How to Build Custom Automation Workflows Using Gemini Pro

Curating information at scale requires robust, low-maintenance scheduling architectures. In this guide, we show you how to leverage Google's new Gemini 2.5 Flash / Pro API to automate a custom technology curation and briefing pipeline.

Step 1: Parsing Technical RSS Feeds

To parse feeds reliably in Python, we use the `feedparser` library. It handles various feed formats (RSS 2.0, Atom) and parses timestamps cleanly.

import feedparser

def parse_feed(url):
    feed = feedparser.parse(url)
    articles = []
    for entry in feed.entries[:5]: # Top 5 latest
        articles.append({
            "title": entry.title,
            "url": entry.link,
            "published": entry.get("published", "")
        })
    return articles
        

Step 2: Curation & Summarization via Gemini

With our aggregated data, we call the Gemini API to filter out noise, write a concise summary, and identify exact "Workflow Impact" ratings for busy professionals.

from google import genai
from google.genai import types

client = genai.Client(api_key="YOUR_GEMINI_API_KEY")

def summarize_article(title, description):
    prompt = f"Analyze: {title}. Desc: {description}. Format as structured JSON card."
    response = client.models.generate_content(
        model='gemini-2.5-flash',
        contents=prompt,
        config=types.GenerateContentConfig(
            response_mime_type="application/json",
            response_schema=CurationSchema
        )
    )
    return response.text
        

Step 3: Cron Scheduling & Delivery

To run the pipeline daily, we register an async cron job using `APScheduler`. The scheduler wakes up at 7:00 AM UTC every morning, executes the scraping, routes content through Gemini, renders HTML templates, and dispatches them via Resend bulk email APIs.

By following this plan, you get a zero-maintenance automation workflow that delivers high-value tech updates on a stable schedule.