import gradio as gr
import requests
import folium
import os
import json
from datetime import datetime, timedelta
import pandas as pd
# Get API key from environment
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
def create_map(lat=40.7128, lon=-74.0060):
"""Create a Folium map centered at given coordinates"""
m = folium.Map(
location=[lat, lon],
zoom_start=10,
tiles="OpenStreetMap"
)
# Add a marker for the selected location
folium.Marker(
[lat, lon],
popup=f"Selected Location: {lat:.4f}, {lon:.4f}",
tooltip="Click to select this location",
icon=folium.Icon(color='red', icon='info-sign')
).add_to(m)
return m._repr_html_()
def get_pollen_data(lat, lon, days=5):
"""Fetch pollen data from Google Pollen API"""
if not GOOGLE_API_KEY:
return "Error: Google API key not found. Please set GOOGLE_API_KEY as a secret."
# Google Pollen API endpoint
url = "https://pollen.googleapis.com/v1/forecast:lookup"
# Calculate date range
start_date = datetime.now()
end_date = start_date + timedelta(days=days-1)
params = {
"key": GOOGLE_API_KEY,
"location.longitude": lon,
"location.latitude": lat,
"days": days,
"plantsDescription": True
}
try:
response = requests.get(url, params=params)
response.raise_for_status()
data = response.json()
# Debug: Print the structure to understand the API response
print(f"API Response keys: {data.keys()}")
if "dailyInfo" in data and len(data["dailyInfo"]) > 0:
print(f"First day info keys: {data['dailyInfo'][0].keys()}")
print(f"Date structure: {data['dailyInfo'][0].get('date', 'No date field')}")
return data
except requests.exceptions.RequestException as e:
error_msg = f"Error fetching pollen data: {str(e)}"
if hasattr(e, 'response') and e.response is not None:
error_msg += f" (Status: {e.response.status_code})"
return error_msg
except json.JSONDecodeError as e:
return f"Error parsing response: {str(e)}"
except Exception as e:
return f"Unexpected error: {str(e)}"
def format_pollen_data(data):
"""Format pollen data for display"""
if isinstance(data, str): # Error message
return data, None
if "dailyInfo" not in data:
return "No pollen data available for this location.", None
# Create formatted output
output = []
output.append("# 🌸 Pollen Forecast Report\n")
# Location info if available
if "regionInfo" in data:
region = data["regionInfo"]
output.append(f"**Location:** {region.get('displayName', 'Unknown')}\n")
# Daily pollen data
daily_data = []
for day_info in data["dailyInfo"]:
# Handle different date formats from the API
date_info = day_info.get("date", {})
if isinstance(date_info, dict):
# If date is a dict, try to extract the date string
if "year" in date_info and "month" in date_info and "day" in date_info:
year = date_info["year"]
month = date_info["month"]
day = date_info["day"]
date_obj = datetime(year, month, day)
else:
# Fallback to today's date if we can't parse
date_obj = datetime.now()
elif isinstance(date_info, str):
# If it's already a string, parse it
try:
date_obj = datetime.strptime(date_info, "%Y-%m-%d")
except ValueError:
date_obj = datetime.now()
else:
# Fallback
date_obj = datetime.now()
formatted_date = date_obj.strftime("%B %d, %Y")
output.append(f"## 📅 {formatted_date}\n")
if "pollenTypeInfo" in day_info:
pollen_types = day_info["pollenTypeInfo"]
# Create a row for the dataframe
row_data = {"Date": formatted_date}
for pollen in pollen_types:
pollen_type = pollen["code"].replace("_", " ").title()
index_info = pollen.get("indexInfo", {})
index_value = index_info.get("value", "N/A")
category = index_info.get("category", "Unknown")
# Add color coding based on category
color_map = {
"VERY_LOW": "🟢",
"LOW": "🟡",
"MEDIUM": "🟠",
"HIGH": "🔴",
"VERY_HIGH": "🟣"
}
color = color_map.get(category, "⚪")
output.append(f"**{pollen_type}:** {color} {category} (Index: {index_value})")
row_data[pollen_type] = f"{category} ({index_value})"
# Add plant descriptions if available
if "plantDescription" in pollen:
plants = pollen["plantDescription"]
if "plants" in plants:
plant_list = [plant["displayName"] for plant in plants["plants"][:3]] # Show top 3
output.append(f" - *Main sources: {', '.join(plant_list)}*")
output.append("")
daily_data.append(row_data)
output.append("---\n")
# Create DataFrame for tabular view
df = None
if daily_data:
df = pd.DataFrame(daily_data)
# Add legend
output.append("\n## 📊 Pollen Index Legend")
output.append("🟢 Very Low | 🟡 Low | 🟠 Medium | 🔴 High | 🟣 Very High\n")
# Add tips
output.append("## 💡 Tips")
output.append("- Check pollen levels before outdoor activities")
output.append("- Take allergy medications during high pollen days")
output.append("- Keep windows closed during peak pollen times")
output.append("- Shower and change clothes after being outdoors")
return "\n".join(output), df
def update_location(lat, lon):
"""Update the map and fetch pollen data for new location"""
if lat is None or lon is None:
return create_map(), "Please select a location on the map.", None
# Create new map
new_map = create_map(lat, lon)
# Get pollen data
pollen_data = get_pollen_data(lat, lon)
formatted_data, df = format_pollen_data(pollen_data)
return new_map, formatted_data, df
# Create the Gradio interface
with gr.Blocks(title="🌸 Pollen Forecast Map", theme=gr.themes.Soft()) as app:
gr.HTML("""
🌸 Pollen Forecast Map
Click on the map to select a location and get detailed pollen forecasts powered by Google Pollen API
""")
with gr.Row():
with gr.Column(scale=1):
gr.HTML("
📍 Location Selection
")
# Coordinate inputs
lat_input = gr.Number(
label="Latitude",
value=40.7128,
precision=6,
info="Enter latitude or click on map"
)
lon_input = gr.Number(
label="Longitude",
value=-74.0060,
precision=6,
info="Enter longitude or click on map"
)
update_btn = gr.Button("🔄 Update Location", variant="primary")
# Preset locations
gr.HTML("