https://github.com/mateolafalce/rag-chroma-openai
This project implements a Retrieval-Augmented Generation (RAG) system using Flask, OpenAI, and ChromaDB. It allows you to perform intelligent queries on your own data, integrating generative AI capabilities.
https://github.com/mateolafalce/rag-chroma-openai
chromadb flask openai rag rag-chatbot
Last synced: about 2 months ago
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This project implements a Retrieval-Augmented Generation (RAG) system using Flask, OpenAI, and ChromaDB. It allows you to perform intelligent queries on your own data, integrating generative AI capabilities.
- Host: GitHub
- URL: https://github.com/mateolafalce/rag-chroma-openai
- Owner: mateolafalce
- License: mit
- Created: 2025-08-12T01:29:30.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-08-15T15:46:21.000Z (11 months ago)
- Last Synced: 2025-08-25T02:26:30.554Z (10 months ago)
- Topics: chromadb, flask, openai, rag, rag-chatbot
- Language: HTML
- Homepage:
- Size: 73.2 KB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# RAG-Chroma-OpenAI
This project implements a Retrieval-Augmented Generation (RAG) system using Flask, OpenAI, and ChromaDB. It allows you to perform intelligent queries on your own data, integrating generative AI capabilities.
## Installation
1. Clone the repository and navigate to the project folder:
```bash
git clone https://github.com/mateolafalce/rag-chroma-openai.git
cd rag-chroma
```
2. Create and activate a virtual environment:
```bash
python3 -m venv venv
source venv/bin/activate
```
3. Install the dependencies:
```bash
pip install -r requirements.txt
```
4. Create a `.env` file in the project root with your OpenAI API key:
```env
OPENAI_API_KEY=sk-...
```
## Usage
1. Start the Flask application:
```bash
python app.py
```
2. Access the web interface at [http://localhost:5000](http://localhost:5000).
## Usar Docker
Para levantar la aplicación usando Docker Compose sigue estos pasos:
1. Crea un archivo `.env` en la raíz del proyecto con tu clave de OpenAI:
```bash
# .env
OPENAI_API_KEY=sk-...
```
Docker Compose cargará automáticamente ese archivo y lo pasará al contenedor.
2. Construye y arranca el servicio:
```bash
docker compose up --build
```
O, si usas la versión clásica de docker-compose:
```bash
docker-compose up --build
```
3. Abre tu navegador en http://localhost:5000
Notas:
- El volumen `./chroma_db` se monta dentro del contenedor para persistir la base de datos de Chroma entre reinicios.
- Si quieres ejecutar en segundo plano añade la opción `-d` (ej.: `docker compose up --build -d`).