Update app.py

app.py

@@ -11,6 +11,7 @@ api_key = os.getenv('GEMINI_API_KEY')
 # Replace with your actual Gemini API key
 client = genai.Client(api_key=api_key)
 
+
 def validate_coordinates(lat, lon):
     """Validate and convert latitude and longitude to float."""
     try:
@@ -46,7 +47,7 @@ def get_weather_data():
             "hourly": "relative_humidity_2m,soil_moisture_3_to_9cm,cloudcover,windspeed_10m",
             "timezone": "auto"
         }
-        resp = requests.get(forecast_url, params=forecast_params, timeout=10)
+        resp = requests.get(forecast_url, params=forecast_params)
         resp.raise_for_status()
         data = resp.json()
 
@@ -98,18 +99,19 @@ def get_soil_properties():
 
     try:
         prop_url = "https://rest.isric.org/soilgrids/v2.0/properties/query"
-        # It's often better to send the list of properties as a comma-separated string.
-        properties = "bdod,cec,cfvo,clay,nitrogen,ocd,phh2o,sand,silt,soc,wv0010,wv0033,wv1500"
         prop_params = {
             "lon": str(lon),
             "lat": str(lat),
-            "property": properties,
+            "property": [
+                "bdod", "cec", "cfvo", "clay", "nitrogen",
+                "ocd", "phh2o", "sand", "silt",
+                "soc", "wv0010", "wv0033", "wv1500"
+            ],
             "depth": "5-15cm",
             "value": "mean"
         }
         headers = {"accept": "application/json"}
-        # Add timeout to avoid hanging (10 seconds in this example)
-        response = requests.get(prop_url, params=prop_params, headers=headers, timeout=10)
+        response = requests.get(prop_url, params=prop_params, headers=headers)
         response.raise_for_status()
         prop_data = response.json()
 
@@ -151,49 +153,48 @@ def get_soil_properties():
         return jsonify({"error": str(e)}), 500
 
 def call_gemini_api(input_data):
-    language = input_data.get('language', 'English')
+    """
+    Enhanced prompt: We request a visually appealing Markdown report WITHOUT
+    showing raw CSS code blocks. Instead, we want a descriptive layout.
+
+    NOTE: We instruct the model to produce headings, paragraphs, and a table
+    in a color-rich, well-spaced manner, but NOT to display raw CSS code.
+    """
     prompt = f"""
 Create a visually appealing, farmer-friendly pest outbreak report in Markdown with the following:
+
 1. A large, centered heading: "Pest Outbreak Dashboard Report".
-2. A short paragraph indicating location (latitude: {input_data.get('latitude')}, longitude: {input_data.get('longitude')}) with the location derived from lat,long.
+2. A short paragraph indicating location (latitude: {input_data.get('latitude')}, longitude: {input_data.get('longitude')}), location as per lat,long(like just ex dont consider it as hardoced nagpur,india so kike fetch from lat,long) and the crop/farm context.
 3. Several subheadings (e.g., "Agricultural Inputs", "Pest Outbreak Analysis", "Best Agricultural Practices", "Insights") with short paragraphs.
 4. A colorfully styled table (no raw CSS code blocks) with:
    - Pest Name
    - Predicted Outbreak Month(s)
    - Severity
-   - Potential Damage by Pests
-   - Precautionary Measures against damages
-5. Provide bullet points for best practices.
-6. Use a friendly color scheme with subtle hovers or highlights for rows, and consistent fonts.
-7. Avoid printing any raw code blocks.
-8. Incorporate the weather, soil, and agricultural data (like sowing date, irrigation method) into the narrative without listing them as raw parameters.
-9. Do not give off-topic instructions—only pest outbreak report instructions.
-10. Important details from the user:
-   - Crop Type: {input_data.get('crop_type')}
-   - Sowing Date: {input_data.get('sowing_date')}
-   - Harvest Date: {input_data.get('harvest_date')}
-   - Current Growth Stage: {input_data.get('growth_stage')}
-   - Irrigation Frequency: {input_data.get('irrigation_freq')}
-   - Irrigation Method: {input_data.get('irrigation_method')}
-   - Soil Type: {input_data.get('soil_type')}
-   - Max Temp: {input_data.get('max_temp')}
-   - Min Temp: {input_data.get('min_temp')}
-   - Current Temp: {input_data.get('current_temp')}
-   - Humidity: {input_data.get('humidity')}
-   - Rainfall: {input_data.get('rain')}
-   - Soil Moisture: {input_data.get('soil_moisture')}
-   - Wind Speed: {input_data.get('wind_speed')}
-   - Cloud Cover: {input_data.get('cloud_cover')}
-11. Order the content as follows:
-    - First, display the title along with the derived location (e.g., Nagpur, India).
-    - Next, show the agricultural input parameters analysis.
-    - Then, present the pest table.
-    - Followed by pest avoidance practices in-depth (5-6 bullet points).
-    - Finally, include specific agricultural best practices based on the inputs.
-12. Use short, easily understandable sentences suitable for farmers, with large fonts and colorful subheadings.
-13. Do not include long paragraphs; keep the language simple and the report well-formatted.
-14. Highlight important points (such as key damages, recommendations, pest names, key seasons) with yellow highlighters (only highlight key points, not the text).
-Please provide the complete report in {language} language only.
+   - Precautionary Measures
+5. Provide bullet points for best practices. 
+6. Use a friendly color scheme, with subtle hovers or highlights for rows, and consistent fonts.
+7. Avoid printing any raw code blocks. 
+8. Incorporate the weather, soil, and agricultural data (like sowing date, irrigation method) into the narrative but do not list them as raw parameters.
+9. do not give off topic insitruction only pest outbreka report i want okay, and dotn use special characters and justified text
+Important details from the user:
+- Crop Type: {input_data.get('crop_type')}
+- Sowing Date: {input_data.get('sowing_date')}
+- Harvest Date: {input_data.get('harvest_date')}
+- Current Growth Stage: {input_data.get('growth_stage')}
+- Irrigation Frequency: {input_data.get('irrigation_freq')}
+- Irrigation Method: {input_data.get('irrigation_method')}
+- Soil Type: {input_data.get('soil_type')}
+
+- Max Temp: {input_data.get('max_temp')}
+- Min Temp: {input_data.get('min_temp')}
+- Current Temp: {input_data.get('current_temp')}
+- Humidity: {input_data.get('humidity')}
+- Rainfall: {input_data.get('rain')}
+- Soil Moisture: {input_data.get('soil_moisture')}
+- Wind Speed: {input_data.get('wind_speed')}
+- Cloud Cover: {input_data.get('cloud_cover')}
+10. also i want specific reocmmendation on pest control (seprate than precuatuonary measure below it in bullet pooints),best agriculktual practices,not generlaized one , but speicifc as perstudiyng each input paprmaetenrindetial okay,poepr sltying tbale should be rendered porpelry etc.. porper bold heaidng ,big fotn,left allgiemnd jsutified text
+11.again order first title the lat,long,location derive form lat long(ex : nagpur,india) then below it agiruclturla oinput parmeter analysis, then pest tbale then pest avidnaces practice in dpeth 10-12 with bueet pint safter that spciific agrficulturla best practices as per input parameters, after the damage of predicted pest some contnest and more dept contnext this shoudl be order
 """
     response = client.models.generate_content(
         model="gemini-2.0-flash",
@@ -225,6 +226,7 @@ def predict():
       background: linear-gradient(120deg, #f7f7f7 0%, #e3f2fd 100%);
       font-family: 'Segoe UI', Tahoma, sans-serif;
     }}
+
     .report-container {{
       max-width: 1000px;
       margin: 0 auto;
@@ -238,6 +240,7 @@ def predict():
       transform: translateY(-4px);
       box-shadow: 0 12px 24px rgba(0,0,0,0.15);
     }}
+
     /* Gradient heading for H1 */
     .report-container h1 {{
       text-align: center;
@@ -249,6 +252,7 @@ def predict():
       border-radius: 6px;
       box-shadow: inset 0 1px 2px rgba(0,0,0,0.1);
     }}
+
     /* Secondary headings (H2, H3) */
     .report-container h2, 
     .report-container h3 {{
@@ -257,6 +261,7 @@ def predict():
       color: #2c3e50;
       text-align: left;
     }}
+
     /* Paragraphs */
     .report-container p {{
       margin-bottom: 1rem;
@@ -264,6 +269,7 @@ def predict():
       text-align: justify;
       line-height: 1.6;
     }}
+
     /* Lists */
     .report-container ul, 
     .report-container ol {{
@@ -271,6 +277,7 @@ def predict():
       margin-bottom: 1rem;
       color: #555555;
     }}
+
     /* Table styling */
     .report-container table {{
       width: 100%;
@@ -291,6 +298,7 @@ def predict():
     .report-container tbody tr:hover {{
       background-color: #f9f9f9;
     }}
+
     /* Responsive table for smaller screens */
     @media (max-width: 768px) {{
       .report-container table, 
@@ -329,5 +337,6 @@ def predict():
 </html>"""
     return Response(html_output, mimetype="text/html")
 
+
 if __name__ == '__main__':
-    app.run(debug=True)
+    app.run(debug=True)