Juergen Kunz a51b002141
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v2.0.0
2026-03-05 19:37:29 +00:00
2024-03-30 12:42:44 +01:00
2024-03-30 12:42:44 +01:00
2026-03-05 19:37:29 +00:00
2024-04-25 10:49:07 +02:00

@push.rocks/smartai

A unified provider registry for the Vercel AI SDK 🧠

npm version TypeScript License: MIT

SmartAI gives you a single getModel() function that returns a standard LanguageModelV3 for any supported provider — Anthropic, OpenAI, Google, Groq, Mistral, XAI, Perplexity, or Ollama. Use the returned model with the Vercel AI SDK's generateText(), streamText(), and tool ecosystem. Specialized capabilities like vision, audio, image generation, document analysis, and web research are available as dedicated subpath imports.

Issue Reporting and Security

For reporting bugs, issues, or security vulnerabilities, please visit community.foss.global/. This is the central community hub for all issue reporting. Developers who sign and comply with our contribution agreement and go through identification can also get a code.foss.global/ account to submit Pull Requests directly.

🎯 Why SmartAI?

  • 🔌 One function, eight providersgetModel() returns a standard LanguageModelV3. Switch providers by changing a string.
  • 🧱 Built on Vercel AI SDK — Uses ai v6 under the hood. Your model works with generateText(), streamText(), tool calling, structured output, and everything else in the AI SDK ecosystem.
  • 🏠 Custom Ollama provider — A full LanguageModelV3 implementation for Ollama with support for think mode, num_ctx, auto-tuned temperature for Qwen models, and native tool calling.
  • 💰 Anthropic prompt caching — Automatic cacheControl middleware reduces cost and latency on repeated calls. Enabled by default, opt out with promptCaching: false.
  • 📦 Modular subpath exports — Vision, audio, image, document, and research capabilities ship as separate imports. Only import what you need.
  • Zero lock-in — Your code uses standard AI SDK types. Swap providers without touching application logic.

📦 Installation

pnpm install @push.rocks/smartai

🚀 Quick Start

import { getModel, generateText, streamText } from '@push.rocks/smartai';

// Get a model for any provider
const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

// Use it with the standard AI SDK functions
const result = await generateText({
  model,
  prompt: 'Explain quantum computing in simple terms.',
});

console.log(result.text);

That's it. Change provider to 'openai' and model to 'gpt-4o' and the rest of your code stays exactly the same.

🔧 Core API

getModel(options): LanguageModelV3

The primary export. Returns a standard LanguageModelV3 you can use with any AI SDK function.

import { getModel } from '@push.rocks/smartai';
import type { ISmartAiOptions } from '@push.rocks/smartai';

const options: ISmartAiOptions = {
  provider: 'anthropic',  // 'anthropic' | 'openai' | 'google' | 'groq' | 'mistral' | 'xai' | 'perplexity' | 'ollama'
  model: 'claude-sonnet-4-5-20250929',
  apiKey: 'sk-ant-...',
  // Anthropic-only: prompt caching (default: true)
  promptCaching: true,
  // Ollama-only: base URL (default: http://localhost:11434)
  baseUrl: 'http://localhost:11434',
  // Ollama-only: model runtime options
  ollamaOptions: { think: true, num_ctx: 4096 },
};

const model = getModel(options);

Re-exported AI SDK Functions

SmartAI re-exports the most commonly used functions from ai for convenience:

import {
  getModel,
  generateText,
  streamText,
  tool,
  jsonSchema,
} from '@push.rocks/smartai';

import type {
  ModelMessage,
  ToolSet,
  StreamTextResult,
  LanguageModelV3,
} from '@push.rocks/smartai';

🤖 Supported Providers

Provider Package Example Models
Anthropic @ai-sdk/anthropic claude-sonnet-4-5-20250929, claude-opus-4-5-20250929
OpenAI @ai-sdk/openai gpt-4o, gpt-4o-mini, o3-mini
Google @ai-sdk/google gemini-2.0-flash, gemini-2.5-pro
Groq @ai-sdk/groq llama-3.3-70b-versatile, mixtral-8x7b-32768
Mistral @ai-sdk/mistral mistral-large-latest, mistral-small-latest
XAI @ai-sdk/xai grok-3, grok-3-mini
Perplexity @ai-sdk/perplexity sonar-pro, sonar
Ollama Custom LanguageModelV3 qwen3:8b, llama3:8b, deepseek-r1

💬 Text Generation

Generate Text

import { getModel, generateText } from '@push.rocks/smartai';

const model = getModel({
  provider: 'openai',
  model: 'gpt-4o',
  apiKey: process.env.OPENAI_TOKEN,
});

const result = await generateText({
  model,
  system: 'You are a helpful assistant.',
  prompt: 'What is 2 + 2?',
});

console.log(result.text); // "4"

Stream Text

import { getModel, streamText } from '@push.rocks/smartai';

const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

const result = await streamText({
  model,
  prompt: 'Count from 1 to 10.',
});

for await (const chunk of result.textStream) {
  process.stdout.write(chunk);
}

Tool Calling

import { getModel, generateText, tool, jsonSchema } from '@push.rocks/smartai';

const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

const result = await generateText({
  model,
  prompt: 'What is the weather in London?',
  tools: {
    getWeather: tool({
      description: 'Get weather for a location',
      parameters: jsonSchema({
        type: 'object',
        properties: {
          location: { type: 'string' },
        },
        required: ['location'],
      }),
      execute: async ({ location }) => {
        return { temperature: 18, condition: 'cloudy' };
      },
    }),
  },
});

🏠 Ollama (Local Models)

The custom Ollama provider implements LanguageModelV3 directly, calling Ollama's native /api/chat endpoint. This gives you features that generic OpenAI-compatible wrappers miss:

import { getModel, generateText } from '@push.rocks/smartai';

const model = getModel({
  provider: 'ollama',
  model: 'qwen3:8b',
  baseUrl: 'http://localhost:11434', // default
  ollamaOptions: {
    think: true,      // Enable thinking/reasoning mode
    num_ctx: 8192,     // Context window size
    temperature: 0.7,  // Override default (Qwen models auto-default to 0.55)
  },
});

const result = await generateText({
  model,
  prompt: 'Solve this step by step: what is 15% of 340?',
});

console.log(result.text);

Ollama Features

  • think mode — Enables reasoning for models that support it (Qwen3, QwQ, DeepSeek-R1). The think parameter is sent at the top level of the request body as required by the Ollama API.
  • Auto-tuned temperature — Qwen models automatically get temperature: 0.55 when no explicit temperature is set, matching the recommended inference setting.
  • Native tool calling — Full tool call support via Ollama's native format (not shimmed through OpenAI-compatible endpoints).
  • Streaming with reasoningdoStream() emits proper reasoning-start, reasoning-delta, reasoning-end parts alongside text.
  • All Ollama optionsnum_ctx, top_k, top_p, repeat_penalty, num_predict, stop, seed.

💰 Anthropic Prompt Caching

When using the Anthropic provider, SmartAI automatically wraps the model with caching middleware that adds cacheControl: { type: 'ephemeral' } to the last system message and last user message. This can significantly reduce cost and latency for repeated calls with the same system prompt.

// Caching enabled by default
const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

// Opt out of caching
const modelNoCaching = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
  promptCaching: false,
});

You can also use the middleware directly:

import { createAnthropicCachingMiddleware } from '@push.rocks/smartai';
import { wrapLanguageModel } from 'ai';

const middleware = createAnthropicCachingMiddleware();
const cachedModel = wrapLanguageModel({ model: baseModel, middleware });

📦 Subpath Exports

SmartAI provides specialized capabilities as separate subpath imports. Each one is a focused utility that takes a model (or API key) and does one thing well.

👁️ Vision — @push.rocks/smartai/vision

Analyze images using any vision-capable model.

import { analyzeImage } from '@push.rocks/smartai/vision';
import { getModel } from '@push.rocks/smartai';
import * as fs from 'fs';

const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

const description = await analyzeImage({
  model,
  image: fs.readFileSync('photo.jpg'),
  prompt: 'Describe this image in detail.',
  mediaType: 'image/jpeg', // optional, defaults to 'image/jpeg'
});

console.log(description);

analyzeImage(options) accepts:

  • model — Any LanguageModelV3 with vision support
  • imageBuffer or Uint8Array
  • prompt — What to ask about the image
  • mediaType'image/jpeg' | 'image/png' | 'image/webp' | 'image/gif'

🎙️ Audio — @push.rocks/smartai/audio

Text-to-speech using OpenAI's TTS models.

import { textToSpeech } from '@push.rocks/smartai/audio';
import * as fs from 'fs';

const stream = await textToSpeech({
  apiKey: process.env.OPENAI_TOKEN,
  text: 'Welcome to the future of AI development!',
  voice: 'nova',     // 'alloy' | 'echo' | 'fable' | 'onyx' | 'nova' | 'shimmer'
  model: 'tts-1-hd', // 'tts-1' | 'tts-1-hd'
  responseFormat: 'mp3', // 'mp3' | 'opus' | 'aac' | 'flac'
  speed: 1.0,         // 0.25 to 4.0
});

stream.pipe(fs.createWriteStream('welcome.mp3'));

🎨 Image — @push.rocks/smartai/image

Generate and edit images using OpenAI's image models.

import { generateImage, editImage } from '@push.rocks/smartai/image';

// Generate an image
const result = await generateImage({
  apiKey: process.env.OPENAI_TOKEN,
  prompt: 'A futuristic cityscape at sunset, digital art',
  model: 'gpt-image-1',     // 'gpt-image-1' | 'dall-e-3' | 'dall-e-2'
  quality: 'high',           // 'low' | 'medium' | 'high' | 'auto'
  size: '1024x1024',
  background: 'transparent', // gpt-image-1 only
  outputFormat: 'png',       // 'png' | 'jpeg' | 'webp'
  n: 1,
});

// result.images[0].b64_json — base64-encoded image data
const imageBuffer = Buffer.from(result.images[0].b64_json!, 'base64');

// Edit an existing image
const edited = await editImage({
  apiKey: process.env.OPENAI_TOKEN,
  image: imageBuffer,
  prompt: 'Add a rainbow in the sky',
  model: 'gpt-image-1',
});

📄 Document — @push.rocks/smartai/document

Analyze PDF documents by converting them to images and using a vision model. Uses @push.rocks/smartpdf for PDF-to-PNG conversion (requires Chromium/Puppeteer).

import { analyzeDocuments, stopSmartpdf } from '@push.rocks/smartai/document';
import { getModel } from '@push.rocks/smartai';
import * as fs from 'fs';

const model = getModel({
  provider: 'anthropic',
  model: 'claude-sonnet-4-5-20250929',
  apiKey: process.env.ANTHROPIC_TOKEN,
});

const analysis = await analyzeDocuments({
  model,
  systemMessage: 'You are a legal document analyst.',
  userMessage: 'Summarize the key terms and conditions.',
  pdfDocuments: [fs.readFileSync('contract.pdf')],
  messageHistory: [],  // optional: prior conversation context
});

console.log(analysis);

// Clean up the SmartPdf instance when done
await stopSmartpdf();

🔬 Research — @push.rocks/smartai/research

Perform web-search-powered research using Anthropic's web_search_20250305 tool.

import { research } from '@push.rocks/smartai/research';

const result = await research({
  apiKey: process.env.ANTHROPIC_TOKEN,
  query: 'What are the latest developments in quantum computing?',
  searchDepth: 'basic',     // 'basic' | 'advanced' | 'deep'
  maxSources: 10,           // optional: limit number of search results
  allowedDomains: ['nature.com', 'arxiv.org'],  // optional: restrict to domains
  blockedDomains: ['reddit.com'],               // optional: exclude domains
});

console.log(result.answer);
console.log('Sources:', result.sources);       // Array<{ url, title, snippet }>
console.log('Queries:', result.searchQueries); // search queries the model used

🧪 Testing

# All tests
pnpm test

# Individual test files
tstest test/test.smartai.ts --verbose    # Core getModel + generateText + streamText
tstest test/test.ollama.ts --verbose     # Ollama provider (mocked, no API needed)
tstest test/test.vision.ts --verbose     # Vision analysis
tstest test/test.image.ts --verbose      # Image generation
tstest test/test.research.ts --verbose   # Web research
tstest test/test.audio.ts --verbose      # Text-to-speech
tstest test/test.document.ts --verbose   # Document analysis (needs Chromium)

Most tests skip gracefully when API keys are not set. The Ollama tests are fully mocked and require no external services.

📐 Architecture

@push.rocks/smartai
├── ts/                          # Core package
│   ├── index.ts                 # Re-exports getModel, AI SDK functions, types
│   ├── smartai.classes.smartai.ts  # getModel() — provider switch
│   ├── smartai.interfaces.ts    # ISmartAiOptions, TProvider, IOllamaModelOptions
│   ├── smartai.provider.ollama.ts  # Custom LanguageModelV3 for Ollama
│   ├── smartai.middleware.anthropic.ts  # Prompt caching middleware
│   └── plugins.ts               # AI SDK provider factories
├── ts_vision/                   # @push.rocks/smartai/vision
├── ts_audio/                    # @push.rocks/smartai/audio
├── ts_image/                    # @push.rocks/smartai/image
├── ts_document/                 # @push.rocks/smartai/document
└── ts_research/                 # @push.rocks/smartai/research

The core package is a thin registry. getModel() creates the appropriate @ai-sdk/* provider, calls it with the model ID, and returns the resulting LanguageModelV3. For Anthropic, it optionally wraps the model with prompt caching middleware. For Ollama, it returns a custom LanguageModelV3 implementation that talks directly to Ollama's /api/chat endpoint.

Subpath modules are independent — they import ai and provider SDKs directly, not through the core package. This keeps the dependency graph clean and allows tree-shaking.

This repository contains open-source code licensed under the MIT License. A copy of the license can be found in the LICENSE file.

Please note: The MIT License does not grant permission to use the trade names, trademarks, service marks, or product names of the project, except as required for reasonable and customary use in describing the origin of the work and reproducing the content of the NOTICE file.

Trademarks

This project is owned and maintained by Task Venture Capital GmbH. The names and logos associated with Task Venture Capital GmbH and any related products or services are trademarks of Task Venture Capital GmbH or third parties, and are not included within the scope of the MIT license granted herein.

Use of these trademarks must comply with Task Venture Capital GmbH's Trademark Guidelines or the guidelines of the respective third-party owners, and any usage must be approved in writing. Third-party trademarks used herein are the property of their respective owners and used only in a descriptive manner, e.g. for an implementation of an API or similar.

Company Information

Task Venture Capital GmbH Registered at District Court Bremen HRB 35230 HB, Germany

For any legal inquiries or further information, please contact us via email at hello@task.vc.

By using this repository, you acknowledge that you have read this section, agree to comply with its terms, and understand that the licensing of the code does not imply endorsement by Task Venture Capital GmbH of any derivative works.

Description
A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.
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