Fleet Context is a CLI tool and API designed to provide question-answering and code generation capabilities over the documentation of over 1200 Python libraries. It targets developers seeking up-to-date information and code examples for Python packages, offering significant improvements in AI model generation scores by leveraging rich, structured metadata.

How It Works

The tool utilizes a vector database populated with embeddings generated from Python library documentation. It employs a retrieval-augmented generation (RAG) approach, fetching relevant documentation chunks based on user queries. The system's advantage lies in its comprehensive metadata, including library_id, page_id, section_index, type (e.g., class, function), and original Markdown-formatted text, which allows for sophisticated filtering, re-ranking, and prompt construction to enhance AI response quality.

Quick Start & Requirements

• Install: pip install fleet-context
• Prerequisites: OpenAI API key (or OpenRouter API key for other models). Local model support requires LM Studio.
• Usage: Run context for CLI, or from context import download_embeddings, query for API.
• Links: Website, Data Visualizer, PyPI

Highlighted Details

• Supports over 1200 Python libraries.
• Achieved 37-point and 34-point generation score improvements for GPT-4 and GPT-4 Turbo, respectively.
• Rich metadata enables advanced retrieval strategies like re-ranking by section_index and filtering by type.
• Supports OpenAI, OpenRouter (Claude, CodeLlama, Mistral), and local models via LM Studio.

Maintenance & Community

• Project maintained by fleet-ai.
• Links to community resources are not explicitly provided in the README.

Licensing & Compatibility

• License is not specified in the README.
• Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The README does not specify the license, making commercial use and closed-source integration uncertain. Metadata type is not guaranteed for all libraries, particularly those not using Sphinx/readthedocs for documentation generation.