Spaces:
Sleeping
Sleeping
File size: 4,819 Bytes
379003a 33ef834 379003a 6098013 379003a |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 |
import logging
from fastapi import FastAPI, HTTPException, BackgroundTasks
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from typing import Dict, Optional, List, Any
import uuid
from datetime import datetime
from contextlib import asynccontextmanager
from models.embedding import EmbeddingModel
from models.summarization import SummarizationModel
from models.nlp import NLPModel
from database.query import DatabaseService
from main import QueryProcessor
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
handlers=[logging.StreamHandler()]
)
logger = logging.getLogger(__name__)
# Initialize models
embedding_model = None
summarization_model = None
nlp_model = None
db_service = None
@asynccontextmanager
async def lifespan(app: FastAPI):
global embedding_model, summarization_model, nlp_model, db_service
# Model initialization
logger.info("Initializing models...")
try:
embedding_model = EmbeddingModel()
summarization_model = SummarizationModel()
nlp_model = NLPModel()
db_service = DatabaseService()
logger.info("All models initialized successfully")
except Exception as e:
logger.error(f"Model initialization failed: {str(e)}")
raise
yield
# Cleanup
logger.info("Shutting down application...")
if db_service:
try:
await db_service.close()
logger.info("Database connection closed successfully")
except Exception as e:
logger.error(f"Error closing database connection: {str(e)}")
app = FastAPI(
title="Kairos News API",
version="1.0",
lifespan=lifespan
)
@app.get("/")
async def root():
return {"message": "Kairos News API is running"}
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
# In-memory job storage
jobs_db: Dict[str, Dict] = {}
class PostRequest(BaseModel):
query: str
topic: Optional[str] = None
start_date: Optional[str] = None
end_date: Optional[str] = None
class JobStatus(BaseModel):
id: str
status: str
created_at: datetime
completed_at: Optional[datetime] = None
request: PostRequest
result: Optional[Dict[str, Any]] = None
@app.post("/index", response_model=JobStatus)
async def create_job(request: PostRequest, background_tasks: BackgroundTasks):
job_id = str(uuid.uuid4())
logger.info(f"Creating new job {job_id} with request: {request.dict()}")
jobs_db[job_id] = {
"id": job_id,
"status": "processing",
"created_at": datetime.now(),
"completed_at": None,
"request": request.dict(),
"result": None
}
background_tasks.add_task(
process_job,
job_id,
request,
embedding_model,
summarization_model,
nlp_model,
db_service
)
logger.info(f"Job {job_id} created and processing started")
return jobs_db[job_id]
@app.get("/loading", response_model=JobStatus)
async def get_job_status(id: str):
logger.info(f"Checking status for job {id}")
if id not in jobs_db:
logger.warning(f"Job {id} not found")
raise HTTPException(status_code=404, detail="Job not found")
logger.info(f"Returning status for job {id}: {jobs_db[id]['status']}")
return jobs_db[id]
async def process_job(
job_id: str,
request: PostRequest,
embedding_model: EmbeddingModel,
summarization_model: SummarizationModel,
nlp_model: NLPModel,
db_service: DatabaseService
):
try:
logger.info(f"Starting processing for job {job_id}")
processor = QueryProcessor(
embedding_model=embedding_model,
summarization_model=summarization_model,
nlp_model=nlp_model,
db_service=db_service
)
logger.debug(f"Processing query: {request.query}")
result = await processor.process(
query=request.query,
topic=request.topic,
start_date=request.start_date,
end_date=request.end_date
)
jobs_db[job_id].update({
"status": "completed",
"completed_at": datetime.now(),
"result": result if result else {"message": "No results found"}
})
logger.info(f"Job {job_id} completed successfully")
except Exception as e:
logger.error(f"Error processing job {job_id}: {str(e)}", exc_info=True)
jobs_db[job_id].update({
"status": "failed",
"completed_at": datetime.now(),
"result": {"error": str(e)}
})
logger.info(f"Job {job_id} marked as failed") |