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Team"},"license":"MIT","homepage":"https://github.com/PolarGrid-AI/polargrid-monorepo#readme","keywords":["ai","ml","edge","inference","polargrid","machine-learning","typescript","llm","voice","tts","stt","whisper"],"repository":{"url":"git+https://github.com/PolarGrid-AI/polargrid-monorepo.git","type":"git","directory":"sdks/js-sdk"},"description":"JavaScript/TypeScript SDK for PolarGrid Edge AI Infrastructure with Full API Support","maintainers":[{"email":"4krutikparikh@gmail.com","name":"parikrut"},{"email":"sev@polargrid.ai","name":"polarsev"}],"readme":"# PolarGrid SDK\n\nThe official JavaScript/TypeScript SDK for PolarGrid Edge AI Infrastructure with full API support and mock data capabilities.\n\n## Features\n\n- ✅ **Text Inference**: Completions and chat completions (streaming support)\n- ✅ **Voice**: Text-to-speech and speech-to-text\n- ✅ **Model Management**: Load, unload, and check model status\n- ✅ **GPU Management**: Monitor and manage GPU resources\n- ✅ **Mock Data Mode**: Develop without backend (perfect for frontend work)\n- ✅ **Full TypeScript Support**: Complete type definitions\n- ✅ **Error Handling**: Comprehensive error types\n- ✅ **Retry Logic**: Automatic retry with exponential backoff\n\n## Installation\n\n```bash\nnpm install @polargrid/polargrid-sdk\n```\n\n## Quick Start\n\n### With Mock Data (Development)\n\nPerfect for frontend development before backend is ready:\n\n```typescript\nimport { PolarGrid } from '@polargrid/polargrid-sdk';\n\nconst client = new PolarGrid({\n  useMockData: true,  // Enable mock mode\n  debug: true,        // See what's happening\n});\n\n// All methods work with realistic mock data\nconst response = await client.chatCompletion({\n  model: 'llama-3.1-8b',\n  messages: [\n    { role: 'user', content: 'Hello!' }\n  ]\n});\n\nconsole.log(response.choices[0].message.content);\n```\n\n### With Real API (Production)\n\n```typescript\nimport { PolarGrid } from '@polargrid/polargrid-sdk';\n\nconst client = new PolarGrid({\n  apiKey: 'pg_your_api_key',\n  useMockData: false,  // Use real API\n});\n```\n\n## API Reference\n\n### Text Inference\n\n#### Chat Completions\n\n```typescript\n// Non-streaming\nconst response = await client.chatCompletion({\n  model: 'llama-3.1-8b',\n  messages: [\n    { role: 'system', content: 'You are a helpful assistant.' },\n    { role: 'user', content: 'What is quantum computing?' }\n  ],\n  maxTokens: 150,\n  temperature: 0.7,\n});\n\nconsole.log(response.choices[0].message.content);\n```\n\n```typescript\n// Streaming\nfor await (const chunk of client.chatCompletionStream({\n  model: 'llama-3.1-8b',\n  messages: [{ role: 'user', content: 'Tell me a story' }],\n})) {\n  if (chunk.choices[0].delta.content) {\n    process.stdout.write(chunk.choices[0].delta.content);\n  }\n}\n```\n\n#### Text Completions\n\n```typescript\nconst response = await client.completion({\n  prompt: 'Once upon a time',\n  model: 'llama-3.1-8b',\n  maxTokens: 100,\n  temperature: 0.8,\n});\n\nconsole.log(response.choices[0].text);\n```\n\n### Voice / Audio\n\n#### Text-to-Speech\n\n```typescript\n// Generate audio\nconst audioBuffer = await client.textToSpeech({\n  model: 'tts-1',\n  input: 'Hello from PolarGrid!',\n  voice: 'alloy',\n  responseFormat: 'mp3',\n  speed: 1.0,\n});\n\n// Save to file (Node.js)\nimport { writeFile } from 'fs/promises';\nawait writeFile('speech.mp3', Buffer.from(audioBuffer));\n```\n\n```typescript\n// Streaming TTS\nfor await (const chunk of client.textToSpeechStream({\n  model: 'tts-1',\n  input: 'Long text to convert...',\n  voice: 'nova',\n})) {\n  // Process audio chunks as they arrive\n  audioStream.write(chunk);\n}\n```\n\n#### Speech-to-Text\n\n```typescript\n// Transcribe audio\nconst file = new File([audioData], 'recording.mp3', { type: 'audio/mpeg' });\n\nconst transcription = await client.transcribe({\n  file,\n  model: 'whisper-1',\n  language: 'en',\n  responseFormat: 'json',\n});\n\nconsole.log(transcription.text);\n```\n\n```typescript\n// Verbose transcription with timestamps\nconst verbose = await client.transcribe({\n  file,\n  model: 'whisper-1',\n  responseFormat: 'verbose_json',\n}) as VerboseTranscriptionResponse;\n\nverbose.segments.forEach(segment => {\n  console.log(`[${segment.start}s - ${segment.end}s]: ${segment.text}`);\n});\n```\n\n```typescript\n// Translate to English\nconst translation = await client.translate({\n  file: spanishAudioFile,\n  model: 'whisper-1',\n  responseFormat: 'json',\n});\n\nconsole.log(translation.text);\n```\n\n### Model Management\n\n```typescript\n// List available models\nconst { data: models } = await client.listModels();\nmodels.forEach(model => {\n  console.log(`${model.id} (${model.ownedBy})`);\n});\n```\n\n```typescript\n// Load a model\nconst result = await client.loadModel({\n  modelName: 'llama-3.1-70b',\n  forceReload: false,\n});\n\nconsole.log(result.message);\n```\n\n```typescript\n// Check model status\nconst status = await client.getModelStatus();\nconsole.log('Loaded models:', status.loaded);\nconsole.log('Loading status:', status.loadingStatus);\n```\n\n```typescript\n// Unload a model\nawait client.unloadModel({ modelName: 'gpt2' });\n\n// Unload all models\nconst result = await client.unloadAllModels();\nconsole.log(`Unloaded ${result.totalUnloaded} models`);\n```\n\n### GPU Management\n\n```typescript\n// Get detailed GPU status\nconst gpuStatus = await client.getGPUStatus();\ngpuStatus.gpus.forEach(gpu => {\n  console.log(`GPU ${gpu.index}: ${gpu.name}`);\n  console.log(`  Memory: ${gpu.memory.usedGb}GB / ${gpu.memory.totalGb}GB`);\n  console.log(`  Utilization: ${gpu.utilization.gpuPercent}%`);\n  console.log(`  Temperature: ${gpu.temperatureC}°C`);\n});\n```\n\n```typescript\n// Get simplified memory info\nconst memory = await client.getGPUMemory();\nconsole.log(`Memory used: ${memory.memory[0].usedGb}GB (${memory.memory[0].percentUsed}%)`);\n```\n\n```typescript\n// Purge GPU memory\nconst purgeResult = await client.purgeGPU({ force: false });\nconsole.log(`Freed ${purgeResult.memoryFreedGb}GB`);\nconsole.log(`Unloaded models:`, purgeResult.modelsUnloaded);\nconsole.log(purgeResult.recommendation);\n```\n\n### Health Check\n\n```typescript\nconst health = await client.health();\nconsole.log(`Status: ${health.status}`);\nconsole.log(`Backend healthy: ${health.backend.healthy}`);\nconsole.log(`Models loaded: ${health.backend.info.modelsLoaded}`);\n```\n\n## Error Handling\n\n```typescript\nimport {\n  PolarGrid,\n  isPolarGridError,\n  AuthenticationError,\n  ValidationError,\n  RateLimitError,\n  ServerError,\n  NetworkError,\n} from '@polargrid/polargrid-sdk';\n\ntry {\n  const response = await client.chatCompletion({\n    model: 'llama-3.1-8b',\n    messages: [{ role: 'user', content: 'Hello' }],\n  });\n} catch (error) {\n  if (isPolarGridError(error)) {\n    console.error(`PolarGrid Error: ${error.message}`);\n    console.error(`Request ID: ${error.requestId}`);\n\n    if (error instanceof AuthenticationError) {\n      // Handle auth errors\n    } else if (error instanceof ValidationError) {\n      // Handle validation errors\n      console.error('Details:', error.details);\n    } else if (error instanceof RateLimitError) {\n      // Handle rate limits\n      console.error(`Retry after: ${error.retryAfter}s`);\n    }\n  }\n}\n```\n\n## Configuration Options\n\n```typescript\nconst client = new PolarGrid({\n  // API key (required for production, optional for mock mode)\n  apiKey: 'pg_your_api_key',\n\n  // Base URL (default: auto-route via https://autorouter.polargrid.ai)\n  baseUrl: 'https://autorouter.polargrid.ai',\n\n  // How wide the autorouter searches when auto-routing (default: 'country').\n  // 'country' — nearest edge in your own country; 'global' — nearest edge\n  // worldwide, ignoring borders. Ignored when `region` or `baseUrl` is set.\n  routingScope: 'country',\n\n  // Route to an edge that already has this model loaded, so the first\n  // request hits a warm node instead of paying a dynamic model load.\n  // Ignored when `region` or `baseUrl` is set.\n  routingModel: 'kokoro',\n\n  // Request timeout in milliseconds (default: 30000)\n  timeout: 30000,\n\n  // Maximum retry attempts (default: 3)\n  maxRetries: 3,\n\n  // Enable debug logging (default: false)\n  debug: true,\n\n  // Use mock data instead of real API (default: false)\n  useMockData: true,\n});\n```\n\n## Mock Data for Development\n\nThe SDK includes comprehensive mock data that matches the API spec exactly:\n\n### Why Use Mock Data?\n\n1. **Frontend Development**: Build UI components before backend is ready\n2. **Testing**: Predictable responses for unit tests\n3. **Demos**: Show realistic flows without production infrastructure\n4. **Development**: Faster iteration without API calls\n\n### What's Mocked?\n\n- ✅ All text inference endpoints with realistic responses\n- ✅ Voice TTS and STT with proper audio formats\n- ✅ Model management with state simulation\n- ✅ GPU metrics with realistic utilization data\n- ✅ Streaming responses (both text and audio)\n- ✅ Error scenarios (configurable)\n\n### Mock Data Examples\n\n```typescript\n// Mock mode returns realistic data instantly\nconst client = new PolarGrid({ useMockData: true });\n\n// Chat completions understand context\nconst response = await client.chatCompletion({\n  model: 'llama-3.1-8b',\n  messages: [\n    { role: 'user', content: 'What is the capital of France?' }\n  ]\n});\n// Returns: \"The capital of France is Paris...\"\n\n// Streaming works chunk by chunk\nfor await (const chunk of client.chatCompletionStream({\n  model: 'llama-3.1-8b',\n  messages: [{ role: 'user', content: 'Hello' }]\n})) {\n  // Each chunk arrives with realistic timing\n}\n\n// GPU status returns current metrics\nconst gpu = await client.getGPUStatus();\nconsole.log(gpu.gpus[0].memory.usedGb); // e.g., 45.2 GB\n```\n\n## Environment Variables\n\n```bash\n# API Key\nPOLARGRID_API_KEY=pg_your_api_key\n\n# Base URL (optional)\nNEXT_PUBLIC_INFERENCE_URL=https://autorouter.polargrid.ai\n```\n\n## TypeScript Support\n\nFull TypeScript support with comprehensive type definitions:\n\n```typescript\nimport type {\n  ChatCompletionRequest,\n  ChatCompletionResponse,\n  ModelInfo,\n  GPUStatusResponse,\n} from '@polargrid/polargrid-sdk';\n```\n\n## Best Practices\n\n### 1. Use Mock Data During Development\n\n```typescript\nconst isDevelopment = process.env.NODE_ENV === 'development';\n\nconst client = new PolarGrid({\n  apiKey: process.env.POLARGRID_API_KEY,\n  useMockData: isDevelopment,\n  debug: isDevelopment,\n});\n```\n\n### 2. Handle Errors Gracefully\n\n```typescript\ntry {\n  const response = await client.chatCompletion(request);\n  return response;\n} catch (error) {\n  if (error instanceof RateLimitError) {\n    // Wait and retry\n    await sleep(error.retryAfter * 1000);\n    return client.chatCompletion(request);\n  }\n  throw error;\n}\n```\n\n### 3. Use Streaming for Long Responses\n\n```typescript\n// Better user experience for long-form content\nfor await (const chunk of client.chatCompletionStream(request)) {\n  updateUI(chunk.choices[0].delta.content);\n}\n```\n\n## Examples\n\nSee the `/examples` directory for complete working examples:\n\n- `examples/basic-chat.ts` - Simple chat completion\n- `examples/streaming.ts` - Streaming responses\n- `examples/voice.ts` - TTS and STT examples\n- `examples/model-management.ts` - Loading and managing models\n- `examples/gpu-monitoring.ts` - GPU metrics dashboard\n\n## Development\n\n```bash\n# Install dependencies\nnpm install\n\n# Build\nnpm run build\n\n# Run tests\nnpm test\n\n# Run tests in watch mode\nnpm run test:watch\n\n# Type checking\nnpm run typecheck\n```\n\n## License\n\nMIT\n\n## Support\n\n- Documentation: https://polargrid.mintlify.app\n- Issues: https://github.com/PolarGrid-AI/polargrid-monorepo/issues\n- Email: support@polargrid.ai\n- Made with ❄️ by the PolarGrid team.\n","readmeFilename":"README.md"}