HauteBot is your AI-powered fashion historian and creative design muse.
Built to inspire and educate, HauteBot is an intelligent assistant that allows users to explore fashion through the ages—one conversation at a time. Whether you're curious about 1920s flapper trends or want to visualize avant-garde concepts, HauteBot bridges the gap between history and creativity with the power of AI.
Think of it as your digital fashion mentor—one that talks and remembers.
Try it out: https://historybuff.onrender.com/
- Conversational Fashion Expert: Ask about styles from specific eras, trends, or movements. HauteBot understands context and gives rich, historically-grounded answers.
- Smart Fashion Retrieval (RAG): HauteBot searches a curated dataset of garments from The Met using real-time vector similarity search to give accurate examples.
- Readable & Structured Output: Responses are parsed and presented in a visually clean layout with bullet points and section headers for easy reading.
HauteBot uses a multi-agent architecture to intelligently route user inputs, whether they’re asking for information or an image.
- Central Router: Interprets the user’s intent and forwards the query.
- Historian Agent:
- Embeds queries using OpenAI's embedding model
- Retrieves garment matches using MongoDB Atlas Vector Search.
- Generates a response using OpenAI’s GPT model.
- Python + Flask
- Gunicorn (production server)
- OpenAI gpt-3.5-turbo model
- OpenAI text-embedding-3-small model
- MongoDB Atlas (with Vector Search)
- HTML + Jinja2
- CSS3
- Vanilla JavaScript
- Render (cloud platform)
- Git + GitLab (version control)
To run this project on your local machine:
- Python 3.11+
- Git
- MongoDB Atlas account
- OpenAI API key
- Google Cloud project with Vertex AI enabled
git clone https://github.com/TwiVyass/historyBuff
cd historyBuff