Twitter AI Bot 🤖

An automated Twitter/X bot that generates and posts engaging AI and tech-related content using Google's Gemini API with integrated web search capabilities.

📋 Overview

This bot automatically:

1. Generates engaging tweets about AI, ML, and tech topics
2. Uses Google's Grounding Search to find latest information
3. Avoids posting duplicate content
4. Posts to Twitter/X automatically
5. Tracks all posted content in CSV format

🏗️ Architecture

Twitter/
├── main.py                 # Main application entry point
├── requirements.txt        # Python dependencies
├── run_main.bat           # Windows batch script for automation
├── core/
│   ├── config.py          # Configuration and credentials
│   ├── genai.py           # Content generation using Gemini
│   ├── posting.py         # Twitter/X posting functionality
│   └── web_search.py      # Web search utilities
└── data/
    └── post_history.csv   # Track posted tweets

🔄 How It Works

1. Initialization & Validation (main.py)

• Validates all required API credentials (Twitter & Gemini)
• Loads post history from CSV to avoid duplicates

2. Content Generation (core/genai.py)

The ContentGenerator class offers two modes:

Web Search Mode (Recommended)

generate_tweet_with_search(topic=None, previous_posts=None)

• Uses Google's Grounding Search to find latest information
• Generates tweets based on current trends and news
• More relevant and timely content

Simple Mode (Faster)

generate_tweet_simple(topic=None, previous_posts=None)

• Generates content without web search
• Faster but may be less current
• Uses Gemini's knowledge cutoff

Tweet Generation Process:

1. Selects a random topic from predefined list (or uses specified topic)
2. Builds a prompt with requirements:
   • Max 280 characters
   • Engaging question, code snippet, or interesting fact
   • 1-2 relevant hashtags
   • Educational but entertaining
3. Uses Gemini API to generate content
4. Cleans and truncates to Twitter limits

3. Duplicate Prevention

• Checks generated tweet against previous_posts list
• Prevents posting identical content
• Maintains post history in CSV file

4. Posting to Twitter (core/posting.py)

post_tweet(text)

• Uses Tweepy library with Twitter API v2
• Authenticates using OAuth 1.0a
• Posts tweet and returns tweet ID
• Handles errors gracefully

5. History Tracking

• Saves each post to data/post_history.csv
• Records: timestamp, topic, and tweet text
• Used for duplicate detection in future runs

🔑 Configuration

Required Environment Variables (.env)

# Twitter API Credentials
BEARER_TOKEN=your_bearer_token
API_KEY=your_api_key
API_SECRET=your_api_secret
ACCESS_TOKEN=your_access_token
ACCESS_TOKEN_SECRET=your_access_token_secret

# Gemini API
GEMINI_API_KEY=your_gemini_api_key

Configurable Settings (core/config.py)

# Topics for tweet generation
TOPICS = [
    'Artificial Intelligence',
    'Generative AI',
    'Machine Learning',
    'Python Programming',
    'Data Science',
    'Deep Learning',
    'Natural Language Processing',
    'Computer Vision',
    'Neural Networks',
    'Large Language Models',
    # ... more topics
]

# Model configurations
GEMINI_TEXT_MODEL = "gemini-2.5-flash"
TEMPERATURE = 0.7
MAX_TWEET_LENGTH = 280

🚀 Installation

1. Clone the repository

cd c:\Users\ravid\Desktop\Codes\Projects\Twitter

2. Install dependencies

pip install -r requirements.txt

3. Set up environment variables

Create a .env file in the root directory with your API credentials:

BEARER_TOKEN=...
API_KEY=...
API_SECRET=...
ACCESS_TOKEN=...
ACCESS_TOKEN_SECRET=...
GEMINI_API_KEY=...

4. Create data directory

mkdir data

💻 Usage

Manual Execution

python main.py

Automated Execution (Windows)

run_main.bat

This batch file can be scheduled using Windows Task Scheduler for automatic posting.

Example Output

🚀 Starting Twitter Bot...
======================================================================
✅ All credentials validated successfully!
======================================================================
📚 Loaded 42 previous posts from history
======================================================================
🔍 Generating tweet with latest information...

📝 Topic: Artificial Intelligence
📄 Generated tweet:
What if AI could explain its reasoning in plain language? 🤔

New research shows models with "chain-of-thought" prompting improve accuracy by 40%!

#AI #MachineLearning

======================================================================
📤 Posting tweet to X...
✅ Tweet posted! ID: 1234567890
💾 Saved to post_history.csv
======================================================================
✅ Tweet posted successfully!
🔗 Tweet ID: 1234567890
======================================================================
🏁 Bot execution completed!

📦 Dependencies

• tweepy (>=4.14.0) - Twitter API client
• google-genai (>=1.0.0) - Google Gemini API
• python-dotenv (>=1.0.0) - Environment variable management
• pandas (>=2.0.0) - Data processing for CSV

🔍 Key Features

1. Smart Content Generation

• Uses Google Grounding Search for latest information
• Generates diverse content types:
  • Thought-provoking questions
  • Code snippets and challenges
  • Interesting facts and recent developments
  • Educational content with entertainment value

2. Duplicate Detection

• Maintains history of all posted tweets
• Compares new content against previous posts
• Prevents accidental reposts

3. Error Handling

• Validates credentials before execution
• Graceful error handling for API failures
• Detailed logging for debugging

4. Flexible Configuration

• Easy topic customization
• Adjustable temperature for creativity
• Multiple model support (Gemini, OpenAI)

🛠️ Advanced Usage

Custom Topic Generation

from core.genai import generate_tweet

topic, tweet = generate_tweet(
    use_web_search=True,
    topic="Quantum Computing",
    previous_posts=[]
)

Tech Article Generation

from core.genai import ContentGenerator

generator = ContentGenerator()
article = generator.generate_tech_article()

Web Search

from core.web_search import WebSearcher

searcher = WebSearcher()
result = searcher.search_tech_news()

📊 Data Storage

Post history is stored in data/post_history.csv:

timestamp	topic	text
2025-11-26T10:30:00	Artificial Intelligence	What if AI could...
2025-11-26T11:45:00	Machine Learning	Here's a cool Python one-liner...

🔐 Security Notes

• Never commit your .env file
• Keep API credentials secure
• Use environment variables for sensitive data
• Regularly rotate access tokens

🤝 Contributing

To add new topics:

1. Edit TOPICS list in core/config.py
2. Keep topics AI/tech-related for best results

To modify tweet style:

1. Edit prompt in _build_tweet_prompt() in core/genai.py
2. Adjust TEMPERATURE for creativity level

📝 License

This project is for personal use. Ensure compliance with Twitter's automation rules and API terms of service.

⚠️ Disclaimer

• Use responsibly and follow Twitter's automation rules
• Avoid excessive posting (rate limits)
• Ensure generated content aligns with Twitter's policies
• Monitor bot activity regularly

🐛 Troubleshooting

"Configuration error" message

• Check .env file exists and has all required variables
• Verify API credentials are correct

"Failed to post tweet"

• Check Twitter API rate limits
• Verify OAuth credentials are valid
• Ensure tweet length is under 280 characters

"Error generating tweet"

• Verify Gemini API key is valid
• Check internet connection for web search
• Review API quota limits

📞 Support

For issues or questions, review the error messages in the console output. Most issues are related to:

• Missing or invalid API credentials
• Network connectivity
• API rate limits
• Duplicate content detection

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Built with ❤️ using Google Gemini and Tweepy