| import gradio as gr |
| import pandas as pd |
|
|
| |
| DATA_URL = "hf://datasets/Ichlibitiche/floradb-houseplants-care-sample/floradb_sample.csv" |
| df = pd.read_csv(DATA_URL) |
|
|
| DISPLAY_COLS = { |
| "common_name": "Common Name", |
| "scientific_name": "Scientific Name", |
| "family": "Family", |
| "light_requirement_level": "Light", |
| "min_lux": "Min Lux", |
| "max_lux": "Max Lux", |
| "watering_frequency_days": "Water Every (days)", |
| "min_temp_celsius": "Min °C", |
| "max_temp_celsius": "Max °C", |
| "is_toxic_to_dogs": "Toxic: Dogs", |
| "is_toxic_to_cats": "Toxic: Cats", |
| "toxicity_status": "Toxicity Source", |
| "care_confidence": "Care Confidence", |
| "gbif_source_url": "GBIF Source", |
| } |
|
|
| PET_FILTERS = [ |
| "All", |
| "Verified safe for dogs", |
| "Verified safe for cats", |
| "Toxic to dogs or cats", |
| "Toxicity unknown", |
| ] |
|
|
| def choices(col): |
| vals = df[col].dropna().astype(str) |
| return ["All"] + sorted(v for v in vals.unique() if v.strip()) |
|
|
| def explore(name_query, family, light, confidence, pet_filter): |
| d = df |
| if name_query and name_query.strip(): |
| q = name_query.strip() |
| hit = ( |
| d["common_name"].fillna("").str.contains(q, case=False, regex=False) |
| | d["scientific_name"].fillna("").str.contains(q, case=False, regex=False) |
| ) |
| d = d[hit] |
| if family != "All": |
| d = d[d["family"] == family] |
| if light != "All": |
| d = d[d["light_requirement_level"] == light] |
| if confidence != "All": |
| d = d[d["care_confidence"] == confidence] |
| |
| if pet_filter == "Verified safe for dogs": |
| d = d[(d["is_toxic_to_dogs"] == 0) & (d["toxicity_status"] != "unknown")] |
| elif pet_filter == "Verified safe for cats": |
| d = d[(d["is_toxic_to_cats"] == 0) & (d["toxicity_status"] != "unknown")] |
| elif pet_filter == "Toxic to dogs or cats": |
| d = d[(d["is_toxic_to_dogs"] == 1) | (d["is_toxic_to_cats"] == 1)] |
| elif pet_filter == "Toxicity unknown": |
| d = d[d["toxicity_status"] == "unknown"] |
|
|
| summary = ( |
| f"**{len(d)} plants** across **{d['family'].nunique()} families** match — " |
| f"out of {len(df)} in the free sample. " |
| f"The full FloraDB has **270 care plants + 891 ASPCA toxicity records + a 20,000+ species GBIF index**." |
| ) |
| return summary, d[list(DISPLAY_COLS)].rename(columns=DISPLAY_COLS) |
|
|
| with gr.Blocks(title="FloraDB Sample Explorer") as demo: |
| gr.Markdown("# 🌿 FloraDB: Houseplant Care & Pet-Toxicity Sample Explorer") |
| gr.Markdown(f"""Explore **{len(df)} houseplants from {df['family'].nunique()} botanical families** — care advice as **quantitative metrics** (Lux, watering days, °C, humidity) with **ASPCA pet toxicity** on GBIF-verified names. |
| |
| --- |
| ### 🌐 This is the free sample. The full FloraDB has 270 care plants, 891 toxicity records & a 20,000+ species index. |
| * **🔗 Official Portal (full dataset, $99 snapshot):** [floradb](https://houseplants-botanical-floradb.pages.dev) |
| * **🤗 Free Sample Dataset (Download CSV):** [Ichlibitiche/floradb-houseplants-care-sample](https://huggingface.co/datasets/Ichlibitiche/floradb-houseplants-care-sample) |
| * **🏆 Kaggle Dataset:** [FloraDB Houseplants Care Sample](https://www.kaggle.com/datasets/ahtiticheamine/floradb-houseplants-care-sample) |
| * **🔄 Live Self-Serve Lookups:** [Houseplant Care & Pet-Toxicity Lookup on Apify](https://apify.com/dataengineered/houseplant-care-toxicity-lookup) |
| ---""") |
|
|
| with gr.Row(): |
| name_tb = gr.Textbox(label="Plant Search", placeholder="e.g. Monstera, Pothos, Ficus...") |
| family_dd = gr.Dropdown(choices=choices("family"), value="All", label="Botanical Family") |
| light_dd = gr.Dropdown(choices=choices("light_requirement_level"), value="All", label="Light Requirement") |
| with gr.Row(): |
| conf_dd = gr.Dropdown(choices=choices("care_confidence"), value="All", label="Care Confidence") |
| pet_dd = gr.Dropdown(choices=PET_FILTERS, value="All", label="Pet Safety (ASPCA-based, conservative)") |
|
|
| btn = gr.Button("Explore Plants", variant="primary") |
|
|
| out_text = gr.Markdown() |
| out_table = gr.Dataframe(label="Matching Plants", wrap=True) |
|
|
| inputs = [name_tb, family_dd, light_dd, conf_dd, pet_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 © FloraDB under CC BY-NC 4.0 — informational, not veterinary advice. Full dataset commercially licensed at [floradb](https://houseplants-botanical-floradb.pages.dev) · contact floradb.hardhat456@simplelogin.com*""") |
|
|
| demo.launch() |
|
|
