Update app.py

app.py

@@ -1,16 +1,14 @@
 import streamlit as st
 import openai
 from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain_groq import ChatGroqGenerativeAI  # Assume this is the correct import for Groq
 from datetime import datetime, timedelta
 import time
 
 # API keys
 GOOGLE_API_KEY = st.secrets["GOOGLE_API_KEY"]
 OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
-GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
 
-# Initialize APIs
+# Initialize OpenAI
 openai.api_key = OPENAI_API_KEY
 
 # In-memory storage for progress tracking
@@ -20,31 +18,14 @@ progress_data = {
     },
     "mock_interviews_taken": 0,
     "feedback_provided": 0,
-    "tips_retrieved": 0,
-    "resources_used": 0
+    "tips_retrieved": 0
 }
 
-# Define list of roles for dropdown
-ROLE_OPTIONS = [
-    "Software Engineer",
-    "Data Scientist",
-    "Product Manager",
-    "UX Designer",
-    "Business Analyst",
-    "Project Manager",
-    "Marketing Specialist",
-    "Sales Manager",
-    "Customer Support Specialist",
-    "Other"
-]
-
 def get_llm(model_choice):
     if model_choice == "Gemini":
         return ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=GOOGLE_API_KEY)
     elif model_choice == "OpenAI":
         return None
-    elif model_choice == "Groq":
-        return ChatGroqGenerativeAI(api_key=GROQ_API_KEY)
     else:
         raise ValueError("Unsupported model choice.")
 
@@ -64,10 +45,6 @@ def generate_questions(model_choice, role, question_type, num_questions, difficu
         llm = get_llm(model_choice)
         response = llm.invoke(prompt)
         return response.content.split("\n")
-    elif model_choice == "Groq":
-        llm = get_llm(model_choice)
-        response = llm.invoke(prompt)
-        return response.content.split("\n")
     else:
         raise ValueError("Unsupported model choice.")
 
@@ -84,10 +61,6 @@ def provide_feedback(model_choice, answer):
         llm = get_llm(model_choice)
         response = llm.invoke(prompt)
         return response.content
-    elif model_choice == "Groq":
-        llm = get_llm(model_choice)
-        response = llm.invoke(prompt)
-        return response.content
     else:
         raise ValueError("Unsupported model choice.")
 
@@ -104,10 +77,6 @@ def get_tips(model_choice, role):
         llm = get_llm(model_choice)
         response = llm.invoke(prompt)
         return response.content
-    elif model_choice == "Groq":
-        llm = get_llm(model_choice)
-        response = llm.invoke(prompt)
-        return response.content
     else:
         raise ValueError("Unsupported model choice.")
 
@@ -214,7 +183,6 @@ def connect_resources():
                 st.error("Please fill out all fields.")
             else:
                 st.success("Thank you for contacting us! We will get back to you soon.")
-                progress_data["resources_used"] += 1
 
 def style_output(text, color):
     return f'<div class="output-container"><span style="color: {color}; font-weight: bold;">{text}</span></div>'
@@ -227,6 +195,10 @@ st.markdown(
     body {
         background-color: #e0f7fa; /* Light cyan background color */
         font-family: Arial, sans-serif;
+        background-image: url('https://example.com/your-watermark-image.png'); /* URL to your watermark image */
+        background-repeat: no-repeat;
+        background-position: center;
+        background-size: cover;
     }
     .stButton>button {
         width: 100%;
@@ -243,11 +215,18 @@ st.markdown(
         background-color: #45a049;
     }
     .output-container {
-        padding: 1em;
-        margin-bottom: 1em;
-        background-color: #f9f9f9;
+        border: 2px solid #2196F3;
+        border-radius: 8px;
+        padding: 15px;
+        margin: 15px 0;
+        background-color: #f1f1f1;
+    }
+    .progress-container {
+        border: 2px solid #2196F3;
         border-radius: 8px;
-        border: 1px solid #d0d0d0;
+        padding: 15px;
+        margin: 15px 0;
+        background-color: #f9f9f9;
     }
     .sidebar {
         background-color: #ffffff; /* Sidebar background color */
@@ -286,17 +265,11 @@ with welcome_message.container():
 time.sleep(4)  # Wait for 4 seconds
 welcome_message.empty()  # Remove the welcome message
 
-# Initialize session state for questions, answers, and current index
+# Initialize session state for questions and current index
 if 'questions' not in st.session_state:
     st.session_state.questions = []
-if 'answers' not in st.session_state:
-    st.session_state.answers = []
-if 'feedback' not in st.session_state:
-    st.session_state.feedback = []
 if 'question_index' not in st.session_state:
     st.session_state.question_index = 0
-if 'show_results' not in st.session_state:
-    st.session_state.show_results = False
 
 # Sidebar Navigation
 st.sidebar.title("TechPrep Navigation")
@@ -307,20 +280,17 @@ nav_option = st.sidebar.radio("Choose an option:",
 if nav_option == "Generate Questions":
     st.header("📝 Generate Interview Questions")
     
-    model_choice = st.selectbox("Choose Model:", ["OpenAI", "Gemini", "Groq"])
-    role = st.selectbox("Role", ROLE_OPTIONS)
+    model_choice = st.selectbox("Choose Model:", ["OpenAI", "Gemini"])
+    role = st.text_input("Role", placeholder="e.g. Software Engineer")
     question_type = st.selectbox("Question Type:", ["Behavioral", "Technical", "Situational", "Case Study", "Problem Solving"])
     num_questions = st.number_input("Number of Questions:", min_value=1, max_value=20, value=5)
-    difficulty = st.selectbox("Difficulty Level:", ["Basic", "Medium", "Complex"])
+    difficulty = st.selectbox("Difficulty Level:", ["Easy", "Medium", "Hard"])
     
     if st.button("Generate Questions", key="generate_questions"):
         with st.spinner("Generating questions..."):
             questions = generate_questions(model_choice, role, question_type, num_questions, difficulty)
             st.session_state.questions = questions
-            st.session_state.answers = ["" for _ in questions]
-            st.session_state.feedback = ["" for _ in questions]
             st.session_state.question_index = 0
-            st.session_state.show_results = False
             progress_data["questions_solved"][question_type] += num_questions
 
     # Display questions with navigation
@@ -328,22 +298,28 @@ if nav_option == "Generate Questions":
         question_list = st.session_state.questions
         index = st.session_state.question_index
         
+        # Debugging information
+        st.write(f"**Current Index:** {index}")
+        st.write(f"**Total Questions:** {len(question_list)}")
+        
         if index < len(question_list):
             st.write(f"**Question {index + 1}:** {question_list[index]}")
             
             # Answer input box
             answer = st.text_area("Your Answer", key="text_area_answer")
-
+            
             col1, col2 = st.columns(2)
             with col1:
                 if index > 0:
                     if st.button("Previous"):
                         st.session_state.question_index -= 1
+                        st.experimental_rerun()  # Re-run to update display
             
             with col2:
                 if index < len(question_list) - 1:
                     if st.button("Next"):
                         st.session_state.question_index += 1
+                        st.experimental_rerun()  # Re-run to update display
 
             # Submit answer and provide feedback
             if st.button("Submit Answer"):
@@ -352,35 +328,10 @@ if nav_option == "Generate Questions":
                 else:
                     with st.spinner("Providing feedback..."):
                         feedback = provide_feedback(model_choice, answer)
-                        st.session_state.answers[index] = answer
-                        st.session_state.feedback[index] = feedback
                         st.markdown(style_output("Feedback Received:", "#FF5722"), unsafe_allow_html=True)
                         st.write(feedback)
                         progress_data["feedback_provided"] += 1
 
-            # Show results and score when all questions have been answered
-            if index == len(question_list) - 1:
-                st.session_state.show_results = True
-
-        if st.session_state.show_results:
-            st.write("### Your Results")
-            total_questions = len(st.session_state.questions)
-            answered_questions = sum(1 for ans in st.session_state.answers if ans)
-            score = (answered_questions / total_questions) * 100
-            st.write(f"**Score:** {score:.2f}%")
-            
-            # Display feedback and tips
-            st.write("### Feedback Summary")
-            for i, (q, ans, fb) in enumerate(zip(st.session_state.questions, st.session_state.answers, st.session_state.feedback)):
-                st.write(f"**Question {i + 1}:** {q}")
-                st.write(f"**Your Answer:** {ans}")
-                st.write(f"**Feedback:** {fb}")
-
-            tips = get_tips(model_choice, role)
-            st.write("### Tips to Improve")
-            st.write(tips)
-            progress_data["tips_retrieved"] += 1
-
 elif nav_option == "Mock Interview":
     st.header("🎥 Mock Interview")
     schedule_mock_interview()