Update api.py

api.py

@@ -1,19 +1,47 @@
-# api.py
-from fastapi import FastAPI, UploadFile, File, Form
-from model import load_vectorstore, ask_question
-import shutil
+import os
+import aiohttp
+from dotenv import load_dotenv
 
-app = FastAPI()
+load_dotenv()
 
-@app.post("/upload")
-async def upload(file: UploadFile = File(...)):
-    with open("document.pdf", "wb") as buffer:
-        shutil.copyfileobj(file.file, buffer)
-    load_vectorstore("document.pdf")
-    return {"message": "File indexed successfully."}
+async def query_rag_api(question):
+    """
+    Asynchronously query the RAG API for answer and contexts.
 
-@app.post("/ask")
-async def ask(question: str = Form(...)):
-    answer = ask_question(question)
-    return {"question": question, "answer": answer}
+    Args:
+        question (str): The user's question.
 
+    Returns:
+        dict: Answer, contexts, or error message.
+
+    Note:
+        Replace API_ENDPOINT with the actual endpoint of your Hugging Face Space
+        (e.g., https://<your-space-id>.hf.space/ask) after deployment.
+    """
+    # Placeholder - REPLACE with your Space's endpoint
+    API_ENDPOINT = "https://huggingface.co/spaces/samim2024/testing:8000/ask"  # Update to Space URL post-deployment
+    api_key = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+    
+    if not api_key:
+        return {"error": "HUGGINGFACEHUB_API_TOKEN not set", "answer": "", "contexts": []}
+
+    headers = {"Content-Type": "application/json"}
+    payload = {"question": question}
+
+    try:
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                API_ENDPOINT,
+                json=payload,
+                headers=headers,
+                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"API call failed: {str(e)}", "answer": "", "contexts": []}