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-2.5-flash" # Replace with your desired model ID def google_search_query(question): try: # Define the Google Search Tool google_search_tool = Tool(google_search=GoogleSearch()) # Make the prompt specific to perfumes and their production perfume_prompt = f""" You are an expert perfumer and fragrance chemist. Answer the following question strictly in the context of: - Perfumes and fragrances - Perfume production and formulation - Raw materials (natural and synthetic) - Extraction methods (steam distillation, enfleurage, solvent extraction, CO2 extraction) - Safety, stability, and IFRA regulations - Perfume notes, accords, and blending techniques Question: {question} """ # Generate the response response = client.models.generate_content( model=MODEL_ID, contents=perfume_prompt, 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 about Perfumes"), outputs=[ gr.Textbox(label="Perfume Expert AI Response"), gr.HTML(label="Perfume-Related Search Results"), ], title="Perfume Production Assistant", description="Ask questions about perfumes, fragrance formulation, raw materials, and production techniques. The AI uses Google search to provide accurate, industry-relevant answers.", ) if __name__ == "__main__": app.launch(share=True)