1npm install @inferencesh/sdk

1import { inference } from '@inferencesh/sdk';2 3const client = inference({ apiKey: 'inf_your_key' });4 5// Run and wait for completion (default)6const result = await client.run({7  app: 'infsh/echo',8  input: { message: 'Hello from JavaScript!' }9});10 11console.log(result.output);

1const result = await client.run(2  { app: 'infsh/flux-schnell', input: {...} },3  {4    onUpdate: (update) => {5      console.log(`Status: ${update.status}`);6      if (update.logs?.length) {7        console.log(update.logs[update.logs.length - 1]);8      }9    }10  }11);

1const task = await client.run(2  { app: 'infsh/slow-task', input: {...} },3  { wait: false }4);5console.log(`Task ID: ${task.id}`);

1import { inference } from '@inferencesh/sdk';2 3const client = inference({ apiKey: 'inf_your_key' });4 5// Use an agent you created in the workspace6const agent = client.agent('my-org/my-agent@abc123'); // Format: namespace/name@version7 8const response = await agent.sendMessage('Hello!');9console.log(response);

1import { inference, tool, string, internalTools } from '@inferencesh/sdk';2 3const client = inference({ apiKey: 'inf_your_key' });4 5// Define tools6const calculator = tool('calculator')7  .describe('Performs math operations')8  .param('expression', string('Math expression'))9  .build();10 11// Create ad-hoc agent12const agent = client.agent({13  core_app_ref: 'infsh/claude-sonnet-4@latest',14  name: 'Math Assistant',15  system_prompt: 'You help with math. Use the calculator tool.',16  tools: [calculator],17  internal_tools: internalTools().memory().build(),18});19 20const response = await agent.sendMessage('What is 42 * 17?');

1await agent.sendMessage('Explain quantum computing', {2  onMessage: (msg) => {3    if (msg.content) {4      for (const c of msg.content) {5        if (c.type === 'text' && c.text) {6          process.stdout.write(c.text);7        }8      }9    }10  },11  onToolCall: async (call) => {12    console.log(`\n[Tool: ${call.name}]`);13    // Execute tool and return result string14    const result = await executeMyTool(call.name, call.args);15    await agent.submitToolResult(call.id, result);16    17    // For widget interactions, you can also pass action + form_data:18    // await agent.submitToolResult(call.id, {19    //   action: { type: 'confirm' },20    //   form_data: { name: 'John', email: '[email protected]' }21    // });22  },23});

1// From Blob2const imageBlob = new Blob([imageBuffer], { type: 'image/png' });3const response = await agent.sendMessage('What\'s in this image?', {4  files: [imageBlob]5});6 7// From data URI8const response = await agent.sendMessage('Analyze this', {9  files: ['data:image/png;base64,iVBORw0KGgo...']10});

1// Get current chat2const chat = await agent.getChat();3console.log(`Chat ID: ${chat?.id}`);4console.log(`Messages: ${chat?.messages.length}`);5 6// Stop generation7await agent.stopChat();8 9// Start fresh10agent.reset();11 12// Cleanup streams13agent.disconnect();

1import {2  tool, appTool, agentTool, webhookTool, internalTools,3  string, number, integer, boolean, enumOf, array, object, optional4} from '@inferencesh/sdk';5 6// Client tool (runs in your code)7const search = tool('search_files')8  .describe('Search for files')9  .param('pattern', string('Glob pattern'))10  .param('recursive', optional(boolean('Search subdirs')))11  .build();12 13// App tool (calls another inference app)14const generate = appTool('generate', 'infsh/flux-schnell@latest')15  .describe('Generate an image')16  .param('prompt', string('Image description'))17  .build();18 19// Agent tool (delegates to sub-agent)20const researcher = agentTool('research', 'my-org/researcher@v1')21  .describe('Research a topic')22  .param('topic', string('Topic'))23  .build();24 25// Webhook tool (calls external API)26const notify = webhookTool('slack', 'https://hooks.slack.com/...')27  .describe('Send Slack message')28  .secret('SLACK_SECRET')29  .param('message', string('Message'))30  .build();31 32// Internal tools config33const internals = internalTools().memory().plan().build();

1import type {2  TaskDTO,3  ChatDTO,4  ChatMessageDTO,5  AgentTool,6  TaskStatusCompleted,7  TaskStatusFailed,8} from '@inferencesh/sdk';9 10// Check task status11if (result.status === TaskStatusCompleted) {12  console.log('Done!');13} else if (result.status === TaskStatusFailed) {14  console.log('Failed:', result.error);15}

1const { inference, tool, string } = require('@inferencesh/sdk');2 3const client = inference({ apiKey: 'inf_...' });4const result = await client.run({...});

1import { RequirementsNotMetException, InferenceError } from '@inferencesh/sdk';2 3try {4  const result = await client.run({ app: 'my-app', input: {...} });5} catch (e) {6  if (e instanceof RequirementsNotMetException) {7    console.log('Missing requirements:');8    for (const err of e.errors) {9      console.log(`  - ${err.type}: ${err.key}`);10    }11  } else if (e instanceof InferenceError) {12    console.log('API error:', e.message);13  }14}

1// Upload separately2const file = await client.uploadFile(buffer, {3  filename: 'image.png',4  contentType: 'image/png'5});6console.log(`Uploaded: ${file.uri}`);7 8// Use in app input9const result = await client.run({10  app: 'image-processor',11  input: { image: file.uri }12});

1curl -N -X POST \2  -H "Authorization: Bearer YOUR_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "agent": "my-org/assistant@abc123",6    "input": {"text": "Hello!", "role": "user"},7    "stream": true8  }' \9  https://api.inference.sh/agents/run

1curl -X POST \2  -H "Authorization: Bearer YOUR_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "agent": "my-org/assistant@abc123",6    "input": {"text": "Hello!", "role": "user"}7  }' \8  https://api.inference.sh/agents/run