Optimize Industrial Knowledge Base Retrieval with LlamaIndex and DSPy

                      
                     
from typing import List, Dict, Any
import os
from llama_index import LlamaIndex
from fastapi import FastAPI, HTTPException

# Configuration
API_KEY = os.getenv('API_KEY')
INDEX_PATH = os.getenv('INDEX_PATH', 'path/to/index')

# Initialize FastAPI app
app = FastAPI()

# Initialize LlamaIndex
index = LlamaIndex(api_key=API_KEY, index_path=INDEX_PATH)

# Endpoint for retrieving knowledge base information
@app.get('/retrieve')
async def retrieve_info(query: str) -> Dict[str, Any]:
    try:
        # Perform retrieval using LlamaIndex
        results: List[str] = index.retrieve(query)
        if not results:
            raise HTTPException(status_code=404, detail='No results found')
        return {'success': True, 'data': results}
    except Exception as e:
        # Error handling
        return {'success': False, 'error': str(e)}

if __name__ == '__main__':
    import uvicorn
    uvicorn.run(app, host='0.0.0.0', port=8000)