app.py

import gradio as gr

# Narrative
narrative = """
# 🚀 Welcome to Nexa Marketplace

Scientific Machine Learning is powerful — but painful. Researchers struggle with scattered datasets, slow infra, and confusing tooling.

**Nexa Marketplace solves this with:**
- Pre-curated ML-ready datasets
- Simple fine-tuned model consulting
- Real tooling for real science
"""

# Dataset offerings
datasets = [
    {
        "name": "🧬 Protein-Lite",
        "desc": "1K protein samples (ML-ready)",
        "price": "$5",
        "link": "https://buy.stripe.com/test_lite"
    },
    {
        "name": "🧬 Protein-Standard",
        "desc": "5K protein samples + README",
        "price": "$20",
        "link": "https://buy.stripe.com/test_standard"
    },
    {
        "name": "🧬 Protein-Max",
        "desc": "10K+ protein samples + entropy rank + docs",
        "price": "$100",
        "link": "https://buy.stripe.com/test_max"
    }
]

# Consulting description
consulting = """
# 💡 LLM + SciML Consulting

I fine-tune scientific LLMs on research corpora (300K+ instructions), optimize datasets for training, and build custom inference pipelines.

### 🔍 Example
- **Model:** Mistral 7B
- **Task:** Hypothesis + methodology generation from papers
- **Dataset:** 300K SciML instructions

📩 **[Email](mailto:[email protected])** or **[Book Time](https://calendly.com/your-link)** to get started.
"""

# Interface
with gr.Blocks(title="Nexa Marketplace") as demo:
    gr.Markdown(narrative)

    gr.Markdown("## 📦 Datasets")
    for ds in datasets:
        with gr.Row():
            gr.Markdown(f"**{ds['name']}**  \n{ds['desc']}  \n💰 {ds['price']}")
            gr.Button("Buy", link=ds["link"])

    gr.Markdown("## 🤝 Consulting")
    gr.Markdown(consulting)

demo.launch()