Mistral

npm install @tanstack/ai-mistral

import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

const stream = chat({
  adapter: mistralText("mistral-large-latest"),
  messages: [{ role: "user", content: "Hello!" }],
});

import { chat } from "@tanstack/ai";
import { createMistralText } from "@tanstack/ai-mistral";

const adapter = createMistralText(
  "mistral-large-latest",
  process.env.MISTRAL_API_KEY!,
);

const stream = chat({
  adapter,
  messages: [{ role: "user", content: "Hello!" }],
});

import {
  createMistralText,
  type MistralTextConfig,
} from "@tanstack/ai-mistral";

const config: Omit<MistralTextConfig, "apiKey"> = {
  serverURL: "https://api.mistral.ai", // Optional, this is the default
  defaultHeaders: {
    "X-Custom-Header": "value",
  },
};

const adapter = createMistralText(
  "mistral-large-latest",
  process.env.MISTRAL_API_KEY!,
  config,
);

import { chat, toServerSentEventsResponse } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

export async function POST(request: Request) {
  const { messages } = await request.json();

  const stream = chat({
    adapter: mistralText("mistral-large-latest"),
    messages,
  });

  return toServerSentEventsResponse(stream);
}

import { chat, toolDefinition } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";
import { z } from "zod";

const getWeatherDef = toolDefinition({
  name: "get_weather",
  description: "Get the current weather for a location",
  inputSchema: z.object({
    location: z.string(),
  }),
});

const getWeather = getWeatherDef.server(async ({ location }) => {
  return { temperature: 72, conditions: "sunny" };
});

const stream = chat({
  adapter: mistralText("mistral-large-latest"),
  messages: [{ role: "user", content: "What's the weather in Paris?" }],
  tools: [getWeather],
});

import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

const stream = chat({
  adapter: mistralText("pixtral-large-latest"),
  messages: [
    {
      role: "user",
      content: [
        { type: "text", content: "What's in this image?" },
        {
          type: "image",
          source: {
            type: "url",
            value: "https://example.com/photo.jpg",
          },
        },
      ],
    },
  ],
});

import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

const base64String = "..."; // your base64-encoded image bytes

const stream = chat({
  adapter: mistralText("pixtral-large-latest"),
  messages: [
    {
      role: "user",
      content: [
        { type: "text", content: "What's in this image?" },
        {
          type: "image",
          source: {
            type: "data",
            mimeType: "image/png",
            value: base64String,
          },
        },
      ],
    },
  ],
});

// ignore: narrowing the raw AG-UI stream by `chunk.type` relies on @ag-ui/core's
// discriminated-union `type` field, which kiira can't resolve in a source-only
// check. The runtime behaviour is exactly as shown.
import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

const stream = chat({
  adapter: mistralText("magistral-medium-latest"),
  messages: [{ role: "user", content: "Why is the sky blue?" }],
});

for await (const chunk of stream) {
  if (chunk.type === "REASONING_MESSAGE_CONTENT") {
    process.stdout.write(`[thinking] ${chunk.delta}`);
  } else if (chunk.type === "TEXT_MESSAGE_CONTENT") {
    process.stdout.write(chunk.delta);
  }
}

import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";
import { z } from "zod";

const recipeSchema = z.object({
  name: z.string(),
  ingredients: z.array(z.string()),
  steps: z.array(z.string()),
});

const recipe = await chat({
  adapter: mistralText("mistral-large-latest"),
  messages: [
    { role: "user", content: "Give me a chocolate chip cookie recipe." },
  ],
  outputSchema: recipeSchema,
});

console.log(recipe.name); // typed as z.infer<typeof recipeSchema>

import { chat } from "@tanstack/ai";
import { mistralText } from "@tanstack/ai-mistral";

const stream = chat({
  adapter: mistralText("mistral-large-latest"),
  messages: [{ role: "user", content: "Hello!" }],
  modelOptions: {
    temperature: 0.7,
    top_p: 0.9,
    max_tokens: 1024,
    random_seed: 42,
    stop: ["END"],
    safe_prompt: true,
    frequency_penalty: 0.5,
    presence_penalty: 0.5,
    parallel_tool_calls: true,
    tool_choice: "auto",
  },
});

MISTRAL_API_KEY=...