app.py

!pip install langchain google-generativeai langchain-google-genai gradio
import os

# Set the path to the service account key
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/content/firm-catalyst-437006-s4-407500537db5.json"

import os
import gradio as gr
from langchain_google_genai.chat_models import ChatGoogleGenerativeAI

# Set the path to the service account key
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "/content/firm-catalyst-437006-s4-407500537db5.json"

# Initialize the LLM
llm = ChatGoogleGenerativeAI(model="gemini-1.5-pro")

def chat_with_gemini(user_input):
    try:
        # Prepare the prompt in the expected format
        response = llm.predict(user_input)  # Using the 'predict' method instead
        return response
    except Exception as e:
        return f"Error: {str(e)}"

# Create a Gradio interface
iface = gr.Interface(
    fn=chat_with_gemini,
    inputs="text",
    outputs="text",
    title="Chatbot with Gemini 1.5",
    description="Ask me anything!"
)

# Launch the interface with debugging
iface.launch(debug=True)