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Stream Chat AI SDK

Shared utilities for building AI copilots that live inside Stream Chat channels. This package wires Stream’s real-time messaging primitives with Vercel’s AI SDK, tool calling, and optional Mem0 long-term memory so you can stand up production agents with minimal glue code.

Features

  • Connect Stream Chat channels to OpenAI, Anthropic, Gemini, or xAI via the Vercel AI SDK.
  • Stream partial responses back to the channel with typing indicators and cancellation support.
  • Register server-hosted tools (Node/TS functions) and propagate client tool definitions that get dispatched to front-end apps.
  • Orchestrate multi-channel deployments with AgentManager, which spins agents up/down on demand and reuses shared tool definitions.
  • Optional Mem0 memory layer (per user/channel) with zero extra code once environment variables are configured.
  • Built-in helper to generate default tools (e.g., getCurrentTemperature) and to summarize conversations for channel lists.

Installation

npm install @stream-io/chat-ai-sdk
# or
yarn add @stream-io/chat-ai-sdk

This library ships TypeScript types and transpiled JavaScript under dist/.

Environment Variables

Set the following before instantiating an agent:

Variable Required Description
STREAM_API_KEY / STREAM_API_SECRET Stream server client used to upsert/connect the agent user.
OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_GENERATIVE_AI_API_KEY/GEMINI_API_KEY, XAI_API_KEY ✅ (per provider) API key for the provider selected via AgentPlatform.
MEM0_API_KEY, MEM0_CONFIG_JSON, MEM0_DEFAULT_* Optional Enables Mem0 memory when present (see VercelAIAgent).
OPENWEATHER_API_KEY Optional Needed only when you use the weather tool returned by createDefaultTools.

Quick Start (Single Agent)

import {
  Agent,
  AgentPlatform,
  createDefaultTools,
  type ClientToolDefinition,
} from '@stream-io/chat-ai-sdk';

const agent = new Agent({
  userId: 'ai-bot-weather',
  channelId: 'support-room',
  platform: AgentPlatform.OPENAI,
  model: 'gpt-4o-mini',
  instructions: [
    'Answer in a friendly, concise tone.',
    'Prefer Celsius unless the user specifies otherwise.',
  ],
  serverTools: createDefaultTools(), // any AgentTool[]
  clientTools: [
    {
      name: 'openHelpCenter',
      description: 'Open the help center in the web app',
      parameters: {
        type: 'object',
        properties: { articleSlug: { type: 'string' } },
      },
    } satisfies ClientToolDefinition,
  ],
  mem0Context: {
    channelId: 'support-room',
    appId: 'stream-chat-support',
  },
});

await agent.start();

// Later:
await agent.stop();

Managing Multiple Agents

Use AgentManager when you need to spin up AI copilots for many channels (e.g., one per customer conversation) and dispose them automatically once idle.

import {
  AgentManager,
  AgentPlatform,
  createDefaultTools,
} from '@stream-io/chat-ai-sdk';

const manager = new AgentManager({
  serverToolsFactory: () => createDefaultTools(),
  inactivityThresholdMs: 15 * 60 * 1000, // stop after 15 minutes of silence
  agentIdResolver: (channelId) => `ai-${channelId}`, // optional custom mapping
});

await manager.startAgent({
  userId: 'ai-support-bot-123', // usually derived from channelId/orgId
  channelId: 'support-room',
  channelType: 'messaging',
  platform: AgentPlatform.OPENAI,
  instructions: 'Answer with step-by-step troubleshooting tips.',
});

manager.registerClientTools('support-room', [
  {
    name: 'openTicket',
    description: 'Open the CRM ticket in the dashboard',
    parameters: {
      type: 'object',
      properties: { ticketId: { type: 'string' } },
      required: ['ticketId'],
    },
  },
]);

// Later in your shutdown hook:
await manager.stopAgent('ai-support-bot-123');
manager.dispose();

AgentManager will:

  • Cache each agent instance per userId, auto-starting it on demand.
  • Rehydrate registered client tools after restarts so front-end actions stay in sync.
  • Periodically stop inactive agents (based on inactivityThresholdMs) to free resources.
  • Expose activeAgentCount for basic monitoring and a dispose method to clean intervals when your process exits.

Tooling

  • Server tools run in Node and receive the channel/message context plus typed arguments (validated by Zod). Register or replace them with agent.registerServerTools.
  • Client tools are JSON-schema definitions that the SDK relays back to clients via Stream events so front-ends can execute privileged actions while maintaining the tool-call UX.

Summaries

Need unread badges or channel list previews? Call await agent.summarize(text) or Agent.generateSummary(text, platform) to produce a short, LLM-generated headline.

Build & Publish

npm run clean
npm run build

Publishing to npm is as simple as bumping the version and running:

npm publish --access public

Project Structure

src/
├─ Agent.ts          // Manages lifecycle of the AI user inside Stream Chat
├─ VercelAIAgent.ts  // Handles streaming, tool invocation, and Mem0 integration
├─ defaultTools.ts   // Example AgentTool implementations
├─ serverClient.ts   // Stream server SDK bootstrap
└─ types.ts          // Shared enums/interfaces

Use dist/ for the compiled output referenced by package.json (main/types).

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