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docs: miscellaneous small fixes (#961)
- **[docs] Fix misc typos and formatting issues in intro docs** - **[docs]: Export variables (e.g. INFERENCE_MODEL) in getting_started** - **[docs] Show that `llama-stack-client configure` will ask for api key** # What does this PR do? Miscellaneous fixes in the documentation; not worth reporting an issue. ## Test Plan No code changes. Addressed issues spotted when walking through the guide. Confirmed locally. ## Sources Please link relevant resources if necessary. ## Before submitting - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Ran pre-commit to handle lint / formatting issues. - [ ] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests. --------- Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
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@ -23,7 +23,7 @@ Which templates / distributions to choose depends on the hardware you have for r
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- {dockerhub}`distribution-together` ([Guide](self_hosted_distro/together))
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- {dockerhub}`distribution-together` ([Guide](self_hosted_distro/together))
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- {dockerhub}`distribution-fireworks` ([Guide](self_hosted_distro/fireworks))
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- {dockerhub}`distribution-fireworks` ([Guide](self_hosted_distro/fireworks))
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- **Do you want to run Llama Stack inference on your iOS / Android device** Lastly, we also provide templates for running Llama Stack inference on your iOS / Android device:
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- **Do you want to run Llama Stack inference on your iOS / Android device?** Lastly, we also provide templates for running Llama Stack inference on your iOS / Android device:
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- [iOS SDK](ondevice_distro/ios_sdk)
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- [iOS SDK](ondevice_distro/ios_sdk)
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- [Android](ondevice_distro/android_sdk)
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- [Android](ondevice_distro/android_sdk)
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@ -25,7 +25,9 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
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| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
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| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
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You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.### Environment Variables
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You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.
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### Environment Variables
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The following environment variables can be configured:
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The following environment variables can be configured:
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@ -1,6 +1,6 @@
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# Quick Start
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# Quick Start
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In this guide, we'll walk through how you can use the Llama Stack (server and client SDK ) to test a simple RAG agent.
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In this guide, we'll walk through how you can use the Llama Stack (server and client SDK) to test a simple RAG agent.
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A Llama Stack agent is a simple integrated system that can perform tasks by combining a Llama model for reasoning with tools (e.g., RAG, web search, code execution, etc.) for taking actions.
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A Llama Stack agent is a simple integrated system that can perform tasks by combining a Llama model for reasoning with tools (e.g., RAG, web search, code execution, etc.) for taking actions.
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@ -42,8 +42,8 @@ To get started quickly, we provide various container images for the server compo
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Lets setup some environment variables that we will use in the rest of the guide.
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Lets setup some environment variables that we will use in the rest of the guide.
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```bash
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```bash
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INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
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export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
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LLAMA_STACK_PORT=8321
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export LLAMA_STACK_PORT=8321
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```
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```
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Next you can create a local directory to mount into the container’s file system.
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Next you can create a local directory to mount into the container’s file system.
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@ -82,8 +82,10 @@ pip install llama-stack-client
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Let's use the `llama-stack-client` CLI to check the connectivity to the server.
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Let's use the `llama-stack-client` CLI to check the connectivity to the server.
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```bash
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```bash
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llama-stack-client configure --endpoint http://localhost:$LLAMA_STACK_PORT
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$ llama-stack-client configure --endpoint http://localhost:$LLAMA_STACK_PORT
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llama-stack-client models list
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> Enter the API key (leave empty if no key is needed):
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Done! You can now use the Llama Stack Client CLI with endpoint http://localhost:8321
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$ llama-stack-client models list
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┃ identifier ┃ provider_id ┃ provider_resource_id ┃ metadata ┃
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┃ identifier ┃ provider_id ┃ provider_resource_id ┃ metadata ┃
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┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
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