ChatTogetherAI integration

Integrate with the ChatTogetherAI chat model using LangChain JavaScript.

Together AI offers an API to query 50+ leading open-source models in a couple lines of code.

This guide will help you getting started with ChatTogetherAI chat models. For detailed documentation of all ChatTogetherAI features and configurations head to the API reference.

Overview

Integration details

Class	Package	Serializable	PY support	Downloads	Version
ChatTogetherAI	@langchain/together-ai	✅	✅

Model features

See the links in the table headers below for guides on how to use specific features.

Tool calling	Structured output	Image input	Audio input	Video input	Token-level streaming	Token usage	Logprobs
✅	✅	✅	✅	✅	✅	✅	✅

Setup

To access ChatTogetherAI models, create a Together account, get an API key, and install the @langchain/together-ai integration package.

Credentials

Head to api.together.ai to sign up to Together AI and generate an API key. Set the TOGETHER_AI_API_KEY environment variable:

export TOGETHER_AI_API_KEY="your-api-key"

If you want to get automated tracing of your model calls you can also set your LangSmith API key by uncommenting below:

# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"

Installation

The LangChain ChatTogetherAI integration lives in the @langchain/together-ai package:

npm

npm install @langchain/together-ai @langchain/core

Instantiation

Now we can instantiate our model object and generate chat completions:

import { ChatTogetherAI } from "@langchain/together-ai";

const llm = new ChatTogetherAI({
    model: "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
    temperature: 0,
    // other params...
})

Invocation

const aiMsg = await llm.invoke([
    [
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ],
    ["human", "I love programming."],
])
aiMsg

AIMessage {
  "id": "chatcmpl-9rT9qEDPZ6iLCk6jt3XTzVDDH6pcI",
  "content": "J'adore la programmation.",
  "additional_kwargs": {},
  "response_metadata": {
    "tokenUsage": {
      "completionTokens": 8,
      "promptTokens": 31,
      "totalTokens": 39
    },
    "finish_reason": "stop"
  },
  "tool_calls": [],
  "invalid_tool_calls": [],
  "usage_metadata": {
    "input_tokens": 31,
    "output_tokens": 8,
    "total_tokens": 39
  }
}

console.log(aiMsg.content)

J'adore la programmation.

---

API reference

For detailed documentation of all ChatTogetherAI features and configurations head to the API reference.

---

Connect these docs to Claude, VSCode, and more via MCP for real-time answers.

Edit this page on GitHub or file an issue.