testing / rag_api_client.py
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Create rag_api_client.py
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import os
import aiohttp
from dotenv import load_dotenv
from urllib.parse import urlencode
load_dotenv()
async def query_rag_api(question):
"""
Asynchronously query the RAG model via Streamlit endpoint.
Args:
question (str): The user's question.
Returns:
dict: Answer, contexts, or error message.
Note:
Replace API_ENDPOINT with your Space's URL (e.g., https://<your-space-id>.hf.space)
after deployment.
"""
# Placeholder - REPLACE with your Space's URL
API_ENDPOINT = "https://huggingface.co/spaces/samim2024/testing"
params = {"query": question}
url = f"{API_ENDPOINT}?{urlencode(params)}"
try:
async with aiohttp.ClientSession() as session:
async with session.get(url, timeout=10) as response:
response_dict = await response.json()
if response_dict.get("error"):
return {"error": response_dict["error"], "answer": "", "contexts": []}
return {
"answer": response_dict.get("answer", ""),
"contexts": response_dict.get("contexts", [])
}
except Exception as e:
return {"error": f"Query failed: {str(e)}", "answer": "", "contexts": []}