by brandondocusen · AI 工具 · ★ 111
🐍 CntxtPY: Minify Your Python Codebase Context for LLMs 🤯 75% Token Reduction In Context Window Usage! Why CntxtPY? Boosts precision: Maps relationships and dependencies for clear analysis. Eliminates noise: Focuses LLMs on key code insights. Supports analysis: Reveals architecture for smarter LLM insights. Speeds solutions: Helps LLMs trace workflows and logic faster. Improves recommendations: Gives LLMs detailed metadata for better suggestions. Optimized prompts: Provides structured context for better LLM responses. Streamlines collaboration: Helps LLMs explain and document code easily.
| Stars | 111 |
| Forks | 12 |
| Language | Python |
| Category | AI 工具 |
| License | MIT |
| Quality Score | 37.3/100 |
| Open Issues | 1 |
| Last Updated | 2024-12-05 |
| Created | 2024-11-27 |
| Platforms | python |
| Est. Tokens | ~7k |
These tools work well together with CntxtPY for enhanced workflows:
Explore other popular ai 工具 tools:
CntxtPY is A discovery and compression tool for your Python codebase. Creates a knowledge graph for a LLM context window, efficiently outlining your project | Code structure visualization | LLM Context Window Ef. It is categorized as a AI 工具 with 111 GitHub stars.
CntxtPY is primarily written in Python. It covers topics such as architecture-insights, code-documentation, code-visualization.
You can find installation instructions and usage details in the CntxtPY GitHub repository at github.com/brandondocusen/CntxtPY. The project has 111 stars and 12 forks, indicating an active community.
CntxtPY is released under the MIT license, making it free to use and modify according to the license terms.