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Mistral

KaibanJS seamlessly integrates with Mistral AI's powerful language models, allowing you to leverage advanced AI capabilities in your applications. This integration supports various Mistral models, designed for a wide range of natural language processing tasks.

Supported Models​

KaibanJS supports Mistral AI's models available through the Mistral AI API. These models are designed for versatile natural language understanding and generation tasks. The list of supported models may evolve as Mistral AI introduces new models or updates existing ones.

Currently supported Mistral models include:

  • mistral-tiny
  • mistral-small
  • mistral-medium
  • mistral-large-latest

For the most up-to-date information on available models and their capabilities, please refer to the official Mistral AI documentation.

Configuration​

To use a Mistral model in your KaibanJS agent, configure the llmConfig property as follows:

const agent = new Agent({
    name: 'Mistral Agent',
    role: 'Assistant',
    llmConfig: {
        provider: 'mistral',
        model: 'mistral-large-latest',  // or any other Mistral model
    }
});

API Key Setup​

To use Mistral models, you need to provide an API key. There are two recommended ways to do this:

  1. Agent Configuration: Specify the API key in the llmConfig when creating an agent:
const agent = new Agent({
    name: 'Mistral Agent',
    role: 'Assistant',
    llmConfig: {
        provider: 'mistral',
        model: 'mistral-large-latest',
        apiKey: 'your-api-key-here'
    }
});
  1. Team Configuration: Provide the API key in the env property when creating a team:
const team = new Team({
    name: 'Mistral Team',
    agents: [agent],
    env: {
        MISTRAL_API_KEY: 'your-api-key-here'
    }
});
API Key Security

Always use environment variables for API keys instead of hardcoding them. This enhances security and simplifies key management across different environments.

Example:

apiKey: process.env.YOUR_API_KEY

Never commit API keys to version control. Use a .env file or a secure secrets management system for sensitive information.

Advanced Configuration and Langchain Compatibility​

KaibanJS uses Langchain under the hood, which means we're compatible with all the parameters that Langchain's Mistral AI integration supports. This provides you with extensive flexibility in configuring your language models.

For more control over the model's behavior, you can pass additional parameters in the llmConfig. These parameters correspond to those supported by Langchain's Mistral AI integration.

Here's an example of how to use advanced configuration options:

const agent = new Agent({
    name: 'Advanced Mistral Agent',
    role: 'Assistant',
    llmConfig: {
        provider: 'mistral',
        model: 'mistral-large-latest',
        temperature: 0,
        maxRetries: 2,
        // Any other Langchain-supported parameters...
    }
});

For a comprehensive list of available parameters and advanced configuration options, please refer to the official Langchain documentation:

Langchain Mistral AI Integration Documentation

Best Practices​

  1. Model Selection: Choose the appropriate model based on your task complexity and required capabilities. For example, use mistral-large-latest for more complex tasks and mistral-tiny for simpler, faster responses.
  2. Cost Management: Be mindful of token usage, especially with larger models.
  3. Error Handling: Implement proper error handling to manage API rate limits and other potential issues.

Limitations​

  • Token limits may vary by model. Ensure your inputs don't exceed these limits.
  • Costs can accumulate with heavy usage. Monitor your usage closely.
  • The Mistral AI API may have specific rate limits or usage quotas. Check the Mistral AI documentation for the most current information.

Further Resources​

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