---
title: 'Chat Response Agent'
description: 'Chat Response Agent API with Multi-Language Support'
---

# Chat Response Agent

The Chat Response Agent generates engaging, contextually appropriate chat responses for dating conversations. The agent provides intelligent suggestions, tone analysis, and conversation guidance - all with **35+ language support** for natural, localized communication.

## 🚀 Endpoint

### Chat Response Generation
**POST** `/api/v1/ai-agents/chat/response`

Generates engaging chat responses with conversation suggestions and tone analysis.

## 📝 Request Format

### Chat Response Request
```json
{
  "message": "Hi! I saw you like photography too",
  "userId": "user123",
  "context": ["dating", "first_message", "shared_interest"],
  "tone": "friendly",
  "language": "en"
}
```

## 🔧 Request Parameters

| Parameter | Type | Required | Description | Example |
|-----------|------|----------|-------------|---------|
| `message` | string | ✅ | User's message to respond to | "Hi! I saw you like photography too" |
| `userId` | string | ✅ | Current user's unique identifier | "user123" |
| `context` | array[string] | ✅ | Conversation context and tags | ["dating", "first_message"] |
| `tone` | string | ✅ | Desired response tone | "friendly", "casual", "flirty" |
| `language` | string | ✅ | User's preferred language | "en", "es", "fr", "sw" |

### Supported Tones
- **friendly** - Warm and approachable
- **casual** - Relaxed and informal
- **flirty** - Playful and romantic
- **professional** - Polite and respectful
- **curious** - Interested and engaging

### Supported Languages
- **English (en)** - Default
- **Spanish (es)** - Español
- **French (fr)** - Français
- **Swahili (sw)** - Kiswahili
- **Arabic (ar)** - العربية
- **Chinese (zh)** - 中文
- **Hindi (hi)** - हिन्दी
- **Portuguese (pt)** - Português
- **Russian (ru)** - Русский
- **Japanese (ja)** - 日本語
- **Korean (ko)** - 한국어
- **German (de)** - Deutsch
- **Italian (it)** - Italiano
- And 20+ more languages...

## 📊 Response Format

### Success Response
```json
{
  "success": true,
  "data": {
    "response": "Hey! Yes, I love photography! What kind of photos do you enjoy taking?",
    "suggestions": [
      "Ask about their favorite photography spots",
      "Share a photography story of your own",
      "Suggest a photo walk together"
    ],
    "tone": "friendly",
    "nextSteps": [
      "Keep the conversation flowing naturally",
      "Show genuine interest in their responses",
      "Share something personal about yourself"
    ]
  },
  "timestamp": "2025-01-15T10:30:00Z"
}
```

### Multi-Language Response Examples

#### Spanish Response
```json
{
  "success": true,
  "data": {
    "response": "¡Hola! ¡Sí, me encanta la fotografía! ¿Qué tipo de fotos te gusta tomar?",
    "suggestions": [
      "Pregunta sobre sus lugares favoritos para fotografiar",
      "Comparte una historia de fotografía tuya",
      "Sugiere una caminata fotográfica juntos"
    ],
    "tone": "amigable",
    "nextSteps": [
      "Mantén la conversación fluyendo naturalmente",
      "Muestra interés genuino en sus respuestas",
      "Comparte algo personal sobre ti"
    ]
  }
}
```

#### French Response
```json
{
  "success": true,
  "data": {
    "response": "Salut ! Oui, j'adore la photographie ! Quel type de photos aimes-tu prendre ?",
    "suggestions": [
      "Demande-leur leurs endroits préférés pour photographier",
      "Partage une histoire de photographie de ta part",
      "Suggère une promenade photo ensemble"
    ],
    "tone": "amical",
    "nextSteps": [
      "Garde la conversation qui coule naturellement",
      "Montre un intérêt sincère pour leurs réponses",
      "Partage quelque chose de personnel sur toi"
    ]
  }
}
```

#### Swahili Response
```json
{
  "success": true,
  "data": {
    "response": "Hujambo! Ndio, napenda picha! Ni aina gani ya picha unayopenda kuchukua?",
    "suggestions": [
      "Uliza kuhusu sehemu zao za kupenda za picha",
      "Shiriki hadithi yako ya picha",
      "Pendekeza kutembea picha pamoja"
    ],
    "tone": "rafiki",
    "nextSteps": [
      "Endesha mazungumzo yakiendelea kwa asili",
      "Onyesha hamu ya kweli kwa majibu yao",
      "Shiriki kitu cha kibinafsi kuhusu wewe"
    ]
  }
}
```

## 🔍 Response Fields

| Field | Type | Description | Example |
|-------|------|-------------|---------|
| `response` | string | Generated chat response | "Hey! Yes, I love photography!..." |
| `suggestions` | array[string] | Conversation starter suggestions | ["Ask about their favorite..."] |
| `tone` | string | Tone used in the response | "friendly" |
| `nextSteps` | array[string] | Guidance for continuing conversation | ["Keep the conversation flowing..."] |

## 🧪 Testing Examples

### English Chat Response
```bash
curl -X POST "https://agents.joinwink.app/api/v1/ai-agents/chat/response" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "message": "Hi! I saw you like photography too",
    "userId": "user123",
    "context": ["dating", "first_message", "shared_interest"],
    "tone": "friendly",
    "language": "en"
  }'
```

### Spanish Chat Response
```bash
curl -X POST "https://agents.joinwink.app/api/v1/ai-agents/chat/response" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "message": "¡Hola! Vi que también te gusta la fotografía",
    "userId": "user123",
    "context": ["dating", "first_message", "shared_interest"],
    "tone": "friendly",
    "language": "es"
  }'
```

### French Chat Response
```bash
curl -X POST "https://agents.joinwink.app/api/v1/ai-agents/chat/response" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "message": "Salut ! J\'ai vu que tu aimes aussi la photographie",
    "userId": "user123",
    "context": ["dating", "first_message", "shared_interest"],
    "tone": "friendly",
    "language": "fr"
  }'
```

## 🔗 Integration Examples

### JavaScript/TypeScript
```typescript
class ChatResponseService {
  private baseURL = 'https://agents.joinwink.app/api/v1/ai-agents';
  private apiKey: string;

  constructor(apiKey: string) {
    this.apiKey = apiKey;
  }

  async generateResponse(message: string, context: string[], language: string = 'en'): Promise<any> {
    const response = await fetch(`${this.baseURL}/chat/response`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${this.apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        message,
        userId: 'user123',
        context,
        tone: 'friendly',
        language
      })
    });

    return response.json();
  }

  async getConversationSuggestions(context: string[], language: string = 'en'): Promise<any> {
    const response = await fetch(`${this.baseURL}/chat/response`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${this.apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        message: "I need some conversation starters",
        userId: 'user123',
        context,
        tone: 'friendly',
        language
      })
    });

    return response.json();
  }

  async analyzeTone(message: string, language: string = 'en'): Promise<any> {
    const response = await fetch(`${this.baseURL}/chat/response`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${this.apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        message,
        userId: 'user123',
        context: ['tone_analysis'],
        tone: 'neutral',
        language
      })
    });

    return response.json();
  }
}
```

### React Native
```javascript
class ChatResponseService {
  constructor(apiKey) {
    this.baseURL = 'https://agents.joinwink.app/api/v1/ai-agents';
    this.apiKey = apiKey;
  }

  async generateResponse(message, context, language = 'en') {
    const response = await fetch(`${this.baseURL}/chat/response`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${this.apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        message,
        userId: 'user123',
        context,
        tone: 'friendly',
        language
      })
    });

    return response.json();
  }

  async getBatchResponses(messages, context, language = 'en') {
    const responses = [];
    
    for (const message of messages) {
      try {
        const response = await this.generateResponse(message, context, language);
        responses.push({
          originalMessage: message,
          ...response.data
        });
      } catch (error) {
        console.error(`Failed to generate response for message: ${message}`, error);
      }
    }

    return responses;
  }

  async getContextualSuggestions(userProfile, matchProfile, language = 'en') {
    const context = ['dating', 'conversation_starters', 'profile_based'];
    
    const response = await fetch(`${this.baseURL}/chat/response`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${this.apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        message: `Generate conversation starters for someone who likes ${userProfile.interests.join(', ')}`,
        userId: 'user123',
        context,
        tone: 'friendly',
        language
      })
    });

    return response.json();
  }
}
```

## 🚀 Best Practices

### 1. Language Handling
- **Always specify language**: Include user's language preference in every request
- **Cultural context**: Ensure responses are culturally appropriate
- **Consistent communication**: Maintain language consistency throughout conversations

### 2. Context Management
- **Rich context**: Provide detailed context for better response generation
- **Conversation flow**: Include conversation history and current state
- **User preferences**: Consider user's communication style and preferences

### 3. Tone Selection
- **Appropriate tone**: Choose tone that matches conversation context
- **User comfort**: Consider user's comfort level with different tones
- **Cultural sensitivity**: Adapt tone based on cultural context

### 4. Response Quality
- **Natural flow**: Ensure responses feel natural and conversational
- **Engagement**: Generate responses that encourage continued conversation
- **Personalization**: Tailor responses to specific user interests and context

## ⚠️ Error Handling

### Common Errors

| Error Code | Description | Solution |
|------------|-------------|----------|
| `invalid_message` | Message text too short or missing | Ensure message is at least 5 characters |
| `missing_context` | No context provided | Include relevant conversation context |
| `invalid_tone` | Unsupported tone value | Use supported tones: friendly, casual, flirty, etc. |
| `invalid_language` | Unsupported language code | Use supported language codes (en, es, fr, etc.) |

### Error Response Example
```json
{
  "success": false,
  "error": {
    "code": "missing_context",
    "message": "Conversation context is required",
    "details": "Please provide relevant context for better response generation",
    "language": "en"
  },
  "timestamp": "2025-01-15T10:30:00Z"
}
```

## 📈 Rate Limits

- **Standard Plan**: 100 requests/hour
- **Premium Plan**: 500 requests/hour  
- **Enterprise Plan**: 2000 requests/hour

## 🔮 Advanced Features

### Context-Aware Responses
- **Conversation history**: Considers previous messages and context
- **User preferences**: Learns from user's communication style
- **Relationship stage**: Adapts responses based on relationship development

### Intelligent Suggestions
- **Dynamic suggestions**: Generates contextually relevant conversation starters
- **Tone adaptation**: Adjusts suggestions based on conversation mood
- **Cultural awareness**: Provides culturally appropriate suggestions

### Quality Assurance
- **Response validation**: Ensures responses meet quality standards
- **Fallback mechanisms**: Provides alternative responses when needed
- **Continuous learning**: Improves response quality based on user feedback

## 🎯 Use Cases

### Dating Apps
- **Conversation starters**: Generate engaging opening messages
- **Response assistance**: Help users craft better replies
- **Tone guidance**: Suggest appropriate communication styles

### Customer Support
- **Chatbot responses**: Generate natural customer service replies
- **Tone management**: Maintain consistent brand voice
- **Context awareness**: Provide relevant support information

### Social Networking
- **Friend conversations**: Generate friendly, engaging responses
- **Group discussions**: Provide contextually appropriate contributions
- **Professional networking**: Generate professional communication

## 🌟 Conversation Examples

### First Message Context
```json
{
  "message": "Hi! I noticed we both love hiking",
  "context": ["dating", "first_message", "shared_interest"],
  "tone": "friendly",
  "language": "en"
}
```

### Follow-up Conversation
```json
{
  "message": "That sounds amazing! Where was your favorite hike?",
  "context": ["dating", "conversation", "travel", "outdoors"],
  "tone": "curious",
  "language": "es"
}
```

### Flirty Interaction
```json
{
  "message": "You have such a beautiful smile in your photos",
  "context": ["dating", "flirting", "compliment"],
  "tone": "flirty",
  "language": "fr"
}
```

---

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