🧠 Logic Validation Agent

🚀 Try it Live: https://ahteshamlatiflogicchatbot.vercel.app/

A web-based, deterministic AI engine designed to validate natural-language arguments using formal Rules of Inference, Rules of Replacement, and Categorical Logic.

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⚙️ Architecture & Engineering Focus

Unlike general-purpose LLMs that are prone to hallucination when handling discrete mathematics, this system forces the AI into a strict, rule-bound state machine.

• Deterministic Output: The core reasoning engine (arcee-ai/trinity-large-thinking) is clamped at temperature: 0 to ensure reproducible mathematical proofs.
• Defensive JSON Parsing: Implemented server-side regex boundary tracking (/\{[\s\S]*\}/) to strictly extract and sanitize the JSON payload, preventing UI crashes from markdown leaks or conversational filler.
• Edge-Case Resilience: Gracefully handles unstructured noise (typos, empty inputs) by yielding formal schema errors rather than wasting pipeline bandwidth.

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✨ Core Capabilities

1. Propositional Logic Validation

Transforms plain-English arguments into symbolic representations and validates them against classical Rules of Inference & Replacement:

• Modus Ponens & Modus Tollens
• Hypothetical & Disjunctive Syllogism
• Addition, Simplification, & Conjunction
• De Morgan’s Laws, Double Negation, Commutation, & Distribution

2. Categorical Logic

Automatically extracts and analyzes complex categorical syllogisms to determine:

• Proposition types (A, E, I, O)
• Mood and Figure (e.g., AAA-1)
• Exact logical fallacies (e.g., Illicit Major, Qualitative Balance)

3. Step-by-Step Proof Generation

Returns a strict JSON array containing the step-by-step mathematical proof, clearly citing the rules applied at each derivation step while explaining why invalid arguments fail.

Example Backend JSON Output

{
  "valid": true,
  "type": "Propositional Logic",
  "mood": null,
  "details": null,
  "proof": [
    { "step": 1, "statement": "R → W", "rule": "Premise" },
    { "step": 2, "statement": "R", "rule": "Premise" },
    { "step": 3, "statement": "W", "rule": "Modus Ponens" }
  ],
  "error": null
}

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🛠 Tech Stack

• Frontend: Vanilla HTML5, CSS3, JavaScript
• Backend: Node.js, Express.js
• AI Integration: OpenRouter API
• Deployment: Vercel

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💻 Local Installation

1. Clone the Repository

git clone https://github.com/Ahtesham-Latif/Logic_Chatbot.git
cd Logic_Chatbot

2. Install Dependencies

npm install

3. Configure Environment Variables

Create a .env file in the root directory:

cp .env.example .env

Add the following values inside .env:

OPENROUTER_API_KEY=your_openrouter_api_key_here
PORT=3030
NODE_ENV=development

4. Start the Development Server

npm start

The application will be available at:

http://localhost:3030

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🎓 Project Purpose

This project was created to help students understand and practice formal logical reasoning.

It is useful for:

• Philosophy and logic students
• Debate preparation
• Critical thinking exercises
• Demonstrations of AI-assisted reasoning systems

The chatbot is intentionally designed to follow strict formal logic rules while avoiding informal or probabilistic reasoning patterns.

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👨‍💻 Author

Ahtesham Latif

• GitHub: https://github.com/Ahtesham-Latif
• LinkedIn: https://www.linkedin.com/in/ahtesham-latif

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📜 License

This project is licensed for educational and academic use.