ydc-ai-sdk-integration

# Integrate AI SDK with You.com Tools

Interactive workflow to add You.com tools to your Vercel AI SDK application using `@youdotcom-oss/ai-sdk-plugin`.

## Workflow

1. **Ask: Package Manager**
   * Which package manager? (npm, bun, yarn, pnpm)
   * Install package using their choice:
     ```bash
     npm install @youdotcom-oss/ai-sdk-plugin
     # or bun add @youdotcom-oss/ai-sdk-plugin
     # or yarn add @youdotcom-oss/ai-sdk-plugin
     # or pnpm add @youdotcom-oss/ai-sdk-plugin
     ```

2. **Ask: Environment Variable Name**
   * Using standard `YDC_API_KEY`?
   * Or custom name? (if custom, get the name)
   * Have they set it in their environment?
   * If NO: Guide them to get key from https://you.com/platform/api-keys

3. **Ask: Which AI SDK Functions?**
   * Do they use `generateText()`?
   * Do they use `streamText()`?
   * Both?

4. **Ask: Existing Files or New Files?**
   * EXISTING: Ask which file(s) to edit
   * NEW: Ask where to create file(s) and what to name them

5. **For Each File, Ask:**
   * Which tools to add?
     - `youSearch` (web search)
     - `youExpress` (AI agent)
     - `youContents` (content extraction)
     - Multiple? (which combination?)
   * Using `generateText()` or `streamText()` in this file?
   * Which AI provider model? (to determine if stopWhen needed)

6. **Reference Integration Examples**

   See "Integration Examples" section below for complete code patterns:
   * generateText() - Basic text generation with tools
   * streamText() - Streaming responses with web frameworks (Next.js, Express, React)

7. **Update/Create Files**

   For each file:
   * Reference integration examples (generateText or streamText based on their answer)
   * Add import for selected tools
   * If EXISTING file: Find their generateText/streamText call and add tools object
   * If NEW file: Create file with example structure
   * Tool invocation pattern based on env var name:
     - Standard `YDC_API_KEY`: `youSearch()`
     - Custom name: `youSearch({ apiKey: process.env.CUSTOM_NAME })`
   * Add selected tools to tools object
   * If streamText + Anthropic: Add stopWhen parameter

## Integration Examples

### generateText() - Basic Text Generation

**Environment Variables Setup:**
```typescript
import { anthropic } from '@ai-sdk/anthropic';
import { generateText } from 'ai';
import { youContents, youExpress, youSearch } from '@youdotcom-oss/ai-sdk-plugin';

// Reads YDC_API_KEY from environment automatically
const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch(),
  },
  prompt: 'What are the latest developments in quantum computing?',
});

console.log(result.text);
```

**Multiple Tools:**
```typescript
const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch(),      // Web search with citations
    agent: youExpress(),      // AI answers with web context
    extract: youContents(),   // Content extraction from URLs
  },
  prompt: 'Research quantum computing and summarize the key papers',
});
```

**Custom API Key:**
```typescript
const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: youSearch({ apiKey: 'your-custom-key' }),
  },
  prompt: 'Your prompt here',
});
```

**Complete Example:**
```typescript
import { anthropic } from '@ai-sdk/anthropic';
import { generateText } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const main = async () => {
  try {
    const result = await generateText({
      model: anthropic('claude-sonnet-4-5-20250929'),
      tools: {
        search: youSearch(),
      },
      maxSteps: 5,
      prompt: 'What are the latest developments in quantum computing?',
    });

    console.log('Generated text:', result.text);
    console.log('\nTool calls:', result.steps.flatMap(s => s.toolCalls));
  } catch (error) {
    console.error('Error:', error);
    process.exit(1);
  }
};

main();
```

### streamText() - Streaming Responses

**Basic Streaming with stopWhen Pattern:**
```typescript
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

// CRITICAL: Always use stopWhen for Anthropic streaming
// Anthropic's SDK requires explicit stop conditions
const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

const result = streamText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: { search: youSearch() },
  stopWhen: stepCountIs(3),  // Required for Anthropic
  prompt: 'What are the latest AI developments?',
});

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

**Next.js Integration (App Router):**
```typescript
// app/api/chat/route.ts
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

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

  const result = streamText({
    model: anthropic('claude-sonnet-4-5-20250929'),
    tools: { search: youSearch() },
    stopWhen: stepCountIs(5),
    prompt,
  });

  return result.toDataStreamResponse();
}
```

**Express.js Integration:**
```typescript
// server.ts
import express from 'express';
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const app = express();
app.use(express.json());

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

app.post('/api/chat', async (req, res) => {
  const { prompt } = req.body;

  const result = streamText({
    model: anthropic('claude-sonnet-4-5-20250929'),
    tools: { search: youSearch() },
    stopWhen: stepCountIs(5),
    prompt,
  });

  res.setHeader('Content-Type', 'text/plain; charset=utf-8');
  res.setHeader('Transfer-Encoding', 'chunked');

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

  res.end();
});

app.listen(3000);
```

**React Client (with Next.js):**
```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} />
        <button type="submit">Send</button>
      </form>
    </div>
  );
}
```

**Complete Streaming Example:**
```typescript
import { anthropic } from '@ai-sdk/anthropic';
import { streamText, type StepResult } from 'ai';
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const stepCountIs = (n: number) => (stepResult: StepResult<any>) =>
  stepResult.stepNumber >= n;

const main = async () => {
  try {
    const result = streamText({
      model: anthropic('claude-sonnet-4-5-20250929'),
      tools: {
        search: youSearch(),
      },
      stopWhen: stepCountIs(3),
      prompt: 'What are the latest AI developments?',
    });

    // Stream to stdout
    console.log('Streaming response:\n');
    for await (const chunk of result.textStream) {
      process.stdout.write(chunk);
    }
    console.log('\n\nDone!');
  } catch (error) {
    console.error('Error:', error);
    process.exit(1);
  }
};

main();
```

## Tool Invocation Patterns

Based on env var name from step 2:

**Standard YDC_API_KEY:**
```typescript
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

tools: {
  search: youSearch(),
}
```

**Custom env var:**
```typescript
import { youSearch } from '@youdotcom-oss/ai-sdk-plugin';

const apiKey = process.env.THEIR_CUSTOM_NAME;

tools: {
  search: youSearch({ apiKey }),
}
```

**Multiple tools with standard env var:**
```typescript
import { youSearch, youExpress, youContents } from '@youdotcom-oss/ai-sdk-plugin';

tools: {
  search: youSearch(),
  agent: youExpress(),
  extract: youContents(),
}
```

**Multiple tools with custom env var:**
```typescript
import { youSearch, youExpress, youContents } from '@youdotcom-oss/ai-sdk-plugin';

const apiKey = process.env.THEIR_CUSTOM_NAME;

tools: {
  search: youSearch({ apiKey }),
  agent: youExpress({ apiKey }),
  extract: youContents({ apiKey }),
}
```

## Available Tools

### youSearch
Web and news search - model determines parameters (query, count, country, etc.)

### youExpress
AI agent with web context - model determines parameters (input, tools)

### youContents
Web page content extraction - model determines parameters (urls, format)

## Key Integration Patterns

The examples above demonstrate:
* Import statements (AI SDK + provider + You.com tools)
* Env var validation (optional for new files)
* Tool configuration based on env var
* generateText/streamText usage with tools
* Result handling (especially textStream destructuring for streamText)
* Anthropic streaming pattern (stopWhen: stepCountIs(3))
* Web framework integration (Next.js, Express, React)

## Implementation Checklist

For each file being updated/created:

- [ ] Import added for selected tools
- [ ] If custom env var: Variable declared with correct name
- [ ] tools object added to generateText/streamText
- [ ] Each selected tool invoked correctly:
  - Standard env: `toolName()`
  - Custom env: `toolName({ apiKey })`
- [ ] If streamText: Destructured `const { textStream } = ...`
- [ ] If Anthropic + streamText: Added `stopWhen: stepCountIs(3)`

Global checklist:

- [ ] Package installed with their package manager
- [ ] Env var set in their environment
- [ ] All files updated/created
- [ ] Ready to test

## Common Issues

**Issue**: "Cannot find module @youdotcom-oss/ai-sdk-plugin"
**Fix**: Install with their package manager

**Issue**: "YDC_API_KEY (or custom name) environment variable is required"
**Fix**: Set in their environment (get key: https://you.com/platform/api-keys)

**Issue**: "Tool execution fails with 401"
**Fix**: Verify API key is valid

**Issue**: "Incomplete or missing response"
**Fix**: If using streamText, increase the step count. Start with 3 and iterate up as needed (see README troubleshooting)

**Issue**: "textStream is not iterable"
**Fix**: Destructure: `const { textStream } = streamText(...)`

**Issue**: "Custom env var not working"
**Fix**: Pass to each tool: `youSearch({ apiKey })`

## Advanced: Tool Development Patterns

For developers creating custom AI SDK tools or contributing to @youdotcom-oss/ai-sdk-plugin:

### Tool Function Structure

Each tool function follows this pattern:

```typescript
export const youToolName = (config: YouToolsConfig = {}) => {
  const apiKey = config.apiKey ?? process.env.YDC_API_KEY;

  return tool({
    description: 'Tool description for AI model',
    inputSchema: ZodSchema,
    execute: async (params) => {
      if (!apiKey) {
        throw new Error('YDC_API_KEY is required');
      }

      const response = await callApiUtility({
        params,
        YDC_API_KEY: apiKey,
        getUserAgent,
      });

      // Return raw API response for maximum flexibility
      return response;
    },
  });
};
```

### Input Schemas Enable Smart Queries

Always use schemas from `@youdotcom-oss/mcp`:

```typescript
// ✅ Import from @youdotcom-oss/mcp
import { SearchQuerySchema } from '@youdotcom-oss/mcp';

export const youSearch = (config: YouToolsConfig = {}) => {
  return tool({
    description: '...',
    inputSchema: SearchQuerySchema,  // Enables AI to use all search parameters
    execute: async (params) => { ... },
  });
};

// ❌ Don't duplicate or simplify schemas
const MySearchSchema = z.object({ query: z.string() });  // Missing filters!
```

**Why this matters:**
- Rich schemas enable AI to use advanced query parameters (filters, freshness, country, etc.)
- AI can construct more intelligent queries based on user intent
- Prevents duplicating schema definitions across packages
- Ensures consistency with MCP server schemas

### API Key Handling

Always provide environment variable fallback and validate before API calls:

```typescript
// ✅ Automatic environment variable fallback
const apiKey = config.apiKey ?? process.env.YDC_API_KEY;

// ✅ Check API key in execute function
execute: async (params) => {
  if (!apiKey) {
    throw new Error('YDC_API_KEY is required');
  }
  const response = await callApi(...);
}
```

### Response Format

Always return raw API response for maximum flexibility:

```typescript
// ✅ Return raw API response
execute: async (params) => {
  const response = await fetchSearchResults({
    searchQuery: params,
    YDC_API_KEY: apiKey,
    getUserAgent,
  });

  return response;  // Raw response for maximum flexibility
}

// ❌ Don't format or transform responses
return {
  text: formatResponse(response),
  data: response,
};
```

**Why raw responses?**
- Maximum flexibility for AI SDK to process results
- No information loss from formatting
- AI SDK handles presentation layer
- Easier to debug (see actual API response)

### Tool Descriptions

Write descriptions that guide AI behavior:

```typescript
// ✅ Clear guidance for AI model
description: 'Search the web for current information, news, articles, and content using You.com. Returns web results with snippets and news articles. Use this when you need up-to-date information or facts from the internet.'

// ❌ Too brief
description: 'Search the web'
```

## Additional Resources

* Package README: https://github.com/youdotcom-oss/dx-toolkit/tree/main/packages/ai-sdk-plugin
* Vercel AI SDK Docs: https://ai-sdk.dev/docs
* You.com API: https://you.com/platform/api-keys