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docs: 0.2.2 doc updates (#1961)
Add updates to android site readme for 0.2.2
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@ -24,7 +24,7 @@ The key files in the app are `ExampleLlamaStackLocalInference.kt`, `ExampleLlama
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Add the following dependency in your `build.gradle.kts` file:
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Add the following dependency in your `build.gradle.kts` file:
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```
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```
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dependencies {
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dependencies {
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implementation("com.llama.llamastack:llama-stack-client-kotlin:0.1.4.2")
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implementation("com.llama.llamastack:llama-stack-client-kotlin:0.2.2")
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}
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}
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```
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```
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This will download jar files in your gradle cache in a directory like `~/.gradle/caches/modules-2/files-2.1/com.llama.llamastack/`
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This will download jar files in your gradle cache in a directory like `~/.gradle/caches/modules-2/files-2.1/com.llama.llamastack/`
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@ -37,11 +37,7 @@ For local inferencing, it is required to include the ExecuTorch library into you
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Include the ExecuTorch library by:
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Include the ExecuTorch library by:
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1. Download the `download-prebuilt-et-lib.sh` script file from the [llama-stack-client-kotlin-client-local](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/llama-stack-client-kotlin-client-local/download-prebuilt-et-lib.sh) directory to your local machine.
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1. Download the `download-prebuilt-et-lib.sh` script file from the [llama-stack-client-kotlin-client-local](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/llama-stack-client-kotlin-client-local/download-prebuilt-et-lib.sh) directory to your local machine.
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2. Move the script to the top level of your Android app where the app directory resides:
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2. Move the script to the top level of your Android app where the `app` directory resides.
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<p align="center">
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<img src="https://github.com/meta-llama/llama-stack-client-kotlin/blob/latest-release/doc/img/example_android_app_directory.png" style="width:300px">
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</p>
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3. Run `sh download-prebuilt-et-lib.sh` to create an `app/libs` directory and download the `executorch.aar` in that path. This generates an ExecuTorch library for the XNNPACK delegate.
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3. Run `sh download-prebuilt-et-lib.sh` to create an `app/libs` directory and download the `executorch.aar` in that path. This generates an ExecuTorch library for the XNNPACK delegate.
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4. Add the `executorch.aar` dependency in your `build.gradle.kts` file:
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4. Add the `executorch.aar` dependency in your `build.gradle.kts` file:
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```
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```
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@ -52,6 +48,8 @@ dependencies {
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}
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}
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```
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```
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See other dependencies for the local RAG in Android app [README](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/examples/android_app#quick-start).
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## Llama Stack APIs in Your Android App
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## Llama Stack APIs in Your Android App
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Breaking down the demo app, this section will show the core pieces that are used to initialize and run inference with Llama Stack using the Kotlin library.
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Breaking down the demo app, this section will show the core pieces that are used to initialize and run inference with Llama Stack using the Kotlin library.
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@ -60,7 +58,7 @@ Start a Llama Stack server on localhost. Here is an example of how you can do th
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```
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```
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conda create -n stack-fireworks python=3.10
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conda create -n stack-fireworks python=3.10
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conda activate stack-fireworks
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conda activate stack-fireworks
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pip install --no-cache llama-stack==0.1.4
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pip install --no-cache llama-stack==0.2.2
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llama stack build --template fireworks --image-type conda
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llama stack build --template fireworks --image-type conda
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export FIREWORKS_API_KEY=<SOME_KEY>
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export FIREWORKS_API_KEY=<SOME_KEY>
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llama stack run fireworks --port 5050
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llama stack run fireworks --port 5050
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