Files
cAIc/routers/search_route.py
gramps 90d2cf8326 Rename: jarvisChat → cAIc (product name)
- jarvisChat/JarvisChat/jarvischat → cAIc/cAIc/caic (branded/lower)
- JARVISCHAT_ env vars → CAIC_
- jc- script/config prefix → caic-
- jarvis_rag → caic_rag
- jarvischat.db / volumes → caic.db / caic_*
- AMQP vhost/user jarvischat → caic
- Syslog, loggers, docstrings all updated
- 47 files, zero stale references, 148 tests pass
2026-07-06 19:56:32 -07:00

108 lines
4.6 KiB
Python

"""JarvisChat routers - /api/search explicit search endpoint."""
import json
import logging
import uuid
from datetime import datetime, timezone
import httpx
from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import StreamingResponse
from config import DEFAULT_MODEL, LLAMA_SERVER_BASE, MAX_SEARCH_QUERY_CHARS
from db import get_db
from search import query_searxng, format_search_results
from routers.chat import parse_llama_stream_chunk
from security import read_json_body, log_incident, BODY_LIMIT_CHAT_BYTES
log = logging.getLogger("caic")
router = APIRouter()
@router.post("/api/search")
async def explicit_search(request: Request):
body = await read_json_body(request, BODY_LIMIT_CHAT_BYTES)
query = body.get("query", "").strip()
if len(query) > MAX_SEARCH_QUERY_CHARS:
raise HTTPException(status_code=413, detail="Search query is too long")
conv_id = body.get("conversation_id")
model = body.get("model", DEFAULT_MODEL)
if not query:
raise HTTPException(status_code=400, detail="Empty query")
db = get_db()
now = datetime.now(timezone.utc).isoformat()
if not conv_id:
conv_id = str(uuid.uuid4())
title = query[:70] + "..." if len(query) > 70 else query
db.execute("INSERT INTO conversations (id, title, model, created_at, updated_at) VALUES (?, ?, ?, ?, ?)",
(conv_id, title, model, now, now))
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", query, now))
db.commit()
db.close()
async def stream_search():
yield f"data: {json.dumps({'conversation_id': conv_id, 'searching': True})}\n\n"
results = await query_searxng(query, max_results=5)
if not results:
error_msg = "No search results found."
yield f"data: {json.dumps({'token': error_msg, 'conversation_id': conv_id})}\n\n"
db2 = get_db()
db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
(conv_id, "assistant", error_msg, datetime.now(timezone.utc).isoformat()))
db2.commit()
db2.close()
yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id})}\n\n"
return
yield f"data: {json.dumps({'search_results': len(results), 'conversation_id': conv_id})}\n\n"
search_context = format_search_results(results)
messages = [
{"role": "system", "content": f"You have access to current web data. Answer directly using ONLY the data below. Be concise. No apologies. No disclaimers.\n\n{search_context}"},
{"role": "user", "content": query},
]
full_response = []
async with httpx.AsyncClient() as client:
try:
async with client.stream(
"POST", f"{LLAMA_SERVER_BASE}/v1/chat/completions",
json={"model": model, "messages": messages, "stream": True},
timeout=httpx.Timeout(300.0, connect=10.0),
) as resp:
async for line in resp.aiter_lines():
if line.strip():
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"
if done:
break
except Exception as e:
incident_key = log_incident("search_summarization_stream",
message="Stream failure during explicit search summarization",
request=request, exc=e)
yield f"data: {json.dumps({'error': 'Search summarization could not complete right now.', 'error_key': incident_key})}\n\n"
return
summary = "".join(full_response)
saved_msg = f"{summary}\n\n---\n*🔍 Web search results*"
db2 = get_db()
db2.execute("INSERT INTO messages (conversation_id, role, content, created_at) VALUES (?, ?, ?, ?)",
(conv_id, "assistant", saved_msg, datetime.now(timezone.utc).isoformat()))
db2.commit()
db2.close()
yield f"data: {json.dumps({'done': True, 'conversation_id': conv_id, 'searched': True})}\n\n"
return StreamingResponse(stream_search(), media_type="text/event-stream")