!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

*   [Get started](/v0.1/docs/get_started/)
    
    *   [Introduction](/v0.1/docs/get_started/introduction/)
    *   [Installation](/v0.1/docs/get_started/installation/)
    *   [Quickstart](/v0.1/docs/get_started/quickstart/)
*   [LangChain Expression Language](/v0.1/docs/expression_language/)
    
    *   [Get started](/v0.1/docs/expression_language/get_started/)
    *   [Why use LCEL?](/v0.1/docs/expression_language/why/)
    *   [Interface](/v0.1/docs/expression_language/interface/)
    *   [Streaming](/v0.1/docs/expression_language/streaming/)
    *   [How to](/v0.1/docs/expression_language/how_to/routing/)
        
    *   [Cookbook](/v0.1/docs/expression_language/cookbook/)
        
    *   [LangChain Expression Language (LCEL)](/v0.1/docs/expression_language/)
*   [Modules](/v0.1/docs/modules/)
    
    *   [Model I/O](/v0.1/docs/modules/model_io/)
        
    *   [Retrieval](/v0.1/docs/modules/data_connection/)
        
    *   [Chains](/v0.1/docs/modules/chains/)
    *   [Agents](/v0.1/docs/modules/agents/)
        
    *   [More](/v0.1/docs/modules/memory/)
        
*   [Security](/v0.1/docs/security/)
*   [Guides](/v0.1/docs/guides/)
    
*   [Ecosystem](/v0.1/docs/ecosystem/)
    
    *   [Integrations](/v0.1/docs/ecosystem/integrations/)
        
        *   [Databerry](/v0.1/docs/ecosystem/integrations/databerry/)
        *   [Helicone](/v0.1/docs/ecosystem/integrations/helicone/)
        *   [Lunary](/v0.1/docs/ecosystem/integrations/lunary/)
        *   [Google MakerSuite](/v0.1/docs/ecosystem/integrations/makersuite/)
        *   [Unstructured](/v0.1/docs/ecosystem/integrations/unstructured/)
    *   [Integrating with LangServe](/v0.1/docs/ecosystem/langserve/)
    *   [LangSmith](https://docs.smith.langchain.com)
*   [LangGraph](/v0.1/docs/langgraph/)
*   * * *
    

*   [](/v0.1/)
*   [Ecosystem](/v0.1/docs/ecosystem/)
*   [Integrations](/v0.1/docs/ecosystem/integrations/)
*   Databerry

On this page

Databerry
=========

This page covers how to use the [Databerry](https://databerry.ai) within LangChain.

What is Databerry?[​](#what-is-databerry "Direct link to What is Databerry?")
-----------------------------------------------------------------------------

Databerry is an [open source](https://github.com/gmpetrov/databerry) document retrieval platform that helps to connect your personal data with Large Language Models.

![Databerry](/v0.1/assets/images/DataberryDashboard-098b0319db0dd6665f993f77f4db822f.png)

Quick start[​](#quick-start "Direct link to Quick start")
---------------------------------------------------------

Retrieving documents stored in Databerry from LangChain is very easy!

    import { DataberryRetriever } from "langchain/retrievers/databerry";const retriever = new DataberryRetriever({  datastoreUrl: "https://api.databerry.ai/query/clg1xg2h80000l708dymr0fxc",  apiKey: "DATABERRY_API_KEY", // optional: needed for private datastores  topK: 8, // optional: default value is 3});// Create a chain that uses the OpenAI LLM and Databerry retriever.const chain = RetrievalQAChain.fromLLM(model, retriever);// Call the chain with a query.const res = await chain.call({  query: "What's Databerry?",});console.log({ res });/*{  res: {    text: 'Databerry provides a user-friendly solution to quickly setup a semantic search system over your personal data without any technical knowledge.'  }}*/

* * *

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

[

Previous

Integrations

](/v0.1/docs/ecosystem/integrations/)[

Next

Helicone

](/v0.1/docs/ecosystem/integrations/helicone/)

*   [What is Databerry?](#what-is-databerry)
*   [Quick start](#quick-start)

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.