- A1: fire the hard filter (Apify is precise); embedding vibe-ranker (embed.py) blends with the floor-free white-box (rank.py) to sift ~90 -> top 18 - A2: Opus curator (curate.py) reads the 18 -> honest <=count + Gemini-voiced report cards; graceful fallback to the white-box + templated cards - LLM via opencode.ai/zen gateway (llm.py): Opus chat + direct-OpenAI embeddings - Run LLM work off the event loop (asyncio.to_thread) so the Redis response publishes - C1: dedicated Postgres (app/db/) persists the per-user feed; get_scout_feed replays it so matches survive navigation/refresh - match contract + report-card fields (schema.py); skills.py; tests/
14 lines
332 B
Plaintext
14 lines
332 B
Plaintext
fastapi>=0.115
|
|
uvicorn[standard]>=0.30
|
|
pydantic>=2.7
|
|
pydantic-settings>=2.3
|
|
httpx>=0.27
|
|
redis>=5.0
|
|
# engine/auto-apply deps land in later slices:
|
|
# openai>=1.40 # GPT-5.4 rerank/explain + tailoring
|
|
# apify-client>=1.7 # on-demand board fetch (or call run-sync via httpx)
|
|
openai>=1.40
|
|
numpy
|
|
sqlalchemy[asyncio]>=2.0
|
|
asyncpg
|