Files
api/app/api/routes/chat.py
2026-04-18 22:18:53 +02:00

117 lines
3.6 KiB
Python

"""Chat routes: POST /chat (REST fallback) and POST /chat/embed (text → vector).
WebSocket chat is handled by the unified device WS endpoint (/api/v1/ws/device).
"""
from __future__ import annotations
import uuid
from typing import Literal
from fastapi import APIRouter, Depends, HTTPException
from fastapi.responses import JSONResponse
from pydantic import BaseModel
from app.api.deps import get_current_user
from app.core.brief_agent import run_home_brief, run_project_brief
from app.core.deep_agent import run_home
from app.core.llm import embed
from app.core.memory_middleware import MemoryMiddleware
from app.db import async_session
from app.schemas import ChatRequest, UserProfile
router = APIRouter(prefix="/chat", tags=["chat"])
# ── Embed helpers ─────────────────────────────────────────────────────────
class _EmbedRequest(BaseModel):
text: str
class _EmbedResponse(BaseModel):
vector: list[float]
# ── Endpoints ─────────────────────────────────────────────────────────────
@router.post("")
async def chat(
body: ChatRequest,
current_user: UserProfile = Depends(get_current_user),
) -> JSONResponse:
"""REST fallback for home chat when websocket streaming is unavailable."""
response = await run_home(
user_id=current_user.id,
message=body.message,
context=body.context.model_dump(),
)
return JSONResponse(content={"response": response})
class _BriefRequest(BaseModel):
mode: Literal["home", "project"]
project_id: str | None = None
class _BriefResponse(BaseModel):
response: str
@router.post("/brief", response_model=_BriefResponse)
async def brief(
body: _BriefRequest,
current_user: UserProfile = Depends(get_current_user),
) -> _BriefResponse:
"""REST fallback for brief when the device WebSocket is not ready."""
if body.mode == "project":
if not body.project_id:
raise HTTPException(status_code=422, detail="project_id required for project mode")
try:
uuid.UUID(body.project_id)
except ValueError:
raise HTTPException(status_code=422, detail="project_id must be a valid UUID")
request_id = str(uuid.uuid4())
async with async_session() as db:
memory = MemoryMiddleware(db)
memory_context = await memory.enrich_context(
current_user.id,
"",
trace_id=request_id,
session_id=request_id,
)
context: dict = {
"_debug": {"request_id": request_id, "user_id": current_user.id},
**memory_context,
}
chunks: list[str] = []
if body.mode == "project":
stream = run_project_brief(current_user.id, body.project_id, context) # type: ignore[arg-type]
else:
stream = run_home_brief(current_user.id, context)
async for event_type, data in stream:
if event_type == "token" and data:
chunks.append(str(data))
return _BriefResponse(response="".join(chunks))
@router.post("/embed", response_model=_EmbedResponse)
async def embed_text(
body: _EmbedRequest,
current_user: UserProfile = Depends(get_current_user),
) -> _EmbedResponse:
"""Generate a 1536-dim embedding vector for the given text.
Uses ``text-embedding-3-small`` via OpenAI. Auth required (JWT).
Used by Electron (vectordb.ts) for local note search.
"""
vector = await embed(body.text)
return _EmbedResponse(vector=vector)