AI SDK - Aihubmix 提供者

npm i @aihubmix/ai-sdk-provider@0.0.1

npm i @aihubmix/ai-sdk-provider

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: aihubmix('o4-mini'),
  prompt: 'Write a vegetarian lasagna recipe for four people.',
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: aihubmix('claude-3-7-sonnet-20250219'),
  prompt: 'Explain quantum computing in simple terms.',
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: aihubmix('gemini-2.5-flash'),
  prompt: 'Create a Python script to sort a list of numbers.',
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { streamText } from 'ai';

const result = streamText({
  model: aihubmix('gpt-3.5-turbo'),
  prompt: 'Write a short story about a robot learning to paint.',
  maxOutputTokens: 256,
  temperature: 0.3,
  maxRetries: 3,
});

let fullText = '';
for await (const textPart of result.textStream) {
  fullText += textPart;
  process.stdout.write(textPart);
}

console.log('\n使用情況:', await result.usage);
console.log('完成原因:', await result.finishReason);

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateObject } from 'ai';
import { z } from 'zod';

const result = await generateObject({
  model: aihubmix('gpt-4o-mini'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(
        z.object({
          name: z.string(),
          amount: z.string(),
        }),
      ),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a lasagna recipe.',
});

console.log(JSON.stringify(result.object.recipe, null, 2));
console.log('Token使用情況:', result.usage);
console.log('完成原因:', result.finishReason);

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { streamObject } from 'ai';
import { z } from 'zod';

const result = await streamObject({
  model: aihubmix('gpt-4o-mini'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(
        z.object({
          name: z.string(),
          amount: z.string(),
        }),
      ),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a lasagna recipe.',
});

for await (const objectPart of result.partialObjectStream) {
  console.log(objectPart);
}

console.log('Token使用情況:', result.usage);
console.log('最終物件:', result.object);

// Aihubmix provider 支援各種工具，包括網路搜尋：
import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: aihubmix('gpt-4'),
  prompt: 'What are the latest developments in AI?',
  tools: {
    webSearchPreview: aihubmix.tools.webSearchPreview({
      searchContextSize: 'high',
    }),
  },
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateImage } from 'ai';

const { image } = await generateImage({
  model: aihubmix.image('gpt-image-1'),
  prompt: 'A beautiful sunset over the mountains',
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { generateSpeech } from 'ai';

const { audio } = await generateSpeech({
  model: aihubmix.speech('tts-1'),
  text: 'Hello, this is a text-to-speech test.',
});

// 儲存音訊檔案
await saveAudioFile(audio);
console.log('音訊生成成功:', audio);

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { transcribe } from 'ai';

const { text } = await transcribe({
  model: aihubmix.transcription('whisper-1'),
  audio: audioFile,
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { embed } from 'ai';

const { embedding } = await embed({
  model: aihubmix.embedding('text-embedding-ada-002'),
  value: '你好，世界！',
});

import { aihubmix } from '@aihubmix/ai-sdk-provider';
import { embedMany } from 'ai';

const { embeddings, usage } = await embedMany({
  model: aihubmix.embedding('text-embedding-3-small'),
  values: [
    '海灘上的晴天',
    '城市裡的雨天下午',
    '山間的雪夜',
  ],
});

console.log('嵌入向量:', embeddings);
console.log('使用情況:', usage);