Update app.py
Browse files
app.py
CHANGED
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@@ -2,8 +2,7 @@ import gradio as gr
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import requests
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import pandas as pd
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import plotly.express as px
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import
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from io import BytesIO
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# ================================================================
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# Helper Function
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@@ -34,20 +33,24 @@ def process_species_data(species_name, habitat, water_disturbance, land_disturba
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extract = "Error fetching data."
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words = extract.split()
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if len(words) < 200:
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extract += "\n\n" + ("Conservation of this species is critical for biodiversity. " * 5)
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summary = " ".join(words[:350])
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Environmental Impact Assessment:
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- Water Disturbance: {water_disturbance}/100
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- Land Disturbance: {land_disturbance}/100
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- Noise Level: {noise_level}/100
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- Habitat: {habitat}
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"""
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# 2. Fetch GBIF Map
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gbif_url = f"https://api.gbif.org/v1/occurrence/search?scientificName={species_name}&limit=200"
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@@ -68,10 +71,17 @@ Environmental Impact Assessment:
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fig = px.scatter_mapbox(pd.DataFrame({"lat":[], "lon":[]}), lat="lat", lon="lon", zoom=1)
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fig.update_layout(mapbox_style="open-street-map")
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# 3.
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# ================================================================
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# CSS Styling (HTML Injection)
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@@ -86,12 +96,11 @@ h1 { color: #2e7d32; text-align: center; }
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"""
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# ================================================================
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# UI Layout
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# ================================================================
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# NOTE: Removed 'theme' and 'css' arguments to prevent errors on old versions
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with gr.Blocks() as demo:
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gr.HTML(css_code)
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gr.Markdown("# 🌿 BioVigilus — Biodiversity Impact Analyzer")
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gr.Markdown("Analyze species, habitats, and environmental stress factors.")
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@@ -108,9 +117,10 @@ with gr.Blocks() as demo:
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with gr.Column(elem_classes="custom-box"):
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out_summary = gr.Textbox(label="Summary", lines=10)
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out_map = gr.Plot(label="Map")
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btn.click(process_species_data, [species_name, habitat, water, land, noise], [out_summary, out_map,
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if __name__ == "__main__":
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demo.launch()
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import requests
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import pandas as pd
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import plotly.express as px
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import os
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# ================================================================
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# Helper Function
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except:
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extract = "Error fetching data."
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# Pad text if too short
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words = extract.split()
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if len(words) < 200:
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extract += "\n\n" + ("Conservation of this species is critical for biodiversity. " * 5)
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summary = " ".join(words[:350])
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# Add Analysis
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analysis_text = f"""
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Environmental Impact Assessment:
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- Water Disturbance: {water_disturbance}/100
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- Land Disturbance: {land_disturbance}/100
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- Noise Level: {noise_level}/100
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- Habitat: {habitat}
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Higher disturbance values indicate increased pressure on this species' survival and reproduction.
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"""
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summary += analysis_text
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# 2. Fetch GBIF Map
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gbif_url = f"https://api.gbif.org/v1/occurrence/search?scientificName={species_name}&limit=200"
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fig = px.scatter_mapbox(pd.DataFrame({"lat":[], "lon":[]}), lat="lat", lon="lon", zoom=1)
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fig.update_layout(mapbox_style="open-street-map")
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# 3. Create Downloadable Report File
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filename = "BioVigilus_Report.txt"
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with open(filename, "w", encoding="utf-8") as f:
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f.write(f"=== BioVigilus Biodiversity Report ===\n\n")
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f.write(f"Species: {species_name}\n")
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f.write(f"Source: Wikipedia & GBIF Data\n")
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f.write(f"--------------------------------------\n")
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f.write(summary)
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# Return path to the file for download
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return summary, fig, filename
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# ================================================================
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# CSS Styling (HTML Injection)
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"""
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# ================================================================
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# UI Layout
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# ================================================================
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with gr.Blocks() as demo:
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gr.HTML(css_code)
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gr.Markdown("# 🌿 BioVigilus — Biodiversity Impact Analyzer")
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gr.Markdown("Analyze species, habitats, and environmental stress factors.")
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with gr.Column(elem_classes="custom-box"):
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out_summary = gr.Textbox(label="Summary", lines=10)
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out_map = gr.Plot(label="Map")
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# Changed from Image (QR) to File (Download)
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out_file = gr.File(label="Download Report")
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btn.click(process_species_data, [species_name, habitat, water, land, noise], [out_summary, out_map, out_file])
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if __name__ == "__main__":
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demo.launch()
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