Auto-generate distro yamls + docs (#468)

# What does this PR do?

Automatically generates
- build.yaml
- run.yaml
- run-with-safety.yaml
- parts of markdown docs

for the distributions.

## Test Plan

At this point, this only updates the YAMLs and the docs. Some testing
(especially with ollama and vllm) has been performed but needs to be
much more tested.

llama_stack/templates/remote-vllm/vllm.py

@@ -0,0 +1,100 @@
+# 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 pathlib import Path
+
+from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
+from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
+from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
+
+
+def get_distribution_template() -> DistributionTemplate:
+    providers = {
+        "inference": ["remote::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-inference",
+        provider_type="remote::vllm",
+        config=VLLMInferenceAdapterConfig.sample_run_config(
+            url="${env.VLLM_URL}",
+        ),
+    )
+
+    inference_model = ModelInput(
+        model_id="${env.INFERENCE_MODEL}",
+        provider_id="vllm-inference",
+    )
+    safety_model = ModelInput(
+        model_id="${env.SAFETY_MODEL}",
+        provider_id="vllm-safety",
+    )
+
+    return DistributionTemplate(
+        name="remote-vllm",
+        distro_type="self_hosted",
+        description="Use (an external) vLLM server for running LLM inference",
+        template_path=Path(__file__).parent / "doc_template.md",
+        providers=providers,
+        default_models=[inference_model, safety_model],
+        run_configs={
+            "run.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": [inference_provider],
+                },
+                default_models=[inference_model],
+            ),
+            "run-with-safety.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": [
+                        inference_provider,
+                        Provider(
+                            provider_id="vllm-safety",
+                            provider_type="remote::vllm",
+                            config=VLLMInferenceAdapterConfig.sample_run_config(
+                                url="${env.SAFETY_VLLM_URL}",
+                            ),
+                        ),
+                    ],
+                },
+                default_models=[
+                    inference_model,
+                    safety_model,
+                ],
+                default_shields=[ShieldInput(shield_id="${env.SAFETY_MODEL}")],
+            ),
+        },
+        docker_compose_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 server",
+            ),
+            "VLLM_URL": (
+                "http://host.docker.internal:5100}/v1",
+                "URL of the vLLM server with the main inference model",
+            ),
+            "MAX_TOKENS": (
+                "4096",
+                "Maximum number of tokens for generation",
+            ),
+            "SAFETY_VLLM_URL": (
+                "http://host.docker.internal:5101/v1",
+                "URL of the vLLM server with the safety model",
+            ),
+            "SAFETY_MODEL": (
+                "meta-llama/Llama-Guard-3-1B",
+                "Name of the safety (Llama-Guard) model to use",
+            ),
+        },
+    )