Files
cAIc/routers/ingest.py
T
gramps 8072fb3dd0 feat: Roadmap K — RAG corpus management with score-based eviction (v0.13.0)
- Config: RAG_MAX_VECTORS, high/low water marks, grace period, weights
- rag.py: get_collection_count, evict_batch, maybe_evict (asyncio.Lock),
  get_rag_operational_stats, EVICTION_LOG, retrieval_count tracking
- routers/rag_admin.py: GET /api/rag/stats, POST /api/rag/flush (admin)
- Wire maybe_evict() into upload.py and ingest.py after Qdrant upsert
- 16 tests: collection stats, eviction scoring, pinned/grace/batch guards,
  endpoint auth, race lock, flush, operational stats shape
- Bump to v0.13.0
2026-07-06 07:56:09 -07:00

70 lines
2.7 KiB
Python

"""JarvisChat routers - /api/ingest terminal command RAG hook."""
import logging
from datetime import datetime, timezone
import httpx
from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import JSONResponse
from config import COMPLETIONS_API_KEY
from rag import chunk_text, maybe_evict, QDRANT_URL, EMBED_URL, EMBED_MODEL, RAG_COLLECTION
log = logging.getLogger("jarvischat")
router = APIRouter()
def _check_api_key(request: Request):
auth = request.headers.get("Authorization", "")
if not auth.startswith("Bearer "):
raise HTTPException(status_code=401, detail="Missing Bearer token")
token = auth[7:].strip()
if token != COMPLETIONS_API_KEY:
raise HTTPException(status_code=401, detail="Invalid API key")
@router.post("/api/ingest")
async def ingest_content(request: Request):
_check_api_key(request)
body = await request.json()
content = (body.get("content") or "").strip()
if not content:
raise HTTPException(status_code=422, detail="content is required")
source = str(body.get("source", "external")).strip() or "external"
metadata = body.get("metadata") or {}
chunks = chunk_text(content)
if not chunks:
raise HTTPException(status_code=422, detail="content produced no chunks")
ingested = 0
async with httpx.AsyncClient() as client:
for i, chunk in enumerate(chunks):
embed_resp = await client.post(
f"{EMBED_URL}/api/embeddings",
json={"model": EMBED_MODEL, "prompt": chunk},
timeout=30.0,
)
if embed_resp.status_code != 200:
log.warning(f"Ingest embedding failed for chunk {i}: {embed_resp.status_code}")
continue
vector = embed_resp.json()["embedding"]
point_id = f"ingest-{source}-{datetime.now(timezone.utc).timestamp()}-{i}"
payload = {"text": chunk, "source": source, "ingest_date": datetime.now(timezone.utc).isoformat(), "type": "ingest"}
payload.update(metadata)
upsert_resp = await client.put(
f"{QDRANT_URL}/collections/{RAG_COLLECTION}/points?wait=true",
json={"points": [{"id": point_id, "vector": vector, "payload": payload}]},
timeout=30.0,
)
if upsert_resp.status_code in (200, 201):
ingested += 1
else:
log.warning(f"Ingest Qdrant upsert failed for chunk {i}: {upsert_resp.status_code}")
if ingested > 0:
evicted = await maybe_evict()
if evicted:
log.info(f"Evicted {evicted} vectors after ingest")
return {"chunks_ingested": ingested, "source": source, "message": f"Ingested {ingested} chunks from {source}"}