Update more distribution docs to be simpler and partially codegen'ed

llama_stack/templates/vllm-gpu/vllm.py

@@ -0,0 +1,74 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from llama_stack.distribution.datatypes import ModelInput, Provider
+from llama_stack.providers.inline.inference.vllm import VLLMConfig
+from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
+
+
+def get_distribution_template() -> DistributionTemplate:
+    providers = {
+        "inference": ["inline::vllm"],
+        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "safety": ["inline::llama-guard"],
+        "agents": ["inline::meta-reference"],
+        "telemetry": ["inline::meta-reference"],
+    }
+
+    inference_provider = Provider(
+        provider_id="vllm",
+        provider_type="inline::vllm",
+        config=VLLMConfig.sample_run_config(),
+    )
+
+    inference_model = ModelInput(
+        model_id="${env.INFERENCE_MODEL}",
+        provider_id="vllm",
+    )
+
+    return DistributionTemplate(
+        name="vllm-gpu",
+        distro_type="self_hosted",
+        description="Use a built-in vLLM engine for running LLM inference",
+        docker_image=None,
+        template_path=None,
+        providers=providers,
+        default_models=[inference_model],
+        run_configs={
+            "run.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": [inference_provider],
+                },
+                default_models=[inference_model],
+            ),
+        },
+        run_config_env_vars={
+            "LLAMASTACK_PORT": (
+                "5001",
+                "Port for the Llama Stack distribution server",
+            ),
+            "INFERENCE_MODEL": (
+                "meta-llama/Llama-3.2-3B-Instruct",
+                "Inference model loaded into the vLLM engine",
+            ),
+            "TENSOR_PARALLEL_SIZE": (
+                "1",
+                "Number of tensor parallel replicas (number of GPUs to use).",
+            ),
+            "MAX_TOKENS": (
+                "4096",
+                "Maximum number of tokens to generate.",
+            ),
+            "ENFORCE_EAGER": (
+                "False",
+                "Whether to use eager mode for inference (otherwise cuda graphs are used).",
+            ),
+            "GPU_MEMORY_UTILIZATION": (
+                "0.7",
+                "GPU memory utilization for the vLLM engine.",
+            ),
+        },
+    )