feat(harness-deepagents): implement harness adapter for Deep Agents

.changeset/deepagents-harness.md

@@ -0,0 +1,5 @@
+---
+'@ai-sdk/harness-deepagents': major
+---
+
+feat(harness-deepagents): add Deep Agents harness adapter 

.github/konsistent.json

@@ -342,6 +342,7 @@
   "kebabToPascalMap": {
     "assemblyai": "AssemblyAI",
     "bytedance": "ByteDance",
+    "deepagents": "DeepAgents",
     "deepinfra": "DeepInfra",
     "deepseek": "DeepSeek",
     "elevenlabs": "ElevenLabs",

content/docs/03-ai-sdk-harnesses/05-harness-adapters.mdx

@@ -16,13 +16,13 @@ The AI SDK includes the following harness adapters:
 
 - [Claude Code](/providers/ai-sdk-harnesses/claude-code) (`@ai-sdk/harness-claude-code`)
 - [Codex](/providers/ai-sdk-harnesses/codex) (`@ai-sdk/harness-codex`)
+- [Deep Agents](/providers/ai-sdk-harnesses/deepagents) (`@ai-sdk/harness-deepagents`)
 - [OpenCode](/providers/ai-sdk-harnesses/opencode) (`@ai-sdk/harness-opencode`)
 - [Pi](/providers/ai-sdk-harnesses/pi) (`@ai-sdk/harness-pi`)
 
 ### Coming Soon
 
 - Amp (`@ai-sdk/harness-amp`)
-- DeepAgents (`@ai-sdk/harness-deepagents`)
 - Goose (`@ai-sdk/harness-goose`)
 - Mastra (`@ai-sdk/harness-mastra`)
 
@@ -32,5 +32,6 @@ The AI SDK includes the following harness adapters:
 | ------------------------------------------------------ | ---------------- | ------------------- | ------------------- | ---------------------- |
 | [Claude Code](/providers/ai-sdk-harnesses/claude-code) | Sandbox bridge   | <Check size={18} /> | <Check size={18} /> | <Check size={18} />    |
 | [Codex](/providers/ai-sdk-harnesses/codex)             | Sandbox bridge   | <Check size={18} /> | <Check size={18} /> | <Cross size={18} />    |
+| [Deep Agents](/providers/ai-sdk-harnesses/deepagents)  | Sandbox bridge   | <Check size={18} /> | <Check size={18} /> | <Check size={18} />    |
 | [OpenCode](/providers/ai-sdk-harnesses/opencode)       | Sandbox bridge   | <Check size={18} /> | <Check size={18} /> | <Check size={18} />    |
 | [Pi](/providers/ai-sdk-harnesses/pi)                   | Host process     | <Check size={18} /> | <Check size={18} /> | <Check size={18} />    |

content/providers/02-ai-sdk-harnesses/05-deepagents.mdx

@@ -0,0 +1,201 @@
+---
+title: Deep Agents
+description: Learn how to use the Deep Agents harness adapter.
+---
+
+# Deep Agents Harness
+
+The Deep Agents harness adapter connects `HarnessAgent` to
+[Deep Agents](https://github.com/langchain-ai/deepagentsjs), a LangGraph-based agent
+runtime. The adapter runs a Node bridge inside the sandbox that drives the
+`deepagents` package and streams its `streamEvents` output back to the host over a
+sandbox-exposed WebSocket.
+
+<Note>
+  Harness packages are **experimental**. Expect breaking changes between
+  releases as this early API gets further refined.
+</Note>
+
+## Setup
+
+<Tabs items={['pnpm', 'npm', 'yarn', 'bun']}>
+  <Tab>
+    <Snippet
+      text="pnpm add @ai-sdk/harness @ai-sdk/harness-deepagents @ai-sdk/sandbox-vercel"
+      dark
+    />
+  </Tab>
+  <Tab>
+    <Snippet
+      text="npm install @ai-sdk/harness @ai-sdk/harness-deepagents @ai-sdk/sandbox-vercel"
+      dark
+    />
+  </Tab>
+  <Tab>
+    <Snippet
+      text="yarn add @ai-sdk/harness @ai-sdk/harness-deepagents @ai-sdk/sandbox-vercel"
+      dark
+    />
+  </Tab>
+  <Tab>
+    <Snippet
+      text="bun add @ai-sdk/harness @ai-sdk/harness-deepagents @ai-sdk/sandbox-vercel"
+      dark
+    />
+  </Tab>
+</Tabs>
+
+The adapter bootstraps the bridge's Node dependencies (the `deepagents` package
+and LangChain) inside the sandbox via `pnpm` when the first session starts.
+
+## Import
+
+```ts
+import { deepAgents, createDeepAgents } from '@ai-sdk/harness-deepagents';
+```
+
+`deepAgents` is equivalent to `createDeepAgents()` with its default
+configuration.
+
+## Basic Usage
+
+```ts
+import { HarnessAgent } from '@ai-sdk/harness/agent';
+import { deepAgents } from '@ai-sdk/harness-deepagents';
+import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';
+
+const agent = new HarnessAgent({
+  harness: deepAgents,
+  sandbox: createVercelSandbox({
+    runtime: 'node24',
+    ports: [4000],
+  }),
+});
+
+const session = await agent.createSession();
+
+let exitCode = 0;
+try {
+  const result = await agent.stream({
+    session,
+    prompt: 'Analyze this codebase and suggest improvements.',
+  });
+
+  for await (const part of result.stream) {
+    if (part.type === 'text-delta') {
+      process.stdout.write(part.text);
+    }
+  }
+} catch (err) {
+  exitCode = 1;
+  console.error(err);
+} finally {
+  await session.destroy();
+  process.exit(exitCode);
+}
+```
+
+To use this agent, ensure environment variables include `VERCEL_OIDC_TOKEN` for
+Vercel Sandbox, and one of the variables listed under
+[authentication](#authentication) for the model provider.
+
+## Adapter Settings
+
+Use `createDeepAgents()` to configure the runtime:
+
+```ts
+const harness = createDeepAgents({
+  model: 'claude-sonnet-4',
+});
+```
+
+Settings:
+
+- `auth`: Anthropic or AI Gateway authentication settings.
+- `model`: model id passed to the Deep Agents (LangChain) runtime. Through AI
+  Gateway, use the `creator/model` slug (e.g. `anthropic/claude-sonnet-4-6`,
+  `google/gemini-2.5-flash`, `openai/gpt-4.1-mini`).
+- `port`: bridge port override.
+- `startupTimeoutMs`: maximum time to wait for the bridge to start.
+
+## Authentication
+
+Deep Agents always drives the Anthropic client. Non-Anthropic models reach it
+through AI Gateway's Anthropic-compatible endpoint, which translates to any
+model (Gemini, OpenAI, etc.), tool calls included. Authentication is resolved
+from the host environment and forwarded to the sandbox bridge: explicit
+Anthropic auth first, then AI Gateway credentials, then ambient Anthropic
+credentials.
+
+Supported environment variables:
+
+- `AI_GATEWAY_API_KEY`
+- `VERCEL_OIDC_TOKEN`
+- `AI_GATEWAY_BASE_URL`
+- `ANTHROPIC_API_KEY`
+- `ANTHROPIC_AUTH_TOKEN`
+- `ANTHROPIC_BASE_URL`
+
+You can also pass explicit auth settings (`anthropic` or `gateway`). To run a
+non-Anthropic model, route it through AI Gateway:
+
+```ts
+const harness = createDeepAgents({
+  model: 'google/gemini-2.5-flash',
+  auth: {
+    gateway: {
+      apiKey: process.env.AI_GATEWAY_API_KEY,
+    },
+  },
+});
+```
+
+## Sandbox
+
+Deep Agents requires a network sandbox with at least one exposed port,
+e.g. `@ai-sdk/sandbox-vercel`:
+
+```ts
+const sandbox = createVercelSandbox({
+  runtime: 'node24',
+  ports: [4000],
+});
+```
+
+## Skills
+
+Skills passed to the session are materialized as native Deep Agents skill folders
+(`<name>/SKILL.md` plus any attached files) under `$HOME/.agents/skills/` in the
+sandbox (outside the work dir, so they can't clash with cloned code), and loaded
+via Deep Agents' `skills` option — so the agent loads them on demand and skill
+file references resolve. Skills already present under `<workDir>/.agents/skills/`
+(e.g. in a cloned repo) are also discovered.
+
+## Built-in Tools
+
+The adapter exposes these Deep Agents built-ins through `agent.tools`:
+
+- `read`
+- `write`
+- `edit`
+- `bash`
+- `grep`
+- `glob`
+- `ls`
+- `task`
+- `write_todos`
+
+## Known Limitations
+
+- **Resuming a stopped session's conversation** is not supported — after
+  `session.stop()`, Deep Agents' in-memory conversation state (LangGraph
+  `MemorySaver`) is gone; only the sandbox workspace persists via its snapshot.
+  Use `session.detach()` for cross-process handoff or `session.suspendTurn()` for
+  turn continuation while keeping the live bridge running.
+- **Manual compaction** is not supported.
+
+## Related
+
+- [HarnessAgent](/docs/ai-sdk-harnesses/harness-agent)
+- [Harness tools](/docs/ai-sdk-harnesses/tools)
+- [Harness adapters](/docs/ai-sdk-harnesses/harness-adapters)

examples/ai-functions/package.json

@@ -30,6 +30,7 @@
     "@ai-sdk/harness": "workspace:*",
     "@ai-sdk/harness-claude-code": "workspace:*",
     "@ai-sdk/harness-codex": "workspace:*",
+    "@ai-sdk/harness-deepagents": "workspace:*",
     "@ai-sdk/harness-opencode": "workspace:*",
     "@ai-sdk/harness-pi": "workspace:*",
     "@ai-sdk/huggingface": "workspace:*",

examples/ai-functions/src/harness-agent/deepagents/attach.ts

@@ -0,0 +1,55 @@
+import {
+  HarnessAgent,
+  type HarnessAgentResumeSessionState,
+} from '@ai-sdk/harness/agent';
+import { deepAgents } from '@ai-sdk/harness-deepagents';
+import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';
+import { printFullStream } from '../../lib/print-full-stream';
+import { run } from '../../lib/run';
+
+// Cross-process ATTACH: detach parks the live bridge + sandbox and returns
+// coordinates; a fresh HarnessAgent reattaches and continues mid-conversation
+// (the in-memory conversation survives because the bridge stays alive).
+run(async () => {
+  const sandbox = createVercelSandbox({
+    runtime: 'node24',
+    ports: [4000],
+    timeout: 10 * 60 * 1000,
+  });
+
+  let sessionId: string;
+  let resumeState: HarnessAgentResumeSessionState;
+  {
+    const agent = new HarnessAgent({ harness: deepAgents, sandbox });
+    const session = await agent.createSession();
+    sessionId = session.sessionId;
+    console.log('--- turn 1 ---');
+    const result = await agent.stream({
+      session,
+      prompt: 'My name is Ada. Remember it.',
+    });
+    await printFullStream({ result });
+    resumeState = await session.detach();
+    console.log('[handle] live coords:', JSON.stringify(resumeState));
+  }
+
+  {
+    const agent = new HarnessAgent({ harness: deepAgents, sandbox });
+    const session = await agent.createSession({
+      sessionId,
+      resumeFrom: resumeState,
+    });
+    console.log('--- turn 2 ---');
+    if (!session.isResume) {
+      throw new Error('expected resumed session');
+    }
+    const result = await agent.stream({
+      session,
+      prompt: 'What is my name? Answer in one word.',
+    });
+    await printFullStream({ result });
+    await session.destroy();
+  }
+
+  process.exit(0);
+});

examples/ai-functions/src/harness-agent/deepagents/bash-shell.ts

@@ -0,0 +1,30 @@
+import { HarnessAgent } from '@ai-sdk/harness/agent';
+import { deepAgents } from '@ai-sdk/harness-deepagents';
+import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';
+import { printFullStream } from '../../lib/print-full-stream';
+import { run } from '../../lib/run';
+
+run(async () => {
+  const sandbox = createVercelSandbox({
+    runtime: 'node24',
+    ports: [4000],
+    timeout: 10 * 60 * 1000,
+  });
+  const agent = new HarnessAgent({ harness: deepAgents, sandbox });
+
+  let exitCode = 0;
+  const session = await agent.createSession();
+  try {
+    const result = await agent.stream({
+      session,
+      prompt: 'Run `uname -a` and tell me what kernel this sandbox is running.',
+    });
+    await printFullStream({ result });
+  } catch (err) {
+    exitCode = 1;
+    console.error('[example] failed:', err);
+  } finally {
+    await session.destroy();
+    process.exit(exitCode);
+  }
+});

examples/ai-functions/src/harness-agent/deepagents/builtin-tool-approval.ts

@@ -0,0 +1,52 @@
+import { HarnessAgent } from '@ai-sdk/harness/agent';
+import { deepAgents } from '@ai-sdk/harness-deepagents';
+import { printFullStream } from '../../lib/print-full-stream';
+import { run } from '../../lib/run';
+import {
+  createToolApprovalResponseMessages,
+  printFullStreamAndCaptureToolApproval,
+} from '../../lib/harness-tool-approval';
+import { createVercelSandbox } from '@ai-sdk/sandbox-vercel';
+
+run(async () => {
+  const sandbox = createVercelSandbox({
+    runtime: 'node24',
+    ports: [4000],
+    timeout: 10 * 60 * 1000,
+  });
+  const agent = new HarnessAgent({
+    harness: deepAgents,
+    sandbox,
+    permissionMode: 'allow-edits',
+  });
+
+  let exitCode = 0;
+  const session = await agent.createSession();
+  try {
+    const first = await agent.stream({
+      session,
+      prompt: 'Run `pwd` with the bash tool and tell me the working directory.',
+    });
+    const approval = await printFullStreamAndCaptureToolApproval({
+      result: first,
+    });
+    if (approval == null) {
+      throw new Error('Expected a built-in bash tool approval request.');
+    }
+
+    const second = await agent.stream({
+      session,
+      messages: createToolApprovalResponseMessages({
+        approval,
+        approved: true,
+      }),
+    });
+    await printFullStream({ result: second });
+  } catch (err) {
+    exitCode = 1;
+    console.error('[example] failed:', err);
+  } finally {
+    await session.destroy();
+    process.exit(exitCode);
+  }
+});