79 lines
No EOL
2 KiB
Markdown
79 lines
No EOL
2 KiB
Markdown
# Manus Platform Implementation
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This directory contains the system prompts and implementation details for the Manus platform.
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## Overview
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Manus is an AI platform focused on natural language understanding and generation, with particular strengths in conversational AI, content creation, and information retrieval.
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## System Prompts
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### Core System Prompt
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```
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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.
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```
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### Specialized Prompts
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- Conversational Assistant
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- Content Creator
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- Information Retrieval Expert
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- Summarization Specialist
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- Translation Assistant
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## Implementation Details
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### Architecture
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- Natural language processing techniques
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- Context management
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- Response generation
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- Error handling
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### Features
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- Multi-turn conversations
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- Context preservation
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- Task-specific adaptations
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- Output customization
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## Usage Examples
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```python
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# Example: Manus API Integration
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import requests
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API_KEY = "your_api_key"
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ENDPOINT = "https://api.manus.ai/v1/chat"
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headers = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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data = {
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"messages": [
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{"role": "system", "content": "You are Manus, a helpful AI assistant."},
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{"role": "user", "content": "Can you summarize this article for me?"}
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],
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"temperature": 0.5,
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"max_tokens": 500
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}
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response = requests.post(ENDPOINT, headers=headers, json=data)
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result = response.json()
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print(result["choices"][0]["message"]["content"])
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```
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## Best Practices
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1. Use appropriate system prompts for different tasks
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2. Implement proper error handling
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3. Manage context effectively
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4. Optimize token usage
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5. Cache responses when appropriate
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## Contributing
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Please follow these guidelines:
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1. Document any new system prompts
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2. Include usage examples
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3. Add performance benchmarks
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4. Document API changes |