Skip to content

FAQ.md

Latest commit

 

History

History
171 lines (121 loc) · 6.94 KB

FAQ.md

File metadata and controls

171 lines (121 loc) · 6.94 KB

FAQ

Table of Contents

Which models does LangManus support?

In LangManus, we categorize models into three types:

1. Chat Model

  • Usage: For conversation scenarios, mainly called in Supervisor and Agent.
  • Supported Models: gpt-4o, qwen-max-latest, gemini-2.0-flash, deepseek-v3.

2. Reasoning Model

  • Usage: For complex reasoning tasks, used in Planner when "Deep Think" mode is enabled.
  • Supported Models: o1, o3-mini, QwQ-Plus, DeepSeek-R1, gemini-2.0-flash-thinking-exp.

3. VL Model (Vision-Language Model)

  • Usage: For handling tasks combining vision and language, mainly called in Browser Tool.
  • Supported Models: gpt-4o, qwen2.5-vl-72b-instruct, gemini-2.0-flash.

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. For the specific configuration method, please refer to README.md.

How to use Ollama models?

LangManus 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:

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

How to use OpenRouter models?

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

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

The following is a configuration example for using OpenRouter models:

  1. Configure OPENROUTER_API_KEY in the environment variable (such as the .env file)
OPENROUTER_API_KEY=""
  1. Configure the model in conf.yaml
REASONING_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 Google Gemini models?

LangManus supports the integration of Google's Gemini models. You can refer to litellm Gemini. To use Gemini models, please follow these steps:

  1. Obtain the Gemini API key from Google AI Studio (https://makersuite.google.com/app/apikey).
  2. Configure the Gemini API key in the environment variable (such as the .env file)
GEMINI_API_KEY="Your Gemini API key"
  1. Configure the model in conf.yaml
REASONING_MODEL:
  model: "gemini/gemini-pro"

Notes:

  • Replace YOUR_GEMINI_KEY with your actual Gemini API key.
  • The base URL is specifically configured to use Gemini through LangManus' OpenAI-compatible interface.
  • The available models include gemini-2.0-flash for chat and visual tasks.

How to use Azure models?

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

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

How to deploy the Web UI frontend project?

LangManus provides an out-of-the-box Web UI frontend project. You can complete the deployment through the following steps. Please visit the LangManus Web UI GitHub repository for more information.

Step 1: Start the LangManus backend service

First, ensure you have cloned and installed the LangManus backend project. Enter the backend project directory and start the service:

cd langmanus
make serve

By default, the LangManus backend service will run on http://localhost:8000.

Step 2: Install the Web UI frontend project and its dependencies

Next, clone the LangManus Web UI frontend project and install dependencies:

git clone https://github.com/langmanus/langmanus-web.git
cd langmanus-web
pnpm install

Note: If you haven't installed pnpm yet, please install it first. You can install it using the following command:

npm install -g pnpm

Step 3: Start the Web UI service

After completing the dependency installation, start the Web UI development server:

pnpm dev

By default, the LangManus Web UI service will run on http://localhost:3000.

Browser Tool not starting properly?

LangManus uses browser-use to implement browser-related functionality, and browser-use is built on Playwright. Therefore, you need to install Playwright's browser instance before first use.

uv run playwright install

Can I use my local Chrome browser as the Browser Tool?

Yes. LangManus uses browser-use to implement browser-related functionality, and browser-use is based on Playwright. By configuring the CHROME_INSTANCE_PATH in the .env file, you can specify the path to your local Chrome browser to use the local browser instance.

Configuration Steps

  1. Exit all Chrome browser processes Before using the local Chrome browser, ensure all Chrome browser processes are completely closed. Otherwise, browser-use cannot start the browser instance properly.

  2. Set CHROME_INSTANCE_PATH In the project's .env file, add or modify the following configuration item:

    CHROME_INSTANCE_PATH=/path/to/your/chrome

    Replace /path/to/your/chrome with the executable file path of your local Chrome browser. For example:

    • macOS: /Applications/Google Chrome.app/Contents/MacOS/Google Chrome
    • Windows: C:\Program Files\Google\Chrome\Application\chrome.exe
    • Linux: /usr/bin/google-chrome

  3. Start LangManus After starting LangManus, browser-use will use your specified local Chrome browser instance.

  4. Access LangManus Web UI Since now your local Chrome browser is being controlled by browser-use, you need to use another browser (such as Safari, Mozilla Firefox) to access LangManus's Web interface, which is typically at http://localhost:3000. Alternatively, you can access the LangManus Web UI from another device.