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| 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 | |
| # 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 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(1.0, desc="Analysis complete!") | |
| return response.text, analysis_file, "✅ Analysis completed successfully!" | |
| except Exception as e: | |
| error_message = f"❌ Error analyzing repository: {str(e)}" | |
| return "", "", error_message | |
| 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, | |
| } | |
| ) | |
| 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 | |
| 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 | |
| Enter a GitHub repository URL (e.g., `https://github.com/owner/repo`) | |
| """) | |
| with gr.Row(): | |
| repo_url = gr.Textbox( | |
| label="GitHub Repository URL", | |
| placeholder="https://github.com/owner/repo", | |
| scale=4 | |
| ) | |
| analyze_btn = gr.Button("🔍 Analyze", variant="primary", scale=1) | |
| # Add status message | |
| status_msg = gr.Markdown("", elem_id="status_message") | |
| with gr.Row(): | |
| # Use Markdown instead of Textbox for better formatting | |
| 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 state for analysis file | |
| analysis_file = gr.State("") | |
| def clear_outputs(): | |
| return "", [], "", "" | |
| # Set up 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, status_msg], | |
| ) | |
| ask_btn.click( | |
| ask_question, | |
| inputs=[question, analysis_file, chatbot], | |
| outputs=[chatbot], | |
| ).then( | |
| lambda: "", # Clear the question input | |
| None, | |
| question, | |
| queue=False | |
| ) | |
| clear_btn.click( | |
| clear_outputs, | |
| inputs=None, | |
| outputs=[summary, chatbot, question, status_msg], | |
| queue=False | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| app.launch( | |
| share=True, | |
| debug=True | |
| ) | |
| # 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 | |
| # ) |