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llama subcommands",id:"llama-subcommands",level:2},{value:"Sample Usage",id:"sample-usage",level:3},{value:"Downloading models",id:"downloading-models",level:2},{value:"List the downloaded models",id:"list-the-downloaded-models",level:2}];function t(e){const l={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",header:"header",li:"li",ol:"ol",p:"p",pre:"pre",strong:"strong",...(0,i.R)(),...e.components};return(0,s.jsxs)(s.Fragment,{children:[(0,s.jsx)(l.header,{children:(0,s.jsx)(l.h1,{id:"llama-server-side-cli-reference",children:"llama (server-side) CLI Reference"})}),"\n",(0,s.jsxs)(l.p,{children:["The ",(0,s.jsx)(l.code,{children:"llama"})," CLI tool helps you set up and use the Llama Stack. The CLI is available on your path after installing the ",(0,s.jsx)(l.code,{children:"llama-stack"})," package."]}),"\n",(0,s.jsx)(l.h2,{id:"installation",children:"Installation"}),"\n",(0,s.jsx)(l.p,{children:"You have two ways to install Llama Stack:"}),"\n",(0,s.jsxs)(l.ol,{children:["\n",(0,s.jsxs)(l.li,{children:["\n",(0,s.jsxs)(l.p,{children:[(0,s.jsx)(l.strong,{children:"Install as a package"}),":\nYou can install the repository directly from ",(0,s.jsx)(l.a,{href:"https://pypi.org/project/llama-stack/",children:"PyPI"})," by running the following command:"]}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{className:"language-bash",children:"pip install llama-stack\n"})}),"\n"]}),"\n",(0,s.jsxs)(l.li,{children:["\n",(0,s.jsxs)(l.p,{children:[(0,s.jsx)(l.strong,{children:"Install from source"}),":\nIf you prefer to install from the source code, follow these steps:"]}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{className:"language-bash",children:" mkdir -p ~/local\n cd ~/local\n git clone git@github.com:meta-llama/llama-stack.git\n\n uv venv myenv --python 3.12\n source myenv/bin/activate # On Windows: myenv\\Scripts\\activate\n\n cd llama-stack\n pip install -e .\n\n"})}),"\n"]}),"\n"]}),"\n",(0,s.jsxs)(l.h2,{id:"llama-subcommands",children:[(0,s.jsx)(l.code,{children:"llama"})," subcommands"]}),"\n",(0,s.jsxs)(l.ol,{children:["\n",(0,s.jsxs)(l.li,{children:[(0,s.jsx)(l.code,{children:"stack"}),": Allows you to build a stack using the ",(0,s.jsx)(l.code,{children:"llama stack"})," distribution and run a Llama Stack server. You can read more about how to build a Llama Stack distribution in the ",(0,s.jsx)(l.a,{href:"../distributions/building_distro",children:"Build your own Distribution"})," documentation."]}),"\n"]}),"\n",(0,s.jsxs)(l.p,{children:["For downloading models, we recommend using the ",(0,s.jsx)(l.a,{href:"https://huggingface.co/docs/huggingface_hub/guides/cli",children:"Hugging Face CLI"}),". See ",(0,s.jsx)(l.a,{href:"#downloading-models",children:"Downloading models"})," for more information."]}),"\n",(0,s.jsx)(l.h3,{id:"sample-usage",children:"Sample Usage"}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{children:"llama --help\n"})}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{children:"usage: llama [-h] {stack} ...\n\nWelcome to the Llama CLI\n\noptions:\n -h, --help show this help message and exit\n\nsubcommands:\n {stack}\n\n stack Operations for the Llama Stack / Distributions\n"})}),"\n",(0,s.jsx)(l.h2,{id:"downloading-models",children:"Downloading models"}),"\n",(0,s.jsxs)(l.p,{children:["You first need to have models downloaded locally. We recommend using the ",(0,s.jsx)(l.a,{href:"https://huggingface.co/docs/huggingface_hub/guides/cli",children:"Hugging Face CLI"})," to download models."]}),"\n",(0,s.jsx)(l.p,{children:"First, install the Hugging Face CLI:"}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{className:"language-bash",children:"pip install huggingface_hub[cli]\n"})}),"\n",(0,s.jsx)(l.p,{children:"Then authenticate and download models:"}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{className:"language-bash",children:"# Authenticate with Hugging Face\nhuggingface-cli login\n\n# Download a model\nhuggingface-cli download meta-llama/Llama-3.2-3B-Instruct --local-dir ~/.llama/Llama-3.2-3B-Instruct\n"})}),"\n",(0,s.jsx)(l.h2,{id:"list-the-downloaded-models",children:"List the downloaded models"}),"\n",(0,s.jsx)(l.p,{children:"To list the downloaded models, you can use the Hugging Face CLI:"}),"\n",(0,s.jsx)(l.pre,{children:(0,s.jsx)(l.code,{className:"language-bash",children:"# List all downloaded models in your local cache\nhuggingface-cli scan-cache\n"})})]})}function h(e={}){const{wrapper:l}={...(0,i.R)(),...e.components};return l?(0,s.jsx)(l,{...e,children:(0,s.jsx)(t,{...e})}):t(e)}}}]);
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It's designed to be a one-stop solution for developers who want to experiment with different AI providers without having to configure each one individually."]}),"\n",(0,s.jsx)(r.h2,{id:"provider-composition",children:"Provider Composition"}),"\n",(0,s.jsx)(r.p,{children:"The starter distribution consists of the following provider configurations:"}),"\n",(0,s.jsxs)(r.table,{children:[(0,s.jsx)(r.thead,{children:(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.th,{children:"API"}),(0,s.jsx)(r.th,{children:"Provider(s)"})]})}),(0,s.jsxs)(r.tbody,{children:[(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"agents"}),(0,s.jsx)(r.td,{children:(0,s.jsx)(r.code,{children:"inline::meta-reference"})})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"datasetio"}),(0,s.jsxs)(r.td,{children:[(0,s.jsx)(r.code,{children:"remote::huggingface"}),", ",(0,s.jsx)(r.code,{children:"inline::localfs"})]})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"eval"}),(0,s.jsx)(r.td,{children:(0,s.jsx)(r.code,{children:"inline::meta-reference"})})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"files"}),(0,s.jsx)(r.td,{children:(0,s.jsx)(r.code,{children:"inline::localfs"})})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"inference"}),(0,s.jsxs)(r.td,{children:[(0,s.jsx)(r.code,{children:"remote::openai"}),", ",(0,s.jsx)(r.code,{children:"remote::fireworks"}),", ",(0,s.jsx)(r.code,{children:"remote::together"}),", ",(0,s.jsx)(r.code,{children:"remote::ollama"}),", ",(0,s.jsx)(r.code,{children:"remote::anthropic"}),", ",(0,s.jsx)(r.code,{children:"remote::gemini"}),", ",(0,s.jsx)(r.code,{children:"remote::groq"}),", ",(0,s.jsx)(r.code,{children:"remote::sambanova"}),", ",(0,s.jsx)(r.code,{children:"remote::vllm"}),", ",(0,s.jsx)(r.code,{children:"remote::tgi"}),", ",(0,s.jsx)(r.code,{children:"remote::cerebras"}),", ",(0,s.jsx)(r.code,{children:"remote::llama-openai-compat"}),", ",(0,s.jsx)(r.code,{children:"remote::nvidia"}),", ",(0,s.jsx)(r.code,{children:"remote::hf::serverless"}),", ",(0,s.jsx)(r.code,{children:"remote::hf::endpoint"}),", ",(0,s.jsx)(r.code,{children:"inline::sentence-transformers"})]})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"safety"}),(0,s.jsx)(r.td,{children:(0,s.jsx)(r.code,{children:"inline::llama-guard"})})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"scoring"}),(0,s.jsxs)(r.td,{children:[(0,s.jsx)(r.code,{children:"inline::basic"}),", ",(0,s.jsx)(r.code,{children:"inline::llm-as-judge"}),", ",(0,s.jsx)(r.code,{children:"inline::braintrust"})]})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"telemetry"}),(0,s.jsx)(r.td,{children:(0,s.jsx)(r.code,{children:"inline::meta-reference"})})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"tool_runtime"}),(0,s.jsxs)(r.td,{children:[(0,s.jsx)(r.code,{children:"remote::brave-search"}),", ",(0,s.jsx)(r.code,{children:"remote::tavily-search"}),", ",(0,s.jsx)(r.code,{children:"inline::rag-runtime"}),", ",(0,s.jsx)(r.code,{children:"remote::model-context-protocol"})]})]}),(0,s.jsxs)(r.tr,{children:[(0,s.jsx)(r.td,{children:"vector_io"}),(0,s.jsxs)(r.td,{children:[(0,s.jsx)(r.code,{children:"inline::faiss"}),", ",(0,s.jsx)(r.code,{children:"inline::sqlite-vec"}),", ",(0,s.jsx)(r.code,{children:"inline::milvus"}),", ",(0,s.jsx)(r.code,{children:"remote::chromadb"}),", ",(0,s.jsx)(r.code,{children:"remote::pgvector"})]})]})]})]}),"\n",(0,s.jsx)(r.h2,{id:"inference-providers",children:"Inference Providers"}),"\n",(0,s.jsx)(r.p,{children:"The starter distribution includes a comprehensive set of inference providers:"}),"\n",(0,s.jsx)(r.h3,{id:"hosted-providers",children:"Hosted Providers"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://openai.com/api/",children:"OpenAI"})}),": GPT-4, GPT-3.5, O1, O3, O4 models and text embeddings -\nprovider ID: ",(0,s.jsx)(r.code,{children:"openai"})," - 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provider ID: ",(0,s.jsx)(r.code,{children:"anthropic"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_anthropic",children:"anthropic"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://gemini.google.com/",children:"Gemini"})}),": Gemini 1.5, 2.0, 2.5 models and text embeddings - provider ID: ",(0,s.jsx)(r.code,{children:"gemini"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_gemini",children:"gemini"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://groq.com/",children:"Groq"})}),": Fast Llama models (3.1, 3.2, 3.3, 4 Scout, 4 Maverick) - provider ID: ",(0,s.jsx)(r.code,{children:"groq"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_groq",children:"groq"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.sambanova.ai/",children:"SambaNova"})}),": Llama 3.1, 3.2, 3.3, 4 Scout, 4 Maverick models - provider ID: ",(0,s.jsx)(r.code,{children:"sambanova"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_sambanova",children:"sambanova"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.cerebras.ai/",children:"Cerebras"})}),": Cerebras AI models - provider ID: ",(0,s.jsx)(r.code,{children:"cerebras"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_cerebras",children:"cerebras"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.nvidia.com/",children:"NVIDIA"})}),": NVIDIA NIM - provider ID: ",(0,s.jsx)(r.code,{children:"nvidia"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_nvidia",children:"nvidia"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://huggingface.co/",children:"HuggingFace"})}),": Serverless and endpoint models - provider ID: ",(0,s.jsx)(r.code,{children:"hf::serverless"})," and ",(0,s.jsx)(r.code,{children:"hf::endpoint"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_hf_serverless",children:"huggingface-serverless"})," and ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_hf_endpoint",children:"huggingface-endpoint"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://aws.amazon.com/bedrock/",children:"Bedrock"})}),": AWS Bedrock models - provider ID: ",(0,s.jsx)(r.code,{children:"bedrock"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_bedrock",children:"bedrock"})]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"localremote-providers",children:"Local/Remote Providers"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://ollama.ai/",children:"Ollama"})}),": Local Ollama models - provider ID: ",(0,s.jsx)(r.code,{children:"ollama"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_ollama",children:"ollama"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://docs.vllm.ai/en/latest/",children:"vLLM"})}),": Local or remote vLLM server - provider ID: ",(0,s.jsx)(r.code,{children:"vllm"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_vllm",children:"vllm"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://github.com/huggingface/text-generation-inference",children:"TGI"})}),": Text Generation Inference server - Dell Enterprise Hub's custom TGI container too (use ",(0,s.jsx)(r.code,{children:"DEH_URL"}),") - provider ID: ",(0,s.jsx)(r.code,{children:"tgi"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/remote_tgi",children:"tgi"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.sbert.net/",children:"Sentence Transformers"})}),": Local embedding models - provider ID: ",(0,s.jsx)(r.code,{children:"sentence-transformers"})," - reference documentation: ",(0,s.jsx)(r.a,{href:"../../providers/inference/inline_sentence-transformers",children:"sentence-transformers"})]}),"\n"]}),"\n",(0,s.jsx)(r.p,{children:"All providers are disabled by default. So you need to enable them by setting the environment variables."}),"\n",(0,s.jsx)(r.h2,{id:"vector-io",children:"Vector IO"}),"\n",(0,s.jsx)(r.p,{children:"The starter distribution includes a comprehensive set of vector IO providers:"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://github.com/facebookresearch/faiss",children:"FAISS"})}),": Local FAISS vector store - enabled by\ndefault - provider ID: ",(0,s.jsx)(r.code,{children:"faiss"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.sqlite.org/index.html",children:"SQLite"})}),": Local SQLite vector store - disabled by default - provider ID: ",(0,s.jsx)(r.code,{children:"sqlite-vec"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://www.trychroma.com/",children:"ChromaDB"})}),": Remote ChromaDB vector store - disabled by default - provider ID: ",(0,s.jsx)(r.code,{children:"chromadb"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://github.com/pgvector/pgvector",children:"PGVector"})}),": PostgreSQL vector store - disabled by default - provider ID: ",(0,s.jsx)(r.code,{children:"pgvector"})]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.strong,{children:(0,s.jsx)(r.a,{href:"https://milvus.io/",children:"Milvus"})}),": Milvus vector store - disabled by default - provider ID: ",(0,s.jsx)(r.code,{children:"milvus"})]}),"\n"]}),"\n",(0,s.jsx)(r.h2,{id:"environment-variables",children:"Environment Variables"}),"\n",(0,s.jsx)(r.p,{children:"The following environment variables can be configured:"}),"\n",(0,s.jsx)(r.h3,{id:"server-configuration",children:"Server Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"LLAMA_STACK_PORT"}),": Port for the Llama Stack distribution server (default: ",(0,s.jsx)(r.code,{children:"8321"}),")"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"api-keys-for-hosted-providers",children:"API Keys for Hosted Providers"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"OPENAI_API_KEY"}),": OpenAI API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"FIREWORKS_API_KEY"}),": Fireworks API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"TOGETHER_API_KEY"}),": Together API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"ANTHROPIC_API_KEY"}),": Anthropic API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"GEMINI_API_KEY"}),": Google Gemini API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"GROQ_API_KEY"}),": Groq API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"SAMBANOVA_API_KEY"}),": SambaNova API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"CEREBRAS_API_KEY"}),": Cerebras API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"LLAMA_API_KEY"}),": Llama API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"NVIDIA_API_KEY"}),": NVIDIA API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"HF_API_TOKEN"}),": HuggingFace API token"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"local-provider-configuration",children:"Local Provider Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"OLLAMA_URL"}),": Ollama server URL (default: ",(0,s.jsx)(r.code,{children:"http://localhost:11434"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"VLLM_URL"}),": vLLM server URL (default: ",(0,s.jsx)(r.code,{children:"http://localhost:8000/v1"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"VLLM_MAX_TOKENS"}),": vLLM max tokens (default: ",(0,s.jsx)(r.code,{children:"4096"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"VLLM_API_TOKEN"}),": vLLM API token (default: ",(0,s.jsx)(r.code,{children:"fake"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"VLLM_TLS_VERIFY"}),": vLLM TLS verification (default: ",(0,s.jsx)(r.code,{children:"true"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"TGI_URL"}),": TGI server URL"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"model-configuration",children:"Model Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"INFERENCE_MODEL"}),": HuggingFace model for serverless inference"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"INFERENCE_ENDPOINT_NAME"}),": HuggingFace endpoint name"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"vector-database-configuration",children:"Vector Database Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"SQLITE_STORE_DIR"}),": SQLite store directory (default: ",(0,s.jsx)(r.code,{children:"~/.llama/distributions/starter"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"ENABLE_SQLITE_VEC"}),": Enable SQLite vector provider"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"ENABLE_CHROMADB"}),": Enable ChromaDB provider"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"ENABLE_PGVECTOR"}),": Enable PGVector provider"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"CHROMADB_URL"}),": ChromaDB server URL"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"PGVECTOR_HOST"}),": PGVector host (default: ",(0,s.jsx)(r.code,{children:"localhost"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"PGVECTOR_PORT"}),": PGVector port (default: ",(0,s.jsx)(r.code,{children:"5432"}),")"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"PGVECTOR_DB"}),": PGVector database name"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"PGVECTOR_USER"}),": PGVector username"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"PGVECTOR_PASSWORD"}),": PGVector password"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"tool-configuration",children:"Tool Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"BRAVE_SEARCH_API_KEY"}),": Brave Search API key"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"TAVILY_SEARCH_API_KEY"}),": Tavily Search API key"]}),"\n"]}),"\n",(0,s.jsx)(r.h3,{id:"telemetry-configuration",children:"Telemetry Configuration"}),"\n",(0,s.jsxs)(r.ul,{children:["\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"OTEL_SERVICE_NAME"}),": OpenTelemetry service name"]}),"\n",(0,s.jsxs)(r.li,{children:[(0,s.jsx)(r.code,{children:"TELEMETRY_SINKS"}),": Telemetry sinks (default: ",(0,s.jsx)(r.code,{children:"[]"}),")"]}),"\n"]}),"\n",(0,s.jsx)(r.h2,{id:"enabling-providers",children:"Enabling Providers"}),"\n",(0,s.jsx)(r.p,{children:"You can enable specific providers by setting appropriate environment variables. For example,"}),"\n",(0,s.jsx)(r.pre,{children:(0,s.jsx)(r.code,{className:"language-bash",children:"# self-hosted\nexport OLLAMA_URL=http://localhost:11434 # enables the Ollama inference provider\nexport VLLM_URL=http://localhost:8000/v1 # enables the vLLM inference provider\nexport TGI_URL=http://localhost:8000/v1 # enables the TGI inference provider\n\n# cloud-hosted requiring API key configuration on the server\nexport CEREBRAS_API_KEY=your_cerebras_api_key # enables the Cerebras inference provider\nexport NVIDIA_API_KEY=your_nvidia_api_key # enables the NVIDIA inference provider\n\n# vector providers\nexport MILVUS_URL=http://localhost:19530 # enables the Milvus vector provider\nexport CHROMADB_URL=http://localhost:8000/v1 # enables the ChromaDB vector provider\nexport PGVECTOR_DB=llama_stack_db # enables the PGVector vector provider\n"})}),"\n",(0,s.jsxs)(r.p,{children:['This distribution comes with a default "llama-guard" shield that can be enabled by setting the ',(0,s.jsx)(r.code,{children:"SAFETY_MODEL"})," environment variable to point to an appropriate Llama Guard model id. Use ",(0,s.jsx)(r.code,{children:"llama-stack-client models list"})," to see the list of available models."]}),"\n",(0,s.jsx)(r.h2,{id:"running-the-distribution",children:"Running the Distribution"}),"\n",(0,s.jsx)(r.p,{children:"You can run the starter distribution via Docker or venv."}),"\n",(0,s.jsx)(r.h3,{id:"via-docker",children:"Via Docker"}),"\n",(0,s.jsx)(r.p,{children:"This method allows you to get started quickly without having to build the distribution code."}),"\n",(0,s.jsx)(r.pre,{children:(0,s.jsx)(r.code,{className:"language-bash",children:"LLAMA_STACK_PORT=8321\ndocker run \\\n -it \\\n --pull always \\\n -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \\\n -e OPENAI_API_KEY=your_openai_key \\\n -e FIREWORKS_API_KEY=your_fireworks_key \\\n -e TOGETHER_API_KEY=your_together_key \\\n llamastack/distribution-starter \\\n --port $LLAMA_STACK_PORT\n"})}),"\n",(0,s.jsx)(r.h3,{id:"via-venv",children:"Via venv"}),"\n",(0,s.jsx)(r.p,{children:"Ensure you have configured the starter distribution using the environment variables explained above."}),"\n",(0,s.jsx)(r.pre,{children:(0,s.jsx)(r.code,{className:"language-bash",children:"# Install dependencies for the starter distribution\nuv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install\n\n# Run the server\nuv run --with llama-stack llama stack run starter\n"})}),"\n",(0,s.jsx)(r.h2,{id:"example-usage",children:"Example Usage"}),"\n",(0,s.jsx)(r.p,{children:"Once the distribution is running, you can use any of the available models. 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diff --git a/docs/v0.3.0/assets/js/0f1e4d85.324e522a.js b/docs/v0.3.0/assets/js/0f1e4d85.324e522a.js
new file mode 100644
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--- /dev/null
+++ b/docs/v0.3.0/assets/js/0f1e4d85.324e522a.js
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This allows you to:"}),"\n",(0,r.jsxs)(a.ul,{children:["\n",(0,r.jsx)(a.li,{children:"Create and maintain your own APIs independently"}),"\n",(0,r.jsx)(a.li,{children:"Share APIs with others without contributing to the main codebase"}),"\n",(0,r.jsx)(a.li,{children:"Keep API-specific code separate from the core Llama Stack code"}),"\n"]}),"\n",(0,r.jsx)(a.h2,{id:"configuration",children:"Configuration"}),"\n",(0,r.jsxs)(a.p,{children:["To enable external APIs, you need to configure the ",(0,r.jsx)(a.code,{children:"external_apis_dir"})," in your Llama Stack configuration. This directory should contain your external API specifications:"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-yaml",children:"external_apis_dir: ~/.llama/apis.d/\n"})}),"\n",(0,r.jsx)(a.h2,{id:"directory-structure",children:"Directory Structure"}),"\n",(0,r.jsx)(a.p,{children:"The external APIs directory should follow this structure:"}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{children:"apis.d/\n custom_api1.yaml\n custom_api2.yaml\n"})}),"\n",(0,r.jsx)(a.p,{children:"Each YAML file in these directories defines an API specification."}),"\n",(0,r.jsx)(a.h2,{id:"api-specification",children:"API Specification"}),"\n",(0,r.jsx)(a.p,{children:"Here's an example of an external API specification for a weather API:"}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-yaml",children:"module: weather\napi_dependencies:\n - inference\nprotocol: WeatherAPI\nname: weather\npip_packages:\n - 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names:"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-python",children:'# llama_stack_api_weather/api.py\nfrom llama_stack.providers.datatypes import Api, InlineProviderSpec, ProviderSpec\n\n\ndef available_providers() -> list[ProviderSpec]:\n return [\n InlineProviderSpec(\n api=Api.weather,\n provider_type="inline::darksky",\n pip_packages=[],\n module="llama_stack_provider_darksky",\n config_class="llama_stack_provider_darksky.DarkSkyWeatherImplConfig",\n ),\n ]\n'})}),"\n",(0,r.jsx)(a.p,{children:"A Protocol class like so:"}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-python",children:'# llama_stack_api_weather/api.py\nfrom typing import Protocol\n\nfrom llama_stack.schema_utils import webmethod\n\n\nclass WeatherAPI(Protocol):\n """\n A protocol for the Weather API.\n """\n\n @webmethod(route="/locations", method="GET")\n async def get_available_locations() -> dict[str, list[str]]:\n """\n Get the available locations.\n """\n ...\n'})}),"\n",(0,r.jsx)(a.h2,{id:"example-custom-api",children:"Example: Custom API"}),"\n",(0,r.jsx)(a.p,{children:"Here's a complete example of creating and using a custom API:"}),"\n",(0,r.jsxs)(a.ol,{children:["\n",(0,r.jsx)(a.li,{children:"First, create the API package:"}),"\n"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-bash",children:"mkdir -p llama-stack-api-weather\ncd llama-stack-api-weather\nmkdir src/llama_stack_api_weather\ngit init\nuv init\n"})}),"\n",(0,r.jsxs)(a.ol,{start:"2",children:["\n",(0,r.jsxs)(a.li,{children:["Edit ",(0,r.jsx)(a.code,{children:"pyproject.toml"}),":"]}),"\n"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-toml",children:'[project]\nname = "llama-stack-api-weather"\nversion = "0.1.0"\ndescription = "Weather API for Llama Stack"\nreadme = "README.md"\nrequires-python = ">=3.12"\ndependencies = ["llama-stack", "pydantic"]\n\n[build-system]\nrequires = ["setuptools"]\nbuild-backend = 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llama-stack-api-weather/src/llama_stack_api_weather/weather.py\nfrom typing import Protocol\n\nfrom llama_stack.providers.datatypes import (\n Api,\n ProviderSpec,\n RemoteProviderSpec,\n)\nfrom llama_stack.schema_utils import webmethod\n\n\ndef available_providers() -> list[ProviderSpec]:\n return [\n RemoteProviderSpec(\n api=Api.weather,\n provider_type="remote::kaze",\n config_class="llama_stack_provider_kaze.KazeProviderConfig",\n adapter_type="kaze",\n module="llama_stack_provider_kaze",\n pip_packages=["llama_stack_provider_kaze"],\n config_class="llama_stack_provider_kaze.KazeProviderConfig",\n ),\n ]\n\n\nclass WeatherProvider(Protocol):\n """\n A protocol for the Weather API.\n """\n\n @webmethod(route="/weather/locations", method="GET")\n async def get_available_locations() -> dict[str, list[str]]:\n """\n Get the available locations.\n """\n ...\n'})}),"\n",(0,r.jsxs)(a.ol,{start:"5",children:["\n",(0,r.jsx)(a.li,{children:"Create the API 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get_adapter_impl(config: KazeProviderConfig, _deps):\n from .kaze import WeatherKazeAdapter\n\n impl = WeatherKazeAdapter(config)\n await impl.initialize()\n return impl\n'})}),"\n",(0,r.jsx)(a.p,{children:"Configuration:"}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-python",children:'# llama-stack-provider-kaze/src/llama_stack_provider_kaze/config.py\nfrom pydantic import BaseModel, Field\n\n\nclass KazeProviderConfig(BaseModel):\n """Configuration for the Kaze weather provider."""\n\n base_url: str = Field(\n "https://api.kaze.io/v1",\n description="Base URL for the Kaze weather API",\n )\n'})}),"\n",(0,r.jsx)(a.p,{children:"Main implementation:"}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-python",children:'# llama-stack-provider-kaze/src/llama_stack_provider_kaze/kaze.py\nfrom llama_stack_api_weather.api import WeatherProvider\n\nfrom .config import KazeProviderConfig\n\n\nclass WeatherKazeAdapter(WeatherProvider):\n """Kaze weather provider implementation."""\n\n def __init__(\n self,\n config: KazeProviderConfig,\n ) -> None:\n self.config = config\n\n async def initialize(self) -> None:\n pass\n\n async def get_available_locations(self) -> dict[str, list[str]]:\n """Get available weather locations."""\n return {"locations": ["Paris", "Tokyo"]}\n'})}),"\n",(0,r.jsxs)(a.ol,{start:"5",children:["\n",(0,r.jsx)(a.li,{children:"Create the provider specification:"}),"\n"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-yaml",children:'# ~/.llama/providers.d/remote/weather/kaze.yaml\nadapter_type: kaze\npip_packages: ["llama_stack_provider_kaze"]\nconfig_class: llama_stack_provider_kaze.config.KazeProviderConfig\nmodule: llama_stack_provider_kaze\noptional_api_dependencies: []\n'})}),"\n",(0,r.jsxs)(a.ol,{start:"6",children:["\n",(0,r.jsx)(a.li,{children:"Install the provider package:"}),"\n"]}),"\n",(0,r.jsx)(a.pre,{children:(0,r.jsx)(a.code,{className:"language-bash",children:"uv pip 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the Llama Stack process"]}),"\n"]}),"\n",(0,a.jsx)(n.h3,{id:"provider-specification-common-between-inline-and-remote-providers",children:"Provider Specification (Common between inline and remote providers)"}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"provider_type"}),": The type of the provider to be installed (remote or inline). eg. ",(0,a.jsx)(n.code,{children:"remote::ollama"})]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"api"}),": The API for this provider, eg. ",(0,a.jsx)(n.code,{children:"inference"})]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"config_class"}),": The full path to the configuration class"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"module"}),": The Python module containing the provider implementation"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"optional_api_dependencies"}),": List of optional Llama Stack APIs that this provider can use"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"api_dependencies"}),": List of Llama Stack APIs that this provider depends on"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"provider_data_validator"}),": Optional validator for provider data."]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"pip_packages"}),": List of Python packages required by the provider"]}),"\n"]}),"\n",(0,a.jsx)(n.h3,{id:"remote-provider-specification",children:"Remote Provider Specification"}),"\n",(0,a.jsx)(n.p,{children:"Remote providers are used when you need to communicate with external services. Here's an example for a custom Ollama provider:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:'adapter_type: custom_ollama\nprovider_type: "remote::ollama"\npip_packages:\n- ollama\n- aiohttp\nconfig_class: llama_stack_ollama_provider.config.OllamaImplConfig\nmodule: llama_stack_ollama_provider\napi_dependencies: []\noptional_api_dependencies: []\n'})}),"\n",(0,a.jsx)(n.h4,{id:"remote-provider-configuration",children:"Remote Provider Configuration"}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"adapter_type"}),": A unique identifier for this adapter, eg. ",(0,a.jsx)(n.code,{children:"ollama"})]}),"\n"]}),"\n",(0,a.jsx)(n.h3,{id:"inline-provider-specification",children:"Inline Provider Specification"}),"\n",(0,a.jsx)(n.p,{children:"Inline providers run locally within the Llama Stack process. Here's an example for a custom vector store provider:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-yaml",children:"module: llama_stack_vector_provider\nprovider_type: inline::llama_stack_vector_provider\nconfig_class: llama_stack_vector_provider.config.VectorStoreConfig\npip_packages:\n - faiss-cpu\n - numpy\napi_dependencies:\n - inference\noptional_api_dependencies:\n - vector_io\nprovider_data_validator: llama_stack_vector_provider.validator.VectorStoreValidator\ncontainer_image: custom-vector-store:latest # optional\n"})}),"\n",(0,a.jsx)(n.h4,{id:"inline-provider-fields",children:"Inline Provider Fields"}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"container_image"}),": Optional container image to use instead of pip packages"]}),"\n"]}),"\n",(0,a.jsx)(n.h2,{id:"required-fields",children:"Required Fields"}),"\n",(0,a.jsx)(n.h3,{id:"all-providers",children:"All Providers"}),"\n",(0,a.jsxs)(n.p,{children:["All providers must contain a ",(0,a.jsx)(n.code,{children:"get_provider_spec"})," function in their ",(0,a.jsx)(n.code,{children:"provider"})," module. This is a standardized structure that Llama Stack expects and is necessary for getting things such as the config class. The ",(0,a.jsx)(n.code,{children:"get_provider_spec"})," method returns a structure identical to the ",(0,a.jsx)(n.code,{children:"adapter"}),". An example function may look like:"]}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:'from llama_stack.providers.datatypes import (\n ProviderSpec,\n Api,\n RemoteProviderSpec,\n)\n\n\ndef get_provider_spec() -> ProviderSpec:\n return RemoteProviderSpec(\n api=Api.inference,\n adapter_type="ramalama",\n pip_packages=["ramalama>=0.8.5", "pymilvus"],\n config_class="ramalama_stack.config.RamalamaImplConfig",\n module="ramalama_stack",\n )\n'})}),"\n",(0,a.jsx)(n.h4,{id:"remote-providers",children:"Remote Providers"}),"\n",(0,a.jsxs)(n.p,{children:["Remote providers must expose a ",(0,a.jsx)(n.code,{children:"get_adapter_impl()"})," function in their module that takes two arguments:"]}),"\n",(0,a.jsxs)(n.ol,{children:["\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"config"}),": An instance of the provider's config class"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"deps"}),": A dictionary of API dependencies"]}),"\n"]}),"\n",(0,a.jsx)(n.p,{children:"This function must return an instance of the provider's adapter class that implements the required protocol for the API."}),"\n",(0,a.jsx)(n.p,{children:"Example:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:"async def get_adapter_impl(\n config: OllamaImplConfig, deps: Dict[Api, Any]\n) -> OllamaInferenceAdapter:\n return OllamaInferenceAdapter(config)\n"})}),"\n",(0,a.jsx)(n.h4,{id:"inline-providers",children:"Inline Providers"}),"\n",(0,a.jsxs)(n.p,{children:["Inline providers must expose a ",(0,a.jsx)(n.code,{children:"get_provider_impl()"})," function in their module that takes two arguments:"]}),"\n",(0,a.jsxs)(n.ol,{children:["\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"config"}),": An instance of the provider's config class"]}),"\n",(0,a.jsxs)(n.li,{children:[(0,a.jsx)(n.code,{children:"deps"}),": A dictionary of API dependencies"]}),"\n"]}),"\n",(0,a.jsx)(n.p,{children:"Example:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-python",children:"async def get_provider_impl(\n config: VectorStoreConfig, deps: Dict[Api, Any]\n) -> VectorStoreImpl:\n impl = VectorStoreImpl(config, deps[Api.inference])\n await impl.initialize()\n return impl\n"})}),"\n",(0,a.jsx)(n.h2,{id:"dependencies",children:"Dependencies"}),"\n",(0,a.jsx)(n.p,{children:"The provider package must be installed on the system. For example:"}),"\n",(0,a.jsx)(n.pre,{children:(0,a.jsx)(n.code,{className:"language-bash",children:"$ uv pip show llama-stack-ollama-provider\nName: llama-stack-ollama-provider\nVersion: 0.1.0\nLocation: /path/to/venv/lib/python3.10/site-packages\n"})}),"\n",(0,a.jsx)(n.h2,{id:"best-practices",children:"Best Practices"}),"\n",(0,a.jsxs)(n.ol,{children:["\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Package Naming"}),": Use the prefix ",(0,a.jsx)(n.code,{children:"llama-stack-provider-"})," for your provider packages to make them easily identifiable."]}),"\n"]}),"\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Version Management"}),": Keep your provider package versioned and compatible with the Llama Stack version you're using."]}),"\n"]}),"\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Dependencies"}),": Only include the minimum required dependencies in your provider package."]}),"\n"]}),"\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Documentation"}),": Include clear documentation in your provider package about:"]}),"\n",(0,a.jsxs)(n.ul,{children:["\n",(0,a.jsx)(n.li,{children:"Installation requirements"}),"\n",(0,a.jsx)(n.li,{children:"Configuration options"}),"\n",(0,a.jsx)(n.li,{children:"Usage examples"}),"\n",(0,a.jsx)(n.li,{children:"Any limitations or known issues"}),"\n"]}),"\n"]}),"\n",(0,a.jsxs)(n.li,{children:["\n",(0,a.jsxs)(n.p,{children:[(0,a.jsx)(n.strong,{children:"Testing"}),": Include tests in your provider package to ensure it works correctly with Llama Stack.\nYou can refer to the ",(0,a.jsx)(n.a,{href:"https://github.com/meta-llama/llama-stack/blob/main/tests/integration/README.md",children:"integration tests\nguide"})," for more\ninformation. 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