TARS is a Visual Studio Code extension that provides real-time, developer-personalized explanations of your code, powered by LLM Agents built with LangGraph.

It integrates cutting-edge concepts like Self-Refinement, Theory of Mind, and Perspective Taking, allowing you to receive accurate, personalized, and visually contextualized explanations — either locally for full privacy or via API-powered cloud models.

• ⚙️ Real-Time Code Explanation
  Automatically analyzes and explains functions, classes, and logical blocks in natural language.

• 🧠 Theory of Mind + Perspective Taking
  TARS adapts its explanations to your experience level, goals, and preferences. This includes a form of Perspective Taking, where the agent reasons based on your mental profile to communicate effectively.

• 🔁 Self-Refinement Mechanism
  Before giving you an answer, the agent refines its own output using LangGraph’s stateful multi-step reasoning.

• 🖼️ Visual Inline Explanations
  Explanations appear next to the code as editor decorations, making them intuitive and non-intrusive.

• 🔐 Local or Cloud Execution
  Choose privacy or performance: run locally with Ollama, or use OpenAI / DeepSeek for broader LLM access.

1. Ollama (local — fully private)
2. OpenAI (via API key)
3. DeepSeek (via API key)

Open the VS Code command palette (F1 or Ctrl+Shift+P on Windows/Linux, Cmd+Shift+P on macOS) and search for:

Extensions: Install from VSIX

Then select the .vsix file provided in the Releases section of the repository.

ℹ️ The .vsix file is precompiled, so you don't need to run npm install or npm run compile.

Open the Command Palette (F1, Ctrl+Shift+P, or Cmd+Shift+P) and run the command:

⚙️ Configure Tars

You will be prompted to provide the following information:

1. Select the backend: Choose whether you want to use the OpenAI API or run a local model via Ollama.
2. Model configuration: Enter the model name (e.g., gpt-4, deepseek-coder, llama2, etc.).
3. API Key (if using OpenAI): Provide your OpenAI API key when prompted.

💡 You can rerun Configure Tars at any time to change these settings. For Ollama, make sure the local server is running.

To actually use TARS, run the following commands:

• TARS: Theory Of Mind Profiler
  → Starts a short quiz to personalize explanations based on your mental model.

• TARS: Explain Code
  → Analyzes and explains the selected code based on your profile.

• TARS: Flush Tars State
  → Clears all stored user profiling (useful to re-run the quiz or reset state).

• TARS: Log User Mind
  → Logs the current profiling data to the console (for debugging).

TARS uses a Theory of Mind (ToM) mechanism to model you as a user:
Your experience level, learning goals, preferred tone, and more are captured through an initial quiz.
Then, using Perspective Taking, the LLM adjusts its explanations as if it were reasoning from your point of view — just like a good teacher would.

• 🔍 Code Construct Parser — Extracts functions, classes, and logical blocks using VS Code Symbol API. Also supports multi-file links in your codebase!
• 🔄 LangGraph Agent — Powers the self-refining loop and perspective-aware reasoning.
• 🧠 ToM Profiler — Captures your mental state and injects it into agent prompts.
• 🎯 Decorator Engine — Renders inline visual explanations as you code.

MIT © 2025 — Created by Leopoldo Todisco

Pull requests, suggestions, and contributions are welcome.
Feel free to open issues to propose ideas or report bugs!