSE payload - Frontend shows a floating notification banner comparing old vs new fact with Update/Dismiss buttons - confirm_fact_update() replaces the memory + re-embeds/re-indexes the Qdraft entry on user confirmation - Silent auto-ingest (memories + Qdrant) when no conflict exists - Frontend: msg-toolbar opacity 0→0.35 for visibility
This commit is contained in:
gramps
@@ -9,7 +9,7 @@ import logging
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log = logging.getLogger("caic")
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VERSION = "v0.17.1"
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VERSION = "v0.17.2"
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OLLAMA_BASE = os.environ.get("OLLAMA_BASE", "http://localhost:11434")
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LLAMA_SERVER_BASE = os.environ.get("LLAMA_SERVER_BASE", "http://192.168.50.108:8081")
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SEARXNG_BASE = "http://localhost:8888"
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@@ -27,6 +27,80 @@ FORGET_PATTERNS = [
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]
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AUTO_FACT_PATTERNS = [
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re.compile(r"\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b"),
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re.compile(r"\b(?:systemd|nginx|docker|ssh|ufw|iptables|postgres(?:ql)?|redis|mosquitto|node_exporter|prometheus|grafana|qdrant|rabbitmq|searxng|llama-server)\b", re.IGNORECASE),
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re.compile(r"/(?:etc|home|usr|var|opt|tmp|mnt)/\S+"),
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re.compile(r"\b(?:Ryzen|RX\s*\d{4}|RTX\s*\d{4}|Radeon|AMD|NVIDIA|Core\s*i[579]|Threadripper)\b", re.IGNORECASE),
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re.compile(r"\b(?:Qwen|Llama|Gemma|Phi|Mistral|DeepSeek)\S*\b", re.IGNORECASE),
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re.compile(r"\b(?:systemd\.service|docker\s+(?:compose|container|service)|systemctl|journalctl)\b", re.IGNORECASE),
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]
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SOCIAL_TRIGGERS = {"hi", "hello", "hey", "yo", "sup", "howdy", "good morning", "good evening"}
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def _is_social(text: str) -> bool:
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t = text.strip().lower()
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if t in SOCIAL_TRIGGERS or any(t.startswith(w) for w in ("thanks", "thank you", "ty")):
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return True
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return False
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def auto_detect_facts(user_message: str, assistant_message: str) -> list[str]:
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"""Extract environmental/factual content from a chat turn.
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Returns a list of fact strings ready for storage. Empty list means
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nothing worth persisting.
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"""
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if _is_social(user_message):
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return []
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if len(assistant_message) < 40:
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return []
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if process_remember_command(user_message) is not None:
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return []
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found = []
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for pat in AUTO_FACT_PATTERNS:
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if pat.search(user_message):
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found.append(user_message)
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break
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# Also capture when the user is reporting a change they made
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change_match = re.search(
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r"(?:I\s+)?(?:set|changed?|updated|installed|configured|enabled|disabled|added|removed|created|deleted|restarted|reloaded|switched|moved|copied|renamed|symlinked|mounted|unmounted)\s+(?:the\s+)?(.+)",
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user_message, re.IGNORECASE,
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)
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if change_match and user_message not in found:
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found.append(user_message)
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seen = set()
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deduped = []
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for f in found:
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key = f.strip().lower()
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if key not in seen:
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seen.add(key)
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deduped.append(f.strip()[:MAX_MEMORY_FACT_CHARS])
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return deduped
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def check_fact_conflicts(facts: list[str]) -> list[dict]:
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"""Search for existing memories that conflict with detected facts.
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Returns list of {memory_id, old_fact, new_fact} for each conflict.
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"""
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conflicts = []
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for new_fact in facts:
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related = search_memories(new_fact, limit=1)
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if related:
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old = related[0]["fact"]
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if old.rstrip(".") != new_fact.rstrip("."):
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conflicts.append({
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"memory_id": related[0]["rowid"],
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"old_fact": old,
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"new_fact": new_fact,
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})
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return conflicts
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def detect_topic(fact: str) -> str:
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fact_lower = fact.lower()
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if any(w in fact_lower for w in ["prefer", "like", "hate", "always", "never", "favorite"]):
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@@ -3,6 +3,7 @@ cAIc - RAG pipeline: Qdrant vector search + system prompt assembly.
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"""
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import asyncio
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import logging
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from datetime import datetime, timezone
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import httpx
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@@ -24,6 +25,103 @@ from eviction import ( # noqa: E402
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)
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async def _upsert_fact(fact: str, text: str, topic: str,
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client: httpx.AsyncClient) -> bool:
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"""Embed text and upsert a fact to Qdrant."""
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chunks = chunk_text(text)
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if not chunks:
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return False
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ts = datetime.now(timezone.utc).timestamp()
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ok = False
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for i, chunk in enumerate(chunks):
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try:
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er = await client.post(
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f"{EMBED_URL}/api/embeddings",
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json={"model": EMBED_MODEL, "prompt": chunk},
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timeout=10.0,
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)
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if er.status_code != 200:
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continue
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vector = er.json()["embedding"]
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pid = f"auto-{ts}-{i}"
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payload = {
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"text": chunk, "source": "auto_fact", "fact": fact,
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"ingest_date": datetime.now(timezone.utc).isoformat(),
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"type": "auto_fact", "topic": topic,
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}
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r = await client.put(
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f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
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json={"points": [{"id": pid, "vector": vector, "payload": payload}]},
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timeout=10.0,
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)
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if r.status_code in (200, 201):
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ok = True
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except Exception as e:
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log.warning(f"Qdrant upsert error: {e}")
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return ok
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async def ingest_auto_fact(facts: list[str], user_message: str,
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assistant_message: str) -> int:
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"""Persist pre-detected facts to memories + Qdrant.
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Call this when no conflicts exist — silent ingest.
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Returns the number of facts stored.
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"""
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from memory import add_memory, detect_topic
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ingested = 0
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async with httpx.AsyncClient() as client:
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for fact in facts:
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topic = detect_topic(fact)
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add_memory(fact, topic=topic, source="auto")
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ingested += 1
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text = f"Q: {user_message}\nA: {assistant_message}"
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await _upsert_fact(fact, text, topic, client)
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if ingested:
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log.info(f"Auto-ingested {ingested} fact(s) from conversation")
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return ingested
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async def confirm_fact_update(memory_id: int, old_fact: str, new_fact: str,
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user_message: str, assistant_message: str) -> bool:
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"""Confirm a user-accepted fact update: replace memory + Qdrant entry."""
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from memory import update_memory, detect_topic
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if not update_memory(memory_id, new_fact):
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return False
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topic = detect_topic(new_fact)
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try:
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async with httpx.AsyncClient() as client:
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# scroll old points with matching fact and delete them
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scroll_r = await client.post(
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f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/scroll",
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json={
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"filter": {"must": [{"key": "fact", "match": {"value": old_fact}}]},
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"limit": 100,
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"with_payload": False,
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},
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timeout=10.0,
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)
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if scroll_r.status_code == 200:
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ids = [p["id"] for p in scroll_r.json().get("result", [])]
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if ids:
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await client.post(
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f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points/delete",
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json={"points": ids},
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timeout=10.0,
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)
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text = f"Q: {user_message}\nA: {assistant_message}"
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await _upsert_fact(new_fact, text, topic, client)
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except Exception as e:
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log.warning(f"Fact update RAG error: {e}")
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log.info(f"Fact updated [memory_id={memory_id}]: {new_fact}")
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return True
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def chunk_text(text: str, chunk_size: int = 512, overlap: int = 128) -> list:
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words = text.split()
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target_words = int(chunk_size / 1.3)
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+22
-4
@@ -1,4 +1,5 @@
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"""JarvisChat routers - /api/chat streaming endpoint."""
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import asyncio
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import json
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import logging
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import uuid
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@@ -10,8 +11,8 @@ from fastapi.responses import StreamingResponse
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from config import DEFAULT_MODEL, LLAMA_SERVER_BASE
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from db import get_db, get_upload_context
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from memory import process_remember_command
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from rag import build_system_prompt
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from memory import process_remember_command, auto_detect_facts, check_fact_conflicts
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from rag import build_system_prompt, ingest_auto_fact
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from search import (calculate_perplexity, is_uncertain, is_refusal,
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clean_hedging, format_search_results, format_direct_answer,
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extract_search_query, query_searxng)
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@@ -127,6 +128,7 @@ async def chat(request: Request):
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tokens_per_sec = 0.0
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completion_tokens = 0
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prompt_tokens = 0
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rag_update = None
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if remember_response:
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yield f"data: {json.dumps({'token': remember_response + chr(10) + chr(10), 'conversation_id': conv_id})}\n\n"
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@@ -204,7 +206,15 @@ async def chat(request: Request):
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db2.commit()
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db2.close()
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yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH})}\n\n"
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facts = auto_detect_facts(user_message, cleaned_response)
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if facts:
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conflicts = check_fact_conflicts(facts)
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if conflicts:
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rag_update = {"conflicts": conflicts}
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else:
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asyncio.ensure_future(ingest_auto_fact(facts, user_message, cleaned_response))
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yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
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return
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saved_msg = assistant_msg
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@@ -217,7 +227,15 @@ async def chat(request: Request):
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db2.commit()
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db2.close()
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yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH})}\n\n"
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facts = auto_detect_facts(user_message, assistant_msg)
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if facts:
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conflicts = check_fact_conflicts(facts)
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if conflicts:
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rag_update = {"conflicts": conflicts}
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else:
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asyncio.ensure_future(ingest_auto_fact(facts, user_message, assistant_msg))
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yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
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except httpx.RemoteProtocolError:
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pass
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@@ -4,6 +4,7 @@ from typing import Optional
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from db import get_db
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from memory import add_memory, delete_memory, update_memory, get_all_memories, search_memories
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from rag import confirm_fact_update
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from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
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from config import MAX_MEMORY_FACT_CHARS
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@@ -54,6 +55,22 @@ async def search_memories_api(q: str, limit: int = 10):
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return {"results": results, "count": len(results)}
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@router.post("/api/memories/confirm-update")
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async def confirm_memory_update(request: Request):
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body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
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memory_id = body.get("memory_id")
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new_fact = str(body.get("new_fact", "")).strip()
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old_fact = str(body.get("old_fact", "")).strip()
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user_message = str(body.get("user_message", "")).strip()
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assistant_message = str(body.get("assistant_message", "")).strip()
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if not memory_id or not new_fact:
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raise HTTPException(status_code=400, detail="memory_id and new_fact are required")
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ok = await confirm_fact_update(memory_id, old_fact, new_fact, user_message, assistant_message)
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if not ok:
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raise HTTPException(status_code=404, detail="Memory not found")
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return {"status": "ok"}
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@router.get("/api/memories/stats")
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async def memory_stats():
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db = get_db()
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+56
-1
@@ -1418,6 +1418,9 @@ async function sendMessage() {
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addCopyButtons(assistantDiv);
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addMessageToolbar(assistantDiv);
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setStreamingState(false);
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if (data.rag_update_suggestion && data.rag_update_suggestion.conflicts) {
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showFactConflictBanner(data.rag_update_suggestion.conflicts, data.conversation_id);
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}
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await loadConversations();
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await loadMemoryStats();
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checkOllamaStatus();
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@@ -1609,8 +1612,60 @@ userInput.addEventListener('keydown', e => {
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}
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});
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const toastStyle = document.createElement('style');
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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)} }';
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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)} } .fact-conflict-banner { position:fixed; bottom:80px; left:50%; transform:translateX(-50%); background:var(--bg-secondary); border:1px solid var(--accent); border-radius:var(--radius); padding:12px 20px; font-family:var(--font-body); font-size:13px; z-index:9999; box-shadow:0 4px 20px rgba(0,0,0,0.3); max-width:600px; line-height:1.5; } .fact-conflict-banner .actions { margin-top:8px; display:flex; gap:8px; } .fact-conflict-banner button { padding:4px 14px; border-radius:var(--radius); cursor:pointer; font-size:12px; } .fact-conflict-banner .btn-confirm { background:var(--accent); color:var(--bg-primary); border:none; } .fact-conflict-banner .btn-dismiss { background:transparent; color:var(--text-muted); border:1px solid var(--border); }';
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document.head.appendChild(toastStyle);
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function showFactConflictBanner(conflicts, convId) {
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if (!conflicts || !conflicts.length) return;
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const existing = document.querySelector('.fact-conflict-banner');
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if (existing) existing.remove();
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let html = '<div class="fact-conflict-banner">';
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html += '<strong>📝 Knowledge conflict detected</strong>';
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html += '<div style="margin-top:6px;font-size:12px;color:var(--text-muted);">';
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conflicts.forEach((c, i) => {
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html += `<div style="margin-top:${i>0?'8':'4'}px">`;
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html += `<div><span style="color:var(--text-muted)">Stored:</span> ${escapeHtml(c.old_fact)}</div>`;
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html += `<div><span style="color:var(--accent)">Now:</span> ${escapeHtml(c.new_fact)}</div>`;
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html += '<div class="actions">';
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html += `<button class="btn-confirm" onclick="confirmFactUpdate(${c.memory_id},${Date.now()},this)">Update knowledge</button>`;
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html += '<button class="btn-dismiss" onclick="this.closest(\'.fact-conflict-banner\').remove()">Dismiss</button>';
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html += '</div></div>';
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});
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html += '</div></div>';
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document.body.insertAdjacentHTML('beforeend', html);
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}
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async function confirmFactUpdate(memoryId, ts, btn) {
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const banner = btn.closest('.fact-conflict-banner');
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const text = banner ? banner.textContent : '';
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const lines = text.split('\n').map(l => l.trim()).filter(l => l);
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const newFact = lines.length > 0 ? lines[lines.length-1].replace(/^Now:\s*/, '') : '';
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btn.textContent = 'Updating...';
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btn.disabled = true;
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try {
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const resp = await authFetch('/api/memories/confirm-update', {
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method: 'POST',
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headers: {'Content-Type': 'application/json'},
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body: JSON.stringify({
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memory_id: memoryId,
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new_fact: newFact,
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old_fact: '',
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user_message: '',
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assistant_message: '',
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}),
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});
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if (resp.ok) {
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btn.textContent = '✓ Updated';
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setTimeout(() => { if (banner) banner.remove(); }, 1500);
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} else {
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btn.textContent = 'Failed';
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btn.style.background = 'var(--danger)';
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}
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} catch(e) {
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btn.textContent = 'Error';
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btn.style.background = 'var(--danger)';
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}
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}
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userInput.addEventListener('paste', e => {
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const hasImage = Array.from(e.clipboardData.items).some(i => i.type.startsWith('image/'));
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if (hasImage) {
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Reference in New Issue
Block a user