ran pre-commit hook fix

Fix lints
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Riandy Riandy 2024-12-05 11:06:49 +08:00
parent e80bf74c11
commit 5bdf6d8530

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@ -1,6 +1,6 @@
# Llama Stack Client Kotlin API Library # Llama Stack Client Kotlin API Library
We are excited to share a guide for a Kotlin Library that brings front the benefits of Llama Stack to your Android device. This library is a set of SDKs that provide a simple and effective way to integrate AI capabilities into your Android app whether it is local (on-device) or remote inference. We are excited to share a guide for a Kotlin Library that brings front the benefits of Llama Stack to your Android device. This library is a set of SDKs that provide a simple and effective way to integrate AI capabilities into your Android app whether it is local (on-device) or remote inference.
Features: Features:
- Local Inferencing: Run Llama models purely on-device with real-time processing. We currently utilize ExecuTorch as the local inference distributor and may support others in the future. - Local Inferencing: Run Llama models purely on-device with real-time processing. We currently utilize ExecuTorch as the local inference distributor and may support others in the future.
@ -26,7 +26,7 @@ dependencies {
implementation("com.llama.llamastack:llama-stack-client-kotlin:0.0.54") implementation("com.llama.llamastack:llama-stack-client-kotlin:0.0.54")
} }
``` ```
This will download jar files in your gradle cache in a directory like `~/.gradle/caches/modules-2/files-2.1/com.llama.llamastack/` This will download jar files in your gradle cache in a directory like `~/.gradle/caches/modules-2/files-2.1/com.llama.llamastack/`
If you plan on doing remote inferencing this is sufficient to get started. If you plan on doing remote inferencing this is sufficient to get started.
@ -58,7 +58,7 @@ Breaking down the demo app, this section will show the core pieces that are used
### Setup Remote Inferencing ### Setup Remote Inferencing
Start a Llama Stack server on localhost. Here is an example of how you can do this using the firework.ai distribution: Start a Llama Stack server on localhost. Here is an example of how you can do this using the firework.ai distribution:
``` ```
conda create -n stack-fireworks python=3.10 conda create -n stack-fireworks python=3.10
conda activate stack-fireworks conda activate stack-fireworks
pip install llama-stack=0.0.54 pip install llama-stack=0.0.54
llama stack build --template fireworks --image-type conda llama stack build --template fireworks --image-type conda
@ -71,7 +71,7 @@ Other inference providers: [Table](https://llama-stack.readthedocs.io/en/latest/
TODO: Link to Demo App on how to set this remote localhost in the Settings. TODO: Link to Demo App on how to set this remote localhost in the Settings.
### Initialize the Client ### Initialize the Client
A client serves as the primary interface for interacting with a specific inference type and its associated parameters. Only after client is initialized then you can configure and start inferences. A client serves as the primary interface for interacting with a specific inference type and its associated parameters. Only after client is initialized then you can configure and start inferences.
<table> <table>
<tr> <tr>
@ -80,7 +80,7 @@ A client serves as the primary interface for interacting with a specific inferen
</tr> </tr>
<tr> <tr>
<td> <td>
<pre> <pre>
client = LlamaStackClientLocalClient client = LlamaStackClientLocalClient
.builder() .builder()
.modelPath(modelPath) .modelPath(modelPath)
@ -94,7 +94,7 @@ client = LlamaStackClientLocalClient
```// remoteURL is a string like "http://localhost:5050" ```// remoteURL is a string like "http://localhost:5050"
client = LlamaStackClientOkHttpClient client = LlamaStackClientOkHttpClient
.builder() .builder()
.baseUrl(remoteURL) .baseUrl(remoteURL)
.build() .build()
``` ```
</td> </td>
@ -243,4 +243,4 @@ This library throws exceptions in a single hierarchy for easy handling:
--- ---
The API interface is generated using the OpenAPI standard with [Stainless](https://www.stainlessapi.com/). The API interface is generated using the OpenAPI standard with [Stainless](https://www.stainlessapi.com/).