https://github.com/cosmic-heart/ai-learning-platform

AI-Learning-Platform, a LLM-RAG pipeline which behaves like a guide and able to solve doubts. Deployed on-premise IBM ppc64le architecture. vLLM for model inference & Qdrant with Langchain for RAG Pipeline. Server written in django, postgres & cassandra as the sql & nosql databases.
https://github.com/cosmic-heart/ai-learning-platform

cassandra django langchain llm postgresql ppc64le qdrant ray-distributed vllm

Last synced: 3 months ago
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AI-Learning-Platform, a LLM-RAG pipeline which behaves like a guide and able to solve doubts. Deployed on-premise IBM ppc64le architecture. vLLM for model inference & Qdrant with Langchain for RAG Pipeline. Server written in django, postgres & cassandra as the sql & nosql databases.

• Host: GitHub
• URL: https://github.com/cosmic-heart/ai-learning-platform
• Owner: cosmic-heart
• License: cc0-1.0
• Created: 2024-01-15T06:32:31.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-05-01T14:28:35.000Z (about 1 year ago)
• Last Synced: 2025-08-18T15:44:57.298Z (10 months ago)
• Topics: cassandra, django, langchain, llm, postgresql, ppc64le, qdrant, ray-distributed, vllm
• Language: Python
• Homepage: https://megnav.com/portfolio/ai-learning-platform
• Size: 1.71 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# AI-Learning Platform

[![Documentation Status](https://readthedocs.org/projects/ai-learning-platform/badge/?version=latest)](https://ai-learning-platform.readthedocs.io/en/latest/?badge=latest)

[![React.js Build and Release](https://github.com/NavinKumarMNK/AI-Learning-Platform/actions/workflows/front-end-release.yml/badge.svg)](https://github.com/NavinKumarMNK/AI-Learning-Platform/actions/workflows/front-end-release.yml)

![Project Image](/assets/project.png)

## About

An intelligent learning platform powered by large language models and vector embeddings. The platform provides personalized AI-driven educational content with document processing capabilities and semantic search.

## Tech Stack

- **Frontend**: React, TypeScript, Vite

- **Backend**: Django, Django REST Framework, PostgreSQL, Cassandra

- **ML Service**: Ray Serve, vLLM, Qdrant (Vector DB)

- **Infrastructure**: Docker, Docker Swarm

# Documentation 

- This project uses `mkdocs` as the documentation service

- serve the document 

```bash

pip install mkdocs

pip install markdown-include

pip install mkdocstrings

mkdocs serve -a localhost:8001

```