π€ Agenite
About
π€ Build powerful AI agents with TypeScript. Agenite makes it easy to create, compose, and control AI agents with first-class support for tools, streaming, and multi-agent architectures. Switch seamlessly between providers like OpenAI, Anthropic, AWS Bedrock, and Ollama.
Details
- Author
- subeshb1
- GitHub stars
- 69
- Downloads
- 444
- Categories
- AI
Jump to
- TypeScript-first design with robust type checking
- Provider agnostic: supports OpenAI, Anthropic, Bedrock, Ollama
- First-class tool integration with JSON Schema validation
- Step-based execution using JavaScript generators
- Built-in state management with reducers and middleware system
- Model Context Protocol (MCP) client for standardized data access
Install core packages (@agenite/agent, @agenite/tool, @agenite/llm) and at least one provider (e.g., @agenite/openai). Then create an Agent instance with a provider, tools, and instructions, and execute it using agent.execute() or iterate with agent.iterate() for streaming control.
π€ Agenite
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<p><strong>A modern, modular, and type-safe framework for building AI agents using typescript</strong></p>
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What is Agenite?
Agenite is a powerful TypeScript framework designed for building sophisticated AI agents. It provides a modular, type-safe, and flexible architecture that makes it easy to create, compose, and control AI agents with advanced capabilities.
β¨ Key features
- Type safety and developer experience
- Built from the ground up with TypeScript
- Robust type checking for tools and agent configurations
- Excellent IDE support and autocompletion
- Tool integration
- First-class support for function calling
- Built-in JSON Schema validation
- Structured error handling
- Easy API integration
- Provider agnostic
- Support for OpenAI, Anthropic, AWS Bedrock, and Ollama
- Consistent interface across providers
- Easy extension for new providers
- Advanced architecture
- Bidirectional flow using JavaScript generators
- Step-based execution model
- Built-in state management with reducers
- Flexible middleware system
- Model context protocol (MCP)
- Standardized protocol for connecting LLMs to data sources
- Client implementation for interacting with MCP servers
- Access to web content, filesystem, databases, and more
π¦ Available packages
| Package | Description | Installation |
|---------|-------------|--------------|
| Core packages | | |
| @agenite/agent | Core agent orchestration framework for managing LLM interactions, tool execution, and state management | npm install @agenite/agent |
| @agenite/tool | Tool definition framework with type safety, schema validation, and error handling | npm install @agenite/tool |
| @agenite/llm | Base provider interface layer that enables abstraction across different LLM providers | npm install @agenite/llm |
| Provider packages | | |
| @agenite/openai | Integration with OpenAI's API for GPT models with function calling support | npm install @agenite/openai |
| @agenite/anthropic | Integration with Anthropic's API for Claude models | npm install @agenite/anthropic |
| @agenite/bedrock | AWS Bedrock integration supporting Claude and other models | npm install @agenite/bedrock |
| @agenite/ollama | Integration with Ollama for running models locally | npm install @agenite/ollama |
| MCP package | | |
| @agenite/mcp | Model Context Protocol client for connecting to standardized data sources and tools | npm install @agenite/mcp |
| Middleware packages | | |
| @agenite/pretty-logger | Colorful console logging middleware for debugging agent execution | npm install @agenite/pretty-logger |
For a typical setup, you'll need the core packages and at least one provider:
```bash
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