init

app.py

@@ -4,21 +4,15 @@ import google.generativeai as genai
 import kagglehub
 import os
 
-# Download the Kaggle dataset
 path = kagglehub.dataset_download("fahmidachowdhury/food-adulteration-dataset")
-
-# List the files in the dataset folder and assign the first one (assuming it's the desired file)
 dataset_file = os.listdir(path)[0]
 path = os.path.join(path, dataset_file)
 
-# Configure Google Gemini API
 gemapi = os.getenv("GeminiApi")
 genai.configure(api_key=gemapi)
 
-# Load the dataset
 data = pd.read_csv(path)
 
-# Define the system instructions for the model
 system_instruction = f"""
 You are a public assistant who specializes in food safety. You look at data and explain to the user any question they ask; here is your data: {str(data.to_json())}
 You are also a food expert in the Indian context. You act as a representative of the government or public agencies, always keeping the needs of the people at the forefront.
@@ -28,30 +22,48 @@ Once the customer asks you to show them the markdown report, you will use the in
 You will ask the customer a single question at a time, which is relevant, and you will not repeat another question until you've generated the report.
 """
 
-# Initialize the model
 model_path = "gemini-1.5-flash"
 FoodSafetyAssistant = genai.GenerativeModel(model_path, system_instruction=system_instruction)
 
-# Define the function to handle the user input
 def respond(usertxt):
-    # Get response from the assistant
     response = FoodSafetyAssistant.send_message(usertxt)
-    return response.text  # Return the generated response
+    return response.text
+
+html_content = """
+<div style="background-color:#f9f9f9; padding:20px; border-radius:10px;">
+    <h1 style="color:#34495e;">Food Safety Assistant</h1>
+    <h3 style="color:#2c3e50;">Your AI-Powered Assistant for Food Safety</h3>
+    <p style="color:#7f8c8d;">
+        Our platform allows consumers to report potential food safety violations, validate reports through AI, and notify local authorities. This proactive approach fosters community involvement in ensuring food integrity.
+    </p>
+    <h4 style="color:#e74c3c; text-align:center;">Core Functionalities</h4>
+    <div style="display:flex; justify-content: space-around; align-items:center; margin-top:20px;">
+        <div style="border: 2px solid #3498db; border-radius: 15px; padding: 20px; width: 150px; text-align: center;">
+            <h4 style="color:#2980b9;">Report Issues</h4>
+            <p style="color:#7f8c8d; font-size: 12px;">Submit details like the restaurant name and the issue, anonymously.</p>
+        </div>
+        <div style="border: 2px solid #3498db; border-radius: 15px; padding: 20px; width: 150px; text-align: center;">
+            <h4 style="color:#2980b9;">AI Validation</h4>
+            <p style="color:#7f8c8d; font-size: 12px;">Validate reports using AI, ensuring accuracy and preventing duplicates.</p>
+        </div>
+        <div style="border: 2px solid #3498db; border-radius: 15px; padding: 20px; width: 150px; text-align: center;">
+            <h4 style="color:#2980b9;">Alerts</h4>
+            <p style="color:#7f8c8d; font-size: 12px;">Notify authorities of repeated issues via email or SMS.</p>
+        </div>
+        <div style="border: 2px solid #3498db; border-radius: 15px; padding: 20px; width: 150px; text-align: center;">
+            <h4 style="color:#2980b9;">Data Chat</h4>
+            <p style="color:#7f8c8d; font-size: 12px;">Enable real-time discussion between consumers and authorities.</p>
+        </div>
+    </div>
+</div>
+"""
 
-# Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Food Safety Assistant")
-    
+    gr.HTML(html_content)
     with gr.Row():
-        # Text input on the left
         user_input = gr.Textbox(label="Your Input", placeholder="Enter your message here...", lines=5)
-        
-        # Text output on the right
         output_text = gr.Textbox(label="Assistant Output", interactive=False, lines=5)
-    
-    # Button to submit input and get output
     submit_btn = gr.Button("Submit")
     submit_btn.click(respond, inputs=user_input, outputs=output_text)
 
-# Launch the Gradio interface
 demo.launch()