DevOps Assistant 🤖

The DevOps Assistant is an AI-powered tool designed to help DevOps engineers and system administrators automate tasks, execute commands on remote servers, and generate accurate Bash commands using a local LLM (Large Language Model). It integrates with Streamlit for a user-friendly interface and uses SQLite for command history and caching.

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Features ✨

• SSH Integration: Connect to remote servers securely via SSH.
• AI-Powered Command Generation: Use a local LLM (e.g., Ollama) to generate accurate Bash commands.
• Command Execution: Execute commands on remote servers and view results in real-time.
• Command History: Store and retrieve past commands and responses for future reference.
• Caching Mechanism: Cache frequently used commands to improve response times.
• User Authentication: Secure access with user authentication (optional).
• Streamlit UI: Intuitive and interactive web-based interface.

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Prerequisites 📊

Before running the DevOps Assistant, ensure you have the following installed:

• Python 3.8+: Download Python
• Ollama: A local LLM server. Install Ollama
• Streamlit: For the web interface.
• Paramiko: For SSH connections.
• SQLite3: For database storage (included with Python).

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Installation 🛠️

1. Clone the repository:

   git clone https://github.com/Rhul27/DevOpsAssistant.git
   cd DevOpsAssistant

2. Install dependencies:

   pip install -r requirements.txt

3. Set up Ollama:

   Install Ollama and start the server:

   ollama serve

   Download a model (e.g., llama3.2):

   ollama pull llama3.2

4. Run the Streamlit app:

   streamlit run main.py

5. Access the app: Open your browser and navigate to http://localhost:8501.

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Usage 🚀

Connect to the Server:

1. Enter the server's IP address, username, and password in the sidebar.
2. Click "Connect to Server".

Connect to the LLM Model:

1. Select a model from the dropdown in the sidebar.
2. Click "Connect to LLM Model".

Ask a Question:

1. Enter your question in the main input box (e.g., "How do I check disk usage on Linux?").
2. Click "Submit" to get a response.

View Command History:

All executed commands and responses are stored in the database and displayed in the Command History section.

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Folder Structure 🗂️

DevOpsAssistant/
├── Core/                     # Core functionality
│   ├── func.py               # SSH, LLM, and command execution
│   ├── database.py           # Database operations
│   ├── auth.py               # User authentication
│   └── utils.py              # Utility functions
├── models/                   # Data models
│   └── command_history.py    # SQLite model for command history
├── main.py                   # Streamlit app entry point
├── requirements.txt          # Python dependencies
└── devops_assistant.db       # SQLite database file

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Configuration ⚙️

• Ollama Server URL: Default is http://localhost:11434. Update in the sidebar if needed.
• Default Model: Set to llama3.2. Change in func.py if required.
• SSH Timeout: Default is 10 seconds. Adjust in func.py.

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Contributing 🤝

Contributions are welcome! If you'd like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/YourFeatureName

3. Commit your changes:

   git commit -m 'Add some feature'

4. Push to the branch:

   git push origin feature/YourFeatureName

5. Open a pull request.

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License 📝

This project is licensed under the MIT License. See the LICENSE file for details.

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Acknowledgments 🙏

• Ollama: For providing the local LLM server.
• Streamlit: For the easy-to-use web interface.
• Paramiko: For SSH connectivity.