Update app.py

app.py

@@ -1,121 +1,121 @@
-import streamlit as st
-from function import GetLLMResponse
+# import streamlit as st
+# from function import GetLLMResponse
 
-from langchain_community.llms import OpenAI
-from langchain_google_genai import ChatGoogleGenerativeAI
+# from langchain_community.llms import OpenAI
+# from langchain_google_genai import ChatGoogleGenerativeAI
 
     
-# Page configuration
-st.set_page_config(page_title="Interview Practice Bot",
-                   page_icon="📚",
-                   layout="wide",
-                   initial_sidebar_state="collapsed")
+# # Page configuration
+# st.set_page_config(page_title="Interview Practice Bot",
+#                    page_icon="📚",
+#                    layout="wide",
+#                    initial_sidebar_state="collapsed")
 
 
 
 
-def main():        
-    roles_and_topics = {      
+# def main():        
+#     roles_and_topics = {      
   
-    "Front-End Developer": ["HTML/CSS", "JavaScript and Frameworks (React, Angular, Vue.js)", "Responsive Design", "Browser Compatibility"],
-    "Back-End Developer": ["Server-Side Languages (Node.js, Python, Ruby, PHP)", "Database Management (SQL, NoSQL)", "API Development", "Server and Hosting Management"],
-    "Full-Stack Developer": ["Combination of Front-End and Back-End Topics", "Integration of Systems", "DevOps Basics"],
-    "Mobile Developer": ["Android Development (Java, Kotlin)", "iOS Development (Swift, Objective-C)", "Cross-Platform Development (Flutter, React Native)"],
-    "Data Scientist": ["Statistical Analysis", "Machine Learning Algorithms", "Data Wrangling and Cleaning", "Data Visualization"],
-    "Data Analyst": ["Data Collection and Processing", "SQL and Database Querying", "Data Visualization Tools (Tableau, Power BI)", "Basic Statistics"],
-    "Machine Learning Engineer": ["Supervised and Unsupervised Learning", "Model Deployment", "Deep Learning", "Natural Language Processing"],
-    "DevOps Engineer": ["Continuous Integration/Continuous Deployment (CI/CD)", "Containerization (Docker, Kubernetes)", "Infrastructure as Code (Terraform, Ansible)", "Cloud Platforms (AWS, Azure, Google Cloud)"],
-    "Cloud Engineer": ["Cloud Architecture", "Cloud Services (Compute, Storage, Networking)", "Security in the Cloud", "Cost Management"],
-    "Cybersecurity Analyst": ["Threat Detection and Mitigation", "Security Protocols and Encryption", "Network Security", "Incident Response"],
-    "Penetration Tester": ["Vulnerability Assessment", "Ethical Hacking Techniques", "Security Tools (Metasploit, Burp Suite)", "Report Writing and Documentation"],
-    "Project Manager": ["Project Planning and Scheduling", "Risk Management", "Agile and Scrum Methodologies", "Stakeholder Communication"],
-    "UX/UI Designer": ["User Research", "Wireframing and Prototyping", "Design Principles", "Usability Testing"],
-    "Quality Assurance (QA) Engineer": ["Testing Methodologies", "Automation Testing", "Bug Tracking", "Performance Testing"],
-    "Blockchain Developer": ["Blockchain Fundamentals", "Smart Contracts", "Cryptographic Algorithms", "Decentralized Applications (DApps)"],
-    "Digital Marketing Specialist": ["SEO/SEM", "Social Media Marketing", "Content Marketing", "Analytics and Reporting"],
-    "AI Research Scientist": ["AI Theory", "Algorithm Development", "Neural Networks", "Natural Language Processing"],
-    "AI Engineer": ["AI Model Deployment", "Machine Learning Engineering", "Deep Learning", "AI Tools and Frameworks"],
-    "Generative AI Specialist (GenAI)": ["Generative Models", "GANs (Generative Adversarial Networks)", "Creative AI Applications", "Ethics in AI"],
-    "Generative Business Intelligence Specialist (GenBI)": ["Automated Data Analysis", "Business Intelligence Tools", "Predictive Analytics", "AI in Business Strategy"]
+#     "Front-End Developer": ["HTML/CSS", "JavaScript and Frameworks (React, Angular, Vue.js)", "Responsive Design", "Browser Compatibility"],
+#     "Back-End Developer": ["Server-Side Languages (Node.js, Python, Ruby, PHP)", "Database Management (SQL, NoSQL)", "API Development", "Server and Hosting Management"],
+#     "Full-Stack Developer": ["Combination of Front-End and Back-End Topics", "Integration of Systems", "DevOps Basics"],
+#     "Mobile Developer": ["Android Development (Java, Kotlin)", "iOS Development (Swift, Objective-C)", "Cross-Platform Development (Flutter, React Native)"],
+#     "Data Scientist": ["Statistical Analysis", "Machine Learning Algorithms", "Data Wrangling and Cleaning", "Data Visualization"],
+#     "Data Analyst": ["Data Collection and Processing", "SQL and Database Querying", "Data Visualization Tools (Tableau, Power BI)", "Basic Statistics"],
+#     "Machine Learning Engineer": ["Supervised and Unsupervised Learning", "Model Deployment", "Deep Learning", "Natural Language Processing"],
+#     "DevOps Engineer": ["Continuous Integration/Continuous Deployment (CI/CD)", "Containerization (Docker, Kubernetes)", "Infrastructure as Code (Terraform, Ansible)", "Cloud Platforms (AWS, Azure, Google Cloud)"],
+#     "Cloud Engineer": ["Cloud Architecture", "Cloud Services (Compute, Storage, Networking)", "Security in the Cloud", "Cost Management"],
+#     "Cybersecurity Analyst": ["Threat Detection and Mitigation", "Security Protocols and Encryption", "Network Security", "Incident Response"],
+#     "Penetration Tester": ["Vulnerability Assessment", "Ethical Hacking Techniques", "Security Tools (Metasploit, Burp Suite)", "Report Writing and Documentation"],
+#     "Project Manager": ["Project Planning and Scheduling", "Risk Management", "Agile and Scrum Methodologies", "Stakeholder Communication"],
+#     "UX/UI Designer": ["User Research", "Wireframing and Prototyping", "Design Principles", "Usability Testing"],
+#     "Quality Assurance (QA) Engineer": ["Testing Methodologies", "Automation Testing", "Bug Tracking", "Performance Testing"],
+#     "Blockchain Developer": ["Blockchain Fundamentals", "Smart Contracts", "Cryptographic Algorithms", "Decentralized Applications (DApps)"],
+#     "Digital Marketing Specialist": ["SEO/SEM", "Social Media Marketing", "Content Marketing", "Analytics and Reporting"],
+#     "AI Research Scientist": ["AI Theory", "Algorithm Development", "Neural Networks", "Natural Language Processing"],
+#     "AI Engineer": ["AI Model Deployment", "Machine Learning Engineering", "Deep Learning", "AI Tools and Frameworks"],
+#     "Generative AI Specialist (GenAI)": ["Generative Models", "GANs (Generative Adversarial Networks)", "Creative AI Applications", "Ethics in AI"],
+#     "Generative Business Intelligence Specialist (GenBI)": ["Automated Data Analysis", "Business Intelligence Tools", "Predictive Analytics", "AI in Business Strategy"]
 
 
-    }
+#     }
 
-    levels = ['Beginner','Intermediate','Advanced']
+#     levels = ['Beginner','Intermediate','Advanced']
 
-    Question_Difficulty = ['Easy','Medium','Hard']
+#     Question_Difficulty = ['Easy','Medium','Hard']
     
 
-    st.header("Select AI:")
-    model = st.radio("Model", [ "Gemini","Open AI",])
-    st.write("Selected option:", model)
+#     st.header("Select AI:")
+#     model = st.radio("Model", [ "Gemini","Open AI",])
+#     st.write("Selected option:", model)
     
     
     
-    # Header and description
-    st.title("Interview Practice Bot 📚")
-    st.text("Choose the role and topic for your Interview.")
+#     # Header and description
+#     st.title("Interview Practice Bot 📚")
+#     st.text("Choose the role and topic for your Interview.")
     
-    # User input for quiz generation
-    ## Layout in columns
-    col4, col1, col2 = st.columns([1, 1, 1])
-    col5, col3 = st.columns([1, 1])
+#     # User input for quiz generation
+#     ## Layout in columns
+#     col4, col1, col2 = st.columns([1, 1, 1])
+#     col5, col3 = st.columns([1, 1])
 
 
-    with col4:
-        selected_level = st.selectbox('Select level of understanding', levels)
+#     with col4:
+#         selected_level = st.selectbox('Select level of understanding', levels)
     
-    with col1:
-        selected_topic_level = st.selectbox('Select Role', list(roles_and_topics.keys()))
+#     with col1:
+#         selected_topic_level = st.selectbox('Select Role', list(roles_and_topics.keys()))
     
-    with col2:
-        selected_topic = st.selectbox('Select Topic', roles_and_topics[selected_topic_level])
+#     with col2:
+#         selected_topic = st.selectbox('Select Topic', roles_and_topics[selected_topic_level])
     
     
 
     
     
-    with col5:
-        selected_Question_Difficulty = st.selectbox('Select Question Difficulty', Question_Difficulty)
+#     with col5:
+#         selected_Question_Difficulty = st.selectbox('Select Question Difficulty', Question_Difficulty)
 
-    with col3:
-        num_quizzes = st.slider('Number of Questions', min_value=1, max_value= 10, value=1)
+#     with col3:
+#         num_quizzes = st.slider('Number of Questions', min_value=1, max_value= 10, value=1)
     
-    submit = st.button('Generate Questions')
-    st.write(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
+#     submit = st.button('Generate Questions')
+#     st.write(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
     
-    # Final Response
-    if submit:
-        questions,answers = GetLLMResponse(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
+#     # Final Response
+#     if submit:
+#         questions,answers = GetLLMResponse(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
        
-        with st.spinner("Generating Quizzes..."):
-            questions,answers =  GetLLMResponse(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
-            st.success("Quizzes Generated!")
+#         with st.spinner("Generating Quizzes..."):
+#             questions,answers =  GetLLMResponse(selected_topic_level, selected_topic, num_quizzes, selected_Question_Difficulty, selected_level, model)
+#             st.success("Quizzes Generated!")
 
 
             
-            # Display questions and answers in a table
-            if questions:
-                st.subheader("Quiz Questions and Answers:")
-                # Prepare data for the table
-                col1, col2 = st.columns(2)
-                with col1:
-                    st.subheader("Questions")
+#             # Display questions and answers in a table
+#             if questions:
+#                 st.subheader("Quiz Questions and Answers:")
+#                 # Prepare data for the table
+#                 col1, col2 = st.columns(2)
+#                 with col1:
+#                     st.subheader("Questions")
                     
-                    st.write(questions)
+#                     st.write(questions)
                 
-                with col2:
-                    st.subheader("Answers")
+#                 with col2:
+#                     st.subheader("Answers")
 
-                    st.write(answers)
+#                     st.write(answers)
 
                
     
-            else:
-                st.warning("No Quiz Questions and Answers")
+#             else:
+#                 st.warning("No Quiz Questions and Answers")
                 
-    else:
-        st.warning("Click the 'Generate Quizzes' button to create quizzes.")
+#     else:
+#         st.warning("Click the 'Generate Quizzes' button to create quizzes.")
 
 
 
@@ -125,5 +125,59 @@ def main():
     
 
 
-if __name__ == "__main__":
-    main()
+# if __name__ == "__main__":
+#     main()
+
+
+
+
+
+
+import openai
+import streamlit as st
+
+# Set your OpenAI API key
+openai.api_key = "YOUR_OPENAI_API_KEY"
+
+def generate_question(role, topic, difficulty_level):
+    prompt = f"Generate an interview question for the role of {role} on the topic of {topic} with difficulty level {difficulty_level}."
+    response = openai.Completion.create(
+        engine="text-davinci-003",  # or any other engine you prefer
+        prompt=prompt,
+        max_tokens=50
+    )
+    return response.choices[0].text.strip()
+
+def evaluate_answer(question, user_answer):
+    prompt = f"Question: {question}\nUser's Answer: {user_answer}\nEvaluate the answer and provide feedback. Also, provide the best possible answer."
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=prompt,
+        max_tokens=150
+    )
+    return response.choices[0].text.strip()
+
+st.title("Mock Interview Bot")
+
+role = st.selectbox("Select the role:", ["Software Engineer", "Data Scientist", "Product Manager"])
+topic = st.text_input("Enter the topic:")
+difficulty_level = st.selectbox("Select difficulty level:", ["Easy", "Medium", "Hard"])
+
+if st.button("Generate Question"):
+    if role and topic and difficulty_level:
+        question = generate_question(role, topic, difficulty_level)
+        st.session_state['current_question'] = question
+        st.write(f"Question: {question}")
+        st.session_state['question_answered'] = False
+
+if 'current_question' in st.session_state and not st.session_state.get('question_answered', False):
+    answer = st.text_area("Your Answer:")
+    if st.button("Submit Answer"):
+        if answer:
+            st.session_state['user_answer'] = answer
+            st.session_state['question_answered'] = True
+
+if 'user_answer' in st.session_state:
+    with st.spinner("Evaluating your answer..."):
+        feedback = evaluate_answer(st.session_state['current_question'], st.session_state['user_answer'])
+        st.write(f"Feedback and Best Answer:\n{feedback}")