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*   [Providers](/v0.1/docs/integrations/platforms/)
    
    *   [Providers](/v0.1/docs/integrations/platforms/)
    *   [Anthropic](/v0.1/docs/integrations/platforms/anthropic/)
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*   [Components](/v0.1/docs/integrations/components/)
    
    *   [LLMs](/v0.1/docs/integrations/llms/)
        
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        *   [Astra DB Chat Memory](/v0.1/docs/integrations/chat_memory/astradb/)
        *   [Cassandra Chat Memory](/v0.1/docs/integrations/chat_memory/cassandra/)
        *   [Cloudflare D1-Backed Chat Memory](/v0.1/docs/integrations/chat_memory/cloudflare_d1/)
        *   [Convex Chat Memory](/v0.1/docs/integrations/chat_memory/convex/)
        *   [DynamoDB-Backed Chat Memory](/v0.1/docs/integrations/chat_memory/dynamodb/)
        *   [Firestore Chat Memory](/v0.1/docs/integrations/chat_memory/firestore/)
        *   [IPFS Datastore Chat Memory](/v0.1/docs/integrations/chat_memory/ipfs_datastore/)
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        *   [Xata Chat Memory](/v0.1/docs/integrations/chat_memory/xata/)
        *   [Zep Memory](/v0.1/docs/integrations/chat_memory/zep_memory/)
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*   [](/v0.1/)
*   [Components](/v0.1/docs/integrations/components/)
*   [Chat Memory](/v0.1/docs/integrations/chat_memory/)
*   Cloudflare D1-Backed Chat Memory

Cloudflare D1-Backed Chat Memory
================================

info

This integration is only supported in Cloudflare Workers.

For longer-term persistence across chat sessions, you can swap out the default in-memory `chatHistory` that backs chat memory classes like `BufferMemory` for a Cloudflare D1 instance.

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

You'll need to install the LangChain Cloudflare integration package. For the below example, we also use Anthropic, but you can use any model you'd like:

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/cloudflare @langchain/anthropic

    yarn add @langchain/cloudflare @langchain/anthropic

    pnpm add @langchain/cloudflare @langchain/anthropic

Set up a D1 instance for your worker by following [the official documentation](https://developers.cloudflare.com/d1/). Your project's `wrangler.toml` file should look something like this:

    name = "YOUR_PROJECT_NAME"main = "src/index.ts"compatibility_date = "2024-01-10"[vars]ANTHROPIC_API_KEY = "YOUR_ANTHROPIC_KEY"[[d1_databases]]binding = "DB"                                       # available in your Worker as env.DBdatabase_name = "YOUR_D1_DB_NAME"database_id = "YOUR_D1_DB_ID"

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

You can then use D1 to store your history as follows:

    import type { D1Database } from "@cloudflare/workers-types";import { BufferMemory } from "langchain/memory";import { CloudflareD1MessageHistory } from "@langchain/cloudflare";import {  ChatPromptTemplate,  MessagesPlaceholder,} from "@langchain/core/prompts";import { RunnableSequence } from "@langchain/core/runnables";import { StringOutputParser } from "@langchain/core/output_parsers";import { ChatAnthropic } from "@langchain/anthropic";export interface Env {  DB: D1Database;  ANTHROPIC_API_KEY: string;}export default {  async fetch(request: Request, env: Env): Promise<Response> {    try {      const { searchParams } = new URL(request.url);      const input = searchParams.get("input");      if (!input) {        throw new Error(`Missing "input" parameter`);      }      const memory = new BufferMemory({        returnMessages: true,        chatHistory: new CloudflareD1MessageHistory({          tableName: "stored_message",          sessionId: "example",          database: env.DB,        }),      });      const prompt = ChatPromptTemplate.fromMessages([        ["system", "You are a helpful chatbot"],        new MessagesPlaceholder("history"),        ["human", "{input}"],      ]);      const model = new ChatAnthropic({        apiKey: env.ANTHROPIC_API_KEY,      });      const chain = RunnableSequence.from([        {          input: (initialInput) => initialInput.input,          memory: () => memory.loadMemoryVariables({}),        },        {          input: (previousOutput) => previousOutput.input,          history: (previousOutput) => previousOutput.memory.history,        },        prompt,        model,        new StringOutputParser(),      ]);      const chainInput = { input };      const res = await chain.invoke(chainInput);      await memory.saveContext(chainInput, {        output: res,      });      return new Response(JSON.stringify(res), {        headers: { "content-type": "application/json" },      });    } catch (err: any) {      console.log(err.message);      return new Response(err.message, { status: 500 });    }  },};

#### API Reference:

*   [BufferMemory](https://api.js.langchain.com/classes/langchain_memory.BufferMemory.html) from `langchain/memory`
*   [CloudflareD1MessageHistory](https://api.js.langchain.com/classes/langchain_cloudflare.CloudflareD1MessageHistory.html) from `@langchain/cloudflare`
*   [ChatPromptTemplate](https://api.js.langchain.com/classes/langchain_core_prompts.ChatPromptTemplate.html) from `@langchain/core/prompts`
*   [MessagesPlaceholder](https://api.js.langchain.com/classes/langchain_core_prompts.MessagesPlaceholder.html) from `@langchain/core/prompts`
*   [RunnableSequence](https://api.js.langchain.com/classes/langchain_core_runnables.RunnableSequence.html) from `@langchain/core/runnables`
*   [StringOutputParser](https://api.js.langchain.com/classes/langchain_core_output_parsers.StringOutputParser.html) from `@langchain/core/output_parsers`
*   [ChatAnthropic](https://api.js.langchain.com/classes/langchain_anthropic.ChatAnthropic.html) from `@langchain/anthropic`

* * *

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

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