impls -> inline, adapters -> remote (#381)

llama_stack/providers/inline/vllm/config.py

@@ -0,0 +1,46 @@
+# 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_models.schema_utils import json_schema_type
+from pydantic import BaseModel, Field, field_validator
+
+from llama_stack.providers.utils.inference import supported_inference_models
+
+
+@json_schema_type
+class VLLMConfig(BaseModel):
+    """Configuration for the vLLM inference provider."""
+
+    model: str = Field(
+        default="Llama3.2-3B-Instruct",
+        description="Model descriptor from `llama model list`",
+    )
+    tensor_parallel_size: int = Field(
+        default=1,
+        description="Number of tensor parallel replicas (number of GPUs to use).",
+    )
+    max_tokens: int = Field(
+        default=4096,
+        description="Maximum number of tokens to generate.",
+    )
+    enforce_eager: bool = Field(
+        default=False,
+        description="Whether to use eager mode for inference (otherwise cuda graphs are used).",
+    )
+    gpu_memory_utilization: float = Field(
+        default=0.3,
+    )
+
+    @field_validator("model")
+    @classmethod
+    def validate_model(cls, model: str) -> str:
+        permitted_models = supported_inference_models()
+        if model not in permitted_models:
+            model_list = "\n\t".join(permitted_models)
+            raise ValueError(
+                f"Unknown model: `{model}`. Choose from [\n\t{model_list}\n]"
+            )
+        return model