🤖 Automated AI Updates System

An AI-powered news automation system that collects the latest AI news from multiple RSS feeds, summarizes it using Google's Gemini API, generates structured Markdown reports, and automatically publishes updates using GitHub Actions.

The system is designed to provide AI information in different formats for managers, executives, business professionals, data scientists, students, researchers, developers, and general readers.

📌 Features

📰 Fetches the latest AI news from multiple RSS feeds
🤖 Generates AI-powered summaries using Google Gemini
📄 Creates a complete AI News Report
📋 Generates an Executive Meeting Brief
✅ Generates an AI Action Board
📚 Generates AI Terminology
📑 Creates an Index of reports
🕒 Stores hourly reports automatically
⚡ Runs automatically using GitHub Actions
🔄 Supports automatic Gemini model fallback
💾 Automatically commits generated reports to GitHub
📊 Provides different reports for different audiences

👥 Who Should Read What?

This project generates different AI reports for different types of readers.

Audience	Recommended File	Purpose
👔 Manager / Executive	`MEETING_BRIEF.md`	Quick overview of important AI developments, business impact, and key points for decision-making
📊 Data Scientist / Data Analyst	`LATEST.md`	Follow detailed AI news, technologies, models, research, and industry trends
👨‍🎓 Student / Learner	`TERMINOLOGY.md`	Learn important AI concepts, technologies, and terminology
💼 Business / Product Professional	`ACTION_BOARD.md`	Identify AI opportunities, implications, and areas requiring action
🔬 Researcher	`INDEX.md` + `hourly/`	Explore historical AI developments and track how AI topics evolve
👨‍💻 Developer	`scripts/`	Understand the Python implementation, AI integration, report generation, and data flow
⚙️ DevOps / Automation Engineer	`.github/workflows/update.yml`	Understand GitHub Actions scheduling, execution, automation, and publishing
🧠 AI / ML Enthusiast	`LATEST.md` + `TERMINOLOGY.md`	Follow current AI developments while learning the concepts behind them
🌐 General Reader	`LATEST.md`	Quickly understand the most important current AI developments
🗂️ Project Maintainer	`scripts/update.py`	Understand the complete application pipeline and how all components work together

🎯 Quick Starting Guide

👔 Manager / Executive

Start with:

MEETING_BRIEF.md

Best for:

Major AI developments
Business impact
Important industry changes
Key points requiring attention
Decision-making

📊 Data Scientist / Data Analyst

Start with:

LATEST.md

Then explore:

INDEX.md

Best for:

AI trends
New AI technologies
Model releases
Research developments
Industry developments

👨‍🎓 Student / Learner

Start with:

TERMINOLOGY.md

Then read:

LATEST.md

Best for:

AI terminology
New technologies
Machine learning concepts
Generative AI
Industry vocabulary

💼 Business / Product Professional

Start with:

ACTION_BOARD.md

Then:

MEETING_BRIEF.md

Best for:

AI opportunities
Business implications
Important developments
Potential actions
Product opportunities

🔬 Researcher

Start with:

INDEX.md

Then explore:

hourly/

Best for:

Historical AI developments
Research announcements
Technology evolution
Tracking AI trends over time

👨‍💻 Developer

Start with:

scripts/update.py

Then explore:

scripts/

Best for understanding:

Python architecture
RSS data collection
Gemini API integration
AI summarization
Report generation
File generation
Automation pipeline

⚙️ DevOps / Automation Engineer

Start with:

.github/workflows/update.yml

Best for understanding:

GitHub Actions
Scheduled execution
Python environment setup
Dependency installation
Automated execution
Git commits
Automatic publishing

🧠 AI / ML Enthusiast

🌐 General Reader

Start with:

LATEST.md

This is the easiest way to understand the latest important developments in AI.

📂 Project Structure

awesome-ai-updates/
│
├── .github/
│   └── workflows/
│       └── update.yml
│
├── scripts/
│   ├── fetch_news.py
│   ├── summarize.py
│   ├── generate_report.py
│   ├── save_report.py
│   ├── generate_index.py
│   ├── save_index.py
│   ├── generate_meeting_brief.py
│   ├── save_meeting_brief.py
│   ├── generate_action_board.py
│   ├── save_action_board.py
│   ├── generate_terminology.py
│   ├── save_terminology.py
│   ├── test_gemini.py
│   └── update.py
│
├── hourly/
│
├── LATEST.md
├── INDEX.md
├── MEETING_BRIEF.md
├── ACTION_BOARD.md
├── TERMINOLOGY.md
├── reports.json
│
├── requirements.txt
├── README.md
└── .gitignore

🚀 Workflow

                    RSS FEEDS
                       │
                       ▼
               Fetch Latest AI News
                       │
                       ▼
                Gemini AI Processing
                       │
                       ▼
                 AI Summarization
                       │
                       ▼
                 Generate AI Report
                       │
          ┌────────────┼────────────┐
          │            │            │
          ▼            ▼            ▼
     LATEST.md    MEETING_BRIEF   ACTION_BOARD
          │            │            │
          └────────────┼────────────┘
                       │
             ┌─────────┴─────────┐
             ▼                   ▼
       TERMINOLOGY.md        INDEX.md
             │                   │
             └─────────┬─────────┘
                       ▼
                 Hourly Reports
                       │
                       ▼
                GitHub Actions
                       │
                       ▼
                 Git Commit
                       │
                       ▼
                GitHub Repository

🧠 Main Application Pipeline

The main controller is:

scripts/update.py

It coordinates the complete system.

Fetch News
    ↓
Generate Report
    ↓
Save Report
    ↓
Generate Index
    ↓
Save Index
    ↓
Generate Meeting Brief
    ↓
Save Meeting Brief
    ↓
Generate Action Board
    ↓
Save Action Board
    ↓
Generate Terminology
    ↓
Save Terminology

📰 News Collection

The system collects AI news from configured RSS feeds.

Main file:

scripts/fetch_news.py

Pipeline:

RSS Feeds
    ↓
fetch_news.py
    ↓
Latest AI Articles

🤖 AI Summarization

The collected news is processed using Google's Gemini API.

Main file:

scripts/summarize.py

Pipeline:

AI News
   ↓
Gemini API
   ↓
AI-generated summaries

The project supports automatic model fallback so that alternative configured Gemini models can be used when required.

📄 Generated Reports

The system generates several different reports for different audiences.

`LATEST.md`

Contains the latest AI news and generated summaries.

Recommended for:

Data Scientists
Data Analysts
AI/ML Enthusiasts
General Readers

`MEETING_BRIEF.md`

Provides an executive-oriented summary of important AI developments.

Recommended for:

Managers
Executives
Team Leads
Business Professionals

`ACTION_BOARD.md`

Converts AI developments into action-oriented insights.

Recommended for:

Product Professionals
Business Professionals
Managers
AI Strategy Teams

`TERMINOLOGY.md`

Contains important AI terminology and concepts extracted from the generated reports.

Recommended for:

Students
Beginners
AI/ML Learners
Developers learning AI

`INDEX.md`

Provides an index of generated reports and historical information.

Recommended for:

Researchers
Analysts
Project Maintainers

`hourly/`

Contains archived hourly AI reports.

Recommended for:

Researchers
Analysts
Anyone interested in historical AI developments

🐍 Python Scripts

The scripts/ directory contains the core implementation.

`fetch_news.py`

Collects AI news from RSS feeds.

`summarize.py`

Uses Gemini to summarize AI news.

`generate_report.py`

Generates the main AI report.

`save_report.py`

Saves generated reports.

`generate_index.py`

Generates the report index.

`save_index.py`

Saves the generated index.

`generate_meeting_brief.py`

Generates the executive meeting brief.

`save_meeting_brief.py`

Saves the meeting brief.

`generate_action_board.py`

Generates the AI action board.

`save_action_board.py`

Saves the action board.

`generate_terminology.py`

Generates AI terminology.

`save_terminology.py`

Saves the terminology report.

`test_gemini.py`

Used to test Gemini API functionality.

`update.py`

Main controller that executes the complete pipeline.

🧠 Technologies Used

Python 3.12
Google Gemini API
Google GenAI SDK
Feedparser
Requests
GitHub Actions
Markdown
Git

📦 Installation

Clone the Repository

git clone https://github.com/vkvinodhkumar/awesome-ai-updates.git

Move into the Project

cd awesome-ai-updates

Install Dependencies

pip install -r requirements.txt

🔑 Environment Variables

Create a .env file in the project root.

GEMINI_API_KEY=YOUR_API_KEY
GEMINI_MODEL=gemini-3-flash-preview

For GitHub Actions, store the Gemini API key as a GitHub Actions Secret.

Never commit API keys or other secrets to the repository.

🚀 How to Use

There are two main ways to use this project:

📖 Read the generated AI reports
⚙️ Run the AI news automation system

📖 1. Read the Generated Reports

You do not need to install anything if you only want to read the reports.

Choose the file based on your requirement:

If you are a...	Read	What you get
👔 Manager / Executive	`MEETING_BRIEF.md`	Executive-level AI updates and business insights
📊 Data Scientist / Analyst	`LATEST.md`	Latest AI news, technologies, models, and trends
👨‍🎓 Student / Learner	`TERMINOLOGY.md`	AI concepts, terminology, and technologies
💼 Business / Product Professional	`ACTION_BOARD.md`	AI opportunities, implications, and actions
🔬 Researcher	`INDEX.md` + `hourly/`	Historical AI developments and archived reports
👨‍💻 Developer	`scripts/`	Source code and implementation
⚙️ DevOps Engineer	`.github/workflows/update.yml`	Automation and scheduled workflow
🌐 General Reader	`LATEST.md`	Quick overview of current AI developments

▶️ 2. Run the Project Locally

Step 1 — Clone the Repository

git clone https://github.com/vkvinodhkumar/awesome-ai-updates.git

Step 2 — Enter the Project Directory

cd awesome-ai-updates

Step 3 — Install Dependencies

pip install -r requirements.txt

Step 4 — Configure Gemini API

Create a .env file in the project root:

GEMINI_API_KEY=YOUR_API_KEY
GEMINI_MODEL=gemini-3-flash-preview

Replace YOUR_API_KEY with your actual Gemini API key.

Never commit the .env file or API key to GitHub.

Step 5 — Run the Automation

Execute:

python scripts/update.py

The program will automatically:

Fetch AI News
      ↓
Process News
      ↓
Generate AI Summaries
      ↓
Generate AI Report
      ↓
Generate INDEX
      ↓
Generate Meeting Brief
      ↓
Generate Action Board
      ↓
Generate Terminology
      ↓
Save Reports

⚙️ GitHub Actions Automation

You can also allow GitHub Actions to run the project automatically.

The workflow is located at:

.github/workflows/update.yml

The workflow performs:

GitHub Actions
      ↓
Setup Python
      ↓
Install Dependencies
      ↓
Run scripts/update.py
      ↓
Generate Reports
      ↓
Commit Changes
      ↓
Push Changes

🔑 Configure GitHub Secret

For GitHub Actions, the Gemini API key should be stored as a repository secret.

Go to:

GitHub Repository
      ↓
Settings
      ↓
Secrets and variables
      ↓
Actions
      ↓
New repository secret

Create:

Name:
GEMINI_API_KEY

Value:
YOUR_GEMINI_API_KEY

The workflow reads the secret using:

env:
  GEMINI_API_KEY: ${{ secrets.GEMINI_API_KEY }}

⏰ Automatic Updates

The GitHub Actions workflow is scheduled to run every hour.

schedule:
  - cron: "0 * * * *"

This means:

Every hour
at minute 00
UTC

The workflow can also be started manually.

Go to:

Actions
   ↓
Automated AI Updates
   ↓
Run workflow

📄 Where to Find the Results

After the automation completes, generated files are available in the repository:

LATEST.md
INDEX.md
MEETING_BRIEF.md
ACTION_BOARD.md
TERMINOLOGY.md
reports.json
hourly/

Latest AI Updates

LATEST.md

Executive Summary

MEETING_BRIEF.md

Actionable Insights

ACTION_BOARD.md

AI Terminology

TERMINOLOGY.md

Historical Reports

hourly/

Report Index

INDEX.md

🔄 Typical Usage

A normal automated execution looks like this:

        New AI News
             ↓
        RSS Feeds
             ↓
       fetch_news.py
             ↓
        Gemini API
             ↓
       AI Summaries
             ↓
     generate_report.py
             ↓
      ┌──────┼──────┐
      ↓      ↓      ↓
   Latest  Meeting  Action
    News    Brief   Board
      │       │       │
      └───────┼───────┘
              ↓
        Terminology
              ↓
           INDEX
              ↓
       Hourly Archive
              ↓
        GitHub Commit

🛠️ Manual Development Usage

If you are modifying the project, you can run individual components for testing.

Test Gemini

python scripts/test_gemini.py

Run the complete pipeline

python scripts/update.py

The recommended approach is:

python scripts/update.py

because it runs the complete pipeline.

🧭 Recommended Usage by User Type

👔 Manager

MEETING_BRIEF.md

Read this when you need a quick understanding of major AI developments and their potential business relevance.

📊 Data Scientist

LATEST.md
INDEX.md

Use these to follow AI technologies, models, research, and industry trends.

👨‍🎓 Student

TERMINOLOGY.md
LATEST.md

Use these to learn AI terminology while following current developments.

💼 Business / Product

ACTION_BOARD.md
MEETING_BRIEF.md

Use these to identify opportunities and potential actions related to AI developments.

🔬 Researcher

INDEX.md
hourly/

Use these to explore historical reports and track AI developments over time.

👨‍💻 Developer

scripts/
scripts/update.py

Use these to understand and modify the automation pipeline.

⚙️ DevOps Engineer

.github/workflows/update.yml

Use this to understand and manage GitHub Actions automation.

🚦 Simplest Way to Use the Project

If you are only interested in AI news:

Open → LATEST.md

If you are a manager:

Open → MEETING_BRIEF.md

If you are a student:

Open → TERMINOLOGY.md

If you want business actions:

Open → ACTION_BOARD.md

If you want historical information:

Open → INDEX.md

If you want to run the system yourself:

python scripts/update.py

If you want automatic hourly updates:

Configure GEMINI_API_KEY
        ↓
Enable GitHub Actions
        ↓
Workflow runs automatically

🗺️ Complete Usage Flow

Clone Repository
       ↓
Install Dependencies
       ↓
Configure Gemini API
       ↓
Run update.py
       ↓
Fetch AI News
       ↓
Generate AI Reports
       ↓
Read Generated Reports
       ↓
Configure GitHub Secret
       ↓
Enable GitHub Actions
       ↓
Automatic Hourly Updates

📊 Current Features

✅ RSS Feed Collection

✅ AI News Summarization

✅ Gemini API Integration

✅ AI News Report

✅ Executive Meeting Brief

✅ AI Action Board

✅ AI Terminology

✅ Report Index

✅ Hourly Report Archive

✅ Automatic GitHub Updates

✅ Scheduled GitHub Actions

✅ Automatic Git Commit and Push

✅ Gemini Model Fallback

🔮 Future Enhancements

📅 Daily Reports
📆 Weekly Reports
🗓️ Monthly Reports
🧠 AI Knowledge Base
📊 Advanced JSON Reporting
📈 AI Trend Analytics
🔎 Search Functionality
📊 Streamlit Dashboard
📈 Historical AI Trend Analysis
🏷️ AI Topic Classification
🔍 Advanced Report Search

⭐ Project Highlights

End-to-end AI news automation
RSS-based AI news collection
Gemini-powered summarization
Automated report generation
Executive-focused reporting
Action-oriented AI insights
AI terminology extraction
Historical hourly reports
Automated GitHub publishing
Scheduled GitHub Actions
Modular Python architecture
API integration
CI/CD automation
Easy to extend with new report types

👨‍💻 Author

Vinodh Kumar

Data Science & Analytics Enthusiast

GitHub: https://github.com/vkvinodhkumar

Name		Name	Last commit message	Last commit date
.github/workflows		.github/workflows
hourly/2026		hourly/2026
scripts		scripts
.gitignore		.gitignore
ACTION_BOARD.md		ACTION_BOARD.md
INDEX.md		INDEX.md
LATEST.md		LATEST.md
MEETING_BRIEF.md		MEETING_BRIEF.md
README.md		README.md
TERMINOLOGY.md		TERMINOLOGY.md
reports.json		reports.json
requirements.txt		requirements.txt

Latest commit

History

Folders and files

Repository files navigation

🤖 Automated AI Updates System

📌 Features

👥 Who Should Read What?

🎯 Quick Starting Guide

👔 Manager / Executive

📊 Data Scientist / Data Analyst

👨‍🎓 Student / Learner

💼 Business / Product Professional

🔬 Researcher

👨‍💻 Developer

⚙️ DevOps / Automation Engineer

🧠 AI / ML Enthusiast

🌐 General Reader

📂 Project Structure

🚀 Workflow

🧠 Main Application Pipeline

📰 News Collection

🤖 AI Summarization

📄 Generated Reports

LATEST.md

MEETING_BRIEF.md

ACTION_BOARD.md

TERMINOLOGY.md

INDEX.md

hourly/

🐍 Python Scripts

fetch_news.py

summarize.py

generate_report.py

save_report.py

generate_index.py

save_index.py

generate_meeting_brief.py

save_meeting_brief.py

generate_action_board.py

save_action_board.py

generate_terminology.py

save_terminology.py

test_gemini.py

update.py

🧠 Technologies Used

📦 Installation

Clone the Repository

Move into the Project

Install Dependencies

🔑 Environment Variables

🚀 How to Use

📖 1. Read the Generated Reports

▶️ 2. Run the Project Locally

Step 1 — Clone the Repository

Step 2 — Enter the Project Directory

Step 3 — Install Dependencies

Step 4 — Configure Gemini API

Step 5 — Run the Automation

⚙️ GitHub Actions Automation

🔑 Configure GitHub Secret

⏰ Automatic Updates

📄 Where to Find the Results

Latest AI Updates

Executive Summary

Actionable Insights

AI Terminology

Historical Reports

Report Index

🔄 Typical Usage

🛠️ Manual Development Usage

Test Gemini

Run the complete pipeline

🧭 Recommended Usage by User Type

👔 Manager

📊 Data Scientist

👨‍🎓 Student

💼 Business / Product

🔬 Researcher

👨‍💻 Developer

⚙️ DevOps Engineer

`LATEST.md`

`MEETING_BRIEF.md`

`ACTION_BOARD.md`

`TERMINOLOGY.md`

`INDEX.md`

`hourly/`

`fetch_news.py`

`summarize.py`

`generate_report.py`

`save_report.py`

`generate_index.py`

`save_index.py`

`generate_meeting_brief.py`

`save_meeting_brief.py`

`generate_action_board.py`

`save_action_board.py`

`generate_terminology.py`

`save_terminology.py`

`test_gemini.py`

`update.py`