AI-in-LMS

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Production-ready RAG assistant for Moodle — containerized with Jenkins CI/CD on AWS.

AI-in-LMS 최신버젼 다운로드

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# 🎓 Moodle AI — Academic Mentoring Assistant

A RAG (Retrieval-Augmented Generation) pipeline embedded in a Moodle-integrated LMS that answers student queries using uploaded course materials, streams responses token-by-token via SSE, and delivers them through a Flutter mobile app.

![Node.js](https://img.shields.io/badge/Node.js-20+-339933?logo=node.js&logoColor=white)
![Flutter](https://img.shields.io/badge/Flutter-3.10-02569B?logo=flutter&logoColor=white)
![Supabase](https://img.shields.io/badge/Supabase-pgvector-3ECF8E?logo=supabase&logoColor=white)
![NVIDIA NIM](https://img.shields.io/badge/NVIDIA-NIM-76B900?logo=nvidia&logoColor=white)
![Docker](https://img.shields.io/badge/Docker-containerized-2496ED?logo=docker&logoColor=white)
![AWS EC2](https://img.shields.io/badge/AWS-EC2-FF9900?logo=amazonaws&logoColor=white)
![License](https://img.shields.io/badge/license-MIT-blue)

---

## ✅ Key Features

### 🧠 Core RAG & AI Pipeline
- **Smart Q&A Retrieval:** Extracts and vectorizes multi-format course materials (PDF, DOCX) via NVIDIA NIM.
- **Vision-Driven Parsing:** Extracts tabular data and calendars using NVIDIA Vision LLM.
- **Dynamic Query Routing:** Intelligently routes queries between vector search, SQL calendar lookup, and LMS APIs.

### 📱 User & Admin Interfaces
- **SSE Streaming:** Delivers token-by-token stream responses with active source references.
- **Mobile Chat App:** Cross-platform Flutter application with history persistence and markdown formatting.
- **Admin Dashboard:** Simple web UI to upload documents, manage subjects, and configure models.

---

## 🏗 Architecture Flow

1. **Student Query:** Student asks a question via the Flutter application chat screen.
2. **Intent Classification:** Backend classifies query intent (`concept_explanation`, `calendar_query`, or `student_data_query`).
3. **Retrieval Search:** System executes pgvector similarity search, SQL calendar lookup, or LMS API retrieval.
4. **LLM Generation:** NVIDIA NIM LLM synthesizes an answer using the retrieved context.
5. **Client SSE Stream:** Flutter receives token-by-token server-sent events (SSE) and displays them in real-time.

---

## ⚡ Supabase Integration

Supabase acts as the primary data store and vector database, combining relational integrity with vector search capabilities:
- **Course Material Vectors (`pgvector`):** Stores chunked course text mapped to `1024-dimensional` embeddings generated via NVIDIA NIM.
- **Relational Tables:** Manages data for academic subjects, document metadata, logs, and calendar event schedules.

### Database Schema View
![Supabase Tables](https://raw.githubusercontent.com/madhanio/AI-in-LMS/main/assets/supabase-tables.png)

---

## 📱 Application Interface

Here is a preview of the student client application interface:

![App Interface](https://raw.githubusercontent.com/madhanio/AI-in-LMS/main/assets/app-interface.png)

## 🚀 Deployment

Deployed live on **AWS EC2** with a full CI/CD pipeline (GitHub Webhook → Jenkins → Docker).

### CI/CD Pipeline

GitHub push on main triggers a webhook to Jenkins, which runs 6 stages: Checkout Code → Cleanup Docker → Build Docker Image → Remove Old Container → Run Docker Container → Health Check. Full pipeline completes in ~2 minutes.

### Screenshots

**Webhook — Last delivery successful**
![Webhook Status](https://raw.githubusercontent.com/madhanio/AI-in-LMS/main/assets/webhook-connection-status.png)

**Jenkins Pipeline — 6-stage Docker CI/CD (latest run #11, all green)**
![Deploy Status](https://raw.githubusercontent.com/madhanio/AI-in-LMS/main/assets/deploy-status.png)

**Docker container live on EC2 — health check confirmed**
```bash
$ docker ps
CONTAINER ID   IMAGE               COMMAND                STATUS             PORTS                                       NAMES
3e3d29e48392   moodle-ai-backend   "docker-entrypoint.s…" Up About a minute  0.0.0.0:3000->3000/tcp, [::]:3000->3000/tcp moodle-ai-container

$ curl http://43.206.238.148:3000/health
{"status":"ok"}
```

### Docker Configuration
The backend runs as a Docker container (`moodle-ai-container`) built from `server/Dockerfile`, exposing port `3000`. Managed via `docker-compose` and orchestrated by Jenkins on every push.

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