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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) |