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pure fetch API, minimal dependencies (zod), WebStreams, memory optimization for Cloudflare Workers and edge computing environments","maintainers":[{"name":"aid-on","email":"hiromi.motodera@aid-on.org"}],"readme":"# @aid-on/unillm\n\n[![npm version](https://img.shields.io/npm/v/@aid-on/unillm.svg)](https://www.npmjs.com/package/@aid-on/unillm)\n[![TypeScript](https://img.shields.io/badge/TypeScript-5.7-blue.svg)](https://www.typescriptlang.org/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\n**unillm** is a unified LLM interface for edge computing. It provides a consistent, type-safe API across multiple LLM providers with minimal dependencies and optimized memory usage for edge environments.\n\n[日本語](./README.ja.md) | English\n\n## Features\n\n- 🚀 **Edge-First**: ~50KB bundle size, ~10ms cold start, optimized for edge runtimes\n- 🔄 **Unified Interface**: Single API for Anthropic, OpenAI, Groq, Gemini, Cloudflare, and more\n- 🌊 **Streaming Native**: Built on Web Streams API with nagare integration\n- 🎯 **Type-Safe**: Full TypeScript support with Zod schema validation\n- 📦 **Minimal Dependencies**: Only Zod (~11KB) required\n- ⚡ **Memory Optimized**: Automatic chunking and backpressure handling\n\n## Installation\n\n```bash\nnpm install @aid-on/unillm\n```\n\n```bash\nyarn add @aid-on/unillm\n```\n\n```bash\npnpm add @aid-on/unillm\n```\n\n## Quick Start\n\n```typescript\nimport { unillm } from \"@aid-on/unillm\";\n\n// Fluent API with type safety\nconst response = await unillm()\n  .model(\"openai:gpt-4o-mini\")\n  .credentials({ openaiApiKey: process.env.OPENAI_API_KEY })\n  .temperature(0.7)\n  .generate(\"Explain quantum computing in simple terms\");\n\nconsole.log(response.text);\n```\n\n## Streaming with nagare\n\nunillm returns **@aid-on/nagare** `Stream<T>` for reactive stream processing:\n\n```typescript\nimport { unillm } from \"@aid-on/unillm\";\nimport type { Stream } from \"@aid-on/nagare\";\n\nconst stream: Stream<string> = await unillm()\n  .model(\"groq:llama-3.3-70b-versatile\")\n  .credentials({ groqApiKey: \"...\" })\n  .stream(\"Write a story about AI\");\n\n// Use nagare's reactive operators\nconst enhanced = stream\n  .map(chunk => chunk.trim())\n  .filter(chunk => chunk.length > 0)\n  .throttle(16)  // ~60fps for UI updates\n  .tap(chunk => console.log(chunk))\n  .toSSE();      // Convert to Server-Sent Events\n```\n\n## Structured Output\n\nGenerate type-safe structured data with Zod schemas:\n\n```typescript\nimport { z } from \"zod\";\n\nconst PersonSchema = z.object({\n  name: z.string(),\n  age: z.number(),\n  skills: z.array(z.string())\n});\n\nconst result = await unillm()\n  .model(\"groq:llama-3.1-8b-instant\")\n  .credentials({ groqApiKey: \"...\" })\n  .schema(PersonSchema)\n  .generate(\"Generate a software engineer profile\");\n\n// Type-safe access\nconsole.log(result.object.name);     // string\nconsole.log(result.object.skills);   // string[]\n```\n\n## Provider Shortcuts\n\nUltra-concise syntax for common models:\n\n```typescript\nimport { anthropic, openai, groq, gemini, cloudflare } from \"@aid-on/unillm\";\n\n// One-liners for quick prototyping\nawait anthropic.sonnet(\"sk-ant-...\").generate(\"Hello\");\nawait openai.mini(\"sk-...\").generate(\"Hello\");\nawait groq.instant(\"gsk_...\").generate(\"Hello\");\nawait gemini.flash(\"AIza...\").generate(\"Hello\");\nawait cloudflare.llama({ accountId: \"...\", apiToken: \"...\" }).generate(\"Hello\");\n```\n\n## Supported Models (48 Models)\n\n### Anthropic (8 models) - v0.4.0\n- `anthropic:claude-opus-4-5-20251101` - Claude Opus 4.5 (Most Intelligent)\n- `anthropic:claude-haiku-4-5-20251001` - Claude Haiku 4.5 (Ultra Fast)\n- `anthropic:claude-sonnet-4-5-20250929` - Claude Sonnet 4.5 (Best for Coding)\n- `anthropic:claude-opus-4-1-20250805` - Claude Opus 4.1\n- `anthropic:claude-opus-4-20250514` - Claude Opus 4\n- `anthropic:claude-sonnet-4-20250514` - Claude Sonnet 4\n- `anthropic:claude-3-5-haiku-20241022` - Claude 3.5 Haiku\n- `anthropic:claude-3-haiku-20240307` - Claude 3 Haiku\n\n### OpenAI (9 models)\n- `openai:gpt-4o` - GPT-4o (Latest, fastest GPT-4)\n- `openai:gpt-4o-mini` - GPT-4o Mini (Cost-effective)\n- `openai:gpt-4o-2024-11-20` - GPT-4o November snapshot\n- `openai:gpt-4o-2024-08-06` - GPT-4o August snapshot\n- `openai:gpt-4-turbo` - GPT-4 Turbo (High capability)\n- `openai:gpt-4-turbo-preview` - GPT-4 Turbo Preview\n- `openai:gpt-4` - GPT-4 (Original)\n- `openai:gpt-3.5-turbo` - GPT-3.5 Turbo (Fast & cheap)\n- `openai:gpt-3.5-turbo-0125` - GPT-3.5 Turbo Latest\n\n### Groq (7 models)\n- `groq:llama-3.3-70b-versatile` - Llama 3.3 70B Versatile\n- `groq:llama-3.1-8b-instant` - Llama 3.1 8B Instant\n- `groq:meta-llama/llama-guard-4-12b` - Llama Guard 4 12B\n- `groq:openai/gpt-oss-120b` - GPT-OSS 120B\n- `groq:openai/gpt-oss-20b` - GPT-OSS 20B\n- `groq:groq/compound` - Groq Compound\n- `groq:groq/compound-mini` - Groq Compound Mini\n\n### Google Gemini (8 models)\n- `gemini:gemini-3-pro-preview` - Gemini 3 Pro Preview\n- `gemini:gemini-3-flash-preview` - Gemini 3 Flash Preview\n- `gemini:gemini-2.5-pro` - Gemini 2.5 Pro\n- `gemini:gemini-2.5-flash` - Gemini 2.5 Flash\n- `gemini:gemini-2.0-flash` - Gemini 2.0 Flash\n- `gemini:gemini-2.0-flash-lite` - Gemini 2.0 Flash Lite\n- `gemini:gemini-1.5-pro-002` - Gemini 1.5 Pro 002\n- `gemini:gemini-1.5-flash-002` - Gemini 1.5 Flash 002\n\n### Cloudflare Workers AI (13 models)\n- `cloudflare:@cf/meta/llama-4-scout-17b-16e-instruct` - Llama 4 Scout\n- `cloudflare:@cf/meta/llama-3.3-70b-instruct-fp8-fast` - Llama 3.3 70B FP8\n- `cloudflare:@cf/meta/llama-3.1-70b-instruct` - Llama 3.1 70B\n- `cloudflare:@cf/meta/llama-3.1-8b-instruct-fast` - Llama 3.1 8B Fast\n- `cloudflare:@cf/meta/llama-3.1-8b-instruct` - Llama 3.1 8B\n- `cloudflare:@cf/openai/gpt-oss-120b` - GPT-OSS 120B\n- `cloudflare:@cf/openai/gpt-oss-20b` - GPT-OSS 20B\n- `cloudflare:@cf/ibm/granite-4.0-h-micro` - IBM Granite 4.0\n- `cloudflare:@cf/mistralai/mistral-small-3.1-24b-instruct` - Mistral Small 3.1\n- `cloudflare:@cf/mistralai/mistral-7b-instruct-v0.2` - Mistral 7B\n- `cloudflare:@cf/google/gemma-3-12b-it` - Gemma 3 12B\n- `cloudflare:@cf/qwen/qwq-32b` - QwQ 32B\n- `cloudflare:@cf/qwen/qwen2.5-coder-32b-instruct` - Qwen 2.5 Coder\n\n## Advanced Usage\n\n### Fluent Builder Pattern\n\n```typescript\nconst builder = unillm()\n  .model(\"groq:llama-3.3-70b-versatile\")\n  .credentials({ groqApiKey: \"...\" })\n  .temperature(0.7)\n  .maxTokens(1000)\n  .topP(0.9)\n  .system(\"You are a helpful assistant\")\n  .messages([\n    { role: \"user\", content: \"Previous question...\" },\n    { role: \"assistant\", content: \"Previous answer...\" }\n  ]);\n\n// Reusable configuration\nconst response1 = await builder.generate(\"New question\");\nconst response2 = await builder.stream(\"Another question\");\n```\n\n### Memory Optimization\n\nAutomatic memory management for edge environments:\n\n```typescript\nimport { createMemoryOptimizedStream } from \"@aid-on/unillm\";\n\nconst stream = await createMemoryOptimizedStream(\n  largeResponse,\n  { \n    maxMemory: 1024 * 1024,  // 1MB limit\n    chunkSize: 512           // Optimal chunk size\n  }\n);\n```\n\n### Error Handling\n\n```typescript\nimport { UnillmError, RateLimitError } from \"@aid-on/unillm\";\n\ntry {\n  const response = await unillm()\n    .model(\"groq:llama-3.3-70b-versatile\")\n    .credentials({ groqApiKey: \"...\" })\n    .generate(\"Hello\");\n} catch (error) {\n  if (error instanceof RateLimitError) {\n    console.log(`Rate limited. Retry after ${error.retryAfter}ms`);\n  } else if (error instanceof UnillmError) {\n    console.log(`LLM error: ${error.message}`);\n  }\n}\n```\n\n## Integration Examples\n\n### With React\n\n```typescript\nimport { useState } from \"react\";\nimport { unillm } from \"@aid-on/unillm\";\n\nexport default function ChatComponent() {\n  const [response, setResponse] = useState(\"\");\n  const [loading, setLoading] = useState(false);\n  \n  const handleGenerate = async () => {\n    setLoading(true);\n    const stream = await unillm()\n      .model(\"groq:llama-3.1-8b-instant\")\n      .credentials({ groqApiKey: import.meta.env.VITE_GROQ_API_KEY })\n      .stream(\"Write a haiku\");\n    \n    for await (const chunk of stream) {\n      setResponse(prev => prev + chunk);\n    }\n    setLoading(false);\n  };\n  \n  return (\n    <div>\n      <button onClick={handleGenerate} disabled={loading}>\n        {loading ? \"Generating...\" : \"Generate\"}\n      </button>\n      <p>{response}</p>\n    </div>\n  );\n}\n```\n\n### With Cloudflare Workers\n\n```typescript\nexport default {\n  async fetch(request: Request, env: Env) {\n    const stream = await unillm()\n      .model(\"cloudflare:@cf/meta/llama-3.1-8b-instruct\")\n      .credentials({\n        accountId: env.CF_ACCOUNT_ID,\n        apiToken: env.CF_API_TOKEN\n      })\n      .stream(\"Hello from the edge!\");\n    \n    return new Response(stream.toReadableStream(), {\n      headers: { \"Content-Type\": \"text/event-stream\" }\n    });\n  }\n};\n```\n\n## API Reference\n\n### unillm() Builder Methods\n\n| Method | Description | Example |\n|--------|-------------|---------|\n| `model(id)` | Set the model ID | `model(\"groq:llama-3.3-70b-versatile\")` |\n| `credentials(creds)` | Set API credentials | `credentials({ groqApiKey: \"...\" })` |\n| `temperature(n)` | Set temperature (0-1) | `temperature(0.7)` |\n| `maxTokens(n)` | Set max tokens | `maxTokens(1000)` |\n| `topP(n)` | Set top-p sampling | `topP(0.9)` |\n| `schema(zod)` | Set output schema | `schema(PersonSchema)` |\n| `system(text)` | Set system prompt | `system(\"You are...\")` |\n| `messages(msgs)` | Set message history | `messages([...])` |\n| `generate(prompt)` | Generate response | `await generate(\"Hello\")` |\n| `stream(prompt)` | Stream response | `await stream(\"Hello\")` |\n\n## License\n\nMIT","readmeFilename":"README.md"}