https://github.com/a3ro-dev/gds_automations
https://github.com/a3ro-dev/gds_automations
Last synced: 8 months ago
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- Host: GitHub
- URL: https://github.com/a3ro-dev/gds_automations
- Owner: a3ro-dev
- License: mit
- Created: 2025-04-18T09:32:26.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2025-04-18T09:47:41.000Z (8 months ago)
- Last Synced: 2025-04-23T18:16:47.518Z (8 months ago)
- Language: Python
- Size: 25.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GDS-Lucknow MUN 2025 Delegate Affairs System
A Streamlit-based application to manage delegate outreach and tracking for the Global Diplomatic Summit-Lucknow MUN 2025.
## Features
- Secure login with optional "Remember Me" cookie-based authentication.
- 📧 **Cold Email Generator**:
- Use a built-in template or customize your own.
- Generate personalized invitation emails using Ollama or GROQ AI models.
- Copy messages to clipboard or export for further editing.
- 👥 **Delegate Management**:
- Add, search, filter, and edit delegate details (name, contact info, response status, follow-up dates).
- Inline data editor with dynamic row operations.
- Export current delegate list as CSV for offline review.
## Getting Started
### Prerequisites
- Python 3.8+
- [Ollama](https://ollama.com) running locally with the `gemma3:4b` model, if using Ollama personalization.
- GROQ API key configured in `.env` (if Ollama is unavailable).
### Installation
1. Clone the repository:
```bash
git clone https://github.com/your-org/GDS_automations.git
cd GDS_automations
```
2. Create a virtual environment and activate it:
```bash
python3 -m venv .venv
source .venv/bin/activate
```
3. Install dependencies:
```bash
pip install --upgrade pip
pip install -r requirements.txt
```
4. Create a `.env` file in the project root with the following variables:
```env
USER_NAME='usrnm'
USER_PASSWORD=G'pswd'
SECRET_KEY=your-secret-key
GROQ_API_KEY=your-groq-api-key # Only needed if Ollama is not available
```
**Note:** The values above are placeholders. Never commit your real credentials. Ensure that your `.env` file is added to `.gitignore` and kept out of version control.
## Usage
Run the Streamlit application:
```bash
streamlit run app.py
```
- Open your browser at `http://localhost:8501`.
- Log in with the credentials defined in `.env` (or use defaults).
- Navigate between **Cold Email Generator** and **Delegate Management** from the home page.
## Project Structure
```
├── app.py # Main Streamlit application
├── backend/ # AI personalization backend logic
│ └── backend.py # Message generation via Ollama or GROQ
├── delegates.csv # Persistent storage for delegate records
├── requirements.txt # Python dependencies
└── README.md # This documentation
```
## Configuration
- **Authentication**: Uses HMAC-signed cookies and session state for persisted login.
- **AI Models**: `ollama` and `groq` Python clients are used to generate personalized emails. Ollama is preferred when available.
- **Email Templates**: A base template is provided and can be edited directly in the UI.
## Contributing
1. Fork the repo and create a new branch for your feature:
```bash
git checkout -b feature/YourFeature
```
2. Make your changes, commit, and push:
```bash
git commit -am "Add your feature"
git push origin feature/YourFeature
```
3. Open a Pull Request describing your changes.
## License
This project is licensed under the MIT License. See [LICENSE](LICENSE) for details.