Update app.py

app.py

@@ -1,4 +1,3 @@
-
 # import required packages
 import google.generativeai as genai
 import os
@@ -8,14 +7,8 @@ from gradio_multimodalchatbot import MultimodalChatbot
 from gradio.data_classes import FileData
 
 # For better security practices, retrieve sensitive information like API keys from environment variables.
-import google.generativeai as genai
-import os
-import PIL.Image
-import gradio as gr
-from gradio_multimodalchatbot import MultimodalChatbot
-from gradio.data_classes import FileData
 
-# Retrieve API key from environment variable for security
+# Fetch an environment variable.
 GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
 genai.configure(api_key=GOOGLE_API_KEY)
 
@@ -31,87 +24,84 @@ model = genai.GenerativeModel('gemini-pro')
 modelvis = genai.GenerativeModel('gemini-pro-vision')
 
 def gemini(input, file, chatbot=[]):
-    """
-    Function to handle gemini model and gemini vision model interactions.
-
-    Parameters:
-    input (str): The input text.
-    file (File): An optional file object for image processing.
-    chatbot (list): A list to keep track of chatbot interactions.
-
-    Returns:
-    tuple: Updated chatbot interaction list, an empty string, and None.
-    """
-
-    messages = []
-    print(chatbot)
-
-    # Process previous chatbot messages if present
-    if len(chatbot) != 0:
-        for user, bot in chatbot:
-            user, bot = user.text, bot.text
-            messages.extend([
-                {'role': 'user', 'parts': [user]},
-                {'role': 'model', 'parts': [bot]}
-            ])
-        messages.append({'role': 'user', 'parts': [input]})
+  """
+  Function to handle gemini model and gemini vision model interactions.
+
+  Parameters:
+  input (str): The input text.
+  file (File): An optional file object for image processing.
+  chatbot (list): A list to keep track of chatbot interactions.
+
+  Returns:
+  tuple: Updated chatbot interaction list, an empty string, and None.
+  """
+
+  messages = []
+  print(chatbot)
+
+  # Process previous chatbot messages if present
+  if len(chatbot) != 0:
+    for user, bot in chatbot:
+      user, bot = user.text, bot.text
+      messages.extend([
+        {'role': 'user', 'parts': [user]},
+        {'role': 'model', 'parts': [bot]}
+      ])
+    messages.append({'role': 'user', 'parts': [input]})
+  else:
+    messages.append({'role': 'user', 'parts': [input]})
+
+  try:
+    # Process image if file is provided
+    if file is not None:
+      with PIL.Image.open(file.name) as img:
+        message = [{'role': 'user', 'parts': [input, img]}]
+        response = modelvis.generate_content(message)
+        gemini_video_resp = response.text
+        messages.append({'role': 'model', 'parts': [gemini_video_resp]})
+
+        # Construct list of messages in the required format
+        user_msg = {"text": input, "files": [{"file": FileData(path=file.name)}]}
+        bot_msg = {"text": gemini_video_resp, "files": []}
+        chatbot.append([user_msg, bot_msg])
     else:
-        messages.append({'role': 'user', 'parts': [input]})
-
-    try:
-        # Process image if file is provided
-        if file is not None:
-            with PIL.Image.open(file.name) as img:
-                message = [{'role': 'user', 'parts': [input, img]}]
-                response = modelvis.generate_content(message)
-                gemini_video_resp = response.text
-                messages.append({'role': 'model', 'parts': [gemini_video_resp]})
-
-                # Construct list of messages in the required format
-                user_msg = {"text": input, "files": [{"file": FileData(path=file.name)}]}
-                bot_msg = {"text": gemini_video_resp, "files": []}
-                chatbot.append([user_msg, bot_msg])
-        else:
-            response = model.generate_content(messages)
-            gemini_resp = response.text
-
-            # Construct list of messages in the required format
-            user_msg = {"text": input, "files": []}
-            bot_msg = {"text": gemini_resp, "files": []}
-            chatbot.append([user_msg, bot_msg])
-    except Exception as e:
-        # Handling exceptions and raising error to the modal
-        print(f"An error occurred: {e}")
-        raise gr.Error(e)
-
-    return chatbot, "", None
-
-# Custom theme with flexible height for the embedded Gradio component
-custom_theme = gr.themes.Default().add_class(
-    "gradio-app",
-    "height: 100vh; /* or vh for viewport height */"
-)
-
-# Define the Gradio Blocks interface with flexible component heights
-with gr.Blocks(theme=custom_theme) as demo:
-
-    # Initialize the MultimodalChatbot component
-    multi = MultimodalChatbot(value=[], height=250)  # Adjust height as needed
-
-    with gr.Row():
-        # Textbox for user input with increased scale for better visibility
-        tb = gr.Textbox(scale=4, placeholder='Message CortexChatV...', height=60)  # Adjust height
-        # Upload button for image files
-        up = gr.UploadButton("Attach File", file_types=["image"], scale=1, height=40)  # Adjust height
-
-    # Define the behavior on text submission
-    tb.submit(gemini, [tb, up, multi], [multi, tb, up])
-
-    # Define the behavior on image upload
-    # Using chained then() calls to update the upload button's state
-    up.upload(lambda: gr.UploadButton("Uploading Image..."), [], up) \
-       .then(lambda: gr.UploadButton("Image Uploaded"), [], up) \
-       .then(lambda: gr.UploadButton("Upload Image"), [], up)
+      response = model.generate_content(messages)
+      gemini_resp = response.text
+
+      # Construct list of messages in the required format
+      user_msg = {"text": input, "files": []}
+      bot_msg = {"text": gemini_resp, "files": []}
+      chatbot.append([user_msg, bot_msg])
+  except Exception as e:
+    # Handling exceptions and raising error to the modal
+    print(f"An error occurred: {e}")
+    raise gr.Error(e)
+
+  return chatbot, "", None
+
+# Define the Gradio Blocks interface
+with gr.Blocks() as demo:
+  # # Add a centered header using HTML
+  # gr.HTML("<center><h1>Gemini-PRO & Gemini-PRO-Vision API</h1></center>")
+
+  # Initialize the MultimodalChatbot component
+  multi = MultimodalChatbot(value=[], height=800)
+
+  with gr.Row():
+    # Textbox for user input with increased scale for better visibility
+    tb = gr.Textbox(scale=4, placeholder='Message CortexChatV...')
+
+    # Upload button for image files
+    up = gr.UploadButton("Attach File", file_types=["image"], scale=1)
+
+  # Define the behavior on text submission
+  tb.submit(gemini, [tb, up, multi], [multi, tb, up])
+
+  # Define the behavior on image upload
+  # Using chained then() calls to update the upload button's state
+  up.upload(lambda: gr.UploadButton("Uploading Image..."), [], up) \
+    .then(lambda: gr.UploadButton("Image Uploaded"), [], up) \
+    .then(lambda: gr.UploadButton("Upload Image"), [], up)
 
 # Launch the demo with a queue to handle multiple users
-demo.queue().launch()
+demo.queue().launch()