mirror of https://github.com/kortix-ai/suna.git
150 lines
5.4 KiB
Markdown
150 lines
5.4 KiB
Markdown
# AgentPress: Building Blocks for AI Agents
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AgentPress is not a agent framework - it's a collection of lightweight, modular utilities that serve as building blocks for creating AI agents. Think of it as "shadcn/ui for AI agents" - a set of utils to copy, paste, and customize in order to quickly bootstrap your AI App / Agent.
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- **Threads**: Simple message thread handling utilities
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- **Automatic Tool**: Flexible tool definition and automatic execution
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- **State Management**: Basic JSON-based state persistence
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- **LLM Integration**: Provider-agnostic LLM calls via LiteLLM
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## Installation & Setup
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1. Install the package:
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```bash
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pip install agentpress
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```
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2. Initialize AgentPress in your project:
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```bash
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agentpress init
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```
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This will create a `agentpress` directory with the core utilities you can customize.
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3. If you selected the example agent during initialization:
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- Creates an `agent.py` file with a web development agent example
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- Creates a `tools` directory with example tools:
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- `files_tool.py`: File operations (create/update files, read directory and load into state)
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- `terminal_tool.py`: Terminal command execution
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- Creates a `workspace` directory for the agent to work in
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## Quick Start
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1. Set up your environment variables (API keys, etc.) in a `.env` file.
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- OPENAI_API_KEY, ANTHROPIC_API_KEY, GROQ_API_KEY, etc... Whatever LLM you want to use, we use LiteLLM (https://litellm.ai) (Call 100+ LLMs using the OpenAI Input/Output Format) – set it up in your `.env` file.. Also check out the agentpress/llm.py and modify as needed to support your wanted LLM.
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2. Create a calculator_tool.py
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```python
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from agentpress.tool import Tool, ToolResult, tool_schema
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class CalculatorTool(Tool):
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@tool_schema({
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"name": "add",
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"description": "Add two numbers",
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"parameters": {
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"type": "object",
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"properties": {
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"a": {"type": "number"},
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"b": {"type": "number"}
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},
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"required": ["a", "b"]
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}
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})
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async def add(self, a: float, b: float) -> ToolResult:
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try:
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result = a + b
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return self.success_response(f"The sum is {result}")
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except Exception as e:
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return self.fail_response(f"Failed to add numbers: {str(e)}")
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```
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3. Use the Thread Manager, create a new thread – or access an existing one. Then Add the Calculator Tool, and run the thread. It will automatically use & execute the python function associated with the tool:
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```python
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import asyncio
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from agentpress.thread_manager import ThreadManager
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from calculator_tool import CalculatorTool
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async def main():
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# Initialize thread manager and add tools
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manager = ThreadManager()
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manager.add_tool(CalculatorTool)
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# Create a new thread
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# Alternatively, you could use an existing thread_id like:
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# thread_id = "existing-thread-uuid"
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thread_id = await manager.create_thread()
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# Add your custom logic here
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await manager.add_message(thread_id, {
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"role": "user",
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"content": "What's 2 + 2?"
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})
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response = await manager.run_thread(
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thread_id=thread_id,
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system_message={
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"role": "system",
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"content": "You are a helpful assistant with calculation abilities."
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},
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model_name="gpt-4",
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use_tools=True,
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execute_model_tool_calls=True
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)
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print("Response:", response)
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asyncio.run(main())
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```
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4. Autonomous Web Developer Agent (the standard example)
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When you run `agentpress init` and select the example agent – you will get code for a simple implementation of an AI Web Developer Agent that leverages architecture similar to platforms like our own [Softgen](https://softgen.ai/) Platform.
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- **Files Tool**: Allows the agent to create, read, update, and delete files within the workspace.
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- **Terminal Tool**: Enables the agent to execute terminal commands.
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- **State Workspace Management**: The agent has access to a workspace whose state is stored and sent on every request. This state includes all file contents, ensuring the agent knows what it is editing.
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- **User Interaction via CLI**: After each action, the agent pauses and allows the user to provide further instructions through the CLI.
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You can find the complete implementation in our [example-agent](agentpress/examples/example-agent/agent.py) directory.
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5. Thread Viewer
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Run the thread viewer to view messages of threads in a stylisedweb UI:
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```bash
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streamlit run agentpress/thread_viewer_ui.py
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```
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## Development
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1. Clone for reference:
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```bash
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git clone https://github.com/kortix-ai/agentpress
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cd agentpress
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```
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2. Install dependencies:
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```bash
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pip install poetry
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poetry install
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```
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## Philosophy
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- **Modular**: Pick and choose what you need. Each component is designed to work independently.
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- **Agnostic**: Built on LiteLLM, supporting any LLM provider. Minimal opinions, maximum flexibility.
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- **Simplicity**: Clean, readable code that's easy to understand and modify.
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- **Plug & Play**: Start with our defaults, then customize to your needs.
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- **No Lock-in**: Take full ownership of the code. Copy what you need directly into your codebase.
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## Contributing
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We welcome contributions! Feel free to:
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- Submit issues for bugs or suggestions
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- Fork the repository and send pull requests
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- Share how you've used AgentPress in your projects
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## License
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[MIT License](LICENSE)
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Built with ❤️ by [Kortix AI Corp](https://kortix.ai) |