Update noRag.py

noRag.py

@@ -1,4 +1,4 @@
-# norag_router.py
+# noRag.py
 
 from fastapi import APIRouter, HTTPException
 from pydantic import BaseModel
@@ -6,7 +6,6 @@ from groq import Groq
 from pymongo import MongoClient
 from config import CONNECTION_STRING, CHATGROQ_API_KEY, CUSTOM_PROMPT
 
-# Create router under /norag
 router = APIRouter(prefix="/norag", tags=["noRag"])
 
 # Initialize Groq client and MongoDB
@@ -15,24 +14,21 @@ mongo  = MongoClient(CONNECTION_STRING)
 db     = mongo["edulearnai"]
 chats  = db["chats"]
 
-# System prompt
 SYSTEM_PROMPT = "You are a helpful assistant which helps people in their tasks."
 
-# Request model
-type ChatRequest(BaseModel):
+class ChatRequest(BaseModel):
     session_id: str
-    question: str
+    question:   str
 
 @router.post("/chat", summary="Ask a question to the noRag assistant")
 async def chat_endpoint(req: ChatRequest):
-    # Fetch or create session
-doc = chats.find_one({"session_id": req.session_id})
+    # Fetch or create session in MongoDB
+    doc = chats.find_one({"session_id": req.session_id})
     if not doc:
         doc = {"session_id": req.session_id, "history": [], "summary": ""}
         chats.insert_one(doc)
 
-    history = doc["history"]
-    summary = doc["summary"]
+    history, summary = doc["history"], doc["summary"]
 
     # Summarize if history too long
     if len(history) >= 10:
@@ -40,7 +36,7 @@ doc = chats.find_one({"session_id": req.session_id})
         combined = summary + "\n" + "\n".join(msgs)
         sum_prompt = (
             "Summarize the following chat history in one or two short sentences:\n\n"
-            + combined + "\n\nSummary:"
+            f"{combined}\n\nSummary:"
         )
         sum_resp = client.chat.completions.create(
             model="meta-llama/llama-4-scout-17b-16e-instruct",
@@ -53,15 +49,15 @@ doc = chats.find_one({"session_id": req.session_id})
         summary = sum_resp.choices[0].message.content.strip()
         history = []
 
-    # Build full prompt
-    chat_hist_text = "\n".join([f"{m['role']}: {m['content']}" for m in history])
+    # Build the prompt for Groq
+    chat_hist_text = "\n".join(f"{m['role']}: {m['content']}" for m in history)
     full_prompt = CUSTOM_PROMPT.format(
         context=SYSTEM_PROMPT,
         chat_history=chat_hist_text or "(no prior messages)",
         question=req.question
     )
 
-    # Call model
+    # Get the assistant’s answer
     resp = client.chat.completions.create(
         model="meta-llama/llama-4-scout-17b-16e-instruct",
         messages=[{"role": "user", "content": full_prompt}],
@@ -72,8 +68,8 @@ doc = chats.find_one({"session_id": req.session_id})
     )
     answer = resp.choices[0].message.content.strip()
 
-    # Update session doc
-    history.append({"role": "user", "content": req.question})
+    # Persist the Q&A
+    history.append({"role": "user",      "content": req.question})
     history.append({"role": "assistant", "content": answer})
     chats.replace_one(
         {"session_id": req.session_id},