Update app.py

app.py

@@ -6,19 +6,16 @@ from typing import Dict
 import hashlib
 from openai import OpenAI
 from dotenv import load_dotenv
-import os
-load_dotenv()
-client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
-# from pathlib import Path
-# from langchain_community.document_loaders import WebBaseLoade as genai
-import os
-import re
-import pandas as pd
 from fastapi.middleware.cors import CORSMiddleware
 from firebase_admin import firestore
 import json
+import re
+import pandas as pd
 import google.generativeai as genai
 from google.generativeai import GenerativeModel
+import os
+load_dotenv()
+client = OpenAI(api_key=os.getenv('DEEPSEEK_API_KEY'), base_url="https://api.deepseek.com",)
 
 # Initialize Gemini LLM
 # load_dotenv()
@@ -29,9 +26,6 @@ model = genai.GenerativeModel("gemini-2.0-flash")
 import firebase_admin
 from firebase_admin import credentials
 
-cred_dic = os.getenv("Firebase_cred")
-
-cred_dict = json.loads(cred_dic)
 # cred = credentials.Certificate("/content/ir-502e5-firebase-adminsdk-3der0-0145a61d7a.json")
 # firebase_admin.initialize_app(cred)
 
@@ -46,7 +40,7 @@ app.add_middleware(
 )
 def generate_df():
     data = []
-    cred = credentials.Certificate(cred_dict)
+    cred = credentials.Certificate("G:/Cognozire/Alguru/Feeback_Api's/fir-502e5-firebase-adminsdk-3der0-0145a61d7a.json")
     firebase_admin.initialize_app(cred)
     db = firestore.client()
     docs = db.collection("test_results").get()
@@ -113,8 +107,11 @@ async def get_overall_feedback(email: str):
 async def get_strong_weak_topics(email: str):   
     df = generate_df()
     df_email = df[df['email'] == email]
-    if not df_email.empty:
-        response = df_email['responses'].values
+    if len(df_email)<10:
+        return JSONResponse(content={"message": "Please attempt atleast 10 tests to enable this feature"})
+
+    elif len(df)>=10:
+        response = df_email['responses'].values[:10]
         # Assuming response is a list of responses
         formatted_data = str(response)  # Convert response to a string format suitable for the API call
         section_info = {
@@ -127,14 +124,14 @@ async def get_strong_weak_topics(email: str):
         
         # Generate response using the client
         completion = client.chat.completions.create(
-            model="gpt-4o",
+            model="deepseek-chat",
             response_format={"type": "json_object"},
             messages=[
                 {
                     "role": "system",
                     "content": f"""You are an Educational Performance Analyst focusing on {section_info['filename'].replace('_', ' ')}.
                     Analyze the provided student responses to identify and categorize topics into 'weak' and 'strong' based on their performance. Try to give
-                    high level concepts like algebra, trignometry, geometry etc in your response.
+                    high level topics like algebra, trignometry, geometry etc in your response.
                     Do not add any explanations, introduction, or comments - return ONLY valid JSON.
                     """
                 },