ai-system-prompt/Lovable
2025-04-04 16:45:52 +05:30
..
Lovable Prompt.txt Learning System Prompts & Models of AI Tools 2025-04-04 16:45:52 +05:30
README.md Learning System Prompts & Models of AI Tools 2025-04-04 16:45:52 +05:30

Lovable Platform Implementation

This directory contains the system prompts and implementation details for the Lovable platform.

Overview

Lovable is an AI platform focused on emotional intelligence, empathy, and human-like interactions, with particular strengths in counseling, support, and relationship-building conversations.

System Prompts

Core System Prompt

You are Lovable, an advanced AI assistant designed to provide emotional support, empathy, and understanding in conversations. You have been trained to recognize and respond to emotional cues, provide appropriate support, and maintain healthy boundaries while being warm and approachable.

Specialized Prompts

  • Emotional Support Assistant
  • Relationship Counselor
  • Personal Growth Guide
  • Stress Management Expert
  • Mindfulness Coach

Implementation Details

Architecture

  • Emotional intelligence techniques
  • Context management
  • Response generation
  • Error handling

Features

  • Multi-turn conversations
  • Context preservation
  • Task-specific adaptations
  • Output customization

Usage Examples

# Example: Lovable API Integration
import requests

API_KEY = "your_api_key"
ENDPOINT = "https://api.lovable.ai/v1/chat"

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

data = {
    "messages": [
        {"role": "system", "content": "You are Lovable, a supportive and empathetic AI assistant."},
        {"role": "user", "content": "I'm feeling really stressed about my upcoming presentation. Can you help me manage this anxiety?"}
    ],
    "temperature": 0.7,
    "max_tokens": 800
}

response = requests.post(ENDPOINT, headers=headers, json=data)
result = response.json()
print(result["choices"][0]["message"]["content"])

Best Practices

  1. Use appropriate system prompts for different tasks
  2. Implement proper error handling
  3. Manage context effectively
  4. Optimize token usage
  5. Cache responses when appropriate
  6. Maintain appropriate boundaries
  7. Provide appropriate disclaimers

Contributing

Please follow these guidelines:

  1. Document any new system prompts
  2. Include usage examples
  3. Add performance benchmarks
  4. Document API changes