init

app.py

@@ -32,65 +32,26 @@ You will ask the customer a single question at a time, which is relevant, and yo
 model_path = "gemini-1.5-flash"
 FoodSafetyAssistant = genai.GenerativeModel(model_path, system_instruction=system_instruction)
 
-# Define the function to handle the chat
-def respond(usertxt, chat_history):
-    # Initialize chat with the previous history
-    chat = FoodSafetyAssistant.start_chat(history=chat_history)
-    
+# Define the function to handle the user input
+def respond(usertxt):
     # Get response from the assistant
-    response = chat.send_message(usertxt)
-    
-    # Append both user input and response to the chat history
-    chat_history.append({"role": "user", "content": usertxt})
-    chat_history.append({"role": "assistant", "content": response.text})
-    
-    return response.text, chat_history  # Return both the response and the updated chat history
+    response = FoodSafetyAssistant.send_message(usertxt)
+    return response.text  # Return the generated response
 
 # Gradio interface
-def gradio_chat(usertxt, chat_history):
-    response, updated_history = respond(usertxt, chat_history)
-    return response, updated_history  # Return the response and updated history
-
-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>
-"""
-
 with gr.Blocks() as demo:
+    gr.Markdown("# Food Safety Assistant")
+    
     with gr.Row():
-        # Left column with chatbot
-        with gr.Column(scale=2):
-            gr.HTML(html_content)
-            chatbot = gr.Chatbot()
-            user_input = gr.Textbox(placeholder="Enter your message here...")
-            chat_history = gr.State([])  # Initialize State here
-            submit_btn = gr.Button("Submit")
-            submit_btn.click(gradio_chat, inputs=[user_input, chat_history], outputs=[chatbot, chat_history])  # Include chat_history as input
-            gr.Dataframe(value=data)
+        # 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()