Ask Noble | Virtual Agent

Overview

This Streamlit application is a virtual assistant, leveraging Retrieval Augmented Generation (RAG) and the LlamaIndex library to provide accurate and insightful information based on indexed documents. It's designed to mirror Noble Ackerson's expertise in emergent technologies, product strategy, and related subjects.

Features

• Factually accurate responses using RAG
• Multiple data handling options (e.g., MongoDB, SimpleDirectory)
• Modular, scalable, and designed for enterprise-grade deployment

Prerequisites

• Python 3.x
• Streamlit
• LlamaIndex library
• MongoDB (Optional)

Installation

1. Clone the repository.

   git clone https://github.com/stigsfoot/ask-noble-virtual-agent.git
   

2. Navigate to the project directory.

   cd ask-noble-virtual-agent
   

3. Install the required packages.

   pip install -r requirements.txt
   

Configuration

• The config_helper.py file sets up the Streamlit app's initial configurations.
• Data handlers are implemented in data_handlers.py.
• The factory pattern is implemented in data_handler_factory.py for future scalability in adding new data handlers.
• The readers.py file is used for different reader classes.

Usage

1. Start the Streamlit app.

   streamlit run streamlit_app.py
   

2. Select the data handler you wish to use from the dropdown.

3. Interact with the virtual assistant.

Troubleshooting

If you encounter any issues, check the following:

• Make sure all dependencies are installed.
• Ensure MongoDB is running if you use it as a data handler.

What does this app look like?

Contributing

Feel free to fork the repository and submit pull requests.

License

I guess this is a use at your own risk license.