fix: rename llama_stack_api dir (#4155)

# What does this PR do?

the directory structure was src/llama-stack-api/llama_stack_api

instead it should just be src/llama_stack_api to match the other
packages.

update the structure and pyproject/linting config

---------

Signed-off-by: Charlie Doern <cdoern@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>

src/llama_stack_api/vector_stores.py

@@ -0,0 +1,51 @@
+# 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 typing import Literal
+
+from pydantic import BaseModel
+
+from llama_stack_api.resource import Resource, ResourceType
+
+
+# Internal resource type for storing the vector store routing and other information
+class VectorStore(Resource):
+    """Vector database resource for storing and querying vector embeddings.
+
+    :param type: Type of resource, always 'vector_store' for vector stores
+    :param embedding_model: Name of the embedding model to use for vector generation
+    :param embedding_dimension: Dimension of the embedding vectors
+    """
+
+    type: Literal[ResourceType.vector_store] = ResourceType.vector_store
+
+    embedding_model: str
+    embedding_dimension: int
+    vector_store_name: str | None = None
+
+    @property
+    def vector_store_id(self) -> str:
+        return self.identifier
+
+    @property
+    def provider_vector_store_id(self) -> str | None:
+        return self.provider_resource_id
+
+
+class VectorStoreInput(BaseModel):
+    """Input parameters for creating or configuring a vector database.
+
+    :param vector_store_id: Unique identifier for the vector store
+    :param embedding_model: Name of the embedding model to use for vector generation
+    :param embedding_dimension: Dimension of the embedding vectors
+    :param provider_vector_store_id: (Optional) Provider-specific identifier for the vector store
+    """
+
+    vector_store_id: str
+    embedding_model: str
+    embedding_dimension: int
+    provider_id: str | None = None
+    provider_vector_store_id: str | None = None