refactor: enforce top-level imports for llama-stack-api

Enforce that all imports from llama-stack-api use the form:

from llama_stack_api import <symbol>

 This prevents external code from accessing internal package structure
 (e.g., llama_stack_api.agents, llama_stack_api.common.*) and establishes
 a clear public API boundary.

 Changes:
 - Export 400+ symbols from llama_stack_api/__init__.py
 - Include all API types, common utilities, and strong_typing helpers
 - Update files across src/llama_stack, docs/, tests/, scripts/
 - Convert all submodule imports to top-level imports
 - ensure docs use the proper importing structure

 Addresses PR review feedback requiring explicit __all__ definition to
 prevent "peeking inside" the API package.

Signed-off-by: Charlie Doern <cdoern@redhat.com>

tests/unit/providers/vector_io/conftest.py

@@ -9,8 +9,7 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import numpy as np
 import pytest
-from llama_stack_api.vector_io import Chunk, ChunkMetadata, QueryChunksResponse
-from llama_stack_api.vector_stores import VectorStore
+from llama_stack_api import Chunk, ChunkMetadata, QueryChunksResponse, VectorStore
 
 from llama_stack.core.storage.datatypes import KVStoreReference, SqliteKVStoreConfig
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig

tests/unit/providers/vector_io/test_faiss.py

@@ -9,10 +9,7 @@ from unittest.mock import MagicMock, patch
 
 import numpy as np
 import pytest
-from llama_stack_api.datatypes import HealthStatus
-from llama_stack_api.files import Files
-from llama_stack_api.vector_io import Chunk, QueryChunksResponse
-from llama_stack_api.vector_stores import VectorStore
+from llama_stack_api import Chunk, Files, HealthStatus, QueryChunksResponse, VectorStore
 
 from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
 from llama_stack.providers.inline.vector_io.faiss.faiss import (

tests/unit/providers/vector_io/test_sqlite_vec.py

@@ -8,7 +8,7 @@ import asyncio
 
 import numpy as np
 import pytest
-from llama_stack_api.vector_io import Chunk, QueryChunksResponse
+from llama_stack_api import Chunk, QueryChunksResponse
 
 from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import (
     SQLiteVecIndex,

tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py

@@ -10,16 +10,16 @@ from unittest.mock import AsyncMock, patch
 
 import numpy as np
 import pytest
-from llama_stack_api.common.errors import VectorStoreNotFoundError
-from llama_stack_api.vector_io import (
+from llama_stack_api import (
     Chunk,
     OpenAICreateVectorStoreFileBatchRequestWithExtraBody,
     OpenAICreateVectorStoreRequestWithExtraBody,
     QueryChunksResponse,
+    VectorStore,
     VectorStoreChunkingStrategyAuto,
     VectorStoreFileObject,
+    VectorStoreNotFoundError,
 )
-from llama_stack_api.vector_stores import VectorStore
 
 from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import VECTOR_DBS_PREFIX
 
@@ -222,7 +222,7 @@ async def test_insert_chunks_missing_db_raises(vector_io_adapter):
 
 async def test_insert_chunks_with_missing_document_id(vector_io_adapter):
     """Ensure no KeyError when document_id is missing or in different places."""
-    from llama_stack_api.vector_io import Chunk, ChunkMetadata
+    from llama_stack_api import Chunk, ChunkMetadata
 
     fake_index = AsyncMock()
     vector_io_adapter.cache["db1"] = fake_index
@@ -255,7 +255,7 @@ async def test_insert_chunks_with_missing_document_id(vector_io_adapter):
 
 async def test_document_id_with_invalid_type_raises_error():
     """Ensure TypeError is raised when document_id is not a string."""
-    from llama_stack_api.vector_io import Chunk
+    from llama_stack_api import Chunk
 
     # Integer document_id should raise TypeError
     from llama_stack.providers.utils.vector_io.vector_utils import generate_chunk_id

tests/unit/providers/vector_io/test_vector_utils.py

@@ -4,7 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from llama_stack_api.vector_io import Chunk, ChunkMetadata
+from llama_stack_api import Chunk, ChunkMetadata
 
 from llama_stack.providers.utils.vector_io.vector_utils import generate_chunk_id