# Stream Chat LangChain SDK The Stream Chat LangChain SDK wires Stream’s real-time messaging primitives to the [LangChain JavaScript SDK](https://github.com/GetStream/stream-chat-langchain). With a single package you can host AI copilots inside Stream channels, connect OpenAI, Anthropic, Gemini, or xAI chat models, stream partial responses with typing indicators, dispatch tool calls, and optionally persist long-term memory via [Mem0](https://github.com/mem0ai/mem0). You can find sample integration with the Langchain AI SDK in our samples [repo](https://github.com/GetStream/chat-ai-samples/tree/main/langchain-sample). --- ## Installation ```bash npm install @stream-io/chat-langchain-sdk # or yarn add @stream-io/chat-langchain-sdk ``` The package ships TypeScript sources plus transpiled JavaScript under `dist/`. Import either ESM or CJS builds depending on your bundler. ## Supported Providers Select a provider at runtime through the `AgentPlatform` enum: | Platform | Enum | Default model | Notes | | --------- | ------------------------- | ---------------------------- | ------------------------------------------------------------------- | | OpenAI | `AgentPlatform.OPENAI` | `gpt-4o-mini` | Enables Mem0 (`provider: openai`) when configured. | | Anthropic | `AgentPlatform.ANTHROPIC` | `claude-3-5-sonnet-20241022` | Uses LangChain’s Anthropic chat wrapper with optional Mem0 support. | | Gemini | `AgentPlatform.GEMINI` | `gemini-1.5-flash` | Accepts `GOOGLE_GENERATIVE_AI_API_KEY` or `GEMINI_API_KEY`. | | xAI | `AgentPlatform.XAI` | `grok-beta` | Mem0 does not expose xAI yet, so long-term memory stays disabled. | Override the model ID per agent via the `model` option to match your LangChain configuration. --- ## Environment Variables Set the following before instantiating an agent: | Variable | Required | Description | | ----------------------------------------------------------------------------------------------------- | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | | `STREAM_API_KEY`, `STREAM_API_SECRET` | ✅ | Used by the server-side Stream client in `serverClient.ts` to upsert and connect the agent user. Missing keys throw immediately on import. | | `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `GOOGLE_GENERATIVE_AI_API_KEY`/`GEMINI_API_KEY`, `XAI_API_KEY` | ✅ (per provider) | Passed into the LangChain chat model wrapper for the configured `AgentPlatform`. | | `MEM0_API_KEY`, `MEM0_CONFIG_JSON`, `MEM0_DEFAULT_*` | Optional | Enables Mem0 memory when present. See [Memory & Mem0](#memory--mem0). | | `OPENWEATHER_API_KEY` | Optional | Required only if you rely on the `getCurrentTemperature` tool returned by `createDefaultTools()`. | > Tip: when running multiple agents, load environment variables once at process start-up so lazy imports such as `serverClient` do not throw intermittently. ## Quick Start: Single Agent ```ts import { Agent, AgentPlatform, createDefaultTools, type ClientToolDefinition, } from "@stream-io/chat-langchain-sdk"; const agent = new Agent({ userId: "ai-bot-weather", channelId: "support-room", channelType: "messaging", platform: AgentPlatform.OPENAI, model: "gpt-4o-mini", instructions: [ "Answer in a friendly, concise tone.", "Prefer Celsius unless the user specifies otherwise.", ], serverTools: createDefaultTools(), clientTools: [ { name: "openHelpCenter", description: "Open the help center in the web app", parameters: { type: "object", properties: { articleSlug: { type: "string" } }, required: ["articleSlug"], }, } satisfies ClientToolDefinition, ], mem0Context: { channelId: "support-room", appId: "stream-chat-support", }, }); await agent.start(); // Later... await agent.stop(); ``` ## Multi-Channel Deployments with `AgentManager` Use `AgentManager` to orchestrate many concurrent agents without leaking resources. It caches instances by `userId`, supports lazy start/stop, and periodically disposes idle bots. ```ts import { AgentManager, AgentPlatform, createDefaultTools, } from "@stream-io/chat-langchain-sdk"; const manager = new AgentManager({ serverToolsFactory: () => createDefaultTools(), inactivityThresholdMs: 30 * 60 * 1000, cleanupIntervalMs: 5_000, }); await manager.startAgent({ userId: "ai-support-bot-123", channelId: "support-room", channelType: "messaging", platform: AgentPlatform.ANTHROPIC, instructions: [ "Provide empathetic troubleshooting tips.", "Offer to escalate tough issues to a human.", ], }); manager.registerClientTools("support-room", [ { name: "openTicket", description: "Open the CRM ticket in the dashboard", parameters: { type: "object", properties: { ticketId: { type: "string" } }, required: ["ticketId"], }, }, ]); // On shutdown: await manager.stopAgent("ai-support-bot-123"); manager.dispose(); ``` Key behaviors: - `serverToolsFactory` runs each time a new agent is constructed, allowing per-channel config. - `registerClientTools(channelId, tools)` persists definitions and re-applies them the next time the channel’s agent starts. - `inactivityThresholdMs` (default ~8 hours) pairs with `cleanupIntervalMs` (default 5 seconds) to stop agents automatically once `Agent#getLastInteraction()` stales. - `dispose()` clears the cleanup interval and caches; call it during process shutdown to avoid hanging timers. ## Working with Tools ### Server Tools (`AgentTool`) Server tools run in Node/TS and receive typed arguments plus channel/message context. Each tool consists of a `name`, human-facing `description`, optional `instructions` (folded into the system prompt), a Zod `parameters` schema, and an async `execute` function that returns the tool output text. ```ts import { z } from "zod"; import type { AgentTool } from "@stream-io/chat-langchain-sdk"; const getOrderStatus: AgentTool = { name: "getOrderStatus", description: "Look up order details by ID.", instructions: "Invoke only when the user provides a valid order number.", parameters: z.object({ orderId: z.string().describe("The e-commerce order number"), }), async execute({ orderId }, { channel }) { const record = await lookupOrder(orderId); if (!record) { throw new Error(`No order found for ${orderId}`); } await channel.sendEvent({ type: "order.viewed", orderId }); return `Status: ${record.status}. ETA ${record.eta}`; }, }; ``` Register tools through `serverTools` in the `Agent` constructor, `agent.addServerTools(...)`, or `agent.registerServerTools([...], { replace: boolean })`. ### Client Tools Client tools are JSON-schema definitions representing capabilities that must be executed on the front end (e.g., “open ticket in CRM”, “navigate to screen”). The SDK converts the schema to a Zod validator and exposes an internal tool that sends a `custom_client_tool_invocation` event containing: ```json { "type": "custom_client_tool_invocation", "cid": "", "message_id": "", "tool": { "name": "openTicket", ... }, "args": { "ticketId": "123" } } ``` Listen for that event in your app, perform the privileged action, and optionally respond in chat. ### Default Tools `createDefaultTools()` returns `getCurrentTemperature`. It requires `OPENWEATHER_API_KEY` and demonstrates: - Fetching an external REST API (`axios`). - Converting units based on tool arguments. - Supplying `instructions` so the LLM only calls the tool when the user explicitly asks about weather. Use it as inspiration for production tools or swap in your own factory. ## Streaming, Indicators, and Cancellation - Messages stream via LangChain’s async generator interfaces, and the SDK pipes partial tokens through `chatClient.partialUpdateMessage` for live typing. - `ai_indicator.update` events surface typing states: `AI_STATE_THINKING`, `AI_STATE_GENERATING`, `AI_STATE_EXTERNAL_SOURCES`, and `AI_STATE_ERROR`. - `ai_indicator.clear` flushes once the final response lands. - The SDK listens for `ai_indicator.stop` events and aborts the underlying LangChain run, which cancels streaming mid-flight. - Partial message text is written through `chatClient.partialUpdateMessage`, enabling front-end live typing plus cancellation UI. ## Memory & Mem0 Mem0 adds “long-term” recall for user+channel pairs. Configuration layers: 1. Optional `MEM0_CONFIG_JSON` (stringified JSON) provides defaults such as `metadata`. 2. Per-process env fallbacks: `MEM0_DEFAULT_USER_ID`, `MEM0_DEFAULT_AGENT_ID`, `MEM0_DEFAULT_APP_ID`. 3. `Agent` option `mem0Context` lets you override `channelId`, `userId`, `appId`, `agentId`, or supply `configOverrides`. 4. During runtime the SDK augments metadata with Stream-specific IDs. Mem0 only runs when the chosen provider matches `openai`, `anthropic`, or `google` and `MEM0_API_KEY` is set. Pass `{ disableMem0: true }` via `Agent.generateSummary(...)` implicitly when generating summaries to keep them fast and deterministic. ## Summaries and Titles Use `agent.summarize(text)` (instance) or `Agent.generateSummary(text, platform, model?)` (static) to request a short, six-word “title” summarizing arbitrary text—ideal for channel list previews, inbox cards, or push notification headers. The helper: - Spins up a lightweight LangChain chat model using the current provider settings. - Disables Mem0 to avoid unnecessary persistence. - Normalizes the resulting string by trimming surrounding quotes. ```ts const headline = await agent.summarize(latestTranscript); await channel.updatePartial({ set: { subtitle: headline } }); ``` --- This page was last updated at 2026-04-17T17:33:37.937Z. For the most recent version of this documentation, visit [https://getstream.io/chat/docs/sdk/ios/v4/ai-integrations/stream-chat-langchain-sdk/](https://getstream.io/chat/docs/sdk/ios/v4/ai-integrations/stream-chat-langchain-sdk/).