Add RoasterDB sample explorer app

README.md

@@ -1,13 +1,19 @@
 ---
-title: Roasterdb Sample Explorer
-emoji: 📚
-colorFrom: red
-colorTo: blue
+title: RoasterDB Specialty Coffee Sample Explorer
+emoji: ☕
+colorFrom: yellow
+colorTo: red
 sdk: gradio
-sdk_version: 6.19.0
-python_version: '3.13'
+sdk_version: 5.9.0
 app_file: app.py
 pinned: false
+license: cc-by-nc-4.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ☕ RoasterDB — Specialty Coffee Sample Explorer
+
+Interactively explore the free sample of [RoasterDB](https://specialty-coffee-roasterdb.pages.dev): specialty-coffee products from artisan roaster storefronts, with tasting notes normalized to the SCA Flavor Wheel and a source URL on every record.
+
+Data: [free sample dataset](https://huggingface.co/datasets/Ichlibitiche/roasterdb-specialty-coffee-sample) (100 verified records, 72 roasters). The full dataset (8,000+ products, 280+ roasters) is available at [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev).
+
+Sample data © RoasterDB, CC BY-NC 4.0.

app.py

@@ -0,0 +1,83 @@
+import gradio as gr
+import pandas as pd
+
+# Load the free sample directly from the public Hugging Face dataset
+DATA_URL = "hf://datasets/Ichlibitiche/roasterdb-specialty-coffee-sample/roasterdb_sample.csv"
+df = pd.read_csv(DATA_URL)
+
+DISPLAY_COLS = {
+    "source_roaster": "Roaster",
+    "title": "Coffee",
+    "origin_country": "Origin",
+    "process_method": "Process",
+    "roast_level": "Roast",
+    "weight_grams": "Weight (g)",
+    "price_value": "Price (USD)",
+    "tasting_notes_sca_nodes": "SCA Flavor Notes",
+    "source_url": "Source URL",
+}
+
+def choices(col):
+    vals = df[col].dropna().astype(str)
+    vals = sorted(v for v in vals.unique() if v.strip() and v != "Unknown")
+    return ["All"] + vals
+
+PRICE_MAX = float(df["price_value"].max())
+
+def explore(roaster, country, process, roast, flavor, max_price):
+    d = df
+    if roaster != "All":
+        d = d[d["source_roaster"] == roaster]
+    if country != "All":
+        d = d[d["origin_country"] == country]
+    if process != "All":
+        d = d[d["process_method"] == process]
+    if roast != "All":
+        d = d[d["roast_level"] == roast]
+    if flavor and flavor.strip():
+        d = d[d["tasting_notes_sca_nodes"].fillna("").str.contains(flavor.strip(), case=False, regex=False)]
+    if max_price < PRICE_MAX:
+        d = d[d["price_value"].fillna(PRICE_MAX + 1) <= max_price]
+
+    summary = (
+        f"**{len(d)} coffees** from **{d['source_roaster'].nunique()} roasters** match — "
+        f"out of {len(df)} records in the free sample. "
+        f"The full RoasterDB has **8,000+ products from 280+ roasters**."
+    )
+    table = d[list(DISPLAY_COLS)].rename(columns=DISPLAY_COLS).sort_values("Price (USD)")
+    return summary, table
+
+with gr.Blocks(title="RoasterDB Sample Explorer") as demo:
+    gr.Markdown("# ☕ RoasterDB: Specialty Coffee Sample Explorer")
+    gr.Markdown(f"""Explore **{len(df)} verified specialty coffees from {df['source_roaster'].nunique()} artisan roasters** — tasting notes normalized to the **SCA Flavor Wheel**, with a verifiable source URL on every record.
+
+---
+### 🌐 This is the free sample. The full RoasterDB has 8,000+ products from 280+ roasters.
+* **🔗 Official Portal (full dataset, $99 snapshot):** [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev)
+* **🤗 Free Sample Dataset (Download CSV):** [Ichlibitiche/roasterdb-specialty-coffee-sample](https://huggingface.co/datasets/Ichlibitiche/roasterdb-specialty-coffee-sample)
+* **🏆 Kaggle Dataset:** [RoasterDB Specialty Coffee Sample](https://www.kaggle.com/datasets/ahtiticheamine/roasterdb-specialty-coffee-sample)
+* **🔄 Live Self-Serve Scraping:** [Specialty Coffee Roaster Scraper on Apify](https://apify.com/dataengineered/specialty-coffee-roaster-scraper)
+---""")
+
+    with gr.Row():
+        roaster_dd = gr.Dropdown(choices=choices("source_roaster"), value="All", label="Roaster")
+        country_dd = gr.Dropdown(choices=choices("origin_country"), value="All", label="Origin Country")
+        process_dd = gr.Dropdown(choices=choices("process_method"), value="All", label="Process Method")
+        roast_dd = gr.Dropdown(choices=choices("roast_level"), value="All", label="Roast Level")
+    with gr.Row():
+        flavor_tb = gr.Textbox(label="SCA Flavor Search", placeholder="e.g. Berry, Chocolate, Floral, Peach...")
+        price_sl = gr.Slider(minimum=0, maximum=PRICE_MAX, value=PRICE_MAX, step=1, label="Max Price (USD)")
+
+    btn = gr.Button("Explore Coffees", variant="primary")
+
+    out_text = gr.Markdown()
+    out_table = gr.Dataframe(label="Matching Coffees", wrap=True)
+
+    inputs = [roaster_dd, country_dd, process_dd, roast_dd, flavor_tb, price_sl]
+    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 © RoasterDB under CC BY-NC 4.0. Full dataset commercially licensed at [roasterdb.net](https://specialty-coffee-roasterdb.pages.dev) · contact RoasterDB@proton.me*""")
+
+demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+pandas
+huggingface_hub