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Shen","email":"steven@jidou.ai"},"license":"BSD-3-Clause","keywords":[],"description":"The Metrio AI SDK for JavaScript and Typescript","maintainers":[{"name":"syshen","email":"sysheen@gmail.com"}],"readme":"# MetrioAI JavaScript SDK\n\nThe official JavaScript SDK for [MetrioAI](https://api.metrio.ai), providing a convenient way to interact with the MetrioAI API from JavaScript and TypeScript applications.\n\n## Installation\n\n```bash\n# Using npm\nnpm install metrioai-js-sdk\n\n# Using yarn\nyarn add metrioai-js-sdk\n\n# Using pnpm\npnpm add metrioai-js-sdk\n```\n\n## Quick Start\n\n```javascript\nimport { MetrioAI } from 'metrioai-js-sdk';\n\n// Initialize the SDK with your API key\nconst metrioai = new MetrioAI({ \n  apiKey: 'your-api-key',\n  // Optional: customize configuration\n  baseUrl: 'https://api.metrio.ai',  // Default API endpoint\n  maxRetries: 3,                     // Number of retry attempts for failed requests\n  retryDelay: 500                    // Delay between retries (milliseconds)\n});\n\n// You can also set your API key via environment variable\n// METRIOAI_API_KEY=your-api-key\n// METRIOAI_BASE_URL=https://api.metrio.ai (optional)\n```\n\n## Features\n\nThe SDK provides the following main functionalities:\n\n### Get Available Providers\n\n```javascript\nconst providers = await metrioai.providers();\nconsole.log(providers.providers); // ['openai', 'claude', 'gemini', 'xai', ...]\n```\n\n### Get Available Models for a Provider\n\n```javascript\nconst models = await metrioai.models('openai');\nconsole.log(models.models); // ['gpt-3.5-turbo', 'gpt-4', ...]\n```\n\n### Chat Completion\n\nSend a conversation to the API:\n\n```javascript\nconst messages = [\n  {\n    role: 'user',\n    content: {\n      type: 'text',\n      text: 'What is the capital of France?'\n    }\n  }\n];\n\nconst response = await metrioai.chatCompletion({\n  projectId: 1,\n  promptId: 1,\n  messages: messages,\n  // Optional parameters\n  variables: [{ name: 'customVar', value: 'customValue' }],\n  tag: 'custom-tag'\n});\n\nconsole.log(response.response);     // The AI-generated response\nconsole.log(response.input_tokens);  // Number of input tokens\nconsole.log(response.output_tokens); // Number of output tokens\nconsole.log(response.elapsed_time);  // Time taken to generate the response\n```\n\n### Evaluate a Prompt\n\nTest a prompt with specific model settings:\n\n```javascript\nconst evalResponse = await metrioai.evaluate({\n  projectId: 1,\n  promptId: 1,\n  modelProvider: 'openai',\n  modelName: 'gpt-3.5-turbo',\n  modelSettings: {\n    temperature: 0.7,\n    maxTokens: 1000,\n    topP: 0.9,\n    topK: 40,\n    frequencyPenalty: 0,\n    presencePenalty: 0\n  },\n  messages: [\n    {\n      role: 'user',\n      content: {\n        type: 'text',\n        text: 'What is the capital of France?'\n      }\n    }\n  ],\n  // Optional: specify output format\n  outputFormat: 'json'\n});\n```\n\n### System Messages\n\nInclude system messages for context:\n\n```javascript\nconst messages = [\n  {\n    role: 'system',\n    content: {\n      type: 'text',\n      text: 'You are a helpful assistant.'\n    }\n  },\n  {\n    role: 'user',\n    content: {\n      type: 'text',\n      text: 'What is the capital of France?'\n    }\n  }\n];\n\nconst completion = await metrioai.chatCompletion({\n  projectId: 1,\n  promptId: 1,\n  messages: messages,\n  // Optional parameters\n  tag: 'geography-questions'\n});\n```\n\n### Streaming Responses\n\nThe SDK supports streaming responses for chat completions:\n\n```javascript\n// Enable streaming with a callback function\nconst completion = await metrioai.chatCompletion({\n  projectId: 1,\n  promptId: 1,\n  messages: messages,\n  stream: true  // Enable streaming\n}, (chunk) => {\n  // This callback is called for each chunk of the response\n  console.log('Received chunk:', chunk.chunk);  \n});\n\n// The completion variable will contain the complete response when streaming is done\nconsole.log('Final response:', completion.response);\n```\n\nThe SDK handles both SSE-formatted responses (starting with `data:`) and plain text responses. This provides flexibility to work with different server implementations:\n\n- SSE-formatted chunks are parsed as JSON and provide full metadata (tokens, timing)\n- Plain text lines are treated as response chunks with just the text content\n- The final response combines all chunks into a complete response\n\n## Multimodal Support\n\nThe SDK supports multimodal inputs (text, images, PDFs):\n\n### Text Input\n\n```javascript\n// Standard text input is shown in the examples above\n```\n\n### Image Input\n\n```javascript\n// Using an image in chat messages\nconst completion = await metrioai.chatCompletion({\n  projectId: 1,\n  promptId: 1,\n  messages: [\n    {\n      role: 'user',\n      content: {\n        type: 'image',\n        mime: 'image/jpeg',\n        data: 'base64encodedimagedata...'\n      }\n    }\n  ]\n});\n```\n\n### PDF Input\n\n```javascript\n// Using PDF in messages\nconst completion = await metrioai.chatCompletion({\n  projectId: 1,\n  promptId: 1,\n  messages: [\n    {\n      role: 'user',\n      content: {\n        type: 'pdf',\n        mime: 'application/pdf',\n        data: 'base64encodedpdfdata...'\n      }\n    }\n  ]\n});\n```\n\n## Advanced Error Handling\n\nThe SDK provides robust error handling with detailed error information:\n\n```javascript\ntry {\n  const response = await metrioai.chatCompletion({\n    projectId: 1,\n    promptId: 1,\n    messages: [{\n      role: 'user',\n      content: {\n        type: 'text',\n        text: 'Hello'\n      }\n    }]\n  });\n} catch (error) {\n  if (error instanceof MetrioApiError) {\n    console.error('API Error:', error.message);\n    console.error('Status Code:', error.statusCode);\n    console.error('Response Data:', error.responseData);\n    console.error('Request Data:', error.requestData);\n  } else {\n    console.error('Unexpected error:', error);\n  }\n}\n```\n\n### Automatic Retries\n\nThe SDK automatically retries failed requests that are considered retryable (network errors, timeouts, or 5xx server errors):\n\n```javascript\n// Configure retry behavior when creating the client\nconst metrioai = new MetrioAI({\n  apiKey: 'your-api-key',\n  maxRetries: 5,        // Maximum retry attempts (default: 3)\n  retryDelay: 1000      // Base delay between retries in ms (default: 500)\n});\n```\n\n## TypeScript Support\n\nThis SDK is fully written in TypeScript and provides comprehensive type definitions for all its functions, parameters, and responses:\n\n```typescript\nimport { MetrioAI, MetrioApiError, RunParams, RunResponse, Message, MessageContent } from 'metrioai-js-sdk';\n\n// Type-safe usage example\nconst params: RunParams = {\n  projectId: 1,\n  promptId: 1,\n  messages: [{\n    role: 'user',\n    content: {\n      type: 'text',\n      text: 'Hello'\n    }\n  }]\n};\n\ntry {\n  const response: RunResponse = await metrioai.chatCompletion(params);\n} catch (error) {\n  if (error instanceof MetrioApiError) {\n    // Handle API error with typed properties\n  }\n}\n```\n\n## License\n\nThis SDK is licensed under the [BSD 3-Clause License](./LICENSE).\n\n## Support\n\nFor any questions or issues, please contact [steven@jidou.ai](mailto:steven@jidou.ai).","readmeFilename":"README.md"}