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import os | |
import google.generativeai as genai | |
import gradio as gr | |
# Configure the API key for Google Generative AI | |
GOOGLE_API_KEY = "AIzaSyA9Bh3WRz6LzKaA7MDm6foj1dw8w8kh-gc" | |
genai.configure(api_key=GOOGLE_API_KEY) | |
# Set up the generation configuration | |
generation_config = { | |
"temperature": 1, | |
"top_p": 0.95, | |
"top_k": 64, | |
"max_output_tokens": 8192, | |
"response_mime_type": "text/plain", | |
} | |
# Load the model (Gemini 1.5 flash in this case) | |
model = genai.GenerativeModel( | |
model_name="gemini-1.5-flash", | |
generation_config=generation_config, | |
) | |
# Function to handle conversation | |
def generate_response(user_input): | |
chat_session = model.start_chat( | |
history=[{ | |
"role": "user", | |
"parts": [user_input], | |
}] | |
) | |
response = chat_session.send_message(user_input) | |
return response.text | |
# Gradio Interface | |
iface = gr.Interface( | |
fn=generate_response, | |
inputs="text", | |
outputs="text", | |
title="Recipe Generator", | |
description="Ask for recipes or any other text-based generation using Google's Gemini AI", | |
theme="default", | |
) | |
# Launch the Gradio app | |
if __name__ == "__main__": | |
iface.launch() |