🤖 Mind-Code Assistant

An intelligent, empathetic coding companion built with Spring Boot and Vanilla JavaScript. It is designed to be a flexible development partner, offering a helping hand during technical challenges as well as being your supportive anchor when imposter syndrome kicks in. By focusing on both clean code and emotional support, it ensures you never have to face a complex bug or a moment of self-doubt alone.

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✨ Features

• Personality Modes: Toggle between Code-Helper, Assistant, and the Mood-Booster—a dedicated system prompt to provide encouragement and perspective when coding stress kicks in.
• Markdown Support: Full rendering of code blocks, bold text, and lists for clear technical communication.
• Flexible Backend: Support for any OpenAI-compatible API.
• Resilient Architecture: Built with Resilience4j (Circuit Breaker and Retries) to ensure a stable experience even during service interruptions.

🛠️ Tech Stack

• Backend – Java 25 & Spring Boot 4.0.6
• Frontend – Thymeleaf, Vanilla JavaScript, Modern CSS
• Stability: Resilience4j (Circuit Breaker & Retry).
• Markdown: Marked.js for real-time rendering.

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🚀 How to Run

To use this assistant, you need an AI backend. You can choose to run it locally (free) or via the cloud (OpenRouter).

1. Setup your AI Backend (Choose one)

Option A: Local (LM Studio)

1. Download: Install LM Studio.
2. Model: Search for and download a model (e.g., Llama 3.1 8B).
3. Server: Go to the Local Server tab, set port to 1234, and click Start Server.

Option B: Cloud (OpenRouter)

1. API Key: Get a key from OpenRouter.
2. Environment Variables: In your IDE (IntelliJ), go to Run > Edit Configurations and add:
   • AI_API_BASE_URL = https://openrouter.ai/api/v1
   • AI_API_KEY = your_key_here
   • AI_API_MODEL_NAME = meta-llama/llama-3.1-8b-instruct

2. Launch the Application

1. Clone: Clone the repository and open it in your IDE.
2. Run: Execute AiIntegratedChatbotApplication.java.
3. Access: Open your browser and go to: http://localhost:8080

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📖 API Documentation

The project includes an interactive Swagger UI, allowing you to explore and test the backend endpoints (like /ai/chat) easily.

• Swagger UI: http://localhost:8080/swagger-ui.html
• OpenAPI Spec: http://localhost:8080/v3/api-docs

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⚙️ Configuration Details

The application uses Environment Variables to manage settings. If no variables are set, it defaults to the local LM Studio setup.

Variable	Description	Default (Local Fallback)
AI_API_BASE_URL	The API endpoint	http://localhost:1234/v1
AI_API_MODEL_NAME	The model identifier	meta-llama-3.1-8b-instruct
AI_API_KEY	Secret API key	no-key-needed