@flink-app/mistral-adapter

Mistral AI adapter for the Flink AI framework. Provides integration with Mistral's models via the Chat Completions API using the official @mistralai/mistralai SDK.

Installation

npm install @flink-app/mistral-adapter
# or
pnpm add @flink-app/mistral-adapter

The @mistralai/mistralai package is included as a dependency, so you don't need to install it separately.

Usage

Basic Setup

import { MistralAdapter } from "@flink-app/mistral-adapter";
import { FlinkApp } from "@flink-app/flink";

const app = new FlinkApp({
  ai: {
    llms: {
      default: new MistralAdapter({
        apiKey: process.env.MISTRAL_API_KEY!,
        model: "mistral-medium-latest"
      }),
    },
  },
});

await app.start();

Legacy API (still supported):

// Backward-compatible constructor
new MistralAdapter(process.env.MISTRAL_API_KEY!, "mistral-medium-latest")

Agent Instructions

Define your agent's behavior using the instructions property:

// src/agents/support_agent.ts
export const Agent: FlinkAgentProps = {
  name: "support_agent",
  instructions: "You are a helpful customer support agent.",
  tools: ["get_order_status"],
  model: { adapterId: "default" },
};

How it works:

• Instructions are prepended as a system message to every conversation
• Follows Vercel AI SDK pattern for consistency
• Additional system messages in the conversation are passed through as-is

Multiple Adapters

You can register multiple Mistral adapters with different configurations:

const app = new FlinkApp({
  ai: {
    llms: {
      // Frontier model - best for agentic and coding use cases
      default: new MistralAdapter({
        apiKey: process.env.MISTRAL_API_KEY!,
        model: "mistral-medium-latest"
      }),

      // Efficient model - good balance of capability and cost
      fast: new MistralAdapter({
        apiKey: process.env.MISTRAL_API_KEY!,
        model: "mistral-small-latest"
      }),

      // Code completion specialist
      code: new MistralAdapter({
        apiKey: process.env.MISTRAL_API_KEY!,
        model: "codestral-latest"
      }),
    },
  },
});

Debug Logging

const adapter = new MistralAdapter({
  apiKey: process.env.MISTRAL_API_KEY!,
  model: "mistral-medium-latest",
  debug: true // Enable debug logging for this adapter
});

When debug: true, the adapter logs full request parameters and tool call decisions made by the LLM.

Supported Models

This adapter works with all Mistral chat models. As of 2026:

| Use Case | Recommended Model | Why | |----------|------------------|-----| | General / agentic / coding | mistral-medium-latest | Mistral Medium 3.5 - frontier-class multimodal model optimized for agentic and coding use cases | | Cost-efficient tasks | mistral-small-latest | Mistral Small 4 - hybrid model unifying instruct, reasoning, and coding | | General-purpose (open weights) | mistral-large-latest | Mistral Large 3 - general-purpose multimodal model (Apache 2.0) | | Code completion | codestral-latest | Codestral - code completion specialist | | Edge / small footprint | Ministral 3 series (3B, 8B, 14B) | Compact text and vision models |

See the Mistral models overview for the full, up-to-date list of model IDs.

Features

• ✅ Full tool calling support - including parallel tool calls in a single response
• ✅ Event-based streaming - via the SDK's chat.stream()
• ✅ Multimodal input - text + image content blocks (https URLs and base64 data URLs)
• ✅ Tool call ID normalization - Mistral requires tool call IDs to be exactly 9 alphanumeric characters; IDs from conversation history that originated with another provider are deterministically remapped
• ✅ Token usage tracking - prompt and completion tokens reported per request
• ✅ Schema sanitization - tool input schemas cleaned for Mistral compatibility

Architecture Notes

Flink Integration

The adapter implements Flink's LLMAdapter interface:

• Flink's instructions → prepended as { role: "system" } message
• Flink's messages → converted to Mistral chat messages (system/user/assistant/tool roles)
• Flink's tool schema → converted to Mistral's function format ({ type: "function", function: {...} })
• Streamed deltas → mapped to Flink's LLMStreamChunk events (text, tool_call, usage, done)

Each API call is one turn:

• Flink's AgentRunner handles the multi-turn loop (call API → execute tools → call API again)
• Tool results are sent back as { role: "tool", toolCallId, content } messages

ESM-only SDK

The @mistralai/mistralai SDK v2 is ESM-only. This adapter is compiled to CommonJS (like the rest of the Flink ecosystem) and loads the SDK via a dynamic import(), so it works in both CommonJS and ESM applications without configuration.

Temperature

Temperature is only sent to the API when the agent explicitly configured one — Mistral recommends values between 0.0 and 0.7, and the default varies by model.

Requirements

• Node.js >= 18
• @flink-app/flink >= 2.0.0-alpha.102

License

MIT

Resources

• Mistral AI documentation
• Mistral models overview
• Function calling guide