codenuk_backend_mine/services/ai-analysis-service

Complete AI Repository Analysis Service

A comprehensive AI-powered repository analysis tool that automatically analyzes ALL files in a repository without any limits or user queries required.

🚀 Features

• Complete Analysis: Analyzes ALL files in the repository (no max-files limit)
• Fully Automated: No user query required - runs completely automatically
• Memory-Enhanced: Learns from previous analyses using advanced memory systems
• Comprehensive Reports: Generates detailed PDF reports with executive summaries
• Multi-Database Support: Uses PostgreSQL, MongoDB, and Redis for optimal performance
• Security Focus: Identifies security vulnerabilities and code quality issues
• Architecture Assessment: Provides architectural insights and recommendations

📋 Requirements

System Dependencies

• Python 3.8+
• PostgreSQL with pgvector extension
• MongoDB
• Redis

Python Dependencies

pip install anthropic python-dotenv git redis pymongo psycopg2-binary numpy reportlab

🛠️ Setup

1. Install Dependencies:

   pip install -r requirements.txt
   

2. Database Setup:

   # Run the database migration
   psql -U postgres -d repo_vectors -f 001-schema.sql
   

3. Environment Variables: Create a .env file with:

   ANTHROPIC_API_KEY=your_api_key_here
   REDIS_HOST=localhost
   REDIS_PORT=6379
   REDIS_DB=0
   MONGODB_URL=mongodb://localhost:27017/
   MONGODB_DB=repo_analyzer
   POSTGRES_HOST=localhost
   POSTGRES_PORT=5432
   POSTGRES_DB=repo_vectors
   POSTGRES_USER=postgres
   POSTGRES_PASSWORD=your_password
   

🎯 Usage

Basic Usage

python ai-analyze.py /path/to/repository

With Custom Output

python ai-analyze.py /path/to/repository --output my_analysis.pdf

With API Key Override

python ai-analyze.py /path/to/repository --api-key your_api_key

📊 What It Analyzes

File Types Supported

• Programming Languages: Python, JavaScript, TypeScript, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin
• Web Technologies: HTML, CSS, SCSS, SASS
• Configuration Files: JSON, YAML, XML, SQL
• Build Files: Dockerfile, Makefile, CMake, package.json, requirements.txt, Cargo.toml, pom.xml, build.gradle
• Documentation: README.md, Markdown files

Analysis Coverage

• Code Quality: Complexity, maintainability, best practices
• Security: Vulnerabilities, injection attacks, authentication issues
• Architecture: Project structure, scalability, design patterns
• Performance: Optimization opportunities, bottlenecks
• Documentation: Completeness and quality

📈 Output

Console Output

• Real-time analysis progress
• Repository statistics
• Quality breakdown by file
• Language distribution
• Memory system statistics

PDF Report

• Executive summary for leadership
• Repository overview with metrics
• Detailed file-by-file analysis
• Security assessment
• Architecture evaluation
• Recommendations and next steps

🧠 Memory System

The tool uses a sophisticated three-tier memory system:

1. Working Memory (Redis): Temporary, fast access for current analysis
2. Episodic Memory (MongoDB): User interactions and analysis sessions
3. Persistent Memory (PostgreSQL): Long-term knowledge and best practices

This allows the tool to learn from previous analyses and provide increasingly accurate insights.

🔧 Configuration

File Size Limits

• Default: 2MB per file (configurable in code)
• Large files are skipped with notification

Excluded Directories

• .git, node_modules, __pycache__, build, dist, target
• venv, env, .next, coverage, vendor
• bower_components, .gradle, .m2, .cargo

Rate Limiting

• 0.1 second delay between file analyses to avoid API rate limits
• Configurable in the code

📝 Example Output

🚀 Starting Complete AI Repository Analysis
============================================================
Repository: /path/to/my-project
Output: complete_repository_analysis.pdf
Mode: Complete automated analysis of ALL files
============================================================

Scanning repository: /path/to/my-project
Found 127 files to analyze
Starting comprehensive analysis of 127 files...
Analyzing file 1/127: main.py
Analyzing file 2/127: config.js
...

🎯 COMPLETE ANALYSIS FINISHED
============================================================
📊 Repository Statistics:
   • Files Analyzed: 127
   • Lines of Code: 15,432
   • Languages: 8
   • Code Quality: 7.2/10

📈 Quality Breakdown:
   • High Quality Files (8-10): 45
   • Medium Quality Files (5-7): 67
   • Low Quality Files (1-4): 15
   • Total Issues Found: 89

🔤 Language Distribution:
   • Python: 45 files
   • JavaScript: 32 files
   • TypeScript: 28 files
   • HTML: 12 files
   • CSS: 10 files

📄 Complete PDF Report: complete_repository_analysis.pdf
✅ Complete analysis finished successfully!

🚨 Troubleshooting

Common Issues

1. Database Connection Errors:

   • Ensure PostgreSQL, MongoDB, and Redis are running
   • Check connection credentials in .env file

2. API Key Issues:

   • Verify Anthropic API key is valid and has sufficient credits
   • Check rate limits if analysis fails

3. Memory Issues:

   • Large repositories may require more RAM
   • Consider increasing system memory or processing in batches

4. File Permission Errors:

   • Ensure read access to repository files
   • Check write permissions for output directory

🤝 Contributing

This is a complete automated analysis system. The tool will:

• Analyze every file in the repository
• Generate comprehensive reports
• Learn from previous analyses
• Provide actionable insights

No user interaction required - just run and get results!