git-repo-intelligence 0.1.0

Git Repository Intelligence Platform - AI-driven repository insights

Git Repository Intelligence Platform

A powerful tool for analyzing Git repositories and extracting meaningful insights about development patterns, technical challenges, and team dynamics.

Overview

The Git Repository Intelligence Platform is a comprehensive solution for understanding software development processes through Git commit history analysis. It extracts valuable intelligence from your repositories to help:

• Track development progression and identify key milestones
• Discover technical challenges and their solutions
• Analyze contributor dynamics and team collaboration patterns
• Evaluate code quality and development impact
• Generate comprehensive, easy-to-understand reports

Features

• Enhanced Git Analysis: Advanced parsing of Git commits, with detailed extraction of changes, messages, and metadata
• Milestone Detection: Identification of significant project milestones and releases
• Commit Clustering: Grouping of related commits to understand development themes
• Technical Challenge Detection: Discovery of problems and their solutions within the codebase
• Contributor Analysis: Insights into team dynamics, contributions, and collaboration
• Impact Analysis: Measurement of code quality, development velocity, and improvement trends
• LLM-Powered Insights: Optional AI-generated observations and recommendations
• Comprehensive Reports: Generation of detailed Markdown and HTML reports

Installation

1. Clone the repository:

git clone https://github.com/yourusername/git-repo-intelligence.git
cd git-repo-intelligence

2. Install requirements:

pip install -r requirements.txt

3. Set up API key (optional for LLM insights):

export OPENAI_API_KEY=your_api_key_here

Quick Start

Use the provided quick demo script:

./quick_demo.sh /path/to/your/git/repository

Or run the main script directly:

./git_repo_intelligence.py --repo-path /path/to/your/repository --mock-llm --generate-html

Usage Options

usage: git_repo_intelligence.py [-h] --repo-path REPO_PATH [--repo-name REPO_NAME]
                              [--start-date START_DATE] [--end-date END_DATE]
                              [--max-commits MAX_COMMITS]
                              [--min-cluster-size MIN_CLUSTER_SIZE]
                              [--cluster-distance CLUSTER_DISTANCE]
                              [--output-dir OUTPUT_DIR] [--save-json]
                              [--json-dir JSON_DIR] [--generate-html]
                              [--report-title REPORT_TITLE] [--api-key API_KEY]
                              [--model MODEL] [--mock-llm] [--skip-milestones]
                              [--skip-clustering] [--skip-challenges]
                              [--skip-contributors] [--skip-impact] [--verbose]

Key Arguments

• --repo-path: Path to the Git repository (required)
• --max-commits: Maximum number of commits to analyze (default: 100)
• --generate-html: Generate HTML report in addition to Markdown
• --mock-llm: Use mock data instead of calling the OpenAI API
• --save-json: Save intermediate analysis results as JSON files

Example Reports

After running the analysis, check the reports directory for generated reports:

• Markdown report: reports/repository_name_date.md
• HTML report: reports/repository_name_date.html

If --save-json is enabled, intermediate data is saved to the data directory.

Components

The platform consists of several integrated components:

• EnhancedGitAnalyzer: Core Git data extraction
• MilestoneDetector: Project milestone identification
• CommitClusterer: Related commit grouping
• TechnicalChallengeDetector: Problem and solution analysis
• ContributorAnalyzer: Team and collaboration assessment
• ImpactAnalyzer: Development impact measurement
• LLMAnalyzer: AI-powered insights generation
• ReportGenerator: Comprehensive report creation

Requirements

• Python 3.7+
• Git
• Required Python packages (see requirements.txt)
• OpenAI API key (optional for LLM insights)

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.