Mistral AI Rust Client

Rust client for the Mistral AI API.

Fork of ivangabriele/mistralai-client-rs, updated to the latest Mistral API with all current endpoints and models.

Supported APIs

• Chat completions (sync, async, streaming)
• Function calling / tool use
• FIM (fill-in-the-middle) code completions
• Embeddings (sync, async)
• Models (list, get, delete)
• Files (upload, list, get, delete, download URL)
• Fine-tuning jobs (create, list, get, cancel, start)
• Batch jobs (create, list, get, cancel)
• OCR (document text extraction)
• Audio transcription
• Moderations & classifications
• Agent completions

Installation

cargo add mistralai-client

API Key

Get your key at https://console.mistral.ai/api-keys.

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

// From MISTRAL_API_KEY environment variable:
let client = Client::new(None, None, None, None).unwrap();

// Or pass directly:
let client = Client::new(Some("your_api_key".to_string()), None, None, None).unwrap();

Usage

Chat

use mistralai_client::v1::{
    chat::{ChatMessage, ChatParams},
    client::Client,
    constants::Model,
};

fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let model = Model::mistral_small_latest();
    let messages = vec![ChatMessage::new_user_message("What is the Eiffel Tower?")];
    let options = ChatParams {
        temperature: Some(0.7),
        ..Default::default()
    };

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

Chat (async)

use mistralai_client::v1::{
    chat::{ChatMessage, ChatParams},
    client::Client,
    constants::Model,
};

#[tokio::main]
async fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let model = Model::mistral_small_latest();
    let messages = vec![ChatMessage::new_user_message("What is the Eiffel Tower?")];

    let result = client.chat_async(model, messages, None).await.unwrap();
    println!("{}", result.choices[0].message.content);
}

Chat with streaming

use futures::stream::StreamExt;
use mistralai_client::v1::{
    chat::{ChatMessage, ChatParams},
    client::Client,
    constants::Model,
};
use std::io::{self, Write};

#[tokio::main]
async fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let model = Model::mistral_small_latest();
    let messages = vec![ChatMessage::new_user_message("Tell me a short story.")];

    let stream = client.chat_stream(model, messages, None).await.unwrap();
    stream
        .for_each(|chunk_result| async {
            match chunk_result {
                Ok(chunks) => chunks.iter().for_each(|chunk| {
                    if let Some(content) = &chunk.choices[0].delta.content {
                        print!("{}", content);
                        io::stdout().flush().unwrap();
                    }
                }),
                Err(error) => eprintln!("Error: {:?}", error),
            }
        })
        .await;
    println!();
}

Function calling

use mistralai_client::v1::{
    chat::{ChatMessage, ChatParams},
    client::Client,
    constants::Model,
    tool::{Function, Tool, ToolChoice},
};
use serde::Deserialize;
use std::any::Any;

#[derive(Debug, Deserialize)]
struct GetWeatherArgs { city: String }

struct GetWeatherFunction;
#[async_trait::async_trait]
impl Function for GetWeatherFunction {
    async fn execute(&self, arguments: String) -> Box<dyn Any + Send> {
        let args: GetWeatherArgs = serde_json::from_str(&arguments).unwrap();
        Box::new(format!("20°C in {}", args.city))
    }
}

fn main() {
    let tools = vec![Tool::new(
        "get_weather".to_string(),
        "Get the weather in a city.".to_string(),
        serde_json::json!({
            "type": "object",
            "properties": {
                "city": { "type": "string", "description": "City name" }
            },
            "required": ["city"]
        }),
    )];

    let mut client = Client::new(None, None, None, None).unwrap();
    client.register_function("get_weather".to_string(), Box::new(GetWeatherFunction));

    let messages = vec![ChatMessage::new_user_message("What's the weather in Paris?")];
    let options = ChatParams {
        tool_choice: Some(ToolChoice::Auto),
        tools: Some(tools),
        ..Default::default()
    };

    client.chat(Model::mistral_small_latest(), messages, Some(options)).unwrap();
    let result = client.get_last_function_call_result().unwrap().downcast::<String>().unwrap();
    println!("{}", result);
}

FIM (code completion)

use mistralai_client::v1::{client::Client, constants::Model, fim::FimParams};

fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let options = FimParams {
        suffix: Some("\n    return result".to_string()),
        ..Default::default()
    };

    let result = client.fim(Model::codestral_latest(), "def fibonacci(".to_string(), Some(options)).unwrap();
    println!("{}", result.choices[0].message.content);
}

Embeddings

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

fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let input = vec!["Hello world".to_string(), "Goodbye world".to_string()];
    let response = client.embeddings(Model::mistral_embed(), input, None).unwrap();
    println!("Dimensions: {}", response.data[0].embedding.len());
}

List models

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

fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let models = client.list_models().unwrap();
    for model in &models.data {
        println!("{}", model.id);
    }
}

OCR

use mistralai_client::v1::{
    client::Client,
    constants::Model,
    ocr::{OcrDocument, OcrRequest},
};

fn main() {
    let client = Client::new(None, None, None, None).unwrap();

    let request = OcrRequest {
        model: Model::mistral_ocr_latest(),
        document: OcrDocument::from_url("https://example.com/document.pdf"),
        pages: Some(vec![0]),
        table_format: None,
        include_image_base64: None,
        image_limit: None,
    };

    let response = client.ocr(&request).unwrap();
    println!("{}", response.pages[0].markdown);
}

Available Models

Use Model::new("any-model-id") for any model, or use the built-in constructors:

Constructor	Model ID
Model::mistral_large_latest()	mistral-large-latest
Model::mistral_medium_latest()	mistral-medium-latest
Model::mistral_small_latest()	mistral-small-latest
Model::mistral_small_4()	mistral-small-4-0-26-03
Model::codestral_latest()	codestral-latest
Model::magistral_medium_latest()	magistral-medium-latest
Model::magistral_small_latest()	magistral-small-latest
Model::mistral_embed()	mistral-embed
Model::mistral_ocr_latest()	mistral-ocr-latest
Model::mistral_moderation_latest()	mistral-moderation-26-03
Model::pixtral_large()	pixtral-large-2411
Model::voxtral_mini_transcribe()	voxtral-mini-transcribe-2-26-02

See constants.rs for the full list.

License

Apache-2.0