graphics-llm / README.md
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Add Datawrapper chart generation mode with clean iframe display
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---
title: Viz LLM
emoji: πŸ“Š
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
short_description: AI assistant for visualization guidance and chart generation
license: mit
---
# πŸ“Š Viz LLM
AI-powered data visualization assistant with two modes:
- **πŸ’‘ Ideation Mode**: Get design recommendations based on research and best practices
- **πŸ“Š Chart Generation Mode**: Upload CSV data and automatically generate publication-ready charts
## Features
**Ideation Mode:**
- Research-backed visualization guidance
- Chart type recommendations
- Design best practices and accessibility advice
- Powered by RAG with Jina-CLIP-v2 embeddings
**Chart Generation Mode:**
- Upload CSV data
- AI analyzes your data and selects optimal chart type
- Automatic chart creation via Datawrapper API
- Publication-ready visualizations with one click
## Quick Start
1. **Install dependencies:**
```bash
pip install -r requirements.txt
```
2. **Set up environment variables:**
```bash
cp .env.example .env
```
Required:
- `SUPABASE_URL` - Your Supabase project URL
- `SUPABASE_KEY` - Your Supabase anon key
- `HF_TOKEN` - Hugging Face API token
- `DATAWRAPPER_ACCESS_TOKEN` - Datawrapper API token
3. **Run the app:**
```bash
python app.py
```
## Technology Stack
- **UI**: Gradio
- **Vector Database**: Supabase PGVector
- **Embeddings**: Jina-CLIP-v2
- **LLM**: Llama 3.1 via Hugging Face Inference Providers
- **Charts**: Datawrapper API
## License
MIT License
---
Built for the data visualization community