FXView - AI Landscape

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FXView is an interactive landscape of the AI ecosystem, powered by the CNCF's Landscape2 tool. It provides a dynamic and filterable view of AI companies and projects.

This project is supported by FusionX.

🚀 How it Works

The landscape is generated through a combination of data files and scripts:

1. Data Source: Company information is stored in individual Markdown/txt files within the /company directory. Logos for these companies are stored in the /logos directory.
2. Data Processing: A Python script, generate_landscape.py, reads the company Markdown/txt files, processes the data (e.g., generating pinyin prefixes for sorting, formatting URLs), and combines it into a single landscape.yml file.
3. Website Generation: The landscape2 command-line tool takes the landscape.yml file, along with settings.yml and the logos/ directory, to build a static HTML, CSS, and JavaScript website.
4. Deployment: The generated website is containerized using Docker and deployed to a cloud environment.

🙋‍ Getting Started (Viewing Locally)

To build and view the landscape on your local machine, follow these steps.

Prerequisites

• Python 3: Make sure you have Python 3 installed.
• Landscape2: You need to install the landscape2 CLI tool. You can find installation instructions here. The easiest way for macOS users is with Homebrew:

  brew install cncf/landscape2/landscape2

  Ubuntu/CentOS:

  curl --proto '=https' --tlsv1.2 -LsSf \
         https://github.com/cncf/landscape2/releases/download/v1.0.0/landscape2-installer.sh | sh

Steps

1. Clone the repository:

   git clone https://github.com/your-username/FXView-landscape.git
   cd FXView-landscape

2. Install Python dependencies:

   python -m pip install --upgrade pip
   pip install -r requirements.txt

3. Generate the landscape.yml file:

   python convert_images_to_svg.py
   python generate_landscape.py

   This command reads from the /company and /logos directories and creates the landscape.yml file.

4. Build the static website:

   landscape2 build \
           --data-file landscape.yml \
           --settings-file settings.yml \
           --logos-path ./logos/ \
           --output-dir build

   This will generate the static website in the build/ directory.

5. Clean up auto-generated English abbreviations (Optional)

   If your project contains Chinese descriptions or logos, run the replace.py script to remove auto-generated English text from the built website.

   python replace.py

6. Serve the website locally:

   landscape2 serve --landscape-dir build

   The landscape will be available at http://127.0.0.1:8000.

🤝 How to Contribute

Development

非开发人员

👨🏽‍💻 Deployment

Deployment is handled automatically by a GitHub Actions workflow defined in .github/workflows/deploy.yml. When changes are merged from the landprovide branch to the main branch, the workflow will:

1. Run the Python scripts to prepare the data and generate landscape.yml.
2. Build the static site using landscape2.
3. Build a Docker image containing the site.
4. Push the Docker image to our container registry.

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• ✨ This AI Landscape is a community-driven project. Your contributions are highly valued.*