update

DEPLOYMENT_GUIDE.md

@@ -0,0 +1,54 @@
+# DEPLOYMENT SOLUTIONS FOR HUGGING FACE SPACES
+
+## Issues Identified:
+1. ✅ Missing dependencies - FIXED
+2. ✅ Missing GROQ_API_KEY - NEEDS CONFIGURATION 
+3. ✅ File paths - FIXED
+4. ❌ Gradio version bug - NEEDS VERSION DOWNGRADE
+
+## Solution 1: Update Requirements.txt with Compatible Gradio Version
+
+Replace your requirements.txt with this:
+
+```
+gradio==4.40.0
+openai-whisper
+pydub
+soundfile
+PyMuPDF
+python-docx
+reportlab
+speechrecognition
+duckduckgo-search
+matplotlib
+regex
+groq
+```
+
+## Solution 2: Set Environment Variables in HF Spaces
+
+In your Hugging Face Space settings, add:
+- Variable name: GROQ_API_KEY
+- Variable value: your_actual_groq_api_key
+
+## Solution 3: Use the Fixed App Version
+
+Use app_fixed.py as your main app.py file - it has better error handling.
+
+## Solution 4: Alternative - Simplify the App
+
+If the Gradio bug persists, use a simpler version without some advanced features.
+
+## Files Ready for Deployment:
+- ✅ config.py (fixed paths)
+- ✅ requirements.txt (compatible versions)
+- ✅ app_fixed.py (better error handling)
+- ✅ All modules updated with graceful fallbacks
+- ✅ Dockerfile updated
+- ✅ Environment validation script
+
+## Deployment Steps:
+1. Update requirements.txt with Gradio 4.40.0
+2. Set GROQ_API_KEY in HF Spaces environment variables
+3. Upload all files to your HF Space
+4. The app should work with limited audio features but full interview functionality

app_fixed.py

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+# app_fixed.py
+import gradio as gr
+import os
+import time
+import datetime
+import config
+
+# Import modules with error handling
+try:
+    from modules.tts_handler import text_to_speech_file
+    from modules.stt_handler import transcribe_audio
+    from modules.doc_processor import extract_text_from_document
+    from modules.llm_handler import generate_question, evaluate_answer
+    from modules.report_generator import generate_pdf_report
+    TTS_AVAILABLE = True
+except ImportError as e:
+    print(f"Warning: Some modules could not be imported: {e}")
+    TTS_AVAILABLE = False
+
+def start_interview(interview_type, doc_file, name, num_questions):
+    if not interview_type or not doc_file:
+        return (
+            {},  # state
+            [["System", "Please select an interview type and upload a document to begin."]],  # chatbot
+            None,  # audio_out
+            gr.update(interactive=False),  # audio_in
+            gr.update(interactive=True)   # start_btn
+        )
+    
+    try:
+        doc_text = extract_text_from_document(doc_file.name)
+        if "Error" in doc_text or "Unsupported" in doc_text:
+            return (
+                {},
+                [["System", f"Error: {doc_text}"]],
+                None,
+                gr.update(interactive=False),
+                gr.update(interactive=True)
+            )
+        
+        initial_state = {
+            "interview_type": interview_type,
+            "doc_text": doc_text,
+            "name": name if name else "User",
+            "question_count": int(num_questions),
+            "current_question_num": 1,
+            "interview_log": [],
+            "start_time": time.time()
+        }
+        
+        first_question = generate_question(interview_type, doc_text)
+        initial_state["current_question_text"] = first_question
+        greeting = f"Hello {initial_state['name']}. We'll go through {int(num_questions)} questions today. Here is your first question:"
+        
+        # Try to generate TTS audio, but don't fail if it's not available
+        ai_voice_path = None
+        if TTS_AVAILABLE:
+            try:
+                tts_prompt = f"{greeting} {first_question}"
+                ai_voice_path = text_to_speech_file(tts_prompt)
+            except Exception as e:
+                print(f"TTS generation failed: {e}")
+        
+        return (
+            initial_state,
+            [["System", f"{greeting}\n\n{first_question}"]],
+            ai_voice_path,
+            gr.update(interactive=True),
+            gr.update(interactive=False)
+        )
+        
+    except Exception as e:
+        return (
+            {},
+            [["System", f"An error occurred: {str(e)}"]],
+            None,
+            gr.update(interactive=False),
+            gr.update(interactive=True)
+        )
+
+def handle_interview_turn(user_audio, chatbot_history, current_state):
+    if not current_state or not user_audio:
+        return current_state, chatbot_history, None, gr.update(interactive=True), gr.update(visible=False)
+    
+    try:
+        user_answer_text = transcribe_audio(user_audio)
+        new_history = chatbot_history + [[user_answer_text, None]]
+        
+        evaluation_text = evaluate_answer(current_state["current_question_text"], user_answer_text)
+        current_state["interview_log"].append({
+            "question": current_state["current_question_text"],
+            "answer": user_answer_text,
+            "evaluation": evaluation_text
+        })
+        
+        if current_state["current_question_num"] >= current_state["question_count"]:
+            end_message = "This concludes the interview. Generating your final report now."
+            final_history = new_history + [["System", end_message]]
+            
+            # Generate PDF
+            pdf_path = generate_pdf_file(current_state)
+            
+            # Try TTS
+            ai_voice_path = None
+            if TTS_AVAILABLE:
+                try:
+                    ai_voice_path = text_to_speech_file(end_message)
+                except Exception as e:
+                    print(f"TTS generation failed: {e}")
+            
+            return (
+                current_state,
+                final_history,
+                ai_voice_path,
+                gr.update(interactive=False),
+                gr.update(value=pdf_path, visible=True)
+            )
+        else:
+            current_state["current_question_num"] += 1
+            next_question = generate_question(current_state["interview_type"], current_state["doc_text"])
+            current_state["current_question_text"] = next_question
+            q_num = current_state["current_question_num"]
+            transition_message = f"Thank you. Here is question {q_num}:\n\n{next_question}"
+            final_history = new_history + [["System", transition_message]]
+            
+            # Try TTS
+            ai_voice_path = None
+            if TTS_AVAILABLE:
+                try:
+                    ai_voice_path = text_to_speech_file(transition_message)
+                except Exception as e:
+                    print(f"TTS generation failed: {e}")
+            
+            return (
+                current_state,
+                final_history,
+                ai_voice_path,
+                gr.update(interactive=True),
+                gr.update(visible=False)
+            )
+            
+    except Exception as e:
+        error_history = chatbot_history + [["System", f"An error occurred: {str(e)}"]]
+        return current_state, error_history, None, gr.update(interactive=True), gr.update(visible=False)
+
+def generate_pdf_file(state):
+    try:
+        total_duration_minutes = (time.time() - state.get("start_time", time.time())) / 60
+        final_data = { 
+            "name": state.get("name", "N/A"), 
+            "type": state.get("interview_type", "N/A"), 
+            "duration": total_duration_minutes,
+            "q_and_a": state.get("interview_log", [])
+        }
+        file_name = f"Report_{state.get('name', 'User')}_{datetime.datetime.now().strftime('%Y-%m-%d')}.pdf"
+        file_path = os.path.join(config.REPORT_FOLDER, file_name)
+        generate_pdf_report(final_data, file_path)
+        return file_path
+    except Exception as e:
+        print(f"PDF generation failed: {e}")
+        return None
+
+with gr.Blocks(theme=gr.themes.Default()) as app:
+    state = gr.State(value={})
+    
+    gr.Markdown("# PM Interview Coach")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### Setup")
+            user_name = gr.Textbox(label="Your Name", placeholder="Enter your name")
+            interview_type_dd = gr.Dropdown(choices=config.INTERVIEW_TYPES, label="Interview Type")
+            num_questions_slider = gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Number of Questions")
+            doc_uploader = gr.File(label="Upload Resume/CV (.pdf, .docx)", file_types=['.pdf', '.docx'])
+            start_btn = gr.Button("Start Interview", variant="primary")
+        
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(label="Conversation", height=500)
+            audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Your Answer", interactive=False)
+            audio_out = gr.Audio(visible=False, autoplay=True)
+            download_pdf_btn = gr.File(label="Download Report", visible=False)
+
+    # Event handlers
+    start_btn.click(
+        fn=start_interview,
+        inputs=[interview_type_dd, doc_uploader, user_name, num_questions_slider],
+        outputs=[state, chatbot, audio_out, audio_in, start_btn]
+    )
+    
+    audio_in.stop_recording(
+        fn=handle_interview_turn,
+        inputs=[audio_in, chatbot, state],
+        outputs=[state, chatbot, audio_out, audio_in, download_pdf_btn]
+    )
+
+if __name__ == "__main__":
+    # Create necessary directories
+    os.makedirs(config.UPLOAD_FOLDER, exist_ok=True)
+    os.makedirs(config.REPORT_FOLDER, exist_ok=True)
+    
+    # Launch the app
+    app.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False
+    )

modules/llm_handler.py

@@ -8,12 +8,19 @@ from modules.web_search import search_for_example_answers
 # Initialize the Groq client
 groq_api_key = os.environ.get("GROQ_API_KEY")
 if not groq_api_key:
-    raise ValueError("GROQ_API_KEY environment variable is required but not set")
-
-client = Groq(api_key=groq_api_key)
-MODEL = "llama3-70b-8192" # Use the more powerful 70B model for detailed analysis
+    print("⚠️  WARNING: GROQ_API_KEY environment variable is not set")
+    print("   The application will not work properly without this API key")
+    print("   Please set your GROQ API key before running the application")
+    client = None
+    MODEL = None
+else:
+    client = Groq(api_key=groq_api_key)
+    MODEL = "llama3-70b-8192" # Use the more powerful 70B model for detailed analysis
 
 def generate_question(interview_type, document_text):
+    if not client:
+        return "Error: GROQ_API_KEY not configured. Please set your API key to use this feature."
+    
     prompt = f"As an expert {interview_type} interviewer, ask one relevant, open-ended question based on this document:\n\n---\n{document_text}\n---"
     try:
         chat_completion = client.chat.completions.create(
@@ -24,6 +31,9 @@ def generate_question(interview_type, document_text):
         return f"Error generating question from API: {e}"
 
 def evaluate_answer(question, answer):
+    if not client:
+        return "Error: GROQ_API_KEY not configured. Please set your API key to use this feature."
+    
     # This new prompt demands a much higher level of detail
     prompt = f"""
     You are a meticulous and insightful interview coach. Your task is to provide a highly detailed evaluation of a candidate's answer.
@@ -80,6 +90,9 @@ def parse_scores_from_evaluation(evaluation_text: str) -> dict:
     return scores
 
 def generate_holistic_feedback(full_interview_log):
+    if not client:
+        return "Error: GROQ_API_KEY not configured. Please set your API key to use this feature."
+    
     # This prompt is also enhanced for more detail
     prompt = f"""
     You are a senior career strategist reviewing a candidate's full interview performance.

modules/web_search.py

@@ -1,6 +1,6 @@
 # modules/web_search.py
 
-from ddgs import DDGS
+from duckduckgo_search import DDGS
 
 def search_for_example_answers(query: str, num_results: int = 2):
     """

requirements.txt

@@ -1,4 +1,4 @@
-gradio==4.44.0
+gradio==4.40.0
 openai-whisper
 pydub
 soundfile
@@ -13,4 +13,5 @@ groq
 # Removed problematic dependencies for HF Spaces:
 # - ollama (local service, not available in HF Spaces)
 # - pyaudio (often causes build issues)
-# - piper-tts (system dependencies issues)
+# - piper-tts (system dependencies issues)
+# Using Gradio 4.40.0 to avoid version 4.44.0 API schema bug

test_simple.py

@@ -0,0 +1,31 @@
+# test_simple.py
+import gradio as gr
+import os
+
+def simple_greeting(name):
+    return f"Hello {name}! The app is working properly."
+
+def test_groq_connection():
+    groq_key = os.environ.get("GROQ_API_KEY")
+    if groq_key:
+        return "✅ GROQ API key is configured"
+    else:
+        return "❌ GROQ API key is missing"
+
+# Create a simple interface to test basic functionality
+with gr.Blocks() as demo:
+    gr.Markdown("# AI Interview Coach - Connection Test")
+    
+    with gr.Row():
+        name_input = gr.Textbox(label="Your Name", placeholder="Enter your name")
+        greeting_output = gr.Textbox(label="Greeting", interactive=False)
+    
+    with gr.Row():
+        test_btn = gr.Button("Test GROQ Connection")
+        status_output = gr.Textbox(label="API Status", interactive=False)
+    
+    name_input.change(simple_greeting, inputs=[name_input], outputs=[greeting_output])
+    test_btn.click(test_groq_connection, outputs=[status_output])
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)