Update app.py

app.py

@@ -6,6 +6,7 @@ import pandas as pd
 import torch
 import matplotlib.pyplot as plt
 import seaborn as sns
+import base64
 
 # Define constants
 MODEL_NAME = "gpt2"  # Publicly accessible model suitable for CPU
@@ -17,7 +18,7 @@ EXAMPLE_FILE = os.path.join(EXAMPLE_DIR, "titanic.csv")
 os.makedirs(FIGURES_DIR, exist_ok=True)
 os.makedirs(EXAMPLE_DIR, exist_ok=True)
 
-# Download the Titanic dataset if it doesn't exist (only for local runs)
+# Download the Titanic dataset if it doesn't exist
 if not os.path.isfile(EXAMPLE_FILE):
     print("Downloading the Titanic dataset for examples...")
     try:
@@ -184,20 +185,15 @@ def interact_with_agent(file_input, additional_notes):
     # Append the summary
     messages.append({"role": "assistant", "content": summary})
 
-    # Append images
+    # Append images by converting them to Base64
     for image_path in visualization_paths:
         # Ensure the image path is valid before attempting to display
         if os.path.isfile(image_path):
-            # To display images in Gradio Chatbot, use the 'gr.Image' component
-            # However, since we're using 'type="messages"', we need to embed images via Markdown
-            # Gradio supports Markdown image embedding
-            image_filename = os.path.basename(image_path)
-            # Convert image path to relative path if necessary
-            # For Spaces, images should be in the repository
-            messages.append({
-                "role": "assistant",
-                "content": f"![{image_filename}]({image_path})"
-            })
+            with open(image_path, "rb") as img_file:
+                img_bytes = img_file.read()
+                encoded_img = base64.b64encode(img_bytes).decode()
+                img_md = f"![{os.path.basename(image_path)}](data:image/png;base64,{encoded_img})"
+                messages.append({"role": "assistant", "content": img_md})
         else:
             messages.append({"role": "assistant", "content": f"⚠️ Unable to find image: {image_path}"})
 
@@ -246,6 +242,9 @@ Upload a `.csv` file, add any additional notes, and **the assistant will analyze
         api_name="run_analysis"
     )
 
+# Launch the Gradio app
 if __name__ == "__main__":
     demo.launch(share=True)
 
+
+