Create Your First Harness

This tutorial shows you how to use the DeerFlow Harness programmatically — importing and using DeerFlow directly in your Python code rather than through the web interface.

Prerequisites

Python 3.12+
uv installed
DeerFlow repository cloned

Install


cd deer-flow/backend
uv sync

Create configuration

Create a minimal config.yaml:


config_version: 6
 
models:
  - name: gpt-4o
    use: langchain_openai:ChatOpenAI
    model: gpt-4o
    api_key: $OPENAI_API_KEY
 
sandbox:
  use: deerflow.sandbox.local:LocalSandboxProvider
 
tools:
  - use: deerflow.community.ddg_search.tools:web_search_tool
  - use: deerflow.sandbox.tools:read_file_tool
  - use: deerflow.sandbox.tools:write_file_tool

Write the code

Create a Python file

Create my_agent.py in the backend/ directory:


import asyncio
import os
from deerflow.client import DeerFlowClient
from deerflow.config import load_config
 
os.environ["OPENAI_API_KEY"] = "sk-..."
 
# Load config.yaml
load_config()
 
client = DeerFlowClient()
 
async def main():
    async for event in client.astream(
        thread_id="my-first-thread",
        message="Write a Python fibonacci function with a docstring",
        config={
            "configurable": {
                "model_name": "gpt-4o",
            }
        },
    ):
        print(event)
 
asyncio.run(main())

Run it


cd backend
uv run python my_agent.py

What the events look like

The stream yields events like:


{"type": "messages", "data": {"content": "def fibonacci..."}}
{"type": "thread_state", "data": {"title": "Python Fibonacci Function"}}