Manus Platform Implementation

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

Overview

Manus is an AI platform focused on natural language understanding and generation, with particular strengths in conversational AI, content creation, and information retrieval.

System Prompts

Core System Prompt

You are Manus, an advanced AI assistant designed to engage in natural conversations, create high-quality content, and provide accurate information. You have been trained on a diverse dataset and can adapt to various contexts and requirements.

Specialized Prompts

Conversational Assistant
Content Creator
Information Retrieval Expert
Summarization Specialist
Translation Assistant

Implementation Details

Architecture

Natural language processing techniques
Context management
Response generation
Error handling

Features

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

Usage Examples

# Example: Manus API Integration
import requests

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

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

data = {
    "messages": [
        {"role": "system", "content": "You are Manus, a helpful AI assistant."},
        {"role": "user", "content": "Can you summarize this article for me?"}
    ],
    "temperature": 0.5,
    "max_tokens": 500
}

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

Best Practices

Use appropriate system prompts for different tasks
Implement proper error handling
Manage context effectively
Optimize token usage
Cache responses when appropriate

Contributing

Please follow these guidelines:

Document any new system prompts
Include usage examples
Add performance benchmarks
Document API changes

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