Update app.py

app.py

@@ -517,747 +517,3 @@ if __name__ == "__main__":
 
 
     
-# import gradio as gr
-# import google.generativeai as genai
-# import os
-# from dotenv import load_dotenv
-# from github import Github
-# import json
-# from pathlib import Path
-# from datetime import datetime
-# from collections import defaultdict
-# import base64
-# from typing import Dict, List, Any, Optional, Tuple
-# import tempfile
-# from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
-# import time
-# import os
-# import re
-# from fpdf import FPDF 
-# import requests
-
-
-
-# # Load environment variables
-# load_dotenv()
-
-# # Configure API keys
-# GITHUB_TOKEN = os.getenv("github_api")
-# GEMINI_API_KEY = os.getenv("gemini_api") 
-
-# if not GITHUB_TOKEN or not GEMINI_API_KEY:
-#     raise ValueError("Both GITHUB_TOKEN and GEMINI_API_KEY must be set in environment")
-
-# # Initialize APIs
-# gh = Github(GITHUB_TOKEN)
-# genai.configure(api_key=GEMINI_API_KEY)
-# model = genai.GenerativeModel(
-#     model_name="gemini-1.5-pro-latest",
-#     generation_config = {
-#   "temperature": 1,
-#   "top_p": 0.95,
-#   "top_k": 40,
-#   "max_output_tokens": 8192,
-#   "response_mime_type": "text/plain",
-# },
-    
-#     safety_settings=[
-#         {
-#             "category": "HARM_CATEGORY_HARASSMENT",
-#             "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-#         },
-#         {
-#             "category": "HARM_CATEGORY_HATE_SPEECH",
-#             "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-#         },
-#         {
-#             "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-#             "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-#         },
-#         {
-#             "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
-#             "threshold": "BLOCK_MEDIUM_AND_ABOVE"
-#         },
-#     ]
-# )
-
-# RELEVANT_EXTENSIONS = {
-#     ".py", ".js", ".ts", ".jsx", ".tsx", ".java", ".cpp", ".c", ".h",
-#     ".hpp", ".rb", ".php", ".go", ".rs", ".swift", ".kt"
-# }
-
-# class RepositoryAnalyzer:
-#     """Handles GitHub repository analysis"""
-
-#     def __init__(self, repo_url: str):
-#         # Extract owner and repo name from URL
-#         parts = repo_url.rstrip('/').split('/')
-#         if len(parts) < 2:
-#             raise ValueError("Invalid repository URL format")
-
-#         self.repo_name = parts[-1]
-#         self.owner = parts[-2]
-#         self.repo = gh.get_repo(f"{self.owner}/{self.repo_name}")
-#         self.analysis_data: Dict[str, Any] = {}
-
-#     def analyze(self) -> Dict[str, Any]:
-#         """Perform complete repository analysis"""
-#         try:
-#             # Basic repository information
-#             self.analysis_data["basic_info"] = {
-#                 "name": self.repo.name,
-#                 "owner": self.repo.owner.login,
-#                 "description": self.repo.description or "No description available",
-#                 "stars": self.repo.stargazers_count,
-#                 "forks": self.repo.forks_count,
-#                 "created_at": self.repo.created_at.isoformat(),
-#                 "last_updated": self.repo.updated_at.isoformat(),
-#                 "primary_language": self.repo.language or "Not specified",
-#             }
-
-#             # Analyze repository structure
-#             self.analysis_data["structure"] = self._analyze_structure()
-
-#             # Analyze code patterns
-#             self.analysis_data["code_patterns"] = self._analyze_code_patterns()
-
-#             # Analyze commit history
-#             self.analysis_data["commit_history"] = self._analyze_commits()
-
-#             # Get contributor statistics
-#             self.analysis_data["contributors"] = self._analyze_contributors()
-
-#             return self.analysis_data
-
-#         except Exception as e:
-#             raise Exception(f"Error analyzing repository: {str(e)}")
-
-#     def _analyze_structure(self) -> Dict[str, Any]:
-#         """Analyze repository structure and organization"""
-#         structure = {
-#             "files": defaultdict(int),
-#             "directories": set(),
-#             "total_size": 0,
-#         }
-
-#         try:
-#             contents = self.repo.get_contents("")
-#             while contents:
-#                 content = contents.pop(0)
-#                 if content.type == "dir":
-#                     structure["directories"].add(content.path)
-#                     contents.extend(self.repo.get_contents(content.path))
-#                 else:
-#                     ext = Path(content.path).suffix.lower()
-#                     if ext in RELEVANT_EXTENSIONS:
-#                         structure["files"][ext] += 1
-#                         structure["total_size"] += content.size
-#         except Exception as e:
-#             print(f"Error analyzing structure: {str(e)}")
-
-#         return {
-#             "file_types": dict(structure["files"]),
-#             "directory_count": len(structure["directories"]),
-#             "total_size": structure["total_size"],
-#             "file_count": sum(structure["files"].values())
-#         }
-
-#     def _analyze_code_patterns(self) -> Dict[str, Any]:
-#         """Analyze code patterns and style"""
-#         patterns = {
-#             "samples": [],
-#             "languages": defaultdict(int),
-#             "complexity_metrics": defaultdict(list)
-#         }
-
-#         try:
-#             files = self.repo.get_contents("")
-#             analyzed = 0
-
-#             while files and analyzed < 5:
-#                 file = files.pop(0)
-#                 if file.type == "dir":
-#                     files.extend(self.repo.get_contents(file.path))
-#                 elif Path(file.path).suffix.lower() in RELEVANT_EXTENSIONS:
-#                     try:
-#                         content = base64.b64decode(file.content).decode('utf-8')
-#                         lines = content.splitlines()
-
-#                         if not lines:
-#                             continue
-
-#                         loc = len([line for line in lines if line.strip()])
-#                         avg_line_length = sum(len(line) for line in lines) / len(lines)
-
-#                         patterns["samples"].append({
-#                             "path": file.path,
-#                             "language": Path(file.path).suffix[1:],
-#                             "loc": loc,
-#                             "avg_line_length": round(avg_line_length, 2)
-#                         })
-
-#                         patterns["languages"][Path(file.path).suffix[1:]] += loc
-#                         patterns["complexity_metrics"]["loc"].append(loc)
-#                         patterns["complexity_metrics"]["avg_line_length"].append(avg_line_length)
-
-#                         analyzed += 1
-
-#                     except Exception as e:
-#                         print(f"Error analyzing file {file.path}: {str(e)}")
-#                         continue
-
-#         except Exception as e:
-#             print(f"Error in code pattern analysis: {str(e)}")
-
-#         return patterns
-
-#     def _analyze_commits(self) -> Dict[str, Any]:
-#         """Analyze commit history and patterns"""
-#         commit_data = []
-#         commit_times = []
-
-#         try:
-#             commits = list(self.repo.get_commits()[:100])  # Get last 100 commits
-
-#             for commit in commits:
-#                 try:
-#                     commit_info = {
-#                         "sha": commit.sha,
-#                         "author": commit.author.login if commit.author else "Unknown",
-#                         "date": commit.commit.author.date.isoformat(),
-#                         "message": commit.commit.message,
-#                         "changes": {
-#                             "additions": commit.stats.additions,
-#                             "deletions": commit.stats.deletions,
-#                         }
-#                     }
-#                     commit_data.append(commit_info)
-#                     commit_times.append(commit.commit.author.date.hour)
-#                 except Exception as e:
-#                     print(f"Error processing commit {commit.sha}: {str(e)}")
-#                     continue
-
-#             # Analyze commit patterns
-#             commit_hours = defaultdict(int)
-#             for hour in commit_times:
-#                 commit_hours[hour] += 1
-
-#             total_commits = len(commit_data)
-#             return {
-#                 "commits": commit_data,
-#                 "total_commits": total_commits,
-#                 "commit_hours": dict(commit_hours),
-#                 "avg_additions": sum(c["changes"]["additions"] for c in commit_data) / total_commits if total_commits else 0,
-#                 "avg_deletions": sum(c["changes"]["deletions"] for c in commit_data) / total_commits if total_commits else 0,
-#             }
-
-#         except Exception as e:
-#             print(f"Error in commit analysis: {str(e)}")
-#             return {
-#                 "commits": [],
-#                 "total_commits": 0,
-#                 "commit_hours": {},
-#                 "avg_additions": 0,
-#                 "avg_deletions": 0
-#             }
-
-#     def _analyze_contributors(self) -> Dict[str, Any]:
-#         """Analyze contributor statistics"""
-#         contributor_data = []
-
-#         try:
-#             contributors = list(self.repo.get_contributors())
-#             for contributor in contributors:
-#                 contributor_data.append({
-#                     "login": contributor.login,
-#                     "contributions": contributor.contributions,
-#                     "type": contributor.type,
-#                 })
-#         except Exception as e:
-#             print(f"Error analyzing contributors: {str(e)}")
-
-#         return {
-#             "total_contributors": len(contributor_data),
-#             "contributors": contributor_data
-#         }
-# def create_pdf_from_markdown(markdown_text: str, filename: str) -> str:
-#     """Convert markdown text to PDF"""
-#     class PDF(FPDF):
-#         def header(self):
-#             self.set_font('Arial', 'B', 12)
-#             self.cell(0, 10, 'Repository Analysis Report', 0, 1, 'C')
-#             self.ln(10)
-
-#         def footer(self):
-#             self.set_y(-15)
-#             self.set_font('Arial', 'I', 8)
-#             self.cell(0, 10, f'Page {self.page_no()}', 0, 0, 'C')
-
-#     pdf = PDF()
-#     pdf.add_page()
-#     pdf.set_auto_page_break(auto=True, margin=15)
-
-#     # Process markdown sections
-#     sections = markdown_text.split('\n## ')
-    
-#     # Handle main title
-#     if sections[0].startswith('# '):
-#         title = sections[0].split('\n')[0].replace('# ', '')
-#         pdf.set_font('Arial', 'B', 16)
-#         pdf.cell(0, 10, title, 0, 1, 'C')
-#         pdf.ln(5)
-#         content = '\n'.join(sections[0].split('\n')[1:])
-#         sections[0] = content
-
-#     for section in sections:
-#         if section:
-#             # Extract section title and content
-#             lines = section.split('\n')
-#             if section == sections[0]:  # First section (after main title)
-#                 section_title = ''
-#                 content = lines
-#             else:
-#                 section_title = lines[0]
-#                 content = lines[1:]
-
-#             # Add section title
-#             if section_title:
-#                 pdf.set_font('Arial', 'B', 14)
-#                 # Remove emojis from section titles
-#                 clean_title = re.sub(r'[^\x00-\x7F]+', '', section_title)
-#                 pdf.cell(0, 10, clean_title.strip(), 0, 1, 'L')
-#                 pdf.ln(5)
-
-#             # Add content
-#             pdf.set_font('Arial', '', 11)
-#             for line in content:
-#                 if line.strip():
-#                     # Remove markdown formatting and emojis
-#                     clean_line = re.sub(r'[\*\[\]]', '', line)
-#                     clean_line = re.sub(r'[^\x00-\x7F]+', '', clean_line)
-                    
-#                     if line.startswith('- '):
-#                         pdf.cell(10, 5, '', 0, 0)
-#                         pdf.multi_cell(0, 5, clean_line[2:])
-#                     else:
-#                         pdf.multi_cell(0, 5, clean_line)
-#             pdf.ln(5)
-
-#     # Save PDF
-#     pdf_path = f"{filename}.pdf"
-#     pdf.output(pdf_path)
-#     return pdf_path
-
-# def download_noto_font():
-#     """Download Google's Noto Color Emoji font if not already present"""
-#     font_path = "NotoColorEmoji.ttf"
-#     if not os.path.exists(font_path):
-#         url = "https://github.com/googlefonts/noto-emoji/raw/main/fonts/NotoColorEmoji.ttf"
-#         response = requests.get(url)
-#         with open(font_path, "wb") as f:
-#             f.write(response.content)
-#     return font_path
-
-# class PDFWithEmoji(FPDF):
-#     def __init__(self):
-#         super().__init__()
-#         self.add_font('DejaVu', '', 'DejaVuSansCondensed.ttf', uni=True)
-#         self.add_font('Noto', '', 'NotoColorEmoji.ttf', uni=True)
-        
-#     def header(self):
-#         self.set_font('DejaVu', '', 12)
-#         self.cell(0, 10, '📊 Repository Analysis Report', 0, 1, 'C')
-#         self.ln(10)
-
-#     def footer(self):
-#         self.set_y(-15)
-#         self.set_font('DejaVu', '', 8)
-#         self.cell(0, 10, f'Page {self.page_no()}', 0, 0, 'C')
-        
-#     def write_with_emoji(self, text):
-#         """Write text with proper emoji support"""
-#         self.set_font('DejaVu', '', 11)
-#         self.multi_cell(0, 5, text)
-
-# def create_pdf_report(markdown_text: str) -> str:
-#     """Create a PDF report with full emoji and Unicode support"""
-#     # Ensure required fonts are available
-#     if not os.path.exists("DejaVuSansCondensed.ttf"):
-#         url = "https://github.com/dejavu-fonts/dejavu-fonts/raw/master/ttf/DejaVuSansCondensed.ttf"
-#         response = requests.get(url)
-#         with open("DejaVuSansCondensed.ttf", "wb") as f:
-#             f.write(response.content)
-    
-#     download_noto_font()
-    
-#     # Create PDF
-#     pdf = PDFWithEmoji()
-#     pdf.add_page()
-#     pdf.set_auto_page_break(auto=True, margin=15)
-
-#     # Process markdown text
-#     sections = markdown_text.split('\n## ')
-    
-#     # Handle main title
-#     if sections[0].startswith('# '):
-#         title = sections[0].split('\n')[0].replace('# ', '')
-#         pdf.set_font('DejaVu', '', 16)
-#         pdf.cell(0, 10, title, 0, 1, 'C')
-#         pdf.ln(5)
-#         content = '\n'.join(sections[0].split('\n')[1:])
-#         sections[0] = content
-
-#     # Process each section
-#     for section in sections:
-#         if section:
-#             lines = section.split('\n')
-#             if section == sections[0]:  # First section
-#                 section_title = ''
-#                 content = lines
-#             else:
-#                 section_title = lines[0]
-#                 content = lines[1:]
-
-#             # Add section title
-#             if section_title:
-#                 pdf.set_font('DejaVu', '', 14)
-#                 pdf.cell(0, 10, section_title, 0, 1, 'L')
-#                 pdf.ln(5)
-
-#             # Add content
-#             pdf.set_font('DejaVu', '', 11)
-#             for line in content:
-#                 if line.strip():
-#                     if line.strip().startswith('- '):
-#                         pdf.cell(10, 5, '•', 0, 0)
-#                         pdf.write_with_emoji(line.strip()[2:])
-#                         pdf.ln()
-#                     else:
-#                         pdf.write_with_emoji(line.strip())
-#                         pdf.ln()
-
-#     # Save PDF
-#     timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
-#     pdf_path = f"repo_analysis_{timestamp}.pdf"
-#     pdf.output(pdf_path)
-#     return pdf_path
-
-# @retry(
-#     retry=retry_if_exception_type(Exception),
-#     stop=stop_after_attempt(3),
-#     wait=wait_exponential(multiplier=1, min=4, max=10)
-# )
-
-
-# def analyze_repository(repo_url: str, progress=gr.Progress()) -> Tuple[str, str, str]:
-#     """Analyze repository and generate LLM summary with rate limit handling"""
-#     try:
-#         # Initialize analyzer
-#         progress(0, desc="Initializing repository analysis...")
-#         analyzer = RepositoryAnalyzer(repo_url)
-
-#         # Perform analysis
-#         progress(0.3, desc="Analyzing repository structure and patterns...")
-#         analysis_data = analyzer.analyze()
-
-#         # Generate LLM summary
-#         progress(0.7, desc="Generating analysis summary...")
-
-#         system_prompt = """You are an expert code analyst with deep experience in software architecture, development practices, and team dynamics. Analyze the provided repository data and create a detailed, insightful analysis using the following markdown template:
-
-# # Repository Analysis
-
-# ## 📊 Project Overview
-# [Provide a comprehensive overview including:
-# - Project purpose and scope
-# - Age and maturity of the project
-# - Current activity level and maintenance status
-# - Key metrics (stars, forks, etc.)
-# - Primary technologies and languages used]
-
-# ## 🏗️ Architecture and Code Organization
-# [Analyze in detail:
-# - Repository structure and organization
-# - Code distribution across different technologies
-# - File and directory organization patterns
-# - Project size and complexity metrics
-# - Code modularity and component structure
-# - Presence of key architectural patterns]
-
-# ## 💻 Development Practices & Code Quality
-# [Evaluate:
-# - Coding standards and consistency
-# - Code complexity and maintainability metrics
-# - Documentation practices
-# - Testing approach and coverage (if visible)
-# - Error handling and logging practices
-# - Use of design patterns and best practices]
-
-# ## 📈 Development Workflow & History
-# [Analyze:
-# - Commit patterns and frequency
-# - Release cycles and versioning
-# - Branch management strategy
-# - Code review practices
-# - Continuous integration/deployment indicators
-# - Peak development periods and cycles]
-
-# ## 👥 Team Dynamics & Collaboration
-# [Examine:
-# - Team size and composition
-# - Contribution patterns
-# - Core maintainer identification
-# - Community engagement level
-# - Communication patterns
-# - Collaboration efficiency]
-
-# ## 🔧 Technical Depth & Innovation
-# [Assess:
-# - Technical sophistication level
-# - Innovative approaches or solutions
-# - Complex problem-solving examples
-# - Performance optimization efforts
-# - Security considerations
-# - Scalability approach]
-
-# ## 🚀 Project Health & Sustainability
-# [Evaluate:
-# - Project momentum and growth trends
-# - Maintenance patterns
-# - Community health indicators
-# - Documentation completeness
-# - Onboarding friendliness
-# - Long-term viability indicators]
-
-# ## 💡 Key Insights & Recommendations
-# [Provide:
-# - 3-5 key strengths identified
-# - 3-5 potential improvement areas
-# - Notable patterns or practices
-# - Unique characteristics
-# - Strategic recommendations]
-
-# Please provide detailed analysis for each section while maintaining the formatting and emojis. Support insights with specific metrics and examples from the repository data where possible."""
-
-#         chat = model.start_chat(history=[])
-#         response = chat.send_message(f"{system_prompt}\n\nRepository Analysis Data:\n{json.dumps(analysis_data, indent=2)}")
-
-#         # Save analysis data
-#         progress(0.9, desc="Saving analysis results...")
-#         with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.json') as f:
-#             json.dump(analysis_data, f, indent=2)
-#             analysis_file = f.name
-
-#         progress(0.9, desc="Generating PDF report...")
-#         try:
-#             pdf_path = create_pdf_report(response.text)
-#         except Exception as pdf_error:
-#             print(f"PDF generation error: {str(pdf_error)}")
-#             pdf_path = ""
-
-        
-        
-#         # Generate PDF
-#         pdf_path = create_pdf_from_markdown(response.text, f"analysis_{datetime.now().strftime('%Y%m%d_%H%M%S')}")
-        
-#         with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.json') as f:
-#             json.dump(analysis_data, f, indent=2)
-#             analysis_file = f.name
-
-        
-        
-
-#         progress(1.0, desc="✨ Analysis complete!")
-#         return response.text, analysis_file, pdf_path, "✅ Analysis completed successfully!"
-
-#     except Exception as e:
-#         error_message = f"❌ Error analyzing repository: {str(e)}"
-#         return "", "", "", error_message  # Return 4 empty values when there's an error
-
-# def create_chat_session() -> Any:
-#     """Create a new chat session for follow-up questions"""
-#     return genai.GenerativeModel(
-#         model_name="gemini-pro",
-#         generation_config={
-#             'temperature': 0.7,
-#             'top_p': 0.8,
-#             'top_k': 40,
-#             'max_output_tokens': 2048,
-#         }
-#     )
-
-# @retry(
-#     retry=retry_if_exception_type(Exception),
-#     stop=stop_after_attempt(3),
-#     wait=wait_exponential(multiplier=1, min=4, max=10)
-# )
-# def ask_question(question: str, analysis_file: str, chat_history: List[Tuple[str, str]]) -> List[Tuple[str, str]]:
-#     """Process a follow-up question about the analysis"""
-#     if not analysis_file:
-#         return chat_history + [(question, "Please analyze a repository first before asking questions.")]
-
-#     try:
-#         # Load analysis data
-#         with open(analysis_file, 'r') as f:
-#             analysis_data = json.load(f)
-
-#         # Initialize chat model
-#         model = create_chat_session()
-
-#         # Build context from chat history and current question
-#         context = "You are an expert code analyst helping users understand repository analysis results.\n\n"
-#         context += f"Repository Analysis Data:\n{json.dumps(analysis_data, indent=2)}\n\n"
-
-#         # Add chat history context
-#         if chat_history:
-#             context += "Previous conversation:\n"
-#             for user_msg, assistant_msg in chat_history:
-#                 context += f"User: {user_msg}\nAssistant: {assistant_msg}\n"
-
-#         # Add current question
-#         prompt = context + f"\nUser: {question}\nPlease provide your analysis:"
-
-#         # Get response
-#         response = model.generate_content(prompt)
-
-#         # Return in the correct tuple format for Gradio chatbot
-#         return chat_history + [(question, response.text)]
-
-#     except Exception as e:
-#         error_message = f"Error processing question: {str(e)}"
-#         return chat_history + [(question, error_message)]
-
-
-
-
-# # Create Gradio interface
-# # Create Gradio interface
-# with gr.Blocks(theme=gr.themes.Soft()) as app:
-#     gr.Markdown("""
-#     # 🔍 GitHub Repository Analyzer
-
-#     Analyze any public GitHub repository using AI. The tool will:
-#     1. 📊 Analyze repository structure and patterns
-#     2. 💡 Generate insights about development practices
-#     3. 💭 Allow you to ask follow-up questions about the analysis
-#     4. 📑 Generate a downloadable PDF report
-#     """)
-
-#     with gr.Row():
-#         repo_url = gr.Textbox(
-#             label="GitHub Repository URL",
-#             placeholder="https://github.com/owner/repo",
-#             scale=4
-#         )
-
-#     with gr.Row():
-#         with gr.Column(scale=1):
-#             analyze_btn = gr.Button("🔍 Analyze", variant="primary")
-#             download_pdf_btn = gr.Button("📄 Download PDF", variant="secondary")
-    
-#     # Status message
-#     status_msg = gr.Markdown("", elem_id="status_message")
-    
-#     # File output for PDF
-#     pdf_output = gr.File(
-#         label="Analysis Report",
-#         visible=False,
-#         interactive=True
-#     )
-    
-#     with gr.Row():
-#         summary = gr.Markdown(label="Analysis Summary")
-
-#     with gr.Row():
-#         chatbot = gr.Chatbot(
-#             label="Ask Questions",
-#             height=400,
-#             show_label=True
-#         )
-
-#     with gr.Row():
-#         question = gr.Textbox(
-#             label="Your Question",
-#             placeholder="Ask about the analysis...",
-#             scale=4
-#         )
-#         ask_btn = gr.Button("💭 Ask", variant="primary", scale=1)
-#         clear_btn = gr.Button("🗑️ Clear Chat", variant="secondary", scale=1)
-
-#     # Hidden states
-#     analysis_file = gr.State("")
-#     current_pdf_path = gr.State("")
-
-#     def handle_pdf_download(pdf_path):
-#         """Handle PDF download when button is clicked"""
-#         if pdf_path and os.path.exists(pdf_path):
-#             return {
-#                 pdf_output: pdf_path
-#             }
-#         return {
-#             pdf_output: None
-#         }
-
-#     def clear_outputs():
-#         """Clear all outputs"""
-#         return {
-#             summary: "",
-#             chatbot: [],
-#             question: "",
-#             status_msg: "",
-#             pdf_output: None,
-#             current_pdf_path: ""
-#         }
-
-#     # Event handlers
-#     analyze_btn.click(
-#         fn=lambda: "⏳ Analysis in progress...",
-#         inputs=None,
-#         outputs=status_msg,
-#         queue=False
-#     ).then(
-#         analyze_repository,
-#         inputs=[repo_url],
-#         outputs=[summary, analysis_file, current_pdf_path, status_msg]
-#     ).then(
-#         lambda: gr.update(visible=True),
-#         None,
-#         download_pdf_btn
-#     )
-
-#     # PDF download handler
-#     download_pdf_btn.click(
-#         handle_pdf_download,
-#         inputs=[current_pdf_path],
-#         outputs=pdf_output
-#     ).then(
-#         lambda: gr.update(visible=True),
-#         None,
-#         pdf_output
-#     )
-
-#     ask_btn.click(
-#         ask_question,
-#         inputs=[question, analysis_file, chatbot],
-#         outputs=[chatbot]
-#     ).then(
-#         lambda: "",
-#         None,
-#         question,
-#         queue=False
-#     )
-
-#     clear_btn.click(
-#         clear_outputs,
-#         inputs=None,
-#         outputs=[summary, chatbot, question, status_msg, pdf_output, current_pdf_path]
-#     )
-
-
-
-# # Launch the app
-# if __name__ == "__main__":
-#     app.launch(
-#         share=True,
-#         debug=True
-#     )