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

routers/chat.py

@@ -1,4 +1,5 @@
 """JarvisChat routers - /api/chat streaming endpoint."""
+import asyncio
 import json
 import logging
 import uuid
@@ -10,8 +11,8 @@ from fastapi.responses import StreamingResponse
 
 from config import DEFAULT_MODEL, LLAMA_SERVER_BASE
 from db import get_db, get_upload_context
-from memory import process_remember_command
-from rag import build_system_prompt
+from memory import process_remember_command, auto_detect_facts, check_fact_conflicts
+from rag import build_system_prompt, ingest_auto_fact
 from search import (calculate_perplexity, is_uncertain, is_refusal,
                     clean_hedging, format_search_results, format_direct_answer,
                     extract_search_query, query_searxng)
@@ -127,6 +128,7 @@ async def chat(request: Request):
         tokens_per_sec = 0.0
         completion_tokens = 0
         prompt_tokens = 0
+        rag_update = None
 
         if remember_response:
             yield f"data: {json.dumps({'token': remember_response + chr(10) + chr(10), 'conversation_id': conv_id})}\n\n"
@@ -204,7 +206,15 @@ async def chat(request: Request):
                         db2.commit()
                         db2.close()
 
-                        yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH})}\n\n"
+                        facts = auto_detect_facts(user_message, cleaned_response)
+                        if facts:
+                            conflicts = check_fact_conflicts(facts)
+                            if conflicts:
+                                rag_update = {"conflicts": conflicts}
+                            else:
+                                asyncio.ensure_future(ingest_auto_fact(facts, user_message, cleaned_response))
+
+                        yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
                         return
 
                 saved_msg = assistant_msg
@@ -217,7 +227,15 @@ async def chat(request: Request):
                 db2.commit()
                 db2.close()
 
-                yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH})}\n\n"
+                facts = auto_detect_facts(user_message, assistant_msg)
+                if facts:
+                    conflicts = check_fact_conflicts(facts)
+                    if conflicts:
+                        rag_update = {"conflicts": conflicts}
+                    else:
+                        asyncio.ensure_future(ingest_auto_fact(facts, user_message, assistant_msg))
+
+                yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'perplexity': round(perplexity, 2), 'tokens_per_sec': round(tokens_per_sec, 1), 'prompt_tokens': prompt_tokens, 'completion_tokens': completion_tokens, 'context_length': MODEL_CONTEXT_LENGTH, **(rag_update and {'rag_update_suggestion': rag_update} or {})})}\n\n"
 
             except httpx.RemoteProtocolError:
                 pass

routers/memories.py

@@ -4,6 +4,7 @@ from typing import Optional
 
 from db import get_db
 from memory import add_memory, delete_memory, update_memory, get_all_memories, search_memories
+from rag import confirm_fact_update
 from security import read_json_body, BODY_LIMIT_DEFAULT_BYTES
 from config import MAX_MEMORY_FACT_CHARS
 
@@ -54,6 +55,22 @@ async def search_memories_api(q: str, limit: int = 10):
     return {"results": results, "count": len(results)}
 
 
+@router.post("/api/memories/confirm-update")
+async def confirm_memory_update(request: Request):
+    body = await read_json_body(request, BODY_LIMIT_DEFAULT_BYTES)
+    memory_id = body.get("memory_id")
+    new_fact = str(body.get("new_fact", "")).strip()
+    old_fact = str(body.get("old_fact", "")).strip()
+    user_message = str(body.get("user_message", "")).strip()
+    assistant_message = str(body.get("assistant_message", "")).strip()
+    if not memory_id or not new_fact:
+        raise HTTPException(status_code=400, detail="memory_id and new_fact are required")
+    ok = await confirm_fact_update(memory_id, old_fact, new_fact, user_message, assistant_message)
+    if not ok:
+        raise HTTPException(status_code=404, detail="Memory not found")
+    return {"status": "ok"}
+
+
 @router.get("/api/memories/stats")
 async def memory_stats():
     db = get_db()