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197 changed files with 9392 additions and 3089 deletions
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@ -60,9 +60,10 @@ Now you are ready to run Llama Stack with Ollama as the inference provider. You
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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export LLAMA_STACK_PORT=5001
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export LLAMA_STACK_PORT=8321
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docker run \
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-it \
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--pull always \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ~/.llama:/root/.llama \
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llamastack/distribution-{{ name }} \
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@ -80,6 +81,7 @@ cd /path/to/llama-stack
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docker run \
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-it \
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--pull always \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ~/.llama:/root/.llama \
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-v ./llama_stack/templates/ollama/run-with-safety.yaml:/root/my-run.yaml \
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@ -96,7 +98,7 @@ docker run \
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Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
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```bash
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export LLAMA_STACK_PORT=5001
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export LLAMA_STACK_PORT=8321
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llama stack build --template {{ name }} --image-type conda
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llama stack run ./run.yaml \
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@ -136,7 +136,7 @@ def get_distribution_template() -> DistributionTemplate:
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},
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run_config_env_vars={
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"LLAMA_STACK_PORT": (
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"5001",
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"8321",
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"Port for the Llama Stack distribution server",
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),
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"OLLAMA_URL": (
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@ -41,7 +41,6 @@ providers:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
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sinks: ${env.TELEMETRY_SINKS:console,sqlite}
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sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/ollama/trace_store.db}
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datasetio:
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@ -39,7 +39,6 @@ providers:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
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sinks: ${env.TELEMETRY_SINKS:console,sqlite}
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sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/ollama/trace_store.db}
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datasetio:
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