Mistral AI Rust Client

Rust client for the Mistral AI API.

---

• Supported APIs
• Installation
  • Mistral API Key
    • As an environment variable
    • As a client argument
• Usage
  • Chat without streaming
  • Chat with streaming
  • Embeddings
  • List models

---

Supported APIs

• Chat without streaming
• Chat with streaming
• Embedding
• List models
• Function Calling

Installation

You can install the library in your project using:

cargo add mistralai-client

Mistral API Key

You can get your Mistral API Key there: https://docs.mistral.ai/#api-access.

As an environment variable

Just set the MISTRAL_API_KEY environment variable.

As a client argument

use mistralai_client::v1::client::Client;

fn main() {
    let api_key = "your_api_key";

    let client = Client::new(Some(api_key), None, None, None);
}

Usage

Chat without streaming

use mistralai_client::v1::{
    chat_completion::{ChatCompletionMessage, ChatCompletionMessageRole, ChatCompletionRequestOptions},
    client::Client,
    constants::Model,
};

fn main() {
    // This example suppose you have set the `MISTRAL_API_KEY` environment variable.
    let client = Client::new(None, None, None, None);

    let model = Model::OpenMistral7b;
    let messages = vec![ChatCompletionMessage {
        role: ChatCompletionMessageRole::user,
        content: "Just guess the next word: \"Eiffel ...\"?".to_string(),
    }];
    let options = ChatCompletionRequestOptions {
        temperature: Some(0.0),
        random_seed: Some(42),
        ..Default::default()
    };

    let result = client.chat(model, messages, Some(options)).unwrap();
    println!("Assistant: {}", result.choices[0].message.content);
    // => "Assistant: Tower. [...]"
}

Chat with streaming

In progress.

Embeddings

use mistralai_client::v1::{client::Client, constants::EmbedModel};

fn main() {
    // This example suppose you have set the `MISTRAL_API_KEY` environment variable.
  let client: Client = Client::new(None, None, None, None);

  let model = EmbedModel::MistralEmbed;
  let input = vec!["Embed this sentence.", "As well as this one."]
      .iter()
      .map(|s| s.to_string())
      .collect();
  let options = None;

  let response = client.embeddings(model, input, options).unwrap();
  println!("Embeddings: {:?}", response.data);
  // => "Embeddings: [{...}, {...}]"
}

List models

use mistralai_client::v1::client::Client;

fn main() {
    // This example suppose you have set the `MISTRAL_API_KEY` environment variable.
    let client = Client::new(None, None, None, None);

    let result = client.list_models().unwrap();
    println!("First Model ID: {:?}", result.data[0].id);
    // => "First Model ID: open-mistral-7b"
}