Added Question Generation Part

core/input_comp_gen.py

@@ -1,21 +1,118 @@
 import streamlit as st
 import PyPDF2
-#import io
+import os
+import json  # Added import for JSON parsing
+from dotenv import load_dotenv
+from openai import OpenAI
+
+load_dotenv()
+api_key = os.getenv("GEMINI_API_KEY")
+client = OpenAI(
+    api_key=api_key,
+    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
+)
 
 def read_resume(file):
-    reader=PyPDF2.PdfReader(file)
-    text= ""
+    reader = PyPDF2.PdfReader(file)
+    text = ""
+    for page in reader.pages:
+        text += page.extract_text() + "\n"
+    return text.strip()
+
+def read_job_description_pdf(file):
+    """Read PDF job description"""
+    reader = PyPDF2.PdfReader(file)
+    text = ""
     for page in reader.pages:
         text += page.extract_text() + "\n"
     return text.strip()
 
-def read_job_description(file):
+def read_job_description_txt(file):
+    """Read TXT job description"""
     return file.read().decode("utf-8").strip()
 
+def generate_question(resume_text, job_desc_text, job_role):
+    prompt = f"""
+    You are an interview coach. Based on this resume and job description, generate exactly 5 interview questions for the role "{job_role}".
+
+    Resume:
+    {resume_text}
+
+    Job Description:
+    {job_desc_text}
+
+    Generate 5 relevant interview questions. Include follow-up prompts in parentheses if needed.
+    You must respond with ONLY a valid JSON array of strings. No explanations, no markdown, just the JSON array.
+
+    Example format: ["Question 1 here", "Question 2 here", "Question 3 here", "Question 4 here", "Question 5 here"]
+    """
+    response = client.chat.completions.create(
+        model="gemini-2.0-flash-lite",
+        messages=[
+            {"role": "system", "content": "You are a JSON generator. You only respond with valid JSON arrays. Never include explanations or markdown formatting."},
+            {"role": "user", "content": prompt}
+        ],
+        temperature=0.7,
+
+    )
+    text = response.choices[0].message.content.strip()
+    #st.write("Raw API Response:", text)  # Debug line
+
+    try:
+        # Debug: Check if response is empty
+        if not text:
+            st.error("Empty response from API")
+            return default_questions()
+            
+        # Debug: Try to clean the response
+        cleaned_text = text
+        if not text.startswith('['):
+            #st.warning("Response not in JSON format, attempting to clean...")
+            # Find JSON array markers
+            start_idx = text.find('[')
+            end_idx = text.rfind(']')
+            
+            if start_idx != -1 and end_idx != -1:
+                cleaned_text = text[start_idx:end_idx + 1]
+                #st.write("Cleaned text:", cleaned_text)  # Debug line
+            else:
+                #st.error("Could not find JSON array markers")
+                return default_questions()
+        
+        # Try parsing the cleaned JSON
+        questions = json.loads(cleaned_text)
+        return questions
+        
+    except json.JSONDecodeError as e:
+        st.error(f"JSON Parse Error: {str(e)}")
+        st.error(f"Problem at position: {e.pos}")
+        st.error(f"Problem line: {e.lineno}, col: {e.colno}")
+        return default_questions()
+    except Exception as e:
+        st.error(f"Other error: {str(e)}")
+        return default_questions()
+
+def default_questions():
+    """Fallback questions if API fails"""
+    return [
+        "Tell me about your relevant experience for this role.",
+        "What are your key strengths and weaknesses?",
+        "Why are you interested in this position?",
+        "Describe a challenging project you've worked on.",
+        "What questions do you have about the role?"
+    ]
+
+# Initialize session state variables
+if 'q_num' not in st.session_state:
+    st.session_state.q_num = 0
+if 'questions' not in st.session_state:
+    st.session_state.questions = []
+if 'processing_complete' not in st.session_state:
+    st.session_state.processing_complete = False
 
 #=== Sidebar: User Inputs ===#
 with st.sidebar:
-    st.title("AI_Job_Matcher – HiredGPT Duel")
+    st.title("AI-Job_Matcher – HiredGPT Duel")
 
     #1 Resume Upload
     st.header("1. Upload Your Resume")
@@ -44,11 +141,13 @@ with st.sidebar:
     #5 Submit Button
     submit = st.button("Submit - (Next: generate rival resume and interview questions)")
 
+    # Status messages in sidebar
+    if submit or st.session_state.processing_complete:
+        st.subheader("📋 Processing Status")
 
 #=== Main Area: Q&A and Duel ===#
 if submit:
-
-    # Input Validation
+    #1 Input Validation
     errors = []
     if not user_resume:
         errors.append("Please upload your resume (PDF).")
@@ -64,72 +163,119 @@ if submit:
             st.toast(error, icon="⚠️")
         st.stop()
 
-
-    # Resume and Job Description Processing    
+    #2 Resume and Job Description Processing    
     resume_text = ""
     if user_resume:
         try:
             resume_text = read_resume(user_resume)
-            st.success("Resume uploaded successfully!")
+            with st.sidebar:
+                st.success("✅ Resume uploaded successfully!")
         except Exception as e:
-            st.error(f"Error reading resume: {e}")
-    else:
-        st.error("Please upload your resume.")
+            with st.sidebar:
+                st.error(f"❌ Error reading resume: {e}")
+            st.stop()
     
-    jd_text=''
+    jd_text = ''
     if job_desc_file:
         try:
             if job_desc_file.type == "application/pdf":
-                jd_text = read_job_description(job_desc_file)   
+                jd_text = read_job_description_pdf(job_desc_file)   
             elif job_desc_file.type == "text/plain":
-                jd_text = job_desc_file.read().decode("utf-8").strip()  
+                jd_text = read_job_description_txt(job_desc_file)  
             else:
                 st.error("Unsupported file type for job description.")
+                st.stop()
+            with st.sidebar:
+                st.success("✅ Job description uploaded successfully!")
         except Exception as e:  
-            st.error(f"Error reading job description: {e}")
+            with st.sidebar:
+                st.error(f"❌ Error reading job description: {e}")
+            st.stop()
     elif job_desc_text:
         jd_text = job_desc_text.strip() 
-        st.success("Job description successfully read.")
+        with st.sidebar:
+            st.success("✅ Job description text processed!")
     else:
         st.error("Please provide the job description to continue.")
+        st.stop()
     
     if resume_text and jd_text:
-        st.success("Resume & JD Preview")
-        with st.expander("View Resume", expanded=False):
-            st.write(resume_text[:3000]) 
-        with st.expander("View Job Description", expanded=False):
-            st.write(jd_text[:3000])
+        # Show preview in main area
+        st.success("🎉 All files processed successfully!")
+        
+        with st.expander("📄 View Resume Preview", expanded=False):
+            st.write(resume_text[:3000] + "..." if len(resume_text) > 3000 else resume_text) 
+        with st.expander("📋 View Job Description Preview", expanded=False):
+            st.write(jd_text[:3000] + "..." if len(jd_text) > 3000 else jd_text)
 
-        st.header("Interview Duel")
+        #3 Generate Interview Questions
+        with st.spinner("🤖 Generating interview questions..."):
+            st.session_state.questions = generate_question(resume_text, jd_text, job_role)
+            st.session_state.processing_complete = True
+            
+        with st.sidebar:
+            st.success("✅ Interview questions generated!")
 
-        questions = ["Tell me about yourself.", "Describe a challenge at work and how you solved it."]
-        if "q_num" not in st.session_state:
-            st.session_state.q_num = 0
-        
-        question = questions[st.session_state.q_num]
-        st.subheader(f"Question {st.session_state.q_num+1}: {question}")
+# Show Interview Duel if processing is complete
+if st.session_state.processing_complete and st.session_state.questions:
+    st.header("🥊 Interview Duel")
+    
+    qn = st.session_state.q_num
+    questions = st.session_state.questions
+
+    if qn < len(questions):
+        st.subheader(f"Question {qn+1}/{len(questions)}:")
+        st.info(questions[qn])
 
         # Duel columns: User vs LLM
         col1, col2 = st.columns(2)
         with col1:
-            st.markdown("**Your Answer:**")
-            user_answer = st.text_area("Type your answer here", key=f"user_ans_{st.session_state.q_num}")
+            st.markdown("**👤 Your Answer:**")
+            user_answer = st.text_area("Type your answer here", key=f"user_ans_{qn}", height=150)
 
         with col2:
-            st.markdown("**Star Applicant's Answer:**")
-            if st.button("Generate Rival's Answer"):
+            st.markdown("**🤖 Rival's Answer:**")
+            if st.button("Generate Rival's Answer", key=f"rival_ans_{qn}"):
                 # Place your LLM call here to get the rival's answer
                 llm_answer = "This is how the star applicant would answer."
                 st.write(llm_answer)
 
         # Scoring/Feedback
-        if st.button("Score & Feedback"):
-            # Call LLM to compare and score
-            st.success("Your Score: 7/10\nStar Applicant's Score: 9/10")
-            st.info("Tip: Give more specific examples to boost your answer.")
-
-        # Next question navigation (simple MVP)
-        if st.session_state.q_num < len(questions) - 1:
-            if st.button("Next Question"):
-                st.session_state.q_num += 1
-                st.experimental_rerun()
+        col3, col4, col5 = st.columns([1, 1, 1])
+        with col3:
+            if st.button("📊 Score & Feedback", key=f"score_{qn}"):
+                # Call LLM to compare and score
+                st.success("Your Score: 7/10\nStar Applicant's Score: 9/10")
+                st.info("💡 Tip: Give more specific examples to boost your answer.")
+
+        # Next question navigation
+        with col4:
+            if st.session_state.q_num < len(questions) - 1:
+                if st.button("➡️ Next Question", key=f"next_{qn}"):
+                    st.session_state.q_num += 1
+                    st.rerun()
+            else:
+                st.success("🎉 Interview Complete!")
+                
+        with col5:
+            if st.session_state.q_num > 0:
+                if st.button("⬅️ Previous Question", key=f"prev_{qn}"):
+                    st.session_state.q_num -= 1
+                    st.rerun()
+
+        # Progress bar
+        progress = (qn + 1) / len(questions)
+        st.progress(progress, text=f"Progress: {qn + 1}/{len(questions)} questions")
+
+elif st.session_state.processing_complete and not st.session_state.questions:
+    st.error("❌ Failed to generate questions. Please try again.")
+    
+# Reset button in sidebar
+if st.session_state.processing_complete:
+    with st.sidebar:
+        st.divider()
+        if st.button("🔄 Start New Interview", type="secondary"):
+            for key in ['q_num', 'questions', 'processing_complete']:
+                if key in st.session_state:
+                    del st.session_state[key]
+            st.rerun()