import gradio as gr
import pandas as pd

# Load the free sample directly from the public Hugging Face dataset
DATA_URL = "hf://datasets/Ichlibitiche/suppdb-supplements-sample/suppdb_sample.csv"
df = pd.read_csv(DATA_URL)

DISPLAY_COLS = {
    "brand": "Brand",
    "product_name": "Product",
    "form_type": "Form",
    "ingredient": "Ingredient",
    "ingredient_form": "Ingredient Form",
    "ingredient_category": "Category",
    "amount_per_serving_mg": "Dose (mg/serving)",
    "is_proprietary_blend": "Hidden in Blend",
    "recommended_daily_mg": "NIH RDA (mg)",
    "upper_safety_limit_mg": "Upper Limit (mg)",
    "molecular_formula": "Formula",
    "source_url": "NIH DSLD Label",
}

BLEND_FILTERS = [
    "All",
    "Disclosed doses only",
    "Proprietary-blend (hidden dose) only",
]

def choices(col):
    vals = df[col].dropna().astype(str)
    return ["All"] + sorted(v for v in vals.unique() if v.strip())

def explore(ingredient_query, brand, category, form, blend_filter):
    d = df
    if ingredient_query and ingredient_query.strip():
        q = ingredient_query.strip()
        hit = (
            d["ingredient"].fillna("").str.contains(q, case=False, regex=False)
            | d["product_name"].fillna("").str.contains(q, case=False, regex=False)
        )
        d = d[hit]
    if brand != "All":
        d = d[d["brand"] == brand]
    if category != "All":
        d = d[d["ingredient_category"] == category]
    if form != "All":
        d = d[d["form_type"] == form]
    if blend_filter == "Disclosed doses only":
        d = d[d["is_proprietary_blend"] == 0]
    elif blend_filter == "Proprietary-blend (hidden dose) only":
        d = d[d["is_proprietary_blend"] == 1]

    summary = (
        f"**{len(d)} ingredient records** across **{d['product_id'].nunique()} products** "
        f"from **{d['brand'].nunique()} brands** match — out of {len(df)} records in the free sample. "
        f"The full SuppDB has **115,000+ ingredient records across 17,000+ products**."
    )
    return summary, d[list(DISPLAY_COLS)].rename(columns=DISPLAY_COLS)

with gr.Blocks(title="SuppDB Sample Explorer") as demo:
    gr.Markdown("# 💊 SuppDB: Supplements & Nootropics Sample Explorer")
    gr.Markdown(f"""Explore **{len(df)} active-ingredient records from {df['product_id'].nunique()} real supplement products ({df['brand'].nunique()} brands)** — NIH DSLD labels with **mg-normalized doses**, **proprietary-blend transparency**, and **PubChem chemistry**.

---
### 🌐 This is the free sample. The full SuppDB has 17,000+ products and 115,000+ ingredient records.
* **🔗 Official Portal (full dataset, $99 snapshot):** [suppdb.net](https://supplements-nootropics-suppdb.pages.dev)
* **🤗 Free Sample Dataset (Download CSV):** [Ichlibitiche/suppdb-supplements-sample](https://huggingface.co/datasets/Ichlibitiche/suppdb-supplements-sample)
* **🏆 Kaggle Dataset:** [SuppDB Supplements Sample](https://www.kaggle.com/datasets/ahtiticheamine/suppdb-supplements-sample)
---""")

    with gr.Row():
        query_tb = gr.Textbox(label="Ingredient / Product Search", placeholder="e.g. Magnesium, Ashwagandha, Vitamin D...")
        brand_dd = gr.Dropdown(choices=choices("brand"), value="All", label="Brand")
    with gr.Row():
        category_dd = gr.Dropdown(choices=choices("ingredient_category"), value="All", label="Ingredient Category")
        form_dd = gr.Dropdown(choices=choices("form_type"), value="All", label="Product Form")
        blend_dd = gr.Dropdown(choices=BLEND_FILTERS, value="All", label="Proprietary-Blend Transparency")

    btn = gr.Button("Explore Supplements", variant="primary")

    out_text = gr.Markdown()
    out_table = gr.Dataframe(label="Matching Ingredient Records", wrap=True)

    inputs = [query_tb, brand_dd, category_dd, form_dd, blend_dd]
    btn.click(fn=explore, inputs=inputs, outputs=[out_text, out_table])
    demo.load(fn=explore, inputs=inputs, outputs=[out_text, out_table])

    gr.Markdown("""---
*Sample data © SuppDB under CC BY-NC 4.0 — factual label data, not medical advice. Full dataset commercially licensed at [suppdb.net](https://supplements-nootropics-suppdb.pages.dev) · contact suppdb.doorframe589@simplelogin.com*""")

demo.launch()