This commit is contained in:
marko-kraemer 2024-11-02 01:01:26 +01:00
parent b09de90e4c
commit 55c1ba58cf
3 changed files with 27 additions and 40 deletions

View File

@ -33,8 +33,12 @@ This will create a `agentpress` directory with the core utilities you can custom
## Quick Start
1. Set up your environment variables (API keys, etc.) in a `.env` file.
- OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
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.
2. Create a tool - copy this code directly into your project:
2. Create a calculator_tool.py
```python
from agentpress.tool import Tool, ToolResult, tool_schema
@ -52,17 +56,27 @@ class CalculatorTool(Tool):
}
})
async def add(self, a: float, b: float) -> ToolResult:
return self.success_response(f"The sum is {a + b}")
try:
result = a + b
return self.success_response(f"The sum is {result}")
except Exception as e:
return self.fail_response(f"Failed to add numbers: {str(e)}")
```
3. Use the Thread Manager - customize as needed:
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:
```python
import asyncio
from agentpress.thread_manager import ThreadManager
from calculator_tool import CalculatorTool
async def main():
# Initialize thread manager and add tools
manager = ThreadManager()
manager.add_tool(CalculatorTool)
# Create a new thread
# Alternatively, you could use an existing thread_id like:
# thread_id = "existing-thread-uuid"
thread_id = await manager.create_thread()
# Add your custom logic here
@ -86,43 +100,17 @@ async def main():
asyncio.run(main())
```
## Building Your Own Agent
4. Autonomous Web Developer Agent (the standard example)
Example of a customized autonomous agent:
```python
import asyncio
from agentpress.thread_manager import ThreadManager
from your_custom_tools import CustomTool
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...
async def run_agent(max_iterations=5):
# Create your own manager instance
manager = ThreadManager()
thread_id = await manager.create_thread()
# Add your custom tools
manager.add_tool(CustomTool)
# Define your agent's behavior
system_message = {
"role": "system",
"content": "Your custom system message here"
}
# Implement your control loop
for iteration in range(max_iterations):
response = await manager.run_thread(
thread_id=thread_id,
system_message=system_message,
model_name="your-preferred-model",
# Customize parameters as needed
)
# Add your custom logic here
process_response(response)
- **Files Tool**: Allows the agent to create, read, update, and delete files within the workspace.
- **Terminal Tool**: Enables the agent to execute terminal commands.
- **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.
- **User Interaction via CLI**: After each action, the agent pauses and allows the user to provide further instructions through the CLI.
You can find the complete implementation in our [example-agent](agentpress/examples/example-agent/agent.py) directory.
if __name__ == "__main__":
asyncio.run(run_agent())
```
## Development

View File

@ -4,7 +4,6 @@ import asyncio
import os
from typing import List, Dict, Any, Optional, Callable, Type
from agentpress.llm import make_llm_api_call
from datetime import datetime, UTC
from agentpress.tool import Tool, ToolResult
from agentpress.tool_registry import ToolRegistry
import uuid

View File

@ -44,7 +44,7 @@ Example:
# Failure case: divide(10, 0) -> ToolResult(success=False, output="Cannot divide by zero")
"""
from typing import Dict, Any
from typing import Dict, Any, Union
from dataclasses import dataclass
from abc import ABC
import json
@ -92,7 +92,7 @@ class Tool(ABC):
"""
return self._schemas
def success_response(self, data: Dict[str, Any] | str) -> ToolResult:
def success_response(self, data: Union[Dict[str, Any], str]) -> ToolResult:
"""
Creates a successful ToolResult with the given data.