-
Component-Based Design:
- The system is built around interchangeable components (strategies, processors, calculators)
- Each component implements a clear interface (IStrategy, IDataProcessor, etc.)
- Dependency injection allows custom implementations
-
Workflow:
Input Data → Process → Stress Calculation → Strategy Selection → Execution → Learning
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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| =============================================================================== | |
| Title: Human Digital Mirror - Comprehensive Data & Simulation Framework | |
| Version: 2.0 (Enhanced & Expanded) | |
| Author: eight.atulya | |
| License: MIT | |
| Date: October 26, 2023 |
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| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8" /> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"/> | |
| <title>PUJA-Dash</title> | |
| <style> | |
| /* CSS Variables for Metamorphosis Theme */ | |
| :root { | |
| --primary: #0b0314; |
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| import openai | |
| # Connect to local LM Studio API | |
| client = openai.OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio") | |
| def generate_response(prompt, model="model-identifier"): | |
| """Sends a prompt to the AI model and returns the response.""" | |
| completion = client.chat.completions.create( | |
| model=model, | |
| messages=[{"role": "user", "content": prompt}], |