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)