|
|
--- |
|
|
title: Doc Alive - RAG to Image |
|
|
emoji: 📦🎨 |
|
|
colorFrom: blue |
|
|
colorTo: pink |
|
|
sdk: gradio |
|
|
sdk_version: "5.44.1" |
|
|
app_file: app.py |
|
|
pinned: false |
|
|
--- |
|
|
|
|
|
# 📦→🧠→🎨 Doc Alive: RAG-to-Image with OpenAI |
|
|
|
|
|
This project turns documents into **illustrations** with the help of RAG (Retrieval-Augmented Generation), LLM prompt engineering, and OpenAI’s image generation. |
|
|
|
|
|
Upload a `.txt`, `.md`, or `.pdf` file, describe your goal, and the app will: |
|
|
1. **Extract text** from your file |
|
|
2. **Retrieve key excerpts** using embeddings |
|
|
3. **Ask an LLM** to craft a structured image generation spec |
|
|
4. **Generate an illustration** with OpenAI’s image model |
|
|
|
|
|
--- |
|
|
|
|
|
## 🚀 Demo |
|
|
|
|
|
This app runs on **Hugging Face Spaces** using **Gradio**. |
|
|
|
|
|
--- |
|
|
|
|
|
## 🔑 API Key |
|
|
|
|
|
You must provide your own **OpenAI API key** to use this demo. |
|
|
- Enter your key in the input box (starts with `sk-...`) |
|
|
- The key is **not stored** — it is only used in memory for your current session |
|
|
|
|
|
--- |
|
|
|
|
|
## 📂 Project Structure |
|
|
|
|
|
|
|
|
├─ app.py # Gradio UI entry |
|
|
├─ requirements.txt # Dependencies |
|
|
├─ rag/ # Text extraction + retrieval |
|
|
├─ llm/ # Structured LLM call helper |
|
|
├─ generation/ # Image generation helper |
|
|
|
|
|
|
|
|
--- |
|
|
|
|
|
## 🛠 Tech Stack |
|
|
|
|
|
- [Gradio](https://www.gradio.app/) – UI framework |
|
|
- [OpenAI](https://platform.openai.com/) – LLM + image generation |
|
|
- [RAG (text-embedding-3-small)](https://platform.openai.com/docs/guides/embeddings) – semantic retrieval |
|
|
|
|
|
--- |
|
|
|
|
|
## ⚠️ Notes |
|
|
|
|
|
- The OpenAI API key is required for both embeddings and image generation |
|
|
- We do **not** log or save your key |
|
|
- Depending on your key usage, OpenAI will bill API calls |
