This application leverages Streamlit and OpenAI's GPT-4V model to analyze networking topology images. It provides a user-friendly interface that allows users to upload images of network topologies and receive insights and analyses generated by the GPT-4V model.
- Upload interface for network topology images.
- Real-time analysis of images using OpenAI's GPT-4V.
- Interactive chat interface to discuss and query network topology features.
- Session state management to maintain interaction history.
See the application in action:
- Python 3.12+
- Poetry for dependency management
- An OpenAI API key or Azure OpenAI deployment with vision support
-
Clone the repository:
git clone https://your-repository-url cd your-project-directory
-
Install dependencies using Poetry:
poetry install
-
Create a
.env
file in the root directory of the project and add your OpenAI API key:OPENAI_API_KEY=your_openai_api_key
-
Alternatively create a .env.azure and add your information such as:
AZURE_OPENAI_API_KEY=<key> AZURE_OPENAI_ENDPOINT=<Azure endpoint URL> AZURE_OPENAI_API_VERSION=2024-02-15-preview AZURE_OPENAI_DEPLOYMENT=<your deployment name>
To run the Streamlit application, use Poetry to handle the environment:
poetry run streamlit run main.py
Navigate to http://localhost:8501
in your web browser to interact with the application. Upload your network topology images to receive detailed analyses and insights.
Contributions are welcome! Please read CONTRIBUTING.md
for how to contribute to this project.
This project is licensed under the Apache-2.0 - see the LICENSE file for details.
- Streamlit for providing an excellent platform to build interactive apps.
For support, open an issue in the GitHub repository or contact the project maintainers.