Show HN: GraphFlow – A lightweight Rust framework for multi-agent orchestration
10 months ago
- #Multi-agent Workflow
- #Rust
- #LLM Integration
- graph-flow is a high-performance, type-safe framework for building multi-agent workflow systems in Rust.
- It combines graph execution for stateful task orchestration with LLM ecosystem integration via LangChain.
- The framework is designed for production environments with features like conditional routing, error handling, and pluggable storage.
- graph-flow supports various execution models: step-by-step, batch, or mixed, with human-in-the-loop capabilities.
- Key features include task orchestration, conditional routing, execution control, error handling, and thread-safe state management.
- The framework integrates with LLM agents using the Rig crate for natural language processing and conversation management.
- Examples provided include an insurance claims service and a recommendation service, showcasing real-world applications.
- graph-flow offers both high-level (FlowRunner) and low-level APIs for workflow execution, catering to different control needs.
- The insurance-claims-service example demonstrates complex workflows with conditional approval and human-in-the-loop processing.
- Getting started involves using cargo to add graph-flow and exploring the examples to understand core concepts and best practices.