Configuration Guide

Quick Settings

Copy the conf.yaml.example file to conf.yaml and modify the configurations to match your specific settings and requirements.

cd deer-flow
cp conf.yaml.example conf.yaml

Which models does DeerFlow support?

In DeerFlow, currently we only support non-reasoning models, which means models like OpenAI's o1/o3 or DeepSeek's R1 are not supported yet, but we will add support for them in the future.

Supported Models

doubao-1.5-pro-32k-250115, gpt-4o, qwen-max-latest, gemini-2.0-flash, deepseek-v3, and theoretically any other non-reasoning chat models that implement the OpenAI API specification.

Note

The Deep Research process requires the model to have a longer context window, which is not supported by all models. A work-around is to set the Max steps of a research plan to 2 in the settings dialog located on the top right corner of the web page, or set max_step_num to 2 when invoking the API.

How to switch models?

You can switch the model in use by modifying the conf.yaml file in the root directory of the project, using the configuration in the litellm format.

How to use OpenAI-Compatible models?

DeerFlow supports integration with OpenAI-Compatible models, which are models that implement the OpenAI API specification. This includes various open-source and commercial models that provide API endpoints compatible with the OpenAI format. You can refer to litellm OpenAI-Compatible for detailed documentation. The following is a configuration example of conf.yaml for using OpenAI-Compatible models:

# An example of Doubao models served by VolcEngine
BASIC_MODEL:
  base_url: "https://ark.cn-beijing.volces.com/api/v3"
  model: "doubao-1.5-pro-32k-250115"
  api_key: YOUR_API_KEY

# An example of Aliyun models
BASIC_MODEL:
  base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1"
  model: "qwen-max-latest"
  api_key: YOUR_API_KEY

# An example of deepseek official models
BASIC_MODEL:
  base_url: "https://api.deepseek.com"
  model: "deepseek-chat"
  api_key: YOU_API_KEY

# An example of Google Gemini models using OpenAI-Compatible interface
BASIC_MODEL:
  base_url: "https://generativelanguage.googleapis.com/v1beta/openai/"
  model: "gemini-2.0-flash"
  api_key: YOUR_API_KEY

How to use Ollama models?

DeerFlow supports the integration of Ollama models. You can refer to litellm Ollama.
The following is a configuration example of conf.yaml for using Ollama models:

BASIC_MODEL:
  model: "ollama/ollama-model-name"
  base_url: "http://localhost:11434" # Local service address of Ollama, which can be started/viewed via ollama serve

How to use OpenRouter models?

DeerFlow supports the integration of OpenRouter models. You can refer to litellm OpenRouter. To use OpenRouter models, you need to:

Obtain the OPENROUTER_API_KEY from OpenRouter (https://openrouter.ai/) and set it in the environment variable.
Add the openrouter/ prefix before the model name.
Configure the correct OpenRouter base URL.

The following is a configuration example for using OpenRouter models:

Configure OPENROUTER_API_KEY in the environment variable (such as the .env file)

OPENROUTER_API_KEY=""

Set the model name in conf.yaml

BASIC_MODEL:
  model: "openrouter/google/palm-2-chat-bison"

Note: The available models and their exact names may change over time. Please verify the currently available models and their correct identifiers in OpenRouter's official documentation.

How to use Azure models?

DeerFlow supports the integration of Azure models. You can refer to litellm Azure. Configuration example of conf.yaml:

BASIC_MODEL:
  model: "azure/gpt-4o-2024-08-06"
  api_base: $AZURE_API_BASE
  api_version: $AZURE_API_VERSION
  api_key: $AZURE_API_KEY

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