crypticpy / SNSensei

A Service Ticket analyzer using AI

StreamSensei

StreamSensei is an advanced ticket analysis tool designed to process and analyze large volumes of help desk tickets efficiently. It uses AI-powered analysis to extract insights, categorize issues, and provide summaries of ticket content.

Features

• Asynchronous processing of large ticket datasets
• Customizable analysis types
• Support for both OpenAI and Azure OpenAI APIs
• Interactive command-line interface
• Streamlit web application for easy use
• Detailed logging and error handling
• Configurable output formats

Prerequisites

• Python 3.10+
• OpenAI API key or Azure OpenAI API access

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/StreamSensei.git
   cd StreamSensei
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   

3. Install the required packages:

   pip install -r requirements.txt
   

4. Set up your environment variables: Create a .env file in the root directory and add your API keys:

   OPENAI_API_KEY=your_openai_api_key
   # Or for Azure OpenAI:
   # AZURE_OPENAI_API_KEY=your_azure_openai_api_key
   # AZURE_OPENAI_API_BASE=your_azure_openai_endpoint
   # AZURE_OPENAI_API_VERSION=your_api_version
   

Usage

Command Line Interface

Run the main script:

python main.py

Follow the interactive prompts to:

1. Select your input file
2. Choose columns for analysis
3. Select analysis types
4. Review job details and confirm execution

Streamlit Web Application

To run the Streamlit app:

streamlit run streamlit_app.py

Navigate to the provided local URL in your web browser to use the graphical interface.

Configuration

You can modify the config.py file to adjust various settings such as:

• API type (OpenAI or Azure)
• Model selection
• Batch processing parameters
• Output file naming conventions

Project Structure

• main.py: Command-line interface for the application
• streamlit_app.py: Streamlit web application
• app/: Core application logic
  • analyzer.py: Ticket analysis implementation
  • config.py: Configuration management
  • logging_config.py: Logging setup
  • menu.py: CLI menu functions
  • postprocessor.py: Output processing
  • preprocessor.py: Input data preprocessing
  • prompts.py: AI prompt generation
  • utils.py: Utility functions
• tests/: Unit tests

Contributing

Contributions to StreamSensei are welcome! Please feel free to submit a Pull Request.

License

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