!function(){function t(t){document.documentElement.setAttribute("data-theme",t)}var e=function(){var t=null;try{t=new URLSearchParams(window.location.search).get("docusaurus-theme")}catch(t){}return t}()||function(){var t=null;try{t=localStorage.getItem("theme")}catch(t){}return t}();t(null!==e?e:"light")}(),document.documentElement.setAttribute("data-announcement-bar-initially-dismissed",function(){try{return"true"===localStorage.getItem("docusaurus.announcement.dismiss")}catch(t){}return!1}())

[Skip to main content](#__docusaurus_skipToContent_fallback)

LangChain v0.2 is coming soon! Preview the new docs [here](/v0.2/docs/introduction/).

[

![🦜️🔗 Langchain](/v0.1/img/brand/wordmark.png)![🦜️🔗 Langchain](/v0.1/img/brand/wordmark-dark.png)

](/v0.1/)[Docs](/v0.1/docs/get_started/introduction/)[Use cases](/v0.1/docs/use_cases/)[Integrations](/v0.1/docs/integrations/platforms/)[API Reference](https://api.js.langchain.com)

[More](#)

*   [People](/v0.1/docs/people/)
*   [Community](/v0.1/docs/community/)
*   [Tutorials](/v0.1/docs/additional_resources/tutorials/)
*   [Contributing](/v0.1/docs/contributing/)

[v0.1](#)

*   [v0.2](https://js.langchain.com/v0.2/docs/introduction)
*   [v0.1](/v0.1/docs/get_started/introduction/)

[🦜🔗](#)

*   [LangSmith](https://smith.langchain.com)
*   [LangSmith Docs](https://docs.smith.langchain.com)
*   [LangChain Hub](https://smith.langchain.com/hub)
*   [LangServe](https://github.com/langchain-ai/langserve)
*   [Python Docs](https://python.langchain.com/)

[Chat](https://chatjs.langchain.com)[](https://github.com/langchain-ai/langchainjs)

Search

*   [Providers](/v0.1/docs/integrations/platforms/)
    
    *   [Providers](/v0.1/docs/integrations/platforms/)
    *   [Anthropic](/v0.1/docs/integrations/platforms/anthropic/)
    *   [AWS](/v0.1/docs/integrations/platforms/aws/)
    *   [Google](/v0.1/docs/integrations/platforms/google/)
    *   [Microsoft](/v0.1/docs/integrations/platforms/microsoft/)
    *   [OpenAI](/v0.1/docs/integrations/platforms/openai/)
*   [Components](/v0.1/docs/integrations/components/)
    
    *   [LLMs](/v0.1/docs/integrations/llms/)
        
    *   [Chat models](/v0.1/docs/integrations/chat/)
        
        *   [Chat models](/v0.1/docs/integrations/chat/)
        *   [Alibaba Tongyi](/v0.1/docs/integrations/chat/alibaba_tongyi/)
        *   [Anthropic](/v0.1/docs/integrations/chat/anthropic/)
        *   [Anthropic Tools](/v0.1/docs/integrations/chat/anthropic_tools/)
        *   [Azure OpenAI](/v0.1/docs/integrations/chat/azure/)
        *   [Baidu Wenxin](/v0.1/docs/integrations/chat/baidu_wenxin/)
        *   [Bedrock](/v0.1/docs/integrations/chat/bedrock/)
        *   [Cloudflare Workers AI](/v0.1/docs/integrations/chat/cloudflare_workersai/)
        *   [Cohere](/v0.1/docs/integrations/chat/cohere/)
        *   [Fake LLM](/v0.1/docs/integrations/chat/fake/)
        *   [Fireworks](/v0.1/docs/integrations/chat/fireworks/)
        *   [Friendli](/v0.1/docs/integrations/chat/friendli/)
        *   [Google GenAI](/v0.1/docs/integrations/chat/google_generativeai/)
        *   [(Legacy) Google PaLM/VertexAI](/v0.1/docs/integrations/chat/google_palm/)
        *   [Google Vertex AI](/v0.1/docs/integrations/chat/google_vertex_ai/)
        *   [Groq](/v0.1/docs/integrations/chat/groq/)
        *   [Llama CPP](/v0.1/docs/integrations/chat/llama_cpp/)
        *   [Minimax](/v0.1/docs/integrations/chat/minimax/)
        *   [Mistral AI](/v0.1/docs/integrations/chat/mistral/)
        *   [NIBittensorChatModel](/v0.1/docs/integrations/chat/ni_bittensor/)
        *   [Ollama](/v0.1/docs/integrations/chat/ollama/)
        *   [Ollama Functions](/v0.1/docs/integrations/chat/ollama_functions/)
        *   [OpenAI](/v0.1/docs/integrations/chat/openai/)
        *   [PremAI](/v0.1/docs/integrations/chat/premai/)
        *   [PromptLayer OpenAI](/v0.1/docs/integrations/chat/prompt_layer_openai/)
        *   [TogetherAI](/v0.1/docs/integrations/chat/togetherai/)
        *   [WebLLM](/v0.1/docs/integrations/chat/web_llm/)
        *   [YandexGPT](/v0.1/docs/integrations/chat/yandex/)
        *   [ZhipuAI](/v0.1/docs/integrations/chat/zhipuai/)
    *   [Document loaders](/v0.1/docs/integrations/document_loaders/)
        
    *   [Document transformers](/v0.1/docs/integrations/document_transformers/)
        
    *   [Document compressors](/v0.1/docs/integrations/document_compressors/)
        
    *   [Text embedding models](/v0.1/docs/integrations/text_embedding/)
        
    *   [Vector stores](/v0.1/docs/integrations/vectorstores/)
        
    *   [Retrievers](/v0.1/docs/integrations/retrievers/)
        
    *   [Tools](/v0.1/docs/integrations/tools/)
        
    *   [Agents and toolkits](/v0.1/docs/integrations/toolkits/)
        
    *   [Chat Memory](/v0.1/docs/integrations/chat_memory/)
        
    *   [Stores](/v0.1/docs/integrations/stores/)
        

*   [](/v0.1/)
*   [Components](/v0.1/docs/integrations/components/)
*   [Chat models](/v0.1/docs/integrations/chat/)
*   Friendli

On this page

Friendli
========

> [Friendli](https://friendli.ai/) enhances AI application performance and optimizes cost savings with scalable, efficient deployment options, tailored for high-demand AI workloads.

This tutorial guides you through integrating `ChatFriendli` for chat applications using LangChain. `ChatFriendli` offers a flexible approach to generating conversational AI responses, supporting both synchronous and asynchronous calls.

Setup[​](#setup "Direct link to Setup")
---------------------------------------

Ensure the `@langchain/community` is installed.

tip

See [this section for general instructions on installing integration packages](/v0.1/docs/get_started/installation/#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/community

    yarn add @langchain/community

    pnpm add @langchain/community

Sign in to [Friendli Suite](https://suite.friendli.ai/) to create a Personal Access Token, and set it as the `FRIENDLI_TOKEN` environment. You can set team id as `FRIENDLI_TEAM` environment.

You can initialize a Friendli chat model with selecting the model you want to use. The default model is `llama-2-13b-chat`. You can check the available models at [docs.friendli.ai](https://docs.friendli.ai/guides/serverless_endpoints/pricing#text-generation-models).

Usage[​](#usage "Direct link to Usage")
---------------------------------------

    import { ChatFriendli } from "@langchain/community/chat_models/friendli";const model = new ChatFriendli({  model: "llama-2-13b-chat", // Default value  friendliToken: process.env.FRIENDLI_TOKEN,  friendliTeam: process.env.FRIENDLI_TEAM,  maxTokens: 800,  temperature: 0.9,  topP: 0.9,  frequencyPenalty: 0,  stop: [],});const response = await model.invoke(  "Draft a cover letter for a role in software engineering.");console.log(response.content);/*Dear [Hiring Manager],I am excited to apply for the role of Software Engineer at [Company Name]. With my passion for innovation, creativity, and problem-solving, I am confident that I would be a valuable asset to your team.As a highly motivated and detail-oriented individual, ...*/const stream = await model.stream(  "Draft a cover letter for a role in software engineering.");for await (const chunk of stream) {  console.log(chunk.content);}/*Dear [Hiring...[Your Name]*/

#### API Reference:

*   [ChatFriendli](https://api.js.langchain.com/classes/langchain_community_chat_models_friendli.ChatFriendli.html) from `@langchain/community/chat_models/friendli`

* * *

#### Help us out by providing feedback on this documentation page:

[

Previous

Fireworks

](/v0.1/docs/integrations/chat/fireworks/)[

Next

Google GenAI

](/v0.1/docs/integrations/chat/google_generativeai/)

*   [Setup](#setup)
*   [Usage](#usage)

Community

*   [Discord](https://discord.gg/cU2adEyC7w)
*   [Twitter](https://twitter.com/LangChainAI)

GitHub

*   [Python](https://github.com/langchain-ai/langchain)
*   [JS/TS](https://github.com/langchain-ai/langchainjs)

More

*   [Homepage](https://langchain.com)
*   [Blog](https://blog.langchain.dev)

Copyright © 2024 LangChain, Inc.