@orka-js/mistral

Mistral AI adapter for OrkaJS — Mistral Large, Codestral, embeddings, and streaming.

Installation

npm install @orka-js/mistral

Quick Start

import { MistralAdapter } from '@orka-js/mistral'
import { Orka } from '@orka-js/core'

const llm = new MistralAdapter({
  apiKey: process.env.MISTRAL_API_KEY!,
  model: 'mistral-large-latest',
})

const orka = new Orka({ llm })

const response = await orka.chat([
  { role: 'user', content: 'Hello!' }
])
console.log(response.content)

Streaming

const stream = await llm.stream([
  { role: 'user', content: 'Explain quantum computing' }
])

for await (const chunk of stream) {
  process.stdout.write(chunk.delta ?? '')
}

Embeddings

const vector = await llm.embed('Hello world')
// Returns: number[]

Configuration

| Option | Type | Default | Description | |--------|------|---------|-------------| | apiKey | string | — | Mistral API key (required) | | model | string | 'mistral-large-latest' | Model to use | | temperature | number | 0.7 | Sampling temperature | | maxTokens | number | — | Max tokens in response |

Supported Models

| Model | Description | |-------|-------------| | mistral-large-latest | Most powerful Mistral model | | mistral-medium | Balanced performance | | mistral-small | Fast and cost-effective | | open-mistral-7b | Open-source 7B model | | open-mixtral-8x7b | Mixture-of-experts model | | codestral | Code-specialized model |

Embeddings: mistral-embed

API

MistralAdapter

const adapter = new MistralAdapter(config)

adapter.chat(messages: ChatMessage[])   // Promise<ChatResponse>
adapter.stream(messages: ChatMessage[]) // AsyncIterable<StreamEvent>
adapter.embed(text: string)             // Promise<number[]>

Implements: LLMAdapter, StreamingLLMAdapter

Related Packages

• @orka-js/core — Core types and LLMAdapter interface
• @orka-js/openai — OpenAI adapter
• orkajs — Full bundle