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Karakas"},"license":"ISC","homepage":"https://github.com/ekremarmagankarakas/LLMrest#readme","keywords":["llmrest","llm","openai","claude","gemini","perplexity"],"repository":{"type":"git","url":"git+https://github.com/ekremarmagankarakas/LLMrest.git"},"description":"Send requests to multiple LLMs concurrently","maintainers":[{"name":"armagank","email":"ekremarmagankarakas@gmail.com"}],"readme":"# LLMrest\n\nA unified TypeScript library for querying multiple LLM providers concurrently — OpenAI, Anthropic Claude, Google Gemini, and Perplexity — from a single client.\n\n[![npm version](https://img.shields.io/npm/v/@armagank/llmrest.svg)](https://www.npmjs.com/package/@armagank/llmrest)\n[![License: ISC](https://img.shields.io/badge/License-ISC-blue.svg)](https://opensource.org/licenses/ISC)\n\n## Features\n\n- **Concurrent requests** — fan out to multiple models in parallel, results arrive as each completes\n- **Unified interface** — one client, four providers\n- **Per-model messages** — send different prompts to different models in a single call\n- **Streaming callbacks** — responses delivered via `onResponse` as each model finishes\n- **Content moderation** — optional OpenAI moderation check before sending\n- **Input size validation** — optional byte-limit enforcement before sending\n- **Full TypeScript** — complete type definitions included\n- **Extensible** — register custom providers via `ModelRegistry`\n\n## Requirements\n\n- Node.js >= 18.0.0\n\n## Installation\n\n```bash\nnpm install @armagank/llmrest\n```\n\n## Quick Start\n\n```typescript\nimport { LLMClient } from '@armagank/llmrest';\n\nconst client = new LLMClient({\n apiKeys: {\n openai: process.env.OPENAI_API_KEY,\n claude: process.env.ANTHROPIC_API_KEY,\n gemini: process.env.GEMINI_API_KEY,\n perplexity: process.env.PERPLEXITY_API_KEY,\n },\n});\n\n// CommonJS\nconst { createAIClient } = require('@armagank/llmrest');\nconst client = createAIClient({ apiKeys: { ... } });\n```\n\nYou only need to provide API keys for the providers you intend to use.\n\n## API\n\n### `createChat(params)`\n\nSend the same messages to multiple models concurrently.\n\n```typescript\nconst result = await client.createChat({\n models: ['gpt-4o', 'claude-sonnet-4-6', 'gemini-2.5-flash'],\n messages: [\n { role: 'system', content: 'You are a helpful assistant.' },\n { role: 'user', content: 'What is the capital of France?' },\n ],\n maxInput: 100_000, // bytes (optional)\n maxOutput: 1_000, // tokens (optional)\n moderationEnabled: false,\n});\n\n// result: Record\nconsole.log(result['gpt-4o']); // \"The capital of France is Paris.\"\nconsole.log(result['claude-sonnet-4-6']); // \"Paris is the capital of France.\"\n```\n\n| Parameter | Type | Required | Description |\n|---|---|---|---|\n| `models` | `string[]` | Yes | Model IDs to query |\n| `messages` | `Message[]` | Yes | Chat messages |\n| `maxInput` | `number` | No | Max input size in bytes |\n| `maxOutput` | `number` | No | Max output tokens |\n| `moderationEnabled` | `boolean` | No | Run OpenAI content moderation first |\n\n### `createChatMessages(params)`\n\nSend different messages to different models in one call.\n\n```typescript\nconst result = await client.createChatMessages({\n models: ['gpt-4o', 'claude-sonnet-4-6'],\n messages: {\n 'gpt-4o': [\n { role: 'system', content: 'You are a coding assistant.' },\n { role: 'user', content: 'Write a TypeScript hello world.' },\n ],\n 'claude-sonnet-4-6': [\n { role: 'system', content: 'You are a poet.' },\n { role: 'user', content: 'Write a haiku about TypeScript.' },\n ],\n },\n maxOutput: 500,\n});\n```\n\n### `createChatStreaming(params)`\n\nDispatch requests concurrently; receive each result via callback as it arrives rather than waiting for all to finish.\n\n```typescript\nawait client.createChatStreaming({\n models: ['gpt-4o', 'claude-sonnet-4-6', 'gemini-2.5-flash'],\n messages: [{ role: 'user', content: 'Tell me a joke.' }],\n maxOutput: 300,\n onResponse: (response) => {\n if (response.status === 'success') {\n console.log(`[${response.model}] ${response.data}`);\n } else {\n console.error(`[${response.model}] Error: ${response.error}`);\n }\n },\n});\n```\n\n`onResponse` receives a `StreamingResponse`:\n\n```typescript\ninterface StreamingResponse {\n model: string;\n status: 'success' | 'error';\n data?: string; // present on success\n error?: string; // present on error\n timestamp: string;\n}\n```\n\nModel-specific messages also work with streaming:\n\n```typescript\nawait client.createChatStreaming({\n models: ['gpt-4o', 'claude-sonnet-4-6'],\n messages: {\n 'gpt-4o': [{ role: 'user', content: 'Explain recursion.' }],\n 'claude-sonnet-4-6': [{ role: 'user', content: 'Explain iteration.' }],\n },\n onResponse: (r) => console.log(r),\n});\n```\n\n## Supported Models\n\n### OpenAI\n`gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5.1`, `gpt-5.2`, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo`, `o1`, `o1-mini`, `o3`, `o3-mini`, `o4-mini`\n\n### Anthropic Claude\n`claude-opus-4-7`, `claude-sonnet-4-6`, `claude-haiku-4-5`, `claude-haiku-4-5-20251001`, `claude-opus-4-6`, `claude-sonnet-4-5`, `claude-opus-4-5`, `claude-opus-4-1`\n\n### Google Gemini\n`gemini-2.5-pro`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-3.1-flash-lite`, `gemini-3-flash-preview`\n\n### Perplexity\n`sonar`, `sonar-pro`, `sonar-reasoning-pro`, `sonar-deep-research`\n\n## Custom Providers\n\nExtend `BaseProvider` to add any model not in the built-in list:\n\n```typescript\nimport { BaseProvider, ModelRegistry } from '@armagank/llmrest';\nimport type { ProviderChatOptions } from '@armagank/llmrest';\n\nclass MyProvider extends BaseProvider {\n async chat({ messages, maxOutput }: ProviderChatOptions): Promise {\n // call your API here\n return 'response text';\n }\n}\n\nconst registry = new ModelRegistry();\nregistry.registerMany(['my-model-v1', 'my-model-v2'], new MyProvider());\n```\n\n## Error Handling\n\nFailed models never throw — they return an error object in the result map. Only pre-flight errors (bad config, moderation rejection, input too large) throw.\n\n```typescript\nconst result = await client.createChat({\n models: ['gpt-4o', 'claude-sonnet-4-6'],\n messages: [{ role: 'user', content: 'Hello' }],\n});\n\nfor (const [model, response] of Object.entries(result)) {\n if (typeof response === 'string') {\n console.log(`${model}: ${response}`);\n } else {\n console.error(`${model} failed: ${response.error}`);\n }\n}\n```\n\n## License\n\nISC\n","readmeFilename":"README.md"}