Implements Option A from the issue design: each cloud user gets their own
data directory (DATA_DIR/users/{user_id}/) with separate pagepiper.db,
pagepiper_vecs.db, uploads/, and books/. Local mode is unchanged.
Key changes:
- app/startup.py: extract apply_migrations, reembed_docs,
check_and_rebuild_vec_schema out of main.py (no circular imports)
- app/config.py: add LOCAL_USER_ID constant and user_data_dir() helper
- app/cloud_session.py: extract resolve_authenticated_user(); require_paid_tier
now returns user_id (str) instead of None
- app/deps.py: add UserCtx dataclass (db_path, vec_db_path, data_dir,
watch_dir, bm25) + get_user_ctx dependency; per-user startup guard runs
migrations + vec schema check once per process per user
- app/main.py: _bm25 singleton -> _bm25_map dict keyed by user_id;
add _get_bm25_for(); lifespan only runs startup checks in local mode
- app/api/library.py, search.py, chat.py: thread UserCtx through all
endpoints; remove module-level _mark_bm25_dirty injection pattern
- tests/conftest.py: override get_user_ctx in addition to get_db so all
endpoints get a consistent test UserCtx
153 lines
3.9 KiB
Python
153 lines
3.9 KiB
Python
# app/api/chat.py
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"""
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RAG chat endpoint — retrieves relevant page chunks and synthesizes an answer.
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BSL 1.1 — BYOK gate: requires PAGEPIPER_OLLAMA_URL or a Paid tier license.
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Returns 402 with clear upgrade message if neither is configured.
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"""
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from __future__ import annotations
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import logging
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import os
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from fastapi import APIRouter, Depends, HTTPException
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from pydantic import BaseModel
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from app.cloud_session import require_paid_tier
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from app.deps import UserCtx, get_user_ctx
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from app.services.retriever import Retriever
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from app.services.synthesizer import Synthesizer
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/chat", tags=["chat"])
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class ChatTurn(BaseModel):
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role: str # "user" | "assistant"
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content: str
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class ChatRequest(BaseModel):
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message: str
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history: list[ChatTurn] = []
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doc_ids: list[str] | None = None
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top_k: int = 10
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class ChatResponse(BaseModel):
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answer: str
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citations: list[dict]
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class ChatFeedbackRequest(BaseModel):
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rating: int # 1 = thumbs up, -1 = thumbs down
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question: str = ""
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answer: str = ""
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doc_ids: list[str] = []
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def _get_llm_router():
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"""Return LLMRouter if Ollama configured, else None."""
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from app.config import get_llm_config
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cfg = get_llm_config()
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if cfg is None:
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return None
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from circuitforge_core.llm import LLMRouter
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return LLMRouter(cfg)
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def _require_llm():
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"""Return LLMRouter or raise 402."""
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llm = _get_llm_router()
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if llm is None:
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raise HTTPException(
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status_code=402,
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detail={
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"error": "ollama_required",
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"message": (
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"RAG chat requires Ollama. Set PAGEPIPER_OLLAMA_URL in your .env file, "
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"then restart. Run: ollama pull nomic-embed-text && ollama pull mistral:7b"
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),
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},
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)
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return llm
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@router.post("")
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def chat(
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req: ChatRequest,
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ctx: UserCtx = Depends(get_user_ctx),
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_tier: str = Depends(require_paid_tier),
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) -> ChatResponse:
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llm = _require_llm()
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retriever = Retriever(ctx.bm25)
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chunks = retriever.hybrid_search(
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query=req.message,
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top_k=req.top_k,
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doc_ids=req.doc_ids,
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db_path=ctx.db_path,
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vec_db_path=ctx.vec_db_path,
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llm=llm,
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)
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if not chunks:
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return ChatResponse(
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answer=(
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"I couldn't find any relevant passages. "
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"Try a different query or check which documents are indexed."
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),
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citations=[],
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)
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synth = Synthesizer(llm)
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result = synth.synthesize(
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message=req.message,
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history=[t.model_dump() for t in req.history],
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chunks=chunks,
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)
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return ChatResponse(
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answer=result.answer,
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citations=[
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{
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"doc_id": c.doc_id,
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"page_number": c.page_number,
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"snippet": c.snippet,
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"bm25_score": c.bm25_score,
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}
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for c in result.citations
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],
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)
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@router.get("/feedback/status")
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def chat_feedback_status() -> dict:
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enabled = os.environ.get("PAGEPIPER_CHAT_FEEDBACK", "").lower() in ("1", "true", "yes")
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return {"enabled": enabled}
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@router.post("/feedback")
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def submit_chat_feedback(
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req: ChatFeedbackRequest,
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ctx: UserCtx = Depends(get_user_ctx),
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) -> dict:
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import json
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import sqlite3
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if req.rating not in (1, -1):
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from fastapi import HTTPException
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raise HTTPException(status_code=422, detail="rating must be 1 or -1")
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con = sqlite3.connect(ctx.db_path)
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try:
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con.execute(
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"INSERT INTO chat_feedback (rating, question, answer, doc_ids) VALUES (?, ?, ?, ?)",
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(req.rating, req.question[:2000], req.answer[:4000], json.dumps(req.doc_ids)),
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)
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con.commit()
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finally:
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con.close()
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return {"ok": True}
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