Remove all Gradio files and dependencies

- Delete app/gradio_app.py (Gradio implementation)
- Delete app.py (Gradio entry point)
- Delete app/styles.css (Gradio CSS file)
- Clean up repository to use only Streamlit implementation

app.py

@@ -1,26 +0,0 @@
-#!/usr/bin/env python3
-"""
-Golf Swing Analysis - Hugging Face Spaces Entry Point (Gradio Interface)
-"""
-
-import os
-import sys
-
-# Add the app directory to the path for imports
-sys.path.append(os.path.join(os.path.dirname(__file__), 'app'))
-
-# Import and run the new Gradio app
-try:
-    from app.gradio_app import create_interface
-    
-    if __name__ == "__main__":
-        demo = create_interface()
-        demo.launch(share=True)
-except ImportError as e:
-    # Fallback import method
-    sys.path.insert(0, 'app')
-    import gradio_app
-    
-    if __name__ == "__main__":
-        demo = gradio_app.create_interface()
-        demo.launch(share=True) 

app/gradio_app.py

@@ -1,492 +0,0 @@
-"""
-Gradio web UI for Golf Swing Analysis with Step-based Flow
-"""
-
-import os
-import sys
-import tempfile
-import gradio as gr
-from dotenv import load_dotenv
-import base64
-from pathlib import Path
-import shutil
-import cv2
-from PIL import Image
-from datetime import datetime
-
-# Load environment variables
-load_dotenv()
-
-# Add the app directory to the path
-sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
-# Import analysis modules
-from utils.video_downloader import download_youtube_video, download_pro_reference, cleanup_video_file, cleanup_downloads_directory
-from utils.video_processor import process_video
-from models.pose_estimator import analyze_pose
-from models.swing_analyzer import segment_swing, analyze_trajectory
-from models.llm_analyzer import generate_swing_analysis, create_llm_prompt, prepare_data_for_llm, check_llm_services, parse_and_format_analysis
-
-# Import RAG functionality
-try:
-    from golf_swing_rag import GolfSwingRAG
-    RAG_AVAILABLE = True
-except ImportError:
-    RAG_AVAILABLE = False
-
-def validate_youtube_url(url):
-    """Validate if the URL is a YouTube URL"""
-    return "youtube.com" in url or "youtu.be" in url
-
-def start_analysis(input_text, video_file):
-    """Start video analysis process"""
-    try:
-        video_path = None
-        
-        # Handle video input
-        if video_file is not None:
-            # Save uploaded file
-            os.makedirs("downloads", exist_ok=True)
-            video_path = os.path.join("downloads", f"uploaded_{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp4")
-            shutil.copy(video_file.name, video_path)
-        elif input_text and validate_youtube_url(input_text):
-            # Download from YouTube
-            video_path = download_youtube_video(input_text)
-        else:
-                    return ("### Step 1: Upload Your Video", 
-               "Please provide either a valid YouTube URL or upload a video file.", 
-               1, None)
-        
-        if not video_path or not os.path.exists(video_path):
-            return ("### Step 1: Upload Your Video", 
-                   "Failed to process video. Please try again.", 
-                   1, None)
-        
-        # Move to analysis step
-        return ("### Step 2: Analyzing Video and Pose", 
-               "🔄 **Processing your swing video...**\n\nPlease wait while we analyze your golf swing.", 
-               2, {'video_path': video_path})
-        
-    except Exception as e:
-        error_message = f"Error starting analysis: {str(e)}"
-        return ("### Step 1: Upload Your Video", 
-               error_message, 1, None)
-
-def process_analysis(analysis_state):
-    """Process the actual video analysis"""
-    if not analysis_state or 'video_path' not in analysis_state:
-        return ("### Step 1: Upload Your Video", 
-               "No video to analyze. Please upload a video first.", 
-               1, None)
-    
-    try:
-        video_path = analysis_state['video_path']
-        
-        # Process video analysis
-        frames, detections = process_video(video_path, sample_rate=1)
-        pose_data = analyze_pose(frames)
-        swing_phases = segment_swing(pose_data, detections, sample_rate=1)
-        trajectory_data = analyze_trajectory(frames, detections, swing_phases, sample_rate=1)
-        analysis_data = prepare_data_for_llm(pose_data, swing_phases, trajectory_data)
-        
-        # Store complete results
-        results = {
-            'video_path': video_path,
-            'pose_data': pose_data,
-            'swing_phases': swing_phases,
-            'trajectory_data': trajectory_data,
-            'analysis_data': analysis_data
-        }
-        
-        # Generate results summary
-        results_content = f"""
-## 🏌️ Swing Analysis Results
-
-**Video:** {os.path.basename(video_path)}
-
-### 📊 **Analysis Summary**
-- **Swing Phases Detected:** {len(swing_phases) if swing_phases else 0}
-- **Pose Data Points:** {len(pose_data) if pose_data else 0}
-- **Trajectory Analysis:** {'✅ Complete' if trajectory_data else '❌ Failed'}
-
-### 🎯 **Key Findings**
-- Swing timing and rhythm patterns identified
-- Pose alignment and form analyzed
-- Ball trajectory and impact mechanics evaluated
-
-**Ready to dive deeper?** Choose how you'd like to explore your swing analysis:
-        """
-        
-        return ("### Step 3: See Your Results", 
-               results_content, 3, results)
-        
-    except Exception as e:
-        error_message = f"Error during analysis: {str(e)}"
-        return ("### Step 2: Analyzing Video and Pose", 
-               f"❌ **Analysis Failed**\n\n{error_message}\n\nPlease try again.", 
-               2, analysis_state)
-
-
-
-def go_to_improvements(analysis_results):
-    """Navigate to improvements step"""
-    return ("### Step 4: AI-Powered Improvements", 
-           "🎯 **Generating personalized swing improvements...**", 
-           4, analysis_results)
-
-def go_to_chatbot(analysis_results):
-    """Navigate to chatbot step"""
-    return ("### Step 5: Ask the Golf Expert", 
-           "💬 **Ready to answer your swing questions!**", 
-           5, analysis_results)
-
-def go_back_to_results(analysis_results):
-    """Go back to results step"""
-    if not analysis_results:
-        return ("### Step 1: Upload Your Video", 
-               "No analysis data available. Please start over.", 
-               1, None)
-    
-    results_content = f"""
-## 🏌️ Swing Analysis Results
-
-**Video:** {os.path.basename(analysis_results.get('video_path', 'Unknown'))}
-
-### 📊 **Analysis Summary**
-- **Swing Phases Detected:** {len(analysis_results.get('swing_phases', [])) if analysis_results.get('swing_phases') else 0}
-- **Pose Data Points:** {len(analysis_results.get('pose_data', [])) if analysis_results.get('pose_data') else 0}
-- **Trajectory Analysis:** {'✅ Complete' if analysis_results.get('trajectory_data') else '❌ Failed'}
-
-### 🎯 **Key Findings**
-- Swing timing and rhythm patterns identified
-- Pose alignment and form analyzed
-- Ball trajectory and impact mechanics evaluated
-
-**Ready to dive deeper?** Choose how you'd like to explore your swing analysis:
-    """
-    
-    return ("### Step 3: See Your Results", 
-           results_content, 3, analysis_results)
-
-def start_over():
-    """Reset to beginning"""
-    return ("### Step 1: Upload Your Video", 
-           "**Choose your input method:**", 
-           1, None)
-
-def handle_next_step(current_step, youtube_input, video_upload, analysis_results):
-    """Handle moving to next step"""
-    if current_step == 1:
-        # Start analysis
-        header, content, step, results = start_analysis(youtube_input, video_upload)
-        return (header, content, step, results,
-                gr.update(visible=False), gr.update(visible=True), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=True), gr.update(visible=False),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False))
-    elif current_step == 2:
-        # Process analysis
-        header, content, step, results = process_analysis(analysis_results)
-        if step == 3:  # Analysis complete
-            return (header, content, step, results,
-                    gr.update(visible=False), gr.update(visible=True), gr.update(visible=True),
-                    gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                    gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                    gr.update(visible=True), gr.update(visible=True), gr.update(visible=True))
-        else:
-            return (header, content, step, results,
-                    gr.update(visible=False), gr.update(visible=True), gr.update(visible=True),
-                    gr.update(visible=False), gr.update(visible=True), gr.update(visible=False),
-                    gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-                    gr.update(visible=False), gr.update(visible=False), gr.update(visible=False))
-    else:
-        # Should not happen with current flow
-        return (gr.update(), gr.update(), current_step, analysis_results,
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update())
-
-def handle_back_step(current_step, analysis_results):
-    """Handle going back one step"""
-    header, content, step, results = go_back_step(current_step, analysis_results)
-    
-    if step == 1:
-        return (header, content, step,
-                gr.update(value="🏌️ Start Analysis"), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=True), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False))
-    elif step == 3:
-        return (header, content, step,
-                gr.update(visible=False), gr.update(visible=True), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=True), gr.update(visible=True), gr.update(visible=True))
-    else:
-        return (header, content, step,
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update())
-
-def handle_go_to_step(target_step, analysis_results):
-    """Handle navigation to specific step"""
-    if target_step == 3:
-        header, content, step, results = go_back_to_results(analysis_results)
-        return (header, content, step,
-                gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=True), gr.update(visible=True), gr.update(visible=True))
-    elif target_step == 4:
-        header, content, step, results = go_to_improvements(analysis_results)
-        improvements_content = generate_improvements(analysis_results)
-        return (header, content, step,
-                gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=True), gr.update(visible=False), gr.update(visible=False),
-                gr.update(value=improvements_content), gr.update(visible=True), gr.update(visible=False), gr.update(visible=True))
-    elif target_step == 5:
-        header, content, step, results = go_to_chatbot(analysis_results)
-        return (header, content, step,
-                gr.update(visible=False), gr.update(visible=True),
-                gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-                gr.update(visible=False), gr.update(visible=True), gr.update(visible=False),
-                gr.update(visible=True), gr.update(visible=False), gr.update(visible=True))
-    else:
-        return (gr.update(), gr.update(), target_step,
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-                gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update())
-
-def handle_start_over():
-    """Handle starting over"""
-    header, content, step, results = start_over()
-    return (header, content, step, results,
-            gr.update(value="🏌️ Start Analysis"), gr.update(visible=False), gr.update(visible=False),
-            gr.update(visible=True), gr.update(visible=False), gr.update(visible=False),
-            gr.update(visible=False), gr.update(visible=False), gr.update(visible=False),
-            gr.update(visible=False), gr.update(visible=False), gr.update(visible=False))
-
-def generate_improvements(analysis_results):
-    """Generate AI-powered swing improvements"""
-    if not analysis_results:
-        return "No analysis data available. Please analyze a video first."
-    
-    try:
-        # Generate detailed analysis with recommendations
-        analysis = generate_swing_analysis(
-            analysis_results['pose_data'], 
-            analysis_results['swing_phases'],
-            analysis_results['trajectory_data']
-        )
-        
-        return f"""
-## 🎯 Personalized Swing Improvements
-
-{analysis}
-
----
-*Analysis generated using AI-powered swing analysis technology*
-        """
-        
-    except Exception as e:
-        return f"Error generating improvements: {str(e)}"
-
-def get_chatbot_response(question, analysis_results, chat_history):
-    """Get response from golf swing chatbot"""
-    if not RAG_AVAILABLE:
-        return chat_history + [("System", "Chatbot is not available due to missing dependencies.")], ""
-    
-    try:
-        # Initialize RAG system if needed
-        if not hasattr(get_chatbot_response, 'rag_system'):
-            get_chatbot_response.rag_system = GolfSwingRAG()
-            get_chatbot_response.rag_system.load_and_process_data()
-            get_chatbot_response.rag_system.create_embeddings()
-        
-        # Search for relevant information
-        relevant_chunks = get_chatbot_response.rag_system.search_similar_chunks(question, top_k=3)
-        
-        # Generate response (simplified version)
-        if relevant_chunks:
-            best_chunk = relevant_chunks[0]
-            response = f"Based on {best_chunk['metadata']['title']}: {best_chunk['chunk'][:300]}..."
-        else:
-            response = "I couldn't find specific information about that topic. Could you try rephrasing your question?"
-        
-        # Add to chat history
-        chat_history.append((question, response))
-        
-        return chat_history, ""
-        
-    except Exception as e:
-        chat_history.append((question, f"Error: {str(e)}"))
-        return chat_history, ""
-
-def go_back_step(current_step, analysis_results):
-    """Go back one step"""
-    if current_step <= 1:
-        return start_over()
-    elif current_step == 2:
-        return start_over()
-    elif current_step >= 3:
-        return go_back_to_results(analysis_results)
-    else:
-        return start_over()
-
-# Create the Gradio interface
-def create_interface():
-    with gr.Blocks(css="styles.css", title="Par-ity Project: Golf Swing Analysis") as demo:
-        # States
-        current_step = gr.State(1)
-        analysis_results = gr.State(None)
-        
-        with gr.Row():
-            # Floating sidebar (initially hidden)
-            with gr.Column(scale=1, visible=False, elem_id="sidebar") as sidebar:
-                gr.Markdown("### Navigation", elem_classes="sidebar-header")
-                results_btn = gr.Button("📊 Results", variant="secondary", size="sm", visible=False)
-                improvements_btn = gr.Button("🎯 Improvements", variant="secondary", size="sm", visible=False) 
-                chatbot_btn = gr.Button("💬 Chatbot", variant="secondary", size="sm", visible=False)
-                start_over_btn = gr.Button("🔄 Start Over", variant="secondary", size="sm")
-            
-            # Main content area
-            with gr.Column(scale=4, elem_classes="centered"):
-                # Logo
-                logo = gr.Image("1.png", show_label=False, width=150, height=75, container=False)
-                
-                # Step header with zigzag effect
-                step_header = gr.Markdown("### Step 1: Upload Your Video", elem_id="step-header")
-                
-                # Main content area
-                content_box = gr.Markdown("**Choose your input method:**")
-                
-                # Step 1: Upload section
-                with gr.Group(visible=True) as step1_content:
-                    with gr.Tab("YouTube URL"):
-                        youtube_input = gr.Textbox(
-                            lines=2, 
-                            placeholder="Paste YouTube URL of golf swing here...",
-                            label="YouTube URL",
-                            show_label=False
-                        )
-                    
-                    with gr.Tab("Upload Video"):
-                        video_upload = gr.File(
-                            file_types=["video"],
-                            label="Upload Video File", 
-                            show_label=False
-                        )
-                
-                # Step 2: Analysis in progress (hidden initially)
-                with gr.Group(visible=False) as step2_content:
-                    gr.Markdown("### 🔄 Processing Your Video")
-                    gr.Markdown("Please wait while we analyze your golf swing...")
-                    analysis_progress = gr.HTML("⏳ Starting analysis...")
-                
-                # Step 3: Results (hidden initially)  
-                with gr.Group(visible=False) as step3_content:
-                    results_display = gr.Markdown()
-                
-                # Step 4: Improvements (hidden initially)
-                with gr.Group(visible=False) as step4_content:
-                    improvements_output = gr.Markdown()
-                
-                # Step 5: Chatbot (hidden initially)
-                with gr.Group(visible=False) as step5_content:
-                    chatbot = gr.Chatbot(height=400)
-                    chatbot_input = gr.Textbox(placeholder="Ask about golf swing technique...", show_label=False)
-                    ask_btn = gr.Button("Ask Question")
-                
-                # Navigation buttons
-                with gr.Row():
-                    back_btn = gr.Button("← Back", variant="secondary", visible=False)
-                    next_btn = gr.Button("🏌️ Start Analysis", variant="primary", size="lg")
-                    
-                # Step 3 action buttons (shown only on results step)
-                with gr.Row(visible=False) as step3_actions:
-                    step3_improvements_btn = gr.Button("🎯 Get Improvements", variant="primary", size="lg")
-                    step3_chatbot_btn = gr.Button("💬 Ask Questions", variant="secondary", size="lg")
-        
-        # Event handlers for step navigation
-        next_btn.click(
-            fn=handle_next_step,
-            inputs=[current_step, youtube_input, video_upload, analysis_results],
-            outputs=[step_header, content_box, current_step, analysis_results, 
-                    next_btn, back_btn, sidebar, step1_content, step2_content, step3_content, 
-                    step4_content, step5_content, step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        back_btn.click(
-            fn=handle_back_step,
-            inputs=[current_step, analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn, 
-                    sidebar, step1_content, step2_content, step3_content, step4_content, 
-                    step5_content, step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        # Step 3 action buttons
-        step3_improvements_btn.click(
-            fn=lambda analysis_results: handle_go_to_step(4, analysis_results),
-            inputs=[analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn,
-                    step1_content, step2_content, step3_content, step4_content, step5_content, 
-                    step3_actions, improvements_output, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        step3_chatbot_btn.click(
-            fn=lambda analysis_results: handle_go_to_step(5, analysis_results),
-            inputs=[analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn,
-                    step1_content, step2_content, step3_content, step4_content, step5_content, 
-                    step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        # Sidebar navigation
-        results_btn.click(
-            fn=lambda analysis_results: handle_go_to_step(3, analysis_results),
-            inputs=[analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn,
-                    step1_content, step2_content, step3_content, step4_content, step5_content, 
-                    step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        improvements_btn.click(
-            fn=lambda analysis_results: handle_go_to_step(4, analysis_results),
-            inputs=[analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn,
-                    step1_content, step2_content, step3_content, step4_content, step5_content, 
-                    step3_actions, improvements_output, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        chatbot_btn.click(
-            fn=lambda analysis_results: handle_go_to_step(5, analysis_results),
-            inputs=[analysis_results],
-            outputs=[step_header, content_box, current_step, next_btn, back_btn,
-                    step1_content, step2_content, step3_content, step4_content, step5_content, 
-                    step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        start_over_btn.click(
-            fn=handle_start_over,
-            outputs=[step_header, content_box, current_step, analysis_results, 
-                    next_btn, back_btn, sidebar, step1_content, step2_content, step3_content, 
-                    step4_content, step5_content, step3_actions, results_btn, improvements_btn, chatbot_btn]
-        )
-        
-        # Chatbot functionality
-        ask_btn.click(
-            fn=get_chatbot_response,
-            inputs=[chatbot_input, analysis_results, chatbot],
-            outputs=[chatbot, chatbot_input]
-        )
-        
-        chatbot_input.submit(
-            fn=get_chatbot_response,
-            inputs=[chatbot_input, analysis_results, chatbot],
-            outputs=[chatbot, chatbot_input]
-        )
-    
-    return demo
-
-# Launch the app
-if __name__ == "__main__":
-    demo = create_interface()
-    demo.launch(share=True)

app/styles.css

@@ -1,122 +0,0 @@
-body {
-  background-color: #FFFFFF;
-  font-family: 'Georgia', serif;
-  color: #0B3B0B;
-}
-
-.centered {
-  min-height: 100vh;
-  display: flex;
-  flex-direction: column;
-  justify-content: center;
-  align-items: center;
-  gap: 20px;
-}
-
-button, .gr-button {
-  background-color: #0B3B0B !important;
-  color: #FFFFFF !important;
-  border-radius: 25px !important;
-  padding: 12px 28px !important;
-  font-weight: bold !important;
-  font-size: 16px !important;
-  transition: all 0.3s ease !important;
-  border: none !important;
-  box-shadow: 0 2px 8px rgba(11, 59, 11, 0.2) !important;
-}
-
-button:hover, .gr-button:hover {
-  background-color: #4CAF50 !important;
-  transform: translateY(-1px) !important;
-  box-shadow: 0 4px 12px rgba(11, 59, 11, 0.3) !important;
-}
-
-textarea, input, .gr-textbox {
-  border: 2px solid #4CAF50 !important;
-  border-radius: 10px;
-}
-
-#step-header::after {
-  content: "";
-  display: block;
-  height: 10px;
-  background-image: repeating-linear-gradient(
-    135deg,
-    #1D6F42,
-    #1D6F42 5px,
-    #A9DFBF 5px,
-    #A9DFBF 10px
-  );
-  margin-top: 8px;
-}
-
-/* Sidebar styling */
-#sidebar {
-  background-color: rgba(76, 175, 80, 0.05) !important;
-  border-right: 2px solid rgba(76, 175, 80, 0.2) !important;
-  padding: 20px !important;
-  position: sticky !important;
-  top: 20px !important;
-  height: fit-content !important;
-  border-radius: 15px !important;
-  margin-right: 20px !important;
-}
-
-.sidebar-header {
-  color: #0B3B0B !important;
-  font-weight: bold !important;
-  text-align: center !important;
-  margin-bottom: 15px !important;
-  font-size: 16px !important;
-}
-
-#sidebar button {
-  width: 100% !important;
-  margin-bottom: 10px !important;
-  font-size: 12px !important;
-  padding: 8px 12px !important;
-  text-align: left !important;
-}
-
-/* Mobile responsive styles */
-@media (max-width: 768px) {
-  .centered {
-    padding: 20px;
-    gap: 15px;
-  }
-  
-  button, .gr-button {
-    padding: 10px 20px !important;
-    font-size: 14px !important;
-    width: 100% !important;
-    max-width: 280px !important;
-  }
-  
-  #sidebar {
-    padding: 15px !important;
-    margin-right: 10px !important;
-    position: relative !important;
-  }
-  
-  .sidebar-header {
-    font-size: 14px !important;
-    margin-bottom: 10px !important;
-  }
-  
-  #sidebar button {
-    font-size: 11px !important;
-    padding: 6px 10px !important;
-    margin-bottom: 8px !important;
-  }
-}
-
-@media (max-width: 480px) {
-  #sidebar {
-    display: none !important;
-  }
-  
-  .centered {
-    padding: 10px;
-    gap: 12px;
-  }
-}