Llama-github Release v0.2.3

Upgrade to mistral-large-2411

Llama-github Release v0.2.2

Stick to specific LLM model (mistral-large-2407) and switch to Mistral-nemo for simple LLM

Llama-github Release v0.2.1

Approperately handle more file types when calculate file changes in PR

Llama-github Release v0.2.0

fix bugs for generate repo from pool by using Github_install_id

Llama-github Release v0.1.9

fix bugs for get pr content

Llama-github Release v0.1.8

Llama-github Release v0.1.8

Fix bugs for PR Content Code Diff calculation logic

Llama-github Release v0.1.7

Fix bugs for get PR content

Llama-github Release v0.1.6

Llama-GitHub v0.1.6: Enhanced PR Analysis & Issue Linking 🚀

We're excited to announce the release of Llama-GitHub v0.1.6, bringing significant improvements to pull request analysis and issue linking capabilities.

🌟 Highlights

Enhanced Issue Detection

• Comprehensive Issue Linking: Now supports all GitHub issue reference formats
• Smart Validation: Improved issue number validation to prevent false positives
• Official Format Support: Implements GitHub's autolink reference formats

Detailed PR Analysis

• Rich Commit Information: Extract detailed commit metadata
• Statistical Analysis: Track additions, deletions, and file changes
• Robust Error Handling: Improved reliability in commit processing

🔧 Key Features

1. Intelligent Issue Linking

   • Full GitHub issue URLs
   • Hash-based references (#123)
   • Closing keyword references (fixes #123)
   • Issue keyword references (issue #123)

2. Enhanced PR Content Analysis

   • Detailed commit information
   • File change tracking
   • Comprehensive statistics
   • Author and timestamp data

📖 Documentation

Full documentation is available in our GitHub Wiki.
For migration guides and examples, please refer to our documentation.

🚀 Installation

pip install llama-github==0.1.6

Llama-github Release v0.1.5

Updated with a more precise requirements.txt list

Llama-github Release v0.1.4

Release Notes

Version 0.1.4

Improvements

• Simplified simple_mode for better performance and compatibility
• Reduced memory usage
• Improved AWS Lambda support

Technical Details

• Removed Torch and Transformers library dependencies in simple_mode
• Optimized imports for lighter execution

We recommend updating to this version for improved efficiency, especially in serverless environments.