Update app.py

app.py

@@ -1,4 +1,3 @@
-# import required packages
 import google.generativeai as genai
 import os
 import PIL.Image
@@ -12,17 +11,10 @@ from gradio.data_classes import FileData
 GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
 genai.configure(api_key=GOOGLE_API_KEY)
 
-# These codelines are just to verify if your api key is correct or not
-# Use them when you clone the repo and build locally
-#!curl \
-#-H 'Content-Type: application/json' \
-#-d '{ "prompt": { "text": "Write a very short story about a magic backpack"} }' \
-#"https://generativelanguage.googleapis.com/v1beta3/models/text-bison-001:generateText?key=<enter-your-key-here>"
 
 # Initialize genai models
 model = genai.GenerativeModel('gemini-pro')
 
-
 def gemini(input, file, chatbot=[]):
     """
     Function to handle gemini model and gemini vision model interactions.
@@ -56,9 +48,7 @@ def gemini(input, file, chatbot=[]):
         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}")
@@ -69,7 +59,7 @@ def gemini(input, file, chatbot=[]):
 # Define the Gradio Blocks interface
 with gr.Blocks() as demo:
     # Add a centered header using HTML
-    gr.HTML("<center><h1>Gemini PRO API</h1></center>")
+    gr.HTML("<center><h1>Gemini Chat PRO API</h1></center>")
 
     # Initialize the MultimodalChatbot component
     multi = MultimodalChatbot(value=[], height=800)
@@ -78,11 +68,11 @@ with gr.Blocks() as demo:
         # Textbox for user input with increased scale for better visibility
         tb = gr.Textbox(scale=4, placeholder='Input text and press Enter')
 
+       
 
     # Define the behavior on text submission
     tb.submit(gemini, [tb, multi], [multi, tb])
 
-   
 
 # Launch the demo with a queue to handle multiple users
 demo.queue().launch()