semvec/pypi-packages huggingface dataset:
fbxloader 0.0.2
utility to read fbx file
Keywords: fbx

## FBXLoader for Python

> [!WARNING]
> This library has very limited features and is only intended for **reading mesh geometry from binary FBX files**, it doesn't support:
> * Reading ASCII FBX files.
> * Reading textures and materials even if they are encoded in the file.
> * Reading skeletons and animations. Note that the geometry may also be incorrect if the mesh is skinned.
> * Writing FBX files.
> However, this can be a starting point to implement more features in the future. Welcome to contribute!


### Install

```bash
# from pypi
pip install fbxloader

# from source
pip install git+https://github.com/ashawkey/fbxloader.git
```

### Usage

Python API:
```python
from fbxloader import FBXLoader

fbx = FBXLoader('model.fbx') # load from file or bytes

# similar to glb, fbx usually contains multiple meshes as a scene
# we provide a method to merge them into a single mesh and export as trimesh.Trimesh
mesh = fbx.export_trimesh()

# write to other formats (using trimesh API)
mesh.export('model.obj')

# meta: this is to provide some information on unimplemented features, you may inspect it to make sure if the model is expected to load correctly. e.g., hasDeformers=True usually means the model is skinned.
print(fbx.meta)
# {'hasImages': False, 'hasTextures': False, 'hasMaterials': True, 'hasDeformers': True, 'hasAnimations': True}
```

We also provide a CLI tool:
```bash
fbxconverter <input.fbx> <output.obj/ply/glb>
```

Lastly, we provide a testing script and also a fbx mesh as an example:
```bash
python tests/test.py examples/annulus.fbx
```

### Reference
The code is basically translated from [threejs's FBXLoader](https://github.com/mrdoob/three.js/blob/b1046960d9adb597ba0ead7ff4a31f16d0a49a79/examples/jsm/loaders/FBXLoader.js). 
Thanks to the threejs team and also copilot!
aicli100 1.1.1
A CLI to use AI directly from the Terminal.
Requires Python: >=3.8

# aicli100

AICLI100 is a command line interface for using AI.

## Features

- **Install and Check Ollama**: Automatically installs and checks the Ollama AI tool on Linux systems.
- **API Key Management**: Easily set and check API keys for OpenAI and Anthropic.
- **Model Management**: List available AI models and set the desired model for AI requests.
- **Command Line Interface**: Interact with the AI directly from the terminal using simple commands.

## Installation
### Using git
1. Clone the repository:
   ```sh
   git clone https://github.com/yourusername/aicli.git
   cd aicli
   ```

2. Create a virtual environment and activate it:
   ```sh
   python -m venv env
   source env/bin/activate  # On Windows use `env\Scripts\activate`
   ```

3. Install the required dependencies:
   ```sh
   pip install -r requirements.txt
   ```

4. Build the project:
   ```sh
   python -m build
   ```

### Using pip

1. Install the package:
   ```sh
   pip install aicli100
   ```
2. Run the app:
   ```sh
   aicli100
   ```

## Usage

1. Run the CLI application:
   ```sh
   python src/main.py
   ```

2. Use the following commands within the CLI:
   - `/help` or `/?`: Show help text.
   - `/exit`: Exit the application.
   - `/clear`: Clear the screen.
   - `/keys-check`: Check the status of API keys.
   - `/key-set open_ai <api_key>`: Set the OpenAI API key.
   - `/key-set anthropic <api_key>`: Set the Anthropic API key.
   - `/set-model <model>`: Set the AI model.
   - `/models`: List available AI models.

## Configuration

The configuration file is located at `~/.aicli_config.ini`. It stores API keys and user settings.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please open an issue or submit a pull request.

## Author

Roberto Fernandino - [romfernandino@gmail.com](mailto:romfernandino@gmail.com)

## Acknowledgements

- [Ollama](https://ollama.com)
- [OpenAI](https://openai.com)
- [Anthropic](https://www.anthropic.com)