# Tangram for Elixir
- [Watch the Video](https://www.tangram.xyz)
- [Read the Docs](https://www.tangram.xyz/docs)
The Tangram Elixir package makes it easy to make predictions with your Tangram machine learning model from Elixir.
## Usage
Add the `tangram` package to your `mix.exs`.
```elixir
model = Tangram.load_model_from_path("heart_disease.tangram")
input = %{
:age => 63.0,
:gender => "male",
# ...
}
output = Tangram.predict(model, input)
```
For more information, [read the docs](https://www.tangram.xyz/docs).
## Platform Support
Tangram for Elixir is currently supported on Linux, macOS, and Windows with AMD64 CPUs. Are you interested in another platform? [Open an issue](https://github.com/tangramxyz/tangram/issues/new) or send us an email at [help@tangram.xyz](mailto:help@tangram.xyz).
## Examples
The source for this package contains two examples, `examples/basic.exs` and `examples/advanced.exs`.
### Basic
The basic example demonstrates loading a model from a `.tangram` file and making a prediction.
To run the example:
```
$ mix run examples/basic.exs
```
### Advanced
The advanced example demonstrates logging predictions and true values to the Tangram app. Before running the example, run `tangram app` to start the app running locally, open `http://localhost:8080` in your browser, and upload the file `examples/heart_disease.tangram` to it.
To run the example:
```
$ TANGRAM_URL=http://localhost:8080 mix run examples/advanced.exs
```
Now if you refresh the production stats or production metrics tabs for the model you uploaded, you should see predictions and true values.
For more information, [read the docs](https://www.tangram.xyz/docs).
### Notes
- On Alpine Linux, Tangram for Elixir requires the `libgcc` library to be installed. It is not installed by default in the Alpine Linux docker image, but will very likely be a dependency of software you are already using. If not, you can run `apk add libgcc` to install it. We have opened [this issue](https://github.com/rust-lang/rust/issues/82521) with Rust to hopefully eliminate this requirement in the future.