Create rag_api_client.py

rag_api_client.py

@@ -0,0 +1,38 @@
+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": []}