> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vchata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# AI Services

> AI-powered conversation handling, prompt management, and intelligent automation services

# AI Services

The AI Services provide comprehensive artificial intelligence capabilities including conversation processing, prompt template management, document enhancement, and intelligent automation for the VChata platform.

## Overview

The AI Services layer includes:

* 🤖 **AI Service** - Core AI response generation and provider management
* 📝 **Prompt Template Service** - Template creation, management, and optimization
* 🧠 **Prompt Enhancement Service** - Context-aware prompt enhancement with documents
* 🎯 **AI Agent Service** - Intelligent agent configuration and management
* 🔄 **Conversation Processing** - Advanced conversation flow management
* 📊 **Document Vector Service** - Semantic search and document context

## AI Service

### Core AI Response Generation

The AI Service is the central component for generating intelligent responses using various LLM providers.

#### Provider Management

```typescript theme={null}
// Set the AI provider (OpenAI, Claude, etc.)
aiService.setProvider(LLMProviderType.OPENAI);
```

#### Basic Response Generation

```typescript theme={null}
// Generate a simple response
const response = await aiService.generateResponse(
  "You are a helpful sales assistant.",
  "Tell me about your products"
);
```

#### Response with Conversation History

```typescript theme={null}
// Generate response with conversation context
const response = await aiService.generateResponseWithHistory(
  "You are a helpful sales assistant.",
  [
    { role: "user", content: "Hello" },
    { role: "assistant", content: "Hi! How can I help you?" },
    { role: "user", content: "What products do you have?" }
  ]
);
```

#### Enhanced Response Generation

```typescript theme={null}
// Generate response with document context enhancement
const response = await aiService.generateEnhancedResponse(
  basePrompt,
  userMessage,
  organizationId,
  aiAgentId,
  {
    includeDocuments: true,
    maxTokens: 1000,
    temperature: 0.7
  }
);
```

### Available Methods

<Expandable title="generateResponse(prompt: string, message: string)">
  **Description**: Generates an AI response using a simple prompt and user message.

  **Parameters**:

  * `prompt`: The system prompt/instructions for the AI
  * `message`: The user's message to respond to

  **Returns**: `Promise<string>` - The AI-generated response
</Expandable>

<Expandable title="generateResponseWithHistory(prompt: string, conversationHistory: ConversationMessage[])">
  **Description**: Generates an AI response with full conversation context.

  **Parameters**:

  * `prompt`: The system prompt/instructions for the AI
  * `conversationHistory`: Array of previous messages in the conversation

  **Returns**: `Promise<string>` - The AI-generated response with context
</Expandable>

<Expandable title="generateEnhancedResponse(basePrompt, userMessage, organizationId, aiAgentId?, options?)">
  **Description**: Generates an AI response with document context enhancement.

  **Parameters**:

  * `basePrompt`: Base system prompt
  * `userMessage`: User's message
  * `organizationId`: Organization ID for context
  * `aiAgentId`: Optional AI agent ID
  * `options`: Enhancement options (documents, tokens, temperature)

  **Returns**: `Promise<string>` - Enhanced AI response
</Expandable>

## Prompt Template Service

### Template Management

The Prompt Template Service handles creation, management, and optimization of AI prompt templates.

#### Create Template

```typescript theme={null}
// Create a new prompt template
const template = await promptTemplateService.create(organizationId, {
  name: "Sales Assistant",
  description: "Template for sales conversations",
  templateContent: "You are a helpful sales assistant for {{companyName}}...",
  inputVariables: ["companyName", "productName"],
  businessInfo: {
    companyName: "Acme Corp",
    industry: "Technology"
  },
  personalitySettings: {
    tone: "professional",
    style: "conversational"
  },
  isActive: true
});
```

#### Find Templates

```typescript theme={null}
// Find templates with filtering
const templates = await promptTemplateService.findMany(organizationId, {
  page: 1,
  limit: 10,
  campaignId: "campaign_123",
  isActive: true,
  search: "sales",
  sortBy: "createdAt",
  sortOrder: "desc"
});
```

#### Update Template

```typescript theme={null}
// Update an existing template
const updatedTemplate = await promptTemplateService.update(templateId, {
  templateContent: "Updated template content...",
  personalitySettings: {
    tone: "friendly",
    style: "casual"
  }
});
```

#### Delete Template

```typescript theme={null}
// Delete a template
await promptTemplateService.delete(templateId);
```

### Template Features

<Expandable title="Variable Substitution">
  Templates support dynamic variable substitution using `{{variableName}}` syntax:

  ```typescript theme={null}
  {
    templateContent: "Hello {{customerName}}, welcome to {{companyName}}!",
    inputVariables: ["customerName", "companyName"]
  }
  ```
</Expandable>

<Expandable title="Business Context">
  Templates can include business-specific information:

  ```typescript theme={null}
  {
    businessInfo: {
      companyName: "Acme Corp",
      industry: "Technology",
      products: ["Product A", "Product B"],
      services: ["Consulting", "Support"]
    }
  }
  ```
</Expandable>

<Expandable title="Personality Settings">
  Configure AI personality and response style:

  ```typescript theme={null}
  {
    personalitySettings: {
      tone: "professional", // professional, friendly, casual
      style: "conversational", // conversational, formal, technical
      expertise: "sales", // sales, support, marketing
      language: "en" // Language code
    }
  }
  ```
</Expandable>

<Expandable title="A/B Testing Support">
  Templates support A/B testing variants:

  ```typescript theme={null}
  {
    abTestVariant: {
      variant: "A",
      testId: "test_123",
      weight: 0.5
    }
  }
  ```
</Expandable>

## Prompt Enhancement Service

### Document Context Enhancement

The Prompt Enhancement Service enhances prompts with relevant document context and business information.

#### Enhance Prompt

```typescript theme={null}
// Enhance prompt with document context
const enhancedPrompt = await promptEnhancementService.enhancePrompt(
  basePrompt,
  userMessage,
  organizationId,
  aiAgentId,
  {
    includeDocuments: true,
    maxDocuments: 5,
    similarityThreshold: 0.7,
    includeBusinessInfo: true,
    includeProductInfo: true
  }
);
```

#### Document Search

```typescript theme={null}
// Search for relevant documents
const documents = await promptEnhancementService.searchDocuments(
  userMessage,
  organizationId,
  {
    limit: 10,
    threshold: 0.7,
    includeContent: true
  }
);
```

### Enhancement Options

<Expandable title="Document Context">
  ```typescript theme={null}
  {
    includeDocuments: true,
    maxDocuments: 5,
    similarityThreshold: 0.7,
    documentTypes: ["knowledge_base", "product_info", "faq"]
  }
  ```
</Expandable>

<Expandable title="Business Information">
  ```typescript theme={null}
  {
    includeBusinessInfo: true,
    includeProductInfo: true,
    includeContactInfo: true,
    includePricingInfo: false
  }
  ```
</Expandable>

<Expandable title="Response Configuration">
  ```typescript theme={null}
  {
    maxTokens: 1000,
    temperature: 0.7,
    includeExamples: true,
    includeInstructions: true
  }
  ```
</Expandable>

## AI Agent Service

### Agent Configuration

The AI Agent Service manages intelligent agent configurations for automated responses.

#### Create Agent

```typescript theme={null}
// Create an AI agent
const agent = await aiAgentService.create(organizationId, {
  name: "Sales Bot",
  description: "Automated sales assistant",
  promptTemplateId: "template_123",
  channels: ["DIRECT_MESSAGE", "COMMENT"],
  autoResponse: true,
  responseDelay: 30,
  maxResponsesPerConversation: 5,
  businessHoursOnly: false
});
```

#### Update Agent

```typescript theme={null}
// Update agent configuration
const updatedAgent = await aiAgentService.update(agentId, {
  autoResponse: false,
  responseDelay: 60,
  businessHoursOnly: true,
  businessHours: {
    start: "09:00",
    end: "17:00",
    timezone: "America/New_York"
  }
});
```

#### Process Message

```typescript theme={null}
// Process incoming message with agent
const response = await aiAgentService.processMessage(
  agentId,
  userMessage,
  conversationHistory,
  {
    includeContext: true,
    trackInteraction: true
  }
);
```

### Agent Features

<Expandable title="Multi-Channel Support">
  Agents can respond across multiple channels:

  * `DIRECT_MESSAGE` - Private messages
  * `COMMENT` - Public comments
  * `POST` - Direct posts
</Expandable>

<Expandable title="Response Control">
  ```typescript theme={null}
  {
    autoResponse: true,
    responseDelay: 30, // seconds
    maxResponsesPerConversation: 5,
    businessHoursOnly: true,
    businessHours: {
      start: "09:00",
      end: "17:00",
      timezone: "America/New_York"
    }
  }
  ```
</Expandable>

<Expandable title="Context Management">
  ```typescript theme={null}
  {
    includeConversationHistory: true,
    includeUserProfile: true,
    includeBusinessContext: true,
    maxHistoryLength: 10
  }
  ```
</Expandable>

## Conversation Processing Service

### Advanced Conversation Management

The Conversation Processing Service handles complex conversation flows and context management.

#### Process Conversation

```typescript theme={null}
// Process a conversation with advanced features
const result = await conversationProcessingService.processConversation({
  organizationId,
  aiAgentId,
  userMessage,
  conversationHistory,
  context: {
    userProfile: userProfile,
    businessContext: businessContext,
    sessionData: sessionData
  },
  options: {
    includeSentiment: true,
    includeIntent: true,
    trackMetrics: true
  }
});
```

#### Conversation Analytics

```typescript theme={null}
// Get conversation analytics
const analytics = await conversationProcessingService.getAnalytics(organizationId, {
  dateRange: {
    start: "2024-01-01",
    end: "2024-01-31"
  },
  metrics: ["response_time", "satisfaction", "conversion_rate"]
});
```

### Processing Features

<Expandable title="Sentiment Analysis">
  Analyzes user sentiment and adjusts responses accordingly:

  ```typescript theme={null}
  {
    includeSentiment: true,
    sentimentThreshold: 0.7,
    adjustToneBasedOnSentiment: true
  }
  ```
</Expandable>

<Expandable title="Intent Recognition">
  Identifies user intent and routes to appropriate responses:

  ```typescript theme={null}
  {
    includeIntent: true,
    intentCategories: ["sales", "support", "general"],
    intentConfidenceThreshold: 0.8
  }
  ```
</Expandable>

<Expandable title="Context Preservation">
  Maintains conversation context across sessions:

  ```typescript theme={null}
  {
    preserveContext: true,
    contextExpiration: 3600, // seconds
    maxContextLength: 1000
  }
  ```
</Expandable>

## Document Vector Service

### Semantic Search and Context

The Document Vector Service provides semantic search capabilities for document context.

#### Search Documents

```typescript theme={null}
// Search for relevant documents
const results = await documentVectorService.search(
  query,
  organizationId,
  {
    limit: 10,
    threshold: 0.7,
    includeContent: true,
    documentTypes: ["knowledge_base", "product_info"]
  }
);
```

#### Add Document

```typescript theme={null}
// Add document to vector store
const document = await documentVectorService.addDocument({
  organizationId,
  title: "Product Guide",
  content: "Complete product information...",
  metadata: {
    type: "product_info",
    category: "electronics",
    tags: ["guide", "product"]
  }
});
```

#### Update Document

```typescript theme={null}
// Update existing document
const updatedDocument = await documentVectorService.updateDocument(documentId, {
  content: "Updated product information...",
  metadata: {
    updated: true,
    version: "2.0"
  }
});
```

### Vector Features

<Expandable title="Semantic Search">
  Advanced semantic search using vector embeddings:

  * Similarity-based matching
  * Context-aware results
  * Multi-language support
</Expandable>

<Expandable title="Document Management">
  ```typescript theme={null}
  {
    autoIndexing: true,
    chunkSize: 1000,
    overlap: 200,
    supportedFormats: ["text", "markdown", "pdf"]
  }
  ```
</Expandable>

<Expandable title="Metadata Filtering">
  ```typescript theme={null}
  {
    metadata: {
      type: "knowledge_base",
      category: "support",
      tags: ["faq", "troubleshooting"],
      language: "en"
    }
  }
  ```
</Expandable>

## Integration Examples

### Complete AI Response Flow

```typescript theme={null}
// Complete flow for generating AI responses
async function generateIntelligentResponse(
  organizationId: string,
  aiAgentId: string,
  userMessage: string,
  conversationHistory: ConversationMessage[]
) {
  // 1. Get agent configuration
  const agent = await aiAgentService.getAgent(aiAgentId);
  
  // 2. Get prompt template
  const template = await promptTemplateService.getTemplate(agent.promptTemplateId);
  
  // 3. Enhance prompt with context
  const enhancedPrompt = await promptEnhancementService.enhancePrompt(
    template.templateContent,
    userMessage,
    organizationId,
    aiAgentId,
    {
      includeDocuments: true,
      includeBusinessInfo: true,
      maxDocuments: 5
    }
  );
  
  // 4. Generate response
  const response = await aiService.generateEnhancedResponseWithHistory(
    enhancedPrompt.enhancedPrompt,
    userMessage,
    organizationId,
    aiAgentId,
    conversationHistory,
    {
      maxTokens: 1000,
      temperature: 0.7
    }
  );
  
  // 5. Track interaction
  await conversationProcessingService.trackInteraction({
    agentId: aiAgentId,
    userMessage,
    aiResponse: response,
    metrics: {
      responseTime: Date.now() - startTime,
      tokensUsed: response.length,
      contextDocuments: enhancedPrompt.documents.length
    }
  });
  
  return response;
}
```

### Template Management Workflow

```typescript theme={null}
// Template creation and testing workflow
async function createAndTestTemplate(organizationId: string) {
  // 1. Create template
  const template = await promptTemplateService.create(organizationId, {
    name: "Customer Support",
    templateContent: "You are a helpful customer support agent...",
    inputVariables: ["customerName", "issueType"],
    businessInfo: {
      companyName: "Acme Corp",
      supportHours: "24/7"
    }
  });
  
  // 2. Test template
  const testResponse = await aiService.testPrompt(
    template.templateContent,
    "I need help with my order"
  );
  
  // 3. Validate response quality
  const quality = await promptTemplateService.validateResponse(
    template.id,
    testResponse,
    {
      checkTone: true,
      checkCompleteness: true,
      checkRelevance: true
    }
  );
  
  // 4. Activate if quality is good
  if (quality.score > 0.8) {
    await promptTemplateService.update(template.id, { isActive: true });
  }
  
  return { template, testResponse, quality };
}
```

## Performance Optimization

### Caching Strategy

```typescript theme={null}
// Implement caching for frequently used prompts
const cachedPrompt = await promptCache.get(promptId);
if (!cachedPrompt) {
  const prompt = await promptTemplateService.getTemplate(promptId);
  await promptCache.set(promptId, prompt, 3600); // 1 hour cache
}
```

### Batch Processing

```typescript theme={null}
// Batch process multiple messages
const responses = await Promise.all(
  messages.map(message => 
    aiService.generateEnhancedResponse(
      basePrompt,
      message.content,
      organizationId,
      aiAgentId
    )
  )
);
```

### Rate Limiting

```typescript theme={null}
// Implement rate limiting for AI requests
const rateLimiter = new RateLimiter({
  windowMs: 60000, // 1 minute
  max: 100 // 100 requests per minute
});
```

## Error Handling

### Common Error Scenarios

<Expandable title="Provider Errors">
  ```typescript theme={null}
  try {
    const response = await aiService.generateResponse(prompt, message);
  } catch (error) {
    if (error.code === 'PROVIDER_UNAVAILABLE') {
      // Fallback to backup provider
      await aiService.setProvider(LLMProviderType.BACKUP);
      const response = await aiService.generateResponse(prompt, message);
    }
  }
  ```
</Expandable>

<Expandable title="Template Errors">
  ```typescript theme={null}
  try {
    const template = await promptTemplateService.create(organizationId, data);
  } catch (error) {
    if (error.code === 'TEMPLATE_CONFLICT') {
      throw new BadRequestException('Template name already exists');
    }
  }
  ```
</Expandable>

<Expandable title="Enhancement Errors">
  ```typescript theme={null}
  try {
    const enhanced = await promptEnhancementService.enhancePrompt(prompt, message, orgId);
  } catch (error) {
    if (error.code === 'NO_DOCUMENTS_FOUND') {
      // Fallback to basic prompt
      return { enhancedPrompt: prompt, documents: [] };
    }
  }
  ```
</Expandable>

## Monitoring and Analytics

### Performance Metrics

```typescript theme={null}
// Track AI service performance
const metrics = {
  responseTime: Date.now() - startTime,
  tokensUsed: response.length,
  providerLatency: providerResponseTime,
  cacheHitRate: cacheHits / totalRequests,
  errorRate: errors / totalRequests
};

await analyticsService.track('ai_response_generated', metrics);
```

### Quality Monitoring

```typescript theme={null}
// Monitor response quality
const quality = await qualityService.assessResponse(response, {
  checkGrammar: true,
  checkTone: true,
  checkCompleteness: true,
  checkRelevance: true
});

if (quality.score < 0.7) {
  await alertService.sendQualityAlert(agentId, quality);
}
```