Full-Stack RAG App: Typescript + Python + PostgreSQL + OpenAI + CKEditor

This project is a full-stack application that allows users to:

• Create and manage content (CMS)
• Ingest real documentation (.md, .txt) into a vector database
• Ask natural language questions
• Get AI-powered answers grounded in your own documentation (RAG = Retrieval Augmented Generation)

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Create New Post

View, Edit, Delete All Posts

Ask Questions Against the Ingested Documentation (CKE Docs)

Stack Overview

Layer	Tech
Frontend	React + TypeScript
Backend	FastAPI (Python 3.12)
Vector DB	PostgreSQL + pgvector
AI	OpenAI Embeddings + GPT
Auth	(Optional, future-ready)

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Features

• Rich Text Editing with CKEditor
• Document ingestion pipeline
• Vector search using OpenAI embeddings
• GPT-powered question answering with citations
• Full CRUD for posts via REST API
• Frontend search interface using /answer-docs

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Project Structure

. ├── backend/ │ ├── main.py # FastAPI app with endpoints │ ├── models.py # SQLAlchemy models │ ├── database.py # DB setup + pgvector │ ├── schemas.py # Pydantic schemas │ ├── ingest_docs.py # Script to ingest and embed docs │ └── docs/ # Folder with .md, .txt, or .pdf files ├── frontend/ │ ├── src/ │ │ ├── components/ │ │ │ ├── RichTextEditor.tsx │ │ │ ├── AskDocs.tsx │ │ │ └── ... │ │ ├── api/axios.ts │ │ └── App.tsx

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Setup Instructions

1️. Clone the Repo

git clone https://github.com/yourusername/rag-assistant-app.git cd rag-assistant-app

2. Backend Setup (Python 3.12)

cd backend python -m venv venv source venv/bin/activate # or venv\Scripts\activate on Windows

pip install -r requirements.txt

Create .env in /backend/:

OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxx DATABASE_URL=postgresql://postgres:postgres@localhost:5432/mycms

3. Setup PostgreSQL with pgvector

docker run --name postgres-db
-e POSTGRES_USER=postgres
-e POSTGRES_PASSWORD=postgres
-e POSTGRES_DB=mycms
-p 5432:5432
-d ankane/pgvector

Then inside psql:

CREATE EXTENSION vector;

4. Ingest Documentation

python ingest_docs.py

5. Start the Backend

uvicorn main:app --reload

Open Swagger: http://localhost:8000/docs

5. Frontend Setup

cd frontend npm install npm start

React App runs on: http://localhost:3000

Key Endpoints

Route	Description
POST /posts	Create CMS post
POST /ask-docs	Vector search on documentation chunks
POST /answer-docs	Full RAG answer with GPT + top chunks

Credits & Acknowledgements

• FastAPI
• OpenAI API
• pgvector
• LangChain TextSplitter
• CKEditor

License

MIT License

Copyright (c) 2025 Alexis Roberson

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.