Spaces:
Sleeping
Sleeping
File size: 4,940 Bytes
19dc325 | 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 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 | from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from app.core.config import settings
from app.api.router import api_router
app = FastAPI(
title=settings.PROJECT_NAME,
openapi_url=f"{settings.API_V1_STR}/openapi.json"
)
# Set all CORS enabled origins
from app.db.base import Base
from app.db.session import engine
from app.models.resume import Resume
from app.models.score import ResumeScore
from app.models.user import User
# Create tables (Moved to startup event)
# Base.metadata.create_all(bind=engine)
import asyncio
@app.on_event("startup")
async def startup_event():
print("Server ready")
async def load_models_background():
print("Models loading in background...")
try:
# 1. Initialize DB
Base.metadata.create_all(bind=engine)
print("Database initialized.")
# Models will load lazily on usage, saving startup memory.
# print("Loading Embedding Model...")
# EmbeddingService().load_model()
# print("Embedding Model loaded.")
# print("Initializing Vector Store...")
# FAISSStore().initialize()
# print("Vector Store initialized.")
# 2. Rebuild FAISS index from DB if needed (Stateless Recovery)
from app.vectorstore.faiss_store import FAISSStore
from app.services.embedding_service import EmbeddingService
from app.db.session import SessionLocal
faiss_store = FAISSStore()
faiss_store.initialize()
db = SessionLocal()
try:
db_resumes = db.query(Resume).all()
if db_resumes:
print(f"Startup check: Found {len(db_resumes)} resumes in database.")
unique_faiss_resumes = faiss_store.get_all_resumes()
unique_faiss_ids = {r.get("resume_id") for r in unique_faiss_resumes if r.get("resume_id")}
missing_resumes = [r for r in db_resumes if r.resume_id not in unique_faiss_ids]
if missing_resumes:
print(f"Rebuilding FAISS index: {len(missing_resumes)} resumes are missing from the FAISS store. Indexing...")
embedding_service = EmbeddingService()
embedding_service.load_model()
for resume in missing_resumes:
if resume.extracted_text:
print(f"Generating embeddings and indexing resume: {resume.filename} (v{resume.version_number})")
embeddings = embedding_service.generate_embeddings(resume.extracted_text)
base_metadata = {
"source": resume.filepath,
"page_count": 0,
"author": None,
"creation_date": None,
"producer": None,
"resume_id": resume.resume_id,
"filename": resume.filename,
"filepath": resume.filepath,
"version": resume.version_number,
}
metadatas = [base_metadata] * len(embeddings)
faiss_store.add_vectors(embeddings, metadatas)
print("FAISS index rebuild completed successfully.")
else:
print("Startup check: FAISS index is fully in sync with database.")
else:
print("Startup check: No resumes found in database.")
except Exception as e:
print(f"FAISS startup rebuild failed: {e}")
finally:
db.close()
except Exception as e:
print(f"Startup initialization failed (non-critical, retrying or continuing): {e}")
# Schedule the task to run in the background
asyncio.create_task(load_models_background())
# Set all CORS enabled origins
origins = [
"http://localhost:3000",
"http://127.0.0.1:3000",
"http://localhost:3001",
"http://127.0.0.1:3001",
]
# Append dynamic CORS origins from environment config
if settings.BACKEND_CORS_ORIGINS:
for origin in settings.BACKEND_CORS_ORIGINS:
origin_str = str(origin).rstrip("/")
if origin_str not in origins:
origins.append(origin_str)
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
app.include_router(api_router, prefix=settings.API_V1_STR)
|