update code

app.py

@@ -1,25 +1,102 @@
 import gradio as gr
 from transformers import pipeline
+import plotly.graph_objs as go
 
+# Load the Visual QA model
 generator = pipeline("visual-question-answering", model="jihadzakki/blip1-medvqa")
 
-def format_answer(image, question):
-    result = generator(image, question)
-    print(result)  # Print the result to see its structure
-    predicted_answer = result[0].get('answer', 'No answer found')  # Adjust this key if necessary
-
-    return f"Predicted Answer: {predicted_answer}"
-
-VisualQAApp = gr.Interface(
-    fn=format_answer,
-    inputs=[
-        gr.Image(label="Upload image", type="pil"),
-        gr.Textbox(label="Question"),
-    ],
-    outputs=[gr.Textbox(label="Answer")],
-    title="Visual Question Answering using BLIP Model",
-    description="VQA",
-    allow_flagging="never"
-)
-
-VisualQAApp.launch(share=True)
+def format_answer(image, question, history):
+    try:
+        result = generator(image, question, max_new_tokens=50)
+        predicted_answer = result[0].get('answer', 'No answer found')
+        history.append(f"Question: {question} | Answer: {predicted_answer}")
+        # Create a simple chart for demonstration purposes
+        chart = create_chart(predicted_answer)
+        return f"Predicted Answer: {predicted_answer}", chart, history
+    except Exception as e:
+        return f"Error: {str(e)}", None, history
+
+def create_chart(predicted_answer):
+    # Example chart data
+    labels = ['Positive', 'Negative']
+    values = [1, 0] if predicted_answer.lower() == 'yes' else [0, 1]
+    colors = ['blue', 'red'] if predicted_answer.lower() == 'yes' else ['red', 'blue']
+
+    fig = go.Figure(data=[go.Pie(labels=labels, values=values, marker=dict(colors=colors))])
+    return fig
+
+def switch_theme(mode):
+    if mode == "Light Mode":
+        return gr.themes.Default()
+    else:
+        return gr.themes.Soft(primary_hue=gr.themes.colors.blue, secondary_hue=gr.themes.colors.orange)
+
+def save_feedback(feedback):
+    return "Thank you for your feedback!"
+
+# Build the Visual QA application using Gradio with improvements
+with gr.Blocks(
+    theme=gr.themes.Soft(
+        font=[gr.themes.GoogleFont("Inconsolata"), "Arial", "sans-serif"],
+        primary_hue=gr.themes.colors.blue,
+        secondary_hue=gr.themes.colors.red,
+    )
+) as VisualQAApp:
+    gr.Markdown("# Visual Question Answering using BLIP Model", elem_classes="title")
+
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(label="Upload image", type="pil")
+            question_input = gr.Textbox(show_label=False, placeholder="Enter your question here...")
+            submit_button = gr.Button("Submit", variant="primary")
+
+        with gr.Column():
+            answer_output = gr.Textbox(label="Result Prediction")
+            chart_output = gr.Plot(label="Interactive Chart")
+
+    history_state = gr.State([])  # Initialize the history state
+
+    submit_button.click(
+        format_answer,
+        inputs=[image_input, question_input, history_state],
+        outputs=[answer_output, chart_output, history_state],
+        show_progress=True
+    )
+
+    with gr.Row():
+        history = gr.Textbox(label="History Log", lines=10)
+        gr.Markdown("**Log of previous interactions:**")
+        submit_button.click(
+            lambda history: "\n".join(history),
+            inputs=[history_state],
+            outputs=[history]
+        )
+
+    with gr.Accordion("Help", open=False):
+        gr.Markdown("**Upload image**: Select the chest X-ray image you want to analyze.")
+        gr.Markdown("**Enter your question**: Type the question you have about the image, such as 'Is there any sign of pneumonia?'")
+        gr.Markdown("**Submit**: Click the submit button to get the prediction from the model.")
+
+    with gr.Accordion("User Preferences", open=False):
+        gr.Markdown("**Mode**: Choose between light and dark mode for your comfort.")
+        mode_selector = gr.Radio(choices=["Light Mode", "Dark Mode"], label="Select Mode")
+        apply_theme_button = gr.Button("Apply Theme")
+
+        apply_theme_button.click(
+            switch_theme,
+            inputs=[mode_selector],
+            outputs=[],
+        )
+
+    with gr.Accordion("Feedback", open=False):
+        gr.Markdown("**We value your feedback!** Please provide any feedback you have about this application.")
+        feedback_input = gr.Textbox(label="Feedback", lines=4)
+        submit_feedback_button = gr.Button("Submit Feedback")
+
+        submit_feedback_button.click(
+            save_feedback,
+            inputs=[feedback_input],
+            outputs=[feedback_input]
+        )
+
+VisualQAApp.launch(share=True, server_name="0.0.0.0", server_port=8080, debug=True)