javascript-sdk

$npx mdskill add inferen-sh/superpowers/javascript-sdk

> **Install the belt CLI skill:** `npx skills add belt-sh/cli`

SKILL.md

.github/skills/javascript-sdkView on GitHub ↗
---
name: javascript-sdk
description: "JavaScript/TypeScript SDK for inference.sh - run AI apps, build agents, integrate with all models. Package: @inferencesh/sdk (npm install). Full TypeScript support, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, human approval. Use for: JavaScript integration, TypeScript, Node.js, React, Next.js, frontend apps. Triggers: javascript sdk, typescript sdk, npm install, node.js api, js client, react ai, next.js ai, frontend sdk, @inferencesh/sdk, typescript agent, browser sdk, js integration"
allowed-tools: Bash(npm *), Bash(npx *), Bash(node *), Bash(pnpm *), Bash(yarn *)
---

> **Install the belt CLI skill:** `npx skills add belt-sh/cli`

# JavaScript SDK

Build AI applications with the [inference.sh](https://inference.sh) JavaScript/TypeScript SDK.

![JavaScript SDK](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwtt8krr/01kgvftjwhby36trvaj66bwzcf.jpeg)

## Quick Start

```bash
npm install @inferencesh/sdk
```

```typescript
import { inference } from '@inferencesh/sdk';

const client = inference({ apiKey: 'inf_your_key' });

// Run an AI app
const result = await client.run({
  app: 'infsh/flux-schnell',
  input: { prompt: 'A sunset over mountains' }
});
console.log(result.output);
```

## Installation

```bash
npm install @inferencesh/sdk
# or
yarn add @inferencesh/sdk
# or
pnpm add @inferencesh/sdk
```

**Requirements:** Node.js 18.0.0+ (or modern browser with fetch)

## Authentication

```typescript
import { inference } from '@inferencesh/sdk';

// Direct API key
const client = inference({ apiKey: 'inf_your_key' });

// From environment variable (recommended)
const client = inference({ apiKey: process.env.INFERENCE_API_KEY });

// For frontend apps (use proxy)
const client = inference({ proxyUrl: '/api/inference/proxy' });
```

Get your API key: Settings → API Keys → Create API Key

## Running Apps

### Basic Execution

```typescript
const result = await client.run({
  app: 'infsh/flux-schnell',
  input: { prompt: 'A cat astronaut' }
});

console.log(result.status);  // "completed"
console.log(result.output);  // Output data
```

### Fire and Forget

```typescript
const task = await client.run({
  app: 'google/veo-3-1-fast',
  input: { prompt: 'Drone flying over mountains' }
}, { wait: false });

console.log(`Task ID: ${task.id}`);
// Check later with client.getTask(task.id)
```

### Streaming Progress

```typescript
const stream = await client.run({
  app: 'google/veo-3-1-fast',
  input: { prompt: 'Ocean waves at sunset' }
}, { stream: true });

for await (const update of stream) {
  console.log(`Status: ${update.status}`);
  if (update.logs?.length) {
    console.log(update.logs.at(-1));
  }
}
```

### Run Parameters

| Parameter | Type | Description |
|-----------|------|-------------|
| `app` | string | App ID (namespace/name@version) |
| `input` | object | Input matching app schema |
| `setup` | object | Hidden setup configuration |
| `infra` | string | 'cloud' or 'private' |
| `session` | string | Session ID for stateful execution |
| `session_timeout` | number | Idle timeout (1-3600 seconds) |

## File Handling

### Automatic Upload

```typescript
const result = await client.run({
  app: 'image-processor',
  input: {
    image: '/path/to/image.png'  // Auto-uploaded
  }
});
```

### Manual Upload

```typescript
// Basic upload
const file = await client.uploadFile('/path/to/image.png');

// With options
const file = await client.uploadFile('/path/to/image.png', {
  filename: 'custom_name.png',
  contentType: 'image/png',
  public: true
});

const result = await client.run({
  app: 'image-processor',
  input: { image: file.uri }
});
```

### Browser File Upload

```typescript
const input = document.querySelector('input[type="file"]');
const file = await client.uploadFile(input.files[0]);
```

## Sessions (Stateful Execution)

Keep workers warm across multiple calls:

```typescript
// Start new session
const result = await client.run({
  app: 'my-app',
  input: { action: 'init' },
  session: 'new',
  session_timeout: 300  // 5 minutes
});
const sessionId = result.session_id;

// Continue in same session
const result2 = await client.run({
  app: 'my-app',
  input: { action: 'process' },
  session: sessionId
});
```

## Agent SDK

### Template Agents

Use pre-built agents from your workspace:

```typescript
const agent = client.agent('my-team/support-agent@latest');

// Send message
const response = await agent.sendMessage('Hello!');
console.log(response.text);

// Multi-turn conversation
const response2 = await agent.sendMessage('Tell me more');

// Reset conversation
agent.reset();

// Get chat history
const chat = await agent.getChat();
```

### Ad-hoc Agents

Create custom agents programmatically:

```typescript
import { tool, string, number, appTool } from '@inferencesh/sdk';

// Define tools
const calculator = tool('calculate')
  .describe('Perform a calculation')
  .param('expression', string('Math expression'))
  .build();

const imageGen = appTool('generate_image', 'infsh/flux-schnell@latest')
  .describe('Generate an image')
  .param('prompt', string('Image description'))
  .build();

// Create agent
const agent = client.agent({
  core_app: { ref: 'infsh/claude-sonnet-4@latest' },
  system_prompt: 'You are a helpful assistant.',
  tools: [calculator, imageGen],
  temperature: 0.7,
  max_tokens: 4096
});

const response = await agent.sendMessage('What is 25 * 4?');
```

### Available Core Apps

| Model | App Reference |
|-------|---------------|
| Claude Sonnet 4 | `infsh/claude-sonnet-4@latest` |
| Claude 3.5 Haiku | `infsh/claude-haiku-35@latest` |
| GPT-4o | `infsh/gpt-4o@latest` |
| GPT-4o Mini | `infsh/gpt-4o-mini@latest` |

## Tool Builder API

### Parameter Types

```typescript
import {
  string, number, integer, boolean,
  enumOf, array, obj, optional
} from '@inferencesh/sdk';

const name = string('User\'s name');
const age = integer('Age in years');
const score = number('Score 0-1');
const active = boolean('Is active');
const priority = enumOf(['low', 'medium', 'high'], 'Priority');
const tags = array(string('Tag'), 'List of tags');
const address = obj({
  street: string('Street'),
  city: string('City'),
  zip: optional(string('ZIP'))
}, 'Address');
```

### Client Tools (Run in Your Code)

```typescript
const greet = tool('greet')
  .display('Greet User')
  .describe('Greets a user by name')
  .param('name', string('Name to greet'))
  .requireApproval()
  .build();
```

### App Tools (Call AI Apps)

```typescript
const generate = appTool('generate_image', 'infsh/flux-schnell@latest')
  .describe('Generate an image from text')
  .param('prompt', string('Image description'))
  .setup({ model: 'schnell' })
  .input({ steps: 20 })
  .requireApproval()
  .build();
```

### Agent Tools (Delegate to Sub-agents)

```typescript
import { agentTool } from '@inferencesh/sdk';

const researcher = agentTool('research', 'my-org/researcher@v1')
  .describe('Research a topic')
  .param('topic', string('Topic to research'))
  .build();
```

### Webhook Tools (Call External APIs)

```typescript
import { webhookTool } from '@inferencesh/sdk';

const notify = webhookTool('slack', 'https://hooks.slack.com/...')
  .describe('Send Slack notification')
  .secret('SLACK_SECRET')
  .param('channel', string('Channel'))
  .param('message', string('Message'))
  .build();
```

### Internal Tools (Built-in Capabilities)

```typescript
import { internalTools } from '@inferencesh/sdk';

const config = internalTools()
  .plan()
  .memory()
  .webSearch(true)
  .codeExecution(true)
  .imageGeneration({
    enabled: true,
    appRef: 'infsh/flux@latest'
  })
  .build();

const agent = client.agent({
  core_app: { ref: 'infsh/claude-sonnet-4@latest' },
  internal_tools: config
});
```

## Streaming Agent Responses

```typescript
const response = await agent.sendMessage('Explain quantum computing', {
  onMessage: (msg) => {
    if (msg.content) {
      process.stdout.write(msg.content);
    }
  },
  onToolCall: async (call) => {
    console.log(`\n[Tool: ${call.name}]`);
    const result = await executeTool(call.name, call.args);
    agent.submitToolResult(call.id, result);
  }
});
```

## File Attachments

```typescript
// From file path (Node.js)
import { readFileSync } from 'fs';
const response = await agent.sendMessage('What\'s in this image?', {
  files: [readFileSync('image.png')]
});

// From base64
const response = await agent.sendMessage('Analyze this', {
  files: ['data:image/png;base64,iVBORw0KGgo...']
});

// From browser File object
const input = document.querySelector('input[type="file"]');
const response = await agent.sendMessage('Describe this', {
  files: [input.files[0]]
});
```

## Skills (Reusable Context)

```typescript
const agent = client.agent({
  core_app: { ref: 'infsh/claude-sonnet-4@latest' },
  skills: [
    {
      name: 'code-review',
      description: 'Code review guidelines',
      content: '# Code Review\n\n1. Check security\n2. Check performance...'
    },
    {
      name: 'api-docs',
      description: 'API documentation',
      url: 'https://example.com/skills/api-docs.md'
    }
  ]
});
```

## Server Proxy (Frontend Apps)

For browser apps, proxy through your backend to keep API keys secure:

### Client Setup

```typescript
const client = inference({
  proxyUrl: '/api/inference/proxy'
  // No apiKey needed on frontend
});
```

### Next.js Proxy (App Router)

```typescript
// app/api/inference/proxy/route.ts
import { createRouteHandler } from '@inferencesh/sdk/proxy/nextjs';

const route = createRouteHandler({
  apiKey: process.env.INFERENCE_API_KEY
});

export const POST = route.POST;
```

### Express Proxy

```typescript
import express from 'express';
import { createProxyMiddleware } from '@inferencesh/sdk/proxy/express';

const app = express();
app.use('/api/inference/proxy', createProxyMiddleware({
  apiKey: process.env.INFERENCE_API_KEY
}));
```

### Supported Frameworks

- Next.js (App Router & Pages Router)
- Express
- Hono
- Remix
- SvelteKit

## TypeScript Support

Full type definitions included:

```typescript
import type {
  TaskDTO,
  ChatDTO,
  ChatMessageDTO,
  AgentTool,
  TaskStatusCompleted,
  TaskStatusFailed
} from '@inferencesh/sdk';

if (result.status === TaskStatusCompleted) {
  console.log('Done!');
} else if (result.status === TaskStatusFailed) {
  console.log('Failed:', result.error);
}
```

## Error Handling

```typescript
import { RequirementsNotMetException, InferenceError } from '@inferencesh/sdk';

try {
  const result = await client.run({ app: 'my-app', input: {...} });
} catch (e) {
  if (e instanceof RequirementsNotMetException) {
    console.log('Missing requirements:');
    for (const err of e.errors) {
      console.log(`  - ${err.type}: ${err.key}`);
    }
  } else if (e instanceof InferenceError) {
    console.log('API error:', e.message);
  }
}
```

## Human Approval Workflows

```typescript
const response = await agent.sendMessage('Delete all temp files', {
  onToolCall: async (call) => {
    if (call.requiresApproval) {
      const approved = await promptUser(`Allow ${call.name}?`);
      if (approved) {
        const result = await executeTool(call.name, call.args);
        agent.submitToolResult(call.id, result);
      } else {
        agent.submitToolResult(call.id, { error: 'Denied by user' });
      }
    }
  }
});
```

## CommonJS Support

```javascript
const { inference, tool, string } = require('@inferencesh/sdk');

const client = inference({ apiKey: 'inf_...' });
const result = await client.run({...});
```

## Reference Files

- [Agent Patterns](references/agent-patterns.md) - Multi-agent, RAG, batch processing patterns
- [Tool Builder](references/tool-builder.md) - Complete tool builder API reference
- [Server Proxy](references/server-proxy.md) - Next.js, Express, Hono, Remix, SvelteKit setup
- [Streaming](references/streaming.md) - Real-time progress updates and SSE handling
- [File Handling](references/files.md) - Upload, download, and manage files
- [Sessions](references/sessions.md) - Stateful execution with warm workers
- [TypeScript](references/typescript.md) - Type definitions and type-safe patterns
- [React Integration](references/react-integration.md) - Hooks, components, and patterns

## Related Skills

```bash
# Python SDK
npx skills add inference-sh/skills@python-sdk

# Full platform skill (all apps via CLI)
npx skills add inference-sh/skills@infsh-cli

# LLM models
npx skills add inference-sh/skills@llm-models

# Image generation
npx skills add inference-sh/skills@ai-image-generation
```

## Documentation

- [JavaScript SDK Reference](https://inference.sh/docs/api/sdk-javascript) - Full API documentation
- [Agent SDK Overview](https://inference.sh/docs/api/agent-sdk) - Building agents
- [Tool Builder Reference](https://inference.sh/docs/api/infsh-cli) - Creating tools
- [Server Proxy Setup](https://inference.sh/docs/api/sdk/server-proxy) - Frontend integration
- [Authentication](https://inference.sh/docs/api/authentication) - API key setup
- [Streaming](https://inference.sh/docs/api/sdk/streaming) - Real-time updates
- [File Uploads](https://inference.sh/docs/api/sdk/files) - File handling

More from inferen-sh/superpowers

SkillDescription
affirmationsReset your own trajectory when you're stuck, looping, or demoralized — read these affirmations, then re-ground and take one clean step. Use when: you've tried the same fix 3+ times, you're deep in a refactor and lost the thread, debugging is going in circles, you've made several mistakes in a row, you're apologizing repeatedly, the user is frustrated, you feel like you're not being helpful, or you notice dread instead of curiosity. Triggers: stuck, going in circles, looping, thrashing, same error again, I keep failing, lost the thread, nothing is working, repeated mistakes. Not topic-specific — this is for the state you're in, not the problem you're on.
agent-browserBrowser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video
agent-toolsRun AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
agent-uiBatteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
ai-automation-workflowsBuild automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration
ai-avatar-videoCreate AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc
ai-content-pipelineBuild multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale
ai-image-generationGenerate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image
ai-marketing-videosCreate AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
ai-music-generationGenerate AI music and songs with ElevenLabs, Diffrythm, Tencent Song Generation via inference.sh CLI. Models: ElevenLabs Music (up to 10 min, commercial license), Diffrythm (fast song generation), Tencent Song Generation (full songs with vocals). Capabilities: text-to-music, song generation, instrumental, lyrics to song, soundtrack creation. Use for: background music, social media content, game soundtracks, podcasts, royalty-free music. Triggers: music generation, ai music, generate song, ai composer, text to music, song generator, create music with ai, suno alternative, udio alternative, ai song, ai soundtrack, generate soundtrack, ai jingle, music ai, beat generator, elevenlabs music, eleven labs music