GraphBit is an enterprise-grade, agentic AI framework designed for developers and AI teams requiring high performance, stability, and low resource usage. Built with a Rust core and Python wrapper, it enables reliable, multi-agent workflows with significant efficiency gains over alternatives, making it suitable for production environments and edge deployments.

How It Works

GraphBit leverages a Rust core for its workflow engine, agents, and LLM providers, ensuring maximum performance and safety. A Python API, built with PyO3 bindings and async support, facilitates integration. This hybrid architecture delivers type-safe AI agent workflows with robust error handling, circuit breakers, and retry policies. Its design prioritizes resource management, concurrency control, and memory optimization for efficient parallel multi-agent task execution.

Quick Start & Requirements

Installation requires cloning the repo, installing Rust (rustup.rs), and Poetry. Set up a Python environment (3.10-3.13) via Poetry (poetry env use python3.11, source $(poetry env info --path)/bin/activate, poetry install --no-root). Build Rust core with cargo build --release and Python bindings with maturin develop --release in python/. Crucially, set API keys (e.g., OPENAI_API_KEY) as environment variables.

Highlighted Details

• Achieves up to 68× lower CPU usage and 140× lower memory footprint compared to some alternatives, with comparable throughput.
• Supports multiple LLM providers including OpenAI, Anthropic, DeepSeek, and Ollama.
• Features built-in observability, concurrency controls, and memory optimization.
• Enables intelligent tool selection by LLMs based on descriptions and offers strong type safety throughout the execution pipeline.

Maintenance & Community

Contributions are welcomed via CONTRIBUTING.md. Community engagement is facilitated through a Discord server. GitHub Actions are used for CI/CD.

Licensing & Compatibility

The README does not explicitly state a software license. This absence requires clarification for commercial use or integration into closed-source projects.

Limitations & Caveats

The README does not detail specific limitations, known bugs, or alpha/beta status. The primary adoption blocker is the lack of a clearly defined license, impacting usability and commercial integration.