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README.md
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README.md
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@ -33,8 +33,12 @@ This will create a `agentpress` directory with the core utilities you can custom
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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=
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ANTHROPIC_API_KEY=
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GROQ_API_KEY=
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Whatever LLM you want to use, we use LiteLLM (Call 100+ LLMs using the OpenAI Input/Output Format) https://docs.litellm.ai/ – 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 tool - copy this code directly into your project:
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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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@ -52,17 +56,27 @@ class CalculatorTool(Tool):
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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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return self.success_response(f"The sum is {a + b}")
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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 - customize as needed:
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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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@ -86,43 +100,17 @@ async def main():
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asyncio.run(main())
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```
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## Building Your Own Agent
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4. Autonomous Web Developer Agent (the standard example)
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Example of a customized autonomous agent:
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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 your_custom_tools import CustomTool
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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 [Softgen](https://softgen.ai/), [Bolt](https://bolt.new/), [GPT Engineer](https://gptengineer.app/), [V0](https://v0.dev/), etc...
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async def run_agent(max_iterations=5):
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# Create your own manager instance
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manager = ThreadManager()
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thread_id = await manager.create_thread()
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# Add your custom tools
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manager.add_tool(CustomTool)
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# Define your agent's behavior
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system_message = {
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"role": "system",
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"content": "Your custom system message here"
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}
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# Implement your control loop
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for iteration in range(max_iterations):
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response = await manager.run_thread(
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thread_id=thread_id,
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system_message=system_message,
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model_name="your-preferred-model",
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# Customize parameters as needed
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)
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# Add your custom logic here
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process_response(response)
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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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if __name__ == "__main__":
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asyncio.run(run_agent())
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```
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## Development
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@ -4,7 +4,6 @@ import asyncio
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import os
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from typing import List, Dict, Any, Optional, Callable, Type
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from agentpress.llm import make_llm_api_call
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from datetime import datetime, UTC
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from agentpress.tool import Tool, ToolResult
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from agentpress.tool_registry import ToolRegistry
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import uuid
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@ -44,7 +44,7 @@ Example:
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# Failure case: divide(10, 0) -> ToolResult(success=False, output="Cannot divide by zero")
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"""
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from typing import Dict, Any
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from typing import Dict, Any, Union
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from dataclasses import dataclass
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from abc import ABC
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import json
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@ -92,7 +92,7 @@ class Tool(ABC):
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"""
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return self._schemas
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def success_response(self, data: Dict[str, Any] | str) -> ToolResult:
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def success_response(self, data: Union[Dict[str, Any], str]) -> ToolResult:
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"""
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Creates a successful ToolResult with the given data.
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