pyr0ball
c81fa3a93a
- Add app/api/endpoints/plex.py with Plex webhook receiver (fail-closed on missing secret) - Add app/services/plex/ with Plex API client and gardening content filter - Wire plex router into routes.py at /plex prefix - Add Plex + cf-video config vars to app/core/config.py and .env.example - Rename /knowledge/ingest endpoint to /knowledge/glean (pipeline verb alignment) - Update tests to use /knowledge/glean endpoint - Add python-multipart to environment.yml for form/webhook body parsing - Add dev/dev-stop/dev-logs commands to manage.sh (hot-reload without Docker) - Fix frontend/tsconfig.node.json to extend tsconfig.json (not tsconfig.node.json) - Add .dev-pids/ to .gitignore - Add frontend/package-lock.json
100 lines
2.7 KiB
Python
100 lines
2.7 KiB
Python
"""cf-harvest knowledge ingest + query endpoints."""
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from __future__ import annotations
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import json
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from typing import Optional
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from fastapi import APIRouter, Depends, HTTPException, Query
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from app.core.config import settings
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from app.db.store import Store
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from app.models.schemas.knowledge import (
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IngestResponse,
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KnowledgeFactOut,
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KnowledgeIngestRequest,
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)
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from app.services.knowledge.ingest import ingest
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router = APIRouter()
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def _get_store() -> Store:
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s = Store(settings.DB_PATH)
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try:
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yield s
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finally:
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s.close()
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@router.post("/glean", response_model=IngestResponse)
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async def ingest_knowledge(
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body: KnowledgeIngestRequest, store: Store = Depends(_get_store)
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):
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return ingest(store.conn, body)
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@router.get("", response_model=list[KnowledgeFactOut])
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async def query_knowledge(
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fact_type: Optional[str] = Query(None),
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subject: Optional[str] = Query(None),
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presenter: Optional[str] = Query(None),
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min_confidence: Optional[float] = Query(None, ge=0.0, le=1.0),
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limit: int = Query(50, ge=1, le=500),
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offset: int = Query(0, ge=0),
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store: Store = Depends(_get_store),
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):
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conditions = []
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params: list = []
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if fact_type:
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conditions.append("kf.fact_type = ?")
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params.append(fact_type)
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if subject:
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conditions.append("kf.subject LIKE ?")
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params.append(f"%{subject}%")
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if presenter:
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conditions.append("kf.presenter LIKE ?")
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params.append(f"%{presenter}%")
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if min_confidence is not None:
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conditions.append("kf.confidence >= ?")
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params.append(min_confidence)
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where = ("WHERE " + " AND ".join(conditions)) if conditions else ""
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params += [limit, offset]
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rows = store.conn.execute(
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f"""
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SELECT kf.*, ks.video_path, ks.location
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FROM knowledge_facts kf
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LEFT JOIN knowledge_sources ks ON ks.id = kf.source_id
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{where}
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ORDER BY kf.created_at DESC
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LIMIT ? OFFSET ?
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""",
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params,
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).fetchall()
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result = []
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for row in rows:
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d = store._row_to_dict(row)
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d["payload"] = json.loads(d["payload"])
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result.append(d)
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return result
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@router.get("/{fact_id}", response_model=KnowledgeFactOut)
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async def get_knowledge_fact(fact_id: int, store: Store = Depends(_get_store)):
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row = store.conn.execute(
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"""
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SELECT kf.*, ks.video_path, ks.location
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FROM knowledge_facts kf
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LEFT JOIN knowledge_sources ks ON ks.id = kf.source_id
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WHERE kf.id = ?
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""",
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(fact_id,),
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).fetchone()
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if not row:
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raise HTTPException(status_code=404, detail="Knowledge fact not found")
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d = store._row_to_dict(row)
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d["payload"] = json.loads(d["payload"])
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return d
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