app.py

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

# For better security practices, retrieve sensitive information like API keys from environment variables.

# Fetch an environment variable.
GOOGLE_API_KEY = os.environ.get('GOOGLE_API_KEY')
genai.configure(api_key=GOOGLE_API_KEY)


# Initialize genai models
model = genai.GenerativeModel('gemini-pro')

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 messages_dict in chatbot:
 user_text = messages_dict[0]['text']
 bot_text = messages_dict[1]['text']
 messages.extend([
 {'role': 'user', 'parts': [user_text]},
 {'role': 'model', 'parts': [bot_text]}
 ])
 messages.append({'role': 'user', 'parts': [input]})
 else:
 messages.append({'role': 'user', 'parts': [input]})

 try:
 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 Chat PRO 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='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()