AI Workflow Automation: From Idea to Production in One Hour

AI Workflow Automation: From Idea to Production in One Hour

💡 What You Will Learn

AI Workflow Automation: From Idea to Production in One Hour

import pandas as pd
from openai import OpenAI

def auto_report(csv_path):
    df = pd.read_csv(csv_path)
    summary = df.describe().to_string()
    client = OpenAI()
    resp = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{
            "role": "user",
            "content": ": \n" + summary
        }]
    )
    insights = resp.choices[0].message.content
    with pd.ExcelWriter("report.xlsx") as writer:
        df.to_excel(writer, sheet_name="", index=False)
        pd.DataFrame({"": [insights]}).to_excel(writer, sheet_name="AI", index=False)

auto_report("sales_2026.csv")

import schedule, time

def daily_pipeline():
    emails = check_gmail(label="INBOX", query="has:attachment")
    if not emails:
        return
    for email in emails:
        attachment = download_attachment(email)
        data = pd.read_csv(attachment)
        analysis = ai_analyze(data)
        report_path = generate_charts(analysis)
        send_email(
            to="manager@company.com",
            subject=f" - {email.date}",
            body=analysis["summary"],
            attachments=[report_path]
        )

schedule.every().day.at("09:00").do(daily_pipeline)

from crewai import Agent, Task, Crew

analyst = Agent(role="Analyst", goal="")
writer = Agent(role="Report Writer", goal="")
notifier = Agent(role="", goal="")

crew = Crew(
    agents=[analyst, writer, notifier],
    tasks=[
        Task(description=""),
        Task(description=""),
        Task(description="Slack")
    ]
)
crew.kickoff()