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.env.example

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+GOOGLE_API_KEY="AIzaSyAMs9raAfrTFcOZU27pnEV-BAhZnCZgdpM"

README.md

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----
-title: Interview Prepration
-emoji: 👀
-colorFrom: green
-colorTo: gray
-sdk: streamlit
-sdk_version: 1.41.1
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI Interview Preparation Assistant
+
+An AI-powered application that helps candidates prepare for job interviews by analyzing resumes, conducting assessments, and providing personalized feedback.
+
+## Features
+
+- Resume and job description analysis
+- Keyword extraction
+- MCQ assessment
+- Coding challenges
+- AI-proctored mock interviews
+- Speech-to-text conversion
+- Comprehensive performance analysis
+- Personalized learning recommendations
+
+## Setup
+
+1. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+2. Set up environment variables:
+   - Copy `.env.example` to `.env`
+   - Add your Google Gemini API key
+
+3. Run the application:
+   ```bash
+   streamlit run app.py
+   ```
+
+## Usage
+
+1. Input your resume and the job description
+2. Review the analysis and extracted keywords
+3. Complete the MCQ assessment
+4. Solve coding challenges
+5. Participate in the mock interview
+6. Review your comprehensive analysis and recommendations
+
+## Requirements
+
+- Python 3.8+
+- Streamlit
+- Google Generative AI (Gemini)
+- SpeechRecognition
+- PyAudio
+- Internet connection for API calls

app.py

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+import streamlit as st
+import time
+from utils.text_analysis import (
+    extract_keywords, generate_summary, generate_mcqs,
+    generate_coding_questions, analyze_interview_response,
+    get_learning_resources
+)
+from utils.audio_processor import convert_audio_to_text
+
+def main():
+    st.title("AI Interview Preparation Assistant")
+    
+    # Session state initialization
+    if 'current_step' not in st.session_state:
+        st.session_state.current_step = 1
+    
+    # Step 1: Input Collection
+    if st.session_state.current_step == 1:
+        st.header("Step 1: Upload Resume and Job Description")
+        resume = st.text_area("Paste your resume here")
+        job_description = st.text_area("Paste the job description here")
+        
+        if st.button("Analyze") and resume and job_description:
+            with st.spinner("Analyzing..."):
+                st.session_state.resume_summary = generate_summary(resume)
+                st.session_state.jd_summary = generate_summary(job_description)
+                st.session_state.keywords = extract_keywords(job_description)
+                st.session_state.current_step = 2
+    
+    # Step 2: Summary and Keywords
+    elif st.session_state.current_step == 2:
+        st.header("Step 2: Analysis Results")
+        st.subheader("Resume Summary")
+        st.write(st.session_state.resume_summary)
+        
+        st.subheader("Job Description Summary")
+        st.write(st.session_state.jd_summary)
+        
+        st.subheader("Key Requirements")
+        st.write(", ".join(st.session_state.keywords))
+        
+        if st.button("Start Assessment"):
+            st.session_state.current_step = 3
+    
+    # Step 3: MCQ Assessment
+    elif st.session_state.current_step == 3:
+        st.header("Step 3: MCQ Assessment")
+        if 'mcqs' not in st.session_state:
+            with st.spinner("Generating questions..."):
+                st.session_state.mcqs = generate_mcqs(
+                    st.session_state.resume_summary,
+                    st.session_state.jd_summary
+                )
+                st.session_state.mcq_answers = {}
+                st.session_state.mcq_start_time = time.time()
+        
+        # Display timer
+        elapsed_time = int(time.time() - st.session_state.mcq_start_time)
+        st.write(f"Time elapsed: {elapsed_time} seconds")
+        
+        # Display MCQs
+        for i, mcq in enumerate(st.session_state.mcqs):
+            answer = st.radio(
+                f"Q{i+1}: {mcq['question']}",
+                mcq['options'],
+                key=f"mcq_{i}"
+            )
+            st.session_state.mcq_answers[i] = answer
+        
+        if st.button("Submit MCQs"):
+            st.session_state.current_step = 4
+    
+    # Step 4: Coding Assessment
+    elif st.session_state.current_step == 4:
+        st.header("Step 4: Coding Assessment")
+        if 'coding_questions' not in st.session_state:
+            with st.spinner("Generating coding questions..."):
+                st.session_state.coding_questions = generate_coding_questions(
+                    st.session_state.resume_summary,
+                    st.session_state.jd_summary
+                )
+                st.session_state.coding_start_time = time.time()
+        
+        # Display timer
+        elapsed_time = int(time.time() - st.session_state.coding_start_time)
+        st.write(f"Time elapsed: {elapsed_time} seconds")
+        
+        for i, question in enumerate(st.session_state.coding_questions):
+            st.subheader(f"Question {i+1}")
+            st.write(question['problem_statement'])
+            st.write("Examples:")
+            st.write(question['examples'])
+            st.write("Constraints:")
+            st.write(question['constraints'])
+            
+            if 'coding_answers' not in st.session_state:
+                st.session_state.coding_answers = {}
+            
+            st.session_state.coding_answers[i] = st.text_area(
+                "Your solution:",
+                key=f"coding_{i}"
+            )
+        
+        if st.button("Submit Coding Solutions"):
+            st.session_state.current_step = 5
+    
+    # Step 5: Mock Interview
+    elif st.session_state.current_step == 5:
+        st.header("Step 5: Mock Interview")
+        st.write("Click 'Start' when ready to begin the interview.")
+        
+        if st.button("Start Interview"):
+            st.write("Recording... Speak your answer.")
+            audio_text = convert_audio_to_text()
+            
+            with st.spinner("Analyzing your response..."):
+                st.session_state.interview_analysis = analyze_interview_response(
+                    audio_text,
+                    st.session_state.jd_summary
+                )
+            st.session_state.current_step = 6
+    
+    # Step 6: Final Analysis
+    elif st.session_state.current_step == 6:
+        st.header("Final Analysis")
+        
+        # Calculate overall score
+        mcq_score = sum(1 for i, ans in st.session_state.mcq_answers.items() 
+                       if ans == st.session_state.mcqs[i]['correct_answer'])
+        interview_score = st.session_state.interview_analysis['score']
+        
+        overall_score = (mcq_score / 30 * 0.4 + interview_score / 100 * 0.6) * 100
+        
+        st.subheader("Overall Match Score")
+        st.progress(overall_score / 100)
+        st.write(f"{overall_score:.1f}%")
+        
+        st.subheader("Strengths")
+        st.write(st.session_state.interview_analysis['strengths'])
+        
+        st.subheader("Areas for Improvement")
+        st.write(st.session_state.interview_analysis['improvements'])
+        
+        # Get learning resources
+        resources = get_learning_resources(
+            st.session_state.interview_analysis['concepts_to_study']
+        )
+        
+        st.subheader("Recommended Learning Resources")
+        for concept, links in resources.items():
+            st.write(f"**{concept}:**")
+            for link in links:
+                st.write(f"- {link}")
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+streamlit==1.32.0
+google-generativeai==0.3.2
+python-dotenv==1.0.1
+speechrecognition==3.10.1
+pyaudio==0.2.14
+pandas==2.2.1
+numpy==1.26.4