AI Integration

Basefloor provides built-in support for AI services, making it easy to integrate AI capabilities into your applications.

Configuration

Configure AI services in your basefloor.config.js:

module.exports = (API) => ({
  ai: {
    openai: {
      apiKey: process.env.OPENAI_API_KEY,
      model: 'gpt-4',
      maxTokens: 1000
    },
    anthropic: {
      apiKey: process.env.ANTHROPIC_API_KEY,
      model: 'claude-3-sonnet-20240229',
      maxTokens: 1000
    },
    google: {
      apiKey: process.env.GOOGLE_AI_API_KEY,
      model: 'gemini-pro',
      maxTokens: 1000
    }
  }
})

Usage

Basic Text Generation

// In your route handler
const response = await API.AI.openai.chat({
  messages: [
    { role: 'user', content: 'Hello, how are you?' }
  ]
})

console.log(response.content)

Chat Conversations

const conversation = await API.AI.anthropic.chat({
  messages: [
    { role: 'user', content: 'What is Basefloor?' },
    { role: 'assistant', content: 'Basefloor is a comprehensive API framework...' },
    { role: 'user', content: 'How do I get started?' }
  ]
})

Streaming Responses

const stream = await API.AI.openai.stream({
  messages: [
    { role: 'user', content: 'Write a long story...' }
  ]
})

for await (const chunk of stream) {
  process.stdout.write(chunk.content)
}

Available Providers

OpenAI

• Models: gpt-4, gpt-3.5-turbo, gpt-4-turbo
• Features: Chat, completions, streaming
• Configuration: API key required

Anthropic

• Models: claude-3-opus, claude-3-sonnet, claude-3-haiku
• Features: Chat, streaming, long context
• Configuration: API key required

Google AI

• Models: gemini-pro, gemini-pro-vision
• Features: Chat, multimodal capabilities
• Configuration: API key required

Advanced Features

Custom Prompts

const customPrompt = await API.AI.openai.chat({
  messages: [
    { 
      role: 'system', 
      content: 'You are a helpful assistant that always responds in JSON format.' 
    },
    { role: 'user', content: 'Tell me about the weather' }
  ],
  response_format: { type: 'json_object' }
})

Function Calling

const functionCall = await API.AI.openai.chat({
  messages: [
    { role: 'user', content: 'What is the weather in New York?' }
  ],
  functions: [
    {
      name: 'get_weather',
      description: 'Get the current weather for a location',
      parameters: {
        type: 'object',
        properties: {
          location: { type: 'string' }
        }
      }
    }
  ]
})

Image Analysis (Multimodal)

const imageAnalysis = await API.AI.google.chat({
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'What do you see in this image?' },
        { type: 'image_url', image_url: { url: 'https://example.com/image.jpg' } }
      ]
    }
  ]
})

Error Handling

AI services include built-in error handling and retry logic:

try {
  const response = await API.AI.openai.chat({
    messages: [{ role: 'user', content: 'Hello' }]
  })
} catch (error) {
  if (error.code === 'rate_limit_exceeded') {
    // Handle rate limiting
    await new Promise(resolve => setTimeout(resolve, 1000))
    // Retry logic
  } else if (error.code === 'insufficient_quota') {
    // Handle quota issues
  }
}

Best Practices

1. API Key Security: Store API keys in environment variables
2. Rate Limiting: Implement proper rate limiting in your application
3. Error Handling: Always handle API errors gracefully
4. Cost Management: Monitor token usage and implement limits
5. Content Filtering: Implement content moderation for user inputs