Full backend service with: - FastAPI REST API with CRUD, search, reprocess endpoints - PostgreSQL + pgvector for items and semantic search - Redis + RQ for background job processing - Meilisearch for fast keyword/filter search - Browserless/Chrome for JS rendering and screenshots - OpenAI structured output for AI classification - Local file storage with S3-ready abstraction - Gateway auth via X-Gateway-User-Id header - Own docker-compose stack (6 containers) Classification: fixed folders (Home/Family/Work/Travel/Knowledge/Faith/Projects) and fixed tags (28 predefined). AI assigns exactly 1 folder, 2-3 tags, title, summary, and confidence score per item. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
42 lines
1.1 KiB
Python
42 lines
1.1 KiB
Python
"""Brain service — FastAPI entrypoint."""
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import logging
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from app.api.routes import router
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from app.config import DEBUG
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logging.basicConfig(
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level=logging.DEBUG if DEBUG else logging.INFO,
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format="%(asctime)s %(levelname)s %(name)s: %(message)s",
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)
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app = FastAPI(
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title="Second Brain",
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description="Save everything. AI classifies it. Search it later.",
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version="1.0.0",
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docs_url="/api/docs" if DEBUG else None,
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redoc_url=None,
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)
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# No CORS — internal service only, accessed via gateway
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app.include_router(router)
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@app.on_event("startup")
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async def startup():
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from app.database import engine, Base
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from app.models.item import Item, ItemAsset, AppLink # noqa: import to register models
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# Create tables if they don't exist
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async with engine.begin() as conn:
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await conn.run_sync(Base.metadata.create_all)
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# Ensure Meilisearch index exists
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from app.search.engine import ensure_meili_index
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await ensure_meili_index()
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logging.getLogger(__name__).info("Brain service started")
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