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File size: 2,964 Bytes
37b0787 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | from __future__ import annotations
import logging
import os
import time
from contextlib import asynccontextmanager
# Force offline mode globally to prevent HuggingFace hub HEAD loops
# Must be set before any sentence-transformers imports
os.environ["HF_HUB_OFFLINE"] = "1"
os.environ["TRANSFORMERS_OFFLINE"] = "1"
from fastapi import FastAPI
from src.api.middleware.logging import RequestLoggingMiddleware
from src.api.middleware.validation import InputValidationMiddleware
from src.api.routes.health import init_health, set_index_size, set_model_loaded
from src.api.routes.health import router as health_router
from src.api.routes.ingest import router as ingest_router
from src.api.routes.profiles import init_profiles
from src.api.routes.profiles import router as profiles_router
from src.api.routes.search import init_orchestrator
from src.api.routes.search import router as search_router
from src.core.config import DATA_DIR, get_settings
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
@asynccontextmanager
async def lifespan(app: FastAPI):
_start_time = time.time()
init_health(index_size=0)
logger.info("Starting India Runs — Intelligent Candidate Discovery")
indexes_dir = DATA_DIR / "indexes"
indexes_dir.mkdir(parents=True, exist_ok=True)
faiss_path = indexes_dir / "faiss_index.bin"
id_map_path = indexes_dir / "faiss_id_map.json"
bm25_path = indexes_dir / "bm25_index.pkl"
if not faiss_path.exists():
logger.warning(
"No FAISS index found. Run 'python scripts/build_indexes.py --sample 50' first."
)
init_health(index_size=0)
yield
return
from src.core.config import build_orchestrator
orchestrator, vector_search, profiles = build_orchestrator(
faiss_path=faiss_path,
id_map_path=id_map_path,
bm25_path=bm25_path,
cross_encoder_timeout_ms=get_settings().cross_encoder_timeout_ms,
)
set_model_loaded("embedding", True)
set_model_loaded("cross_encoder", True) # already handled inside build_orchestrator
init_orchestrator(orchestrator)
set_index_size(vector_search.size)
init_profiles(profiles)
logger.info("System initialized successfully (%.1fs)", time.time() - _start_time)
yield
logger.info("Shutting down")
app = FastAPI(
title="India Runs — Intelligent Candidate Discovery",
description="Hybrid semantic search with agentic AI for candidate matching",
version="0.1.0",
lifespan=lifespan,
)
app.add_middleware(RequestLoggingMiddleware)
app.add_middleware(InputValidationMiddleware)
app.include_router(search_router, prefix="/api/v1")
app.include_router(profiles_router, prefix="/api/v1")
app.include_router(ingest_router, prefix="/api/v1")
app.include_router(health_router, prefix="/api/v1")
if __name__ == "__main__":
import uvicorn
uvicorn.run("src.main:app", host="0.0.0.0", port=8000, log_level="info")
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