Gemini Scraper: Intelligent AI Conversation and Business Data Processing

import os
from datetime import datetime
from google import genai

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])


def collect_gemini_response(prompt_text):
    try:
        response = client.models.generate_content(
            model="gemini-2.5-flash",
            contents=prompt_text
        )

        return {
            "Prompt": prompt_text,
            "Response": response.text.strip() if response.text else "N/A",
            "Collected_At": datetime.utcnow().isoformat() + "Z"
        }

    except Exception as error:
        return {
            "Prompt": prompt_text,
            "Response": "N/A",
            "Collected_At": datetime.utcnow().isoformat() + "Z",
            "Error": str(error)
        }

# Example prompt for structured AI data collection.

sample_prompt = (
    "Summarize the latest grocery retail trends and list "
    "three important factors affecting online grocery pricing."
)
result = collect_gemini_response(sample_prompt)
print(result)