remove duplicate

app.py

@@ -1,115 +0,0 @@
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-import os
-import logging
-import sys
-import json
-
-# Configure logging
-logging.basicConfig(
-    level=logging.INFO,
-    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
-    handlers=[
-        logging.StreamHandler(sys.stdout)
-    ]
-)
-logger = logging.getLogger(__name__)
-
-app = FastAPI(title="RAG Pipeline API", description="Multi-dataset RAG API", version="1.0.0")
-
-# Initialize pipelines for all datasets
-pipelines = {}
-google_api_key = os.getenv("GOOGLE_API_KEY")
-
-logger.info(f"Starting RAG Pipeline API")
-logger.info(f"Google API Key present: {'Yes' if google_api_key else 'No'}")
-
-# Don't load datasets during startup - do it asynchronously after server starts
-logger.info("RAG Pipeline API is ready to serve requests - datasets will load in background")
-
-class Question(BaseModel):
-    text: str
-    dataset: str = "developer-portfolio"
-
-@app.post("/answer")
-async def get_answer(question: Question):
-    try:
-        # Check if any pipelines are loaded
-        if not pipelines:
-            return {
-                "answer": "RAG Pipeline is running but datasets are still loading in the background. Please try again in a moment, or check /health for loading status.",
-                "dataset": question.dataset,
-                "status": "datasets_loading"
-            }
-        
-        # Select the appropriate pipeline based on dataset
-        if question.dataset not in pipelines:
-            raise HTTPException(status_code=400, detail=f"Dataset '{question.dataset}' not available. Available datasets: {list(pipelines.keys())}")
-        
-        selected_pipeline = pipelines[question.dataset]
-        answer = selected_pipeline.answer_question(question.text)
-        return {"answer": answer, "dataset": question.dataset}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-@app.get("/datasets")
-async def list_datasets():
-    """List all available datasets"""
-    return {"datasets": list(pipelines.keys())}
-
-async def load_datasets_background():
-    """Load datasets in background after server starts"""
-    global pipelines
-    if google_api_key:
-        try:
-            # Import modules only when needed
-            import sys
-            sys.path.append('/app')
-            from app.pipeline import RAGPipeline
-            from app.config import DATASET_CONFIGS
-            
-            # Only load developer-portfolio to save memory
-            dataset_name = "developer-portfolio"
-            logger.info(f"Loading dataset: {dataset_name}")
-            pipeline = RAGPipeline.from_preset(
-                google_api_key=google_api_key,
-                preset_name=dataset_name
-            )
-            pipelines[dataset_name] = pipeline
-            logger.info(f"Successfully loaded {dataset_name}")
-        except Exception as e:
-            logger.error(f"Failed to load dataset: {e}")
-        logger.info(f"Background loading complete - {len(pipelines)} datasets loaded")
-    else:
-        logger.warning("No Google API key provided - running in demo mode without datasets")
-
-@app.on_event("startup")
-async def startup_event():
-    logger.info("FastAPI application startup complete")
-    logger.info(f"Server should be running on port: 7860")
-    
-    # Start loading datasets in background (non-blocking)
-    import asyncio
-    asyncio.create_task(load_datasets_background())
-
-@app.on_event("shutdown")
-async def shutdown_event():
-    logger.info("FastAPI application shutting down")
-
-@app.get("/")
-async def root():
-    """Root endpoint"""
-    return {"status": "ok", "message": "RAG Pipeline API", "version": "1.0.0", "datasets": list(pipelines.keys())}
-
-@app.get("/health")
-async def health_check():
-    """Health check endpoint"""
-    logger.info("Health check called")
-    loading_status = "complete" if "developer-portfolio" in pipelines else "loading"
-    return {
-        "status": "healthy", 
-        "datasets_loaded": len(pipelines), 
-        "total_datasets": 1,  # Only loading developer-portfolio
-        "loading_status": loading_status,
-        "port": "7860"
-    }

developer-portfolio-rag

@@ -1 +0,0 @@
-Subproject commit 761b11c411795efadbf92045b906c28125597810

start.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 set -e  # Exit on any error
 
-echo "=== RAG Pipeline Startup ==="
+echo "=== RAG Pipeline Startup (TESTING)==="
 echo "PORT environment variable: ${PORT:-'not set'}"
 echo "Using port: 7860"
 if [ -n "$GOOGLE_API_KEY" ]; then
@@ -22,4 +22,4 @@ ls -la app/
 echo "Testing Python import:"
 python -c "import app.main; print('Import successful')" || echo "Import failed"
 echo "Starting uvicorn..."
-uvicorn rag_pipeline.app.main:app --host 0.0.0.0 --port 7860 --log-level info
+uvicorn app.main:app --host 0.0.0.0 --port 7860 --log-level info