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# What does this PR do? Our "run this line to get started" pipes into `sh`, but the default shell on Ubuntu (a common setup) is `dash`, which doesn't support `pipefail`: ``` dalton@ollama-test:~$ ls -l /usr/bin/sh lrwxrwxrwx 1 root root 4 Mar 31 2024 /usr/bin/sh -> dash ``` ``` $ curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/install.sh | sh sh: 8: set: Illegal option -o pipefail ``` Let's be explicit with `bash`? It covers Linux, WSL, macOS and I doubt anyone's trying to run Llama Stack on embedded systems :) ## Test Plan ``` dalton@ollama-test:~/llama-stack$ cat install.sh | sh This script must be run with bash dalton@ollama-test:~/llama-stack$ cat install.sh | bash ❌ Docker or Podman is required. Install Docker: https://docs.docker.com/get-docker/ or Podman: https://podman.io/getting-started/installation ```
177 lines
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Markdown
177 lines
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Markdown
# Llama Stack
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[](https://pypi.org/project/llama_stack/)
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[](https://pypi.org/project/llama-stack/)
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[](https://github.com/meta-llama/llama-stack/blob/main/LICENSE)
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[](https://discord.gg/llama-stack)
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[](https://github.com/meta-llama/llama-stack/actions/workflows/unit-tests.yml?query=branch%3Amain)
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[](https://github.com/meta-llama/llama-stack/actions/workflows/integration-tests.yml?query=branch%3Amain)
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[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb) | [**Discord**](https://discord.gg/llama-stack)
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### ✨🎉 Llama 4 Support 🎉✨
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We released [Version 0.2.0](https://github.com/meta-llama/llama-stack/releases/tag/v0.2.0) with support for the Llama 4 herd of models released by Meta.
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<details>
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<summary>👋 Click here to see how to run Llama 4 models on Llama Stack </summary>
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\
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*Note you need 8xH100 GPU-host to run these models*
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```bash
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pip install -U llama_stack
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MODEL="Llama-4-Scout-17B-16E-Instruct"
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# get meta url from llama.com
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llama model download --source meta --model-id $MODEL --meta-url <META_URL>
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# start a llama stack server
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INFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu
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# install client to interact with the server
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pip install llama-stack-client
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```
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### CLI
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```bash
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# Run a chat completion
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llama-stack-client --endpoint http://localhost:8321 \
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inference chat-completion \
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--model-id meta-llama/$MODEL \
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--message "write a haiku for meta's llama 4 models"
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ChatCompletionResponse(
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completion_message=CompletionMessage(content="Whispers in code born\nLlama's gentle, wise heartbeat\nFuture's soft unfold", role='assistant', stop_reason='end_of_turn', tool_calls=[]),
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logprobs=None,
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metrics=[Metric(metric='prompt_tokens', value=21.0, unit=None), Metric(metric='completion_tokens', value=28.0, unit=None), Metric(metric='total_tokens', value=49.0, unit=None)]
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)
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```
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### Python SDK
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```python
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from llama_stack_client import LlamaStackClient
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client = LlamaStackClient(base_url=f"http://localhost:8321")
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model_id = "meta-llama/Llama-4-Scout-17B-16E-Instruct"
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prompt = "Write a haiku about coding"
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print(f"User> {prompt}")
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response = client.inference.chat_completion(
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model_id=model_id,
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt},
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],
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)
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print(f"Assistant> {response.completion_message.content}")
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```
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As more providers start supporting Llama 4, you can use them in Llama Stack as well. We are adding to the list. Stay tuned!
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</details>
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### 🚀 One-Line Installer 🚀
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To try Llama Stack locally, run:
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```bash
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curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/install.sh | bash
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```
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### Overview
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Llama Stack standardizes the core building blocks that simplify AI application development. It codifies best practices across the Llama ecosystem. More specifically, it provides
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- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
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- **Plugin architecture** to support the rich ecosystem of different API implementations in various environments, including local development, on-premises, cloud, and mobile.
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- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment.
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- **Multiple developer interfaces** like CLI and SDKs for Python, Typescript, iOS, and Android.
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- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack.
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<div style="text-align: center;">
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<img
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src="https://github.com/user-attachments/assets/33d9576d-95ea-468d-95e2-8fa233205a50"
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width="480"
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title="Llama Stack"
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alt="Llama Stack"
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/>
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</div>
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### Llama Stack Benefits
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- **Flexible Options**: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choices.
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- **Consistent Experience**: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
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- **Robust Ecosystem**: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.
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By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.
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### API Providers
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Here is a list of the various API providers and available distributions that can help developers get started easily with Llama Stack.
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| **API Provider Builder** | **Environments** | **Agents** | **Inference** | **Memory** | **Safety** | **Telemetry** | **Post Training** |
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|:------------------------:|:----------------------:|:----------:|:-------------:|:----------:|:----------:|:-------------:|:-----------------:|
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| Meta Reference | Single Node | ✅ | ✅ | ✅ | ✅ | ✅ | |
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| SambaNova | Hosted | | ✅ | | ✅ | | |
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| Cerebras | Hosted | | ✅ | | | | |
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| Fireworks | Hosted | ✅ | ✅ | ✅ | | | |
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| AWS Bedrock | Hosted | | ✅ | | ✅ | | |
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| Together | Hosted | ✅ | ✅ | | ✅ | | |
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| Groq | Hosted | | ✅ | | | | |
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| Ollama | Single Node | | ✅ | | | | |
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| TGI | Hosted and Single Node | | ✅ | | | | |
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| NVIDIA NIM | Hosted and Single Node | | ✅ | | | | |
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| Chroma | Single Node | | | ✅ | | | |
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| PG Vector | Single Node | | | ✅ | | | |
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| PyTorch ExecuTorch | On-device iOS | ✅ | ✅ | | | | |
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| vLLM | Hosted and Single Node | | ✅ | | | | |
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| OpenAI | Hosted | | ✅ | | | | |
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| Anthropic | Hosted | | ✅ | | | | |
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| Gemini | Hosted | | ✅ | | | | |
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| watsonx | Hosted | | ✅ | | | | |
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| HuggingFace | Single Node | | | | | | ✅ |
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| TorchTune | Single Node | | | | | | ✅ |
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| NVIDIA NEMO | Hosted | | | | | | ✅ |
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### Distributions
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A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code. Here are some of the distributions we support:
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| **Distribution** | **Llama Stack Docker** | Start This Distribution |
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| Meta Reference | [llamastack/distribution-meta-reference-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-gpu/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-gpu.html) |
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| SambaNova | [llamastack/distribution-sambanova](https://hub.docker.com/repository/docker/llamastack/distribution-sambanova/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/sambanova.html) |
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| Cerebras | [llamastack/distribution-cerebras](https://hub.docker.com/repository/docker/llamastack/distribution-cerebras/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/cerebras.html) |
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| Ollama | [llamastack/distribution-ollama](https://hub.docker.com/repository/docker/llamastack/distribution-ollama/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/ollama.html) |
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| TGI | [llamastack/distribution-tgi](https://hub.docker.com/repository/docker/llamastack/distribution-tgi/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/tgi.html) |
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| Together | [llamastack/distribution-together](https://hub.docker.com/repository/docker/llamastack/distribution-together/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/together.html) |
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| Fireworks | [llamastack/distribution-fireworks](https://hub.docker.com/repository/docker/llamastack/distribution-fireworks/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/fireworks.html) |
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| vLLM | [llamastack/distribution-remote-vllm](https://hub.docker.com/repository/docker/llamastack/distribution-remote-vllm/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/remote-vllm.html) |
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### Documentation
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Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.
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* CLI references
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* [llama (server-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/index.html): Guide for using the `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
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* [llama (client-side) CLI Reference](https://llama-stack.readthedocs.io/en/latest/references/llama_stack_client_cli_reference.html): Guide for using the `llama-stack-client` CLI, which allows you to query information about the distribution.
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* Getting Started
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* [Quick guide to start a Llama Stack server](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html).
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* [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
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* The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
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* A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
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* [Contributing](CONTRIBUTING.md)
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* [Adding a new API Provider](https://llama-stack.readthedocs.io/en/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.
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### Llama Stack Client SDKs
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| **Language** | **Client SDK** | **Package** |
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| :----: | :----: | :----: |
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| Python | [llama-stack-client-python](https://github.com/meta-llama/llama-stack-client-python) | [](https://pypi.org/project/llama_stack_client/)
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| Swift | [llama-stack-client-swift](https://github.com/meta-llama/llama-stack-client-swift) | [](https://swiftpackageindex.com/meta-llama/llama-stack-client-swift)
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| Typescript | [llama-stack-client-typescript](https://github.com/meta-llama/llama-stack-client-typescript) | [](https://npmjs.org/package/llama-stack-client)
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| Kotlin | [llama-stack-client-kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) | [](https://central.sonatype.com/artifact/com.llama.llamastack/llama-stack-client-kotlin)
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Check out our client SDKs for connecting to a Llama Stack server in your preferred language, you can choose from [python](https://github.com/meta-llama/llama-stack-client-python), [typescript](https://github.com/meta-llama/llama-stack-client-typescript), [swift](https://github.com/meta-llama/llama-stack-client-swift), and [kotlin](https://github.com/meta-llama/llama-stack-client-kotlin) programming languages to quickly build your applications.
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You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repo.
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