GraphBit Documentation¶

Welcome to the comprehensive documentation for GraphBit - a high-performance AI agent workflow automation framework that combines Rust's performance with Python's ease of use.

Quick Navigation¶

🚀 Getting Started¶

• Installation Guide - Install GraphBit on your system
• Quick Start Tutorial - Build your first workflow in 5 minutes
• Basic Examples - Simple examples to get you started

📚 User Guide¶

• Core Concepts - Understand workflows, agents, and nodes
• Workflow Builder - Creating and connecting workflow nodes
• Agent Configuration - Setting up AI agents with different capabilities
• Document Loading - Loading and processing documents (PDF, DOCX, TXT, etc.)
• Text Splitters - Processing large documents with various splitting strategies
• LLM Providers - Working with OpenAI, Anthropic, Ollama, and more
• Dynamic Graph Generation - Auto-generating workflow structures
• Data Validation - Input validation and data quality checks
• Performance Optimization - Tuning for speed and efficiency
• Monitoring & Observability - Metrics collection and debugging
• Embeddings & Vector Search - Text embeddings and similarity search
• Reliability & Fault Tolerance - Circuit breakers, retries, and error handling

🔧 API Reference¶

• Python API - Complete Python API documentation
• Configuration Options - All configuration parameters
• Node Types - Agent, condition, transform, and delay nodes
• Execution Patterns - Sync, async, batch, and concurrent execution

🎯 Advanced Topics¶

• Custom Extensions - Building custom node types and providers
• Plugin Development - Creating GraphBit plugins
• Advanced Patterns - Complex workflow design patterns
• Integration Guides - Connecting with external systems

🛠️ Development¶

• Architecture Overview - System design and components
• Contributing Guide - How to contribute to GraphBit
• Building from Source - Development setup and compilation
• Testing - Running tests and quality checks

📋 Examples & Use Cases¶

• Content Generation Pipeline - Multi-agent content creation
• Data Processing Workflow - ETL pipelines with AI agents
• Code Review Automation - Automated code analysis
• Customer Support Bot - Multi-stage inquiry processing

What is GraphBit?¶

GraphBit is a declarative framework for building reliable AI agent workflows with strong type safety, comprehensive error handling, and predictable performance. It features:

• 🔒 Type Safety - Strong typing throughout the execution pipeline
• 🛡️ Reliability - Circuit breakers, retry policies, and error handling
• 🤖 Multi-LLM Support - OpenAI, Anthropic, Ollama, HuggingFace
• ⚡ Performance - Rust core with Python bindings for optimal speed
• 📊 Observability - Built-in metrics and execution tracing
• 🔧 Resource Management - Concurrency controls and memory optimization

Architecture¶

GraphBit uses a three-tier architecture:

Community & Support¶

• GitHub: github.com/InfinitiBit/graphbit
• Issues: Report bugs and request features
• Discussions: Ask Questions and Share ideas
• Contributing: See Our contributing guide

Ready to build your first AI workflow? Start with GraphBit's Quick Start Tutorial!