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import os
import gradio as gr
from google import genai
from google.genai.types import GenerateContentConfig, GoogleSearch, Tool
# Initialize GenAI Client
API_KEY = os.getenv("GOOGLE_API_KEY") # Ensure to set this in Hugging Face Secrets
client = genai.Client(api_key=API_KEY)
MODEL_ID = "gemini-2.0-flash-exp" # Replace with your desired model ID
def google_search_query(question):
try:
# Define the Google Search Tool
google_search_tool = Tool(google_search=GoogleSearch())
# Generate the response
response = client.models.generate_content(
model=MODEL_ID,
contents=question,
config=GenerateContentConfig(tools=[google_search_tool]),
)
# Extract AI response and search results
ai_response = response.text # AI response as plain text
search_results = response.candidates[0].grounding_metadata.search_entry_point.rendered_content
return ai_response, search_results
except Exception as e:
return f"Error: {str(e)}", ""
# Gradio Interface
app = gr.Interface(
fn=google_search_query,
inputs=gr.Textbox(lines=2, label="Ask a Question"),
outputs=[
gr.Textbox(label="AI Response"),
gr.HTML(label="Search Results"),
],
title="Google Search with Gemini AI",
description="Ask a question, and the AI will use Google search tools to provide an answer along with contextual search results.",
)
if __name__ == "__main__":
app.launch(share=True) |