Create app.py

app.py

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+import os
+import pandas as pd
+import streamlit as st
+from fpdf import FPDF
+from groq import Groq
+
+# Initialize Groq client
+client = Groq(
+    api_key="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",
+)
+
+def analyze_water_quality(data, standards):
+    """Analyze water quality data against standards."""
+    results = []
+    for parameter, value in data.items():
+        standard = standards.get(parameter, None)
+        if standard:
+            exceeded = ((value - standard) / standard) * 100
+            if value < standard:
+                remark = "Below standard. Treatment needed."
+                treatment = "Primary Treatment: Screening, Sedimentation, Grit Removal."
+            else:
+                remark = "Above standard. Treatment needed."
+                if parameter in ["Bacteria"]:
+                    treatment = "Tertiary Treatment: Disinfection using Chlorination or UV."
+                elif parameter in ["Lead", "Mercury", "Arsenic"]:
+                    treatment = "Advanced Treatment: Chemical Precipitation, Adsorption."
+                elif parameter in ["Temperature"]:
+                    treatment = "Cooling, Aeration."
+                elif parameter in ["Clarity"]:
+                    treatment = "Coagulation, Flocculation."
+                elif parameter in ["Conductivity"]:
+                    treatment = "Ion Exchange, Reverse Osmosis."
+                elif parameter in ["pH"]:
+                    treatment = "pH Adjustment: Lime or Acid Addition."
+                elif parameter in ["Alkalinity"]:
+                    treatment = "Alkalinity Control: Lime or Soda Ash."
+                elif parameter in ["Chlorine"]:
+                    treatment = "Dechlorination: Activated Carbon or Sulfite."
+                elif parameter in ["Hardness"]:
+                    treatment = "Softening: Ion Exchange or Reverse Osmosis."
+                elif parameter in ["Dissolved Oxygen"]:
+                    treatment = "Aeration."
+                else:
+                    treatment = "Preliminary Treatment: Removal of large debris."
+            results.append({
+                "Parameter": parameter,
+                "Value": value,
+                "Standard": standard,
+                "Exceedance (%)": exceeded,
+                "Remark": remark,
+                "Treatment": treatment
+            })
+    return results
+
+def generate_pdf_report(results, filename="Water_Quality_Report.pdf"):
+    """Generate a PDF report for water quality analysis."""
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    pdf.cell(200, 10, txt="Water Quality Assessment Report", ln=True, align='C')
+    pdf.ln(10)
+
+    for result in results:
+        pdf.cell(0, 10, txt=f"Parameter: {result['Parameter']}", ln=True)
+        pdf.cell(0, 10, txt=f"Value: {result['Value']} | Standard: {result['Standard']} | Exceedance: {result['Exceedance (%)']:.2f}%", ln=True)
+        pdf.cell(0, 10, txt=f"Remark: {result['Remark']}", ln=True)
+        pdf.cell(0, 10, txt=f"Treatment: {result['Treatment']}", ln=True)
+        pdf.ln(5)
+
+    pdf.output(filename)
+
+def main():
+    st.title("Water Quality Assessment App")
+    st.write("Upload water sample data and analyze it against Punjab, Pakistan water quality standards.")
+
+    uploaded_file = st.file_uploader("Upload your water sample data (Excel format):", type=["xls", "xlsx"])
+
+    if uploaded_file:
+        # Load water sample data
+        sample_data = pd.read_excel(uploaded_file)
+        st.write("Sample Data:")
+        st.dataframe(sample_data)
+
+        # Load water quality standards (to be replaced with your data)
+        standards = {
+            "Lead": 0.01,
+            "Mercury": 0.001,
+            "Bacteria": 0.0,
+            "Temperature": 25,  # Example standard for temperature in Celsius
+            "Clarity": 5,  # Example standard for clarity (NTU)
+            "Conductivity": 1000,  # Example standard for conductivity (µS/cm)
+            "pH": 7,  # Example standard for pH
+            "Alkalinity": 200,  # Example standard for alkalinity (mg/L)
+            "Chlorine": 0.5,  # Example standard for chlorine (mg/L)
+            "Hardness": 200,  # Example standard for hardness (mg/L)
+            "Dissolved Oxygen": 5  # Example standard for dissolved oxygen (mg/L)
+        }
+
+        # Analyze the data
+        results = []
+        for _, row in sample_data.iterrows():
+            parameter = row['Parameter']
+            value = row['Value']
+            result = analyze_water_quality({parameter: value}, standards)
+            results.extend(result)
+
+        # Display results
+        st.write("Analysis Results:")
+        results_df = pd.DataFrame(results)
+        st.dataframe(results_df)
+
+        # Generate and download report
+        if st.button("Generate PDF Report"):
+            report_filename = "Water_Quality_Report.pdf"
+            generate_pdf_report(results, filename=report_filename)
+            st.success("Report generated successfully!")
+            with open(report_filename, "rb") as file:
+                st.download_button(
+                    label="Download Report",
+                    data=file,
+                    file_name=report_filename,
+                    mime="application/pdf"
+                )
+
+if __name__ == "__main__":
+    main()