copilot-swe-agent[bot]
b62ac7672a
Agent-Logs-Url: https://github.com/bytedance/deer-flow/sessions/a5f192e7-8034-4e46-af22-60b90ee27d40 Co-authored-by: foreleven <4785594+foreleven@users.noreply.github.com>
100 lines
1.8 KiB
Plaintext
100 lines
1.8 KiB
Plaintext
import { Callout, Steps } from "nextra/components";
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# Create Your First Harness
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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.
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## Prerequisites
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- Python 3.12+
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- `uv` installed
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- DeerFlow repository cloned
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## Install
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```bash
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cd deer-flow/backend
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uv sync
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```
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## Create configuration
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Create a minimal `config.yaml`:
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```yaml
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config_version: 6
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models:
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- name: gpt-4o
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use: langchain_openai:ChatOpenAI
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model: gpt-4o
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api_key: $OPENAI_API_KEY
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sandbox:
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use: deerflow.sandbox.local:LocalSandboxProvider
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tools:
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- use: deerflow.community.ddg_search.tools:web_search_tool
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- use: deerflow.sandbox.tools:read_file_tool
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- use: deerflow.sandbox.tools:write_file_tool
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```
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## Write the code
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<Steps>
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### Create a Python file
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Create `my_agent.py` in the `backend/` directory:
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```python
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import asyncio
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import os
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from deerflow.client import DeerFlowClient
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from deerflow.config import load_config
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os.environ["OPENAI_API_KEY"] = "sk-..."
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# Load config.yaml
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load_config()
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client = DeerFlowClient()
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async def main():
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async for event in client.astream(
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thread_id="my-first-thread",
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message="Write a Python fibonacci function with a docstring",
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config={
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"configurable": {
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"model_name": "gpt-4o",
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}
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},
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):
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print(event)
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asyncio.run(main())
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```
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### Run it
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```bash
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cd backend
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uv run python my_agent.py
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```
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</Steps>
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## What the events look like
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The stream yields events like:
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```python
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{"type": "messages", "data": {"content": "def fibonacci..."}}
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{"type": "thread_state", "data": {"title": "Python Fibonacci Function"}}
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```
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## Next steps
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- [Use Tools and Skills](/docs/tutorials/use-tools-and-skills)
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- [Harness Quick Start](/docs/harness/quick-start)
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