# ▲ Vercel AI SDK

The [Vercel AI SDK](https://sdk.vercel.ai/) is a TypeScript toolkit for building AI-powered applications. Connect it to Tensorix using the OpenAI-compatible provider.

## Prerequisites

* Node.js 18+
* Tensorix API key from [app.tensorix.ai](https://app.tensorix.ai)

## Installation

```bash
npm install ai @ai-sdk/openai-compatible
# or
pnpm add ai @ai-sdk/openai-compatible
# or
yarn add ai @ai-sdk/openai-compatible
```

## Configuration

### Create Provider Instance

```typescript
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});
```

### Environment Variables

Create a `.env.local` file:

```env
TENSORIX_API_KEY=your-tensorix-api-key
```

## Usage Examples

### Text Generation

```typescript
import { generateText } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

const { text } = await generateText({
  model: tensorix('claude-sonnet-4-20250514'),
  prompt: 'Write a haiku about programming.',
});

console.log(text);
```

### Streaming Text

```typescript
import { streamText } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

const { textStream } = await streamText({
  model: tensorix('gpt-4o'),
  prompt: 'Explain the theory of relativity.',
});

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

### Chat Completions

```typescript
import { generateText } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

const { text } = await generateText({
  model: tensorix('claude-sonnet-4-20250514'),
  messages: [
    { role: 'system', content: 'You are a helpful coding assistant.' },
    { role: 'user', content: 'How do I create a REST API in Node.js?' },
  ],
});

console.log(text);
```

### Structured Output

```typescript
import { generateObject } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
import { z } from 'zod';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

const { object } = await generateObject({
  model: tensorix('gpt-4o'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(z.string()),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a recipe for chocolate chip cookies.',
});

console.log(object.recipe);
```

## Next.js Integration

### API Route (App Router)

```typescript
// app/api/chat/route.ts
import { streamText } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

export async function POST(req: Request) {
  const { messages } = await req.json();

  const result = await streamText({
    model: tensorix('claude-sonnet-4-20250514'),
    messages,
  });

  return result.toDataStreamResponse();
}
```

### React Component

```typescript
// components/Chat.tsx
'use client';

import { useChat } from 'ai/react';

export default function Chat() {
  const { messages, input, handleInputChange, handleSubmit } = useChat({
    api: '/api/chat',
  });

  return (
    <div>
      {messages.map((m) => (
        <div key={m.id}>
          <strong>{m.role}:</strong> {m.content}
        </div>
      ))}
      
      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={handleInputChange}
          placeholder="Say something..."
        />
        <button type="submit">Send</button>
      </form>
    </div>
  );
}
```

## Tool Calling

```typescript
import { generateText, tool } from 'ai';
import { createOpenAICompatible } from '@ai-sdk/openai-compatible';
import { z } from 'zod';

const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,
  baseURL: 'https://api.tensorix.ai/v1',
});

const result = await generateText({
  model: tensorix('gpt-4o'),
  tools: {
    weather: tool({
      description: 'Get the weather in a location',
      parameters: z.object({
        location: z.string().describe('The location to get weather for'),
      }),
      execute: async ({ location }) => {
        // Implement weather lookup
        return { temperature: 72, condition: 'sunny' };
      },
    }),
  },
  prompt: 'What is the weather in San Francisco?',
});

console.log(result);
```

## Available Models

See [Tensorix Models](/api-reference/models.md) for all available models.

| Model                        | Best For                       |
| ---------------------------- | ------------------------------ |
| `claude-sonnet-4-20250514`   | Complex reasoning, coding      |
| `claude-3-5-sonnet-20241022` | General chat, analysis         |
| `gpt-4o`                     | Multi-modal, tool calling      |
| `gpt-4o-mini`                | Fast responses, cost-effective |

## Troubleshooting

### API connection errors

Verify your configuration:

```typescript
const tensorix = createOpenAICompatible({
  name: 'tensorix',
  apiKey: process.env.TENSORIX_API_KEY,  // Must be set
  baseURL: 'https://api.tensorix.ai/v1',  // Include /v1
});
```

### Streaming not working

Ensure you're using `streamText` instead of `generateText` and returning `toDataStreamResponse()`.

## Resources

* [Vercel AI SDK Documentation](https://sdk.vercel.ai/)
* [Vercel AI SDK GitHub](https://github.com/vercel/ai)
* [Tensorix API Reference](/api-reference/overview.md)


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