LUAWMS AI Assistant

An AI-powered chatbot designed for Lasbela University of Agriculture, Water and Marine Sciences (LUAWMS). This assistant leverages Retrieval-Augmented Generation (RAG) to provide accurate information regarding university admissions, fees, departments, and secure student records to students, visitors, and administration.

🚀 Features

• Intelligent RAG Pipeline: Queries a dedicated knowledge base (knowledge_base.json) to answer general university questions with high accuracy.
• Secure Student Portal: Authenticated access for students to view academic results, CGPA, and semester details.
• Dynamic Leaderboards: Automatically generates class standings and merit lists based on batch data (e.g., "2k21").
• Universal Search: Administrative capability to search for specific student records.
• Context-Aware: Maintains session context for a natural conversational experience.

🛠️ Tech Stack

• Framework: FastAPI
• LLM Engine: Groq (Llama 3.1)
• Embeddings: Sentence Transformers (all-MiniLM-L6-v2)
• Database: SQLite (Session management)
• Vector Search: Scikit-learn (Cosine Similarity)

📦 Setup & Installation

1. Clone the repository

   git clone <repository-url>
   cd luawms-ai

2. Create a virtual environment

   python -m venv venv
   # Windows
   venv\Scripts\activate
   # Mac/Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Configure Environment Create a .env file in the root directory and add your Groq API key:

   GROQ_API_KEY=your_groq_api_key_here

5. Prepare Data

   • knowledge_base.json: Pre-loaded with public university information.
   • students.json: Required for student features. Rename students.sample.json to students.json and populate it with actual student records.

⚡ Usage

Start the Server

Run the FastAPI application using the provided entry point:

python main.py

The API will be available at http://127.0.0.1:8000.

Project Structure

• main.py: Core application logic and API endpoints.
• knowledge_base.json: Source data for RAG.