chore: Consistent naming for VectorIO providers (#1023)

# What does this PR do?

This changes all VectorIO providers classes to follow the pattern
`<ProviderName>VectorIOConfig` and `<ProviderName>VectorIOAdapter`. All
API endpoints for VectorIOs are currently consistent with `/vector-io`.

Note that API endpoint for VectorDB stay unchanged as `/vector-dbs`. 

## Test Plan

I don't have a way to test all providers. This is a simple renaming so
things should work as expected.

---------

Signed-off-by: Yuan Tang <terrytangyuan@gmail.com>

llama_stack/providers/remote/vector_io/chroma/__init__.py

@@ -8,10 +8,10 @@ from typing import Dict
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import ChromaRemoteImplConfig
+from .config import ChromaVectorIOConfig
 
 
-async def get_adapter_impl(config: ChromaRemoteImplConfig, deps: Dict[Api, ProviderSpec]):
+async def get_adapter_impl(config: ChromaVectorIOConfig, deps: Dict[Api, ProviderSpec]):
     from .chroma import ChromaVectorIOAdapter
 
     impl = ChromaVectorIOAdapter(config, deps[Api.inference])

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -16,13 +16,12 @@ from llama_stack.apis.inference import InterleavedContent
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
-from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
 from llama_stack.providers.utils.memory.vector_store import (
     EmbeddingIndex,
     VectorDBWithIndex,
 )
 
-from .config import ChromaRemoteImplConfig
+from .config import ChromaVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -89,7 +88,7 @@ class ChromaIndex(EmbeddingIndex):
 class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(
         self,
-        config: Union[ChromaRemoteImplConfig, ChromaInlineImplConfig],
+        config: Union[ChromaVectorIOConfig, ChromaVectorIOConfig],
         inference_api: Api.inference,
     ) -> None:
         log.info(f"Initializing ChromaVectorIOAdapter with url: {config}")
@@ -100,7 +99,7 @@ class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
         self.cache = {}
 
     async def initialize(self) -> None:
-        if isinstance(self.config, ChromaRemoteImplConfig):
+        if isinstance(self.config, ChromaVectorIOConfig):
             log.info(f"Connecting to Chroma server at: {self.config.url}")
             url = self.config.url.rstrip("/")
             parsed = urlparse(url)

llama_stack/providers/remote/vector_io/chroma/config.py

@@ -9,7 +9,7 @@ from typing import Any, Dict
 from pydantic import BaseModel
 
 
-class ChromaRemoteImplConfig(BaseModel):
+class ChromaVectorIOConfig(BaseModel):
     url: str
 
     @classmethod

llama_stack/providers/remote/vector_io/pgvector/__init__.py

@@ -8,12 +8,12 @@ from typing import Dict
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import PGVectorConfig
+from .config import PGVectorVectorIOConfig
 
 
-async def get_adapter_impl(config: PGVectorConfig, deps: Dict[Api, ProviderSpec]):
-    from .pgvector import PGVectorVectorDBAdapter
+async def get_adapter_impl(config: PGVectorVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .pgvector import PGVectorVectorIOAdapter
 
-    impl = PGVectorVectorDBAdapter(config, deps[Api.inference])
+    impl = PGVectorVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/pgvector/config.py

@@ -9,7 +9,7 @@ from pydantic import BaseModel, Field
 
 
 @json_schema_type
-class PGVectorConfig(BaseModel):
+class PGVectorVectorIOConfig(BaseModel):
     host: str = Field(default="localhost")
     port: int = Field(default=5432)
     db: str = Field(default="postgres")

llama_stack/providers/remote/vector_io/pgvector/pgvector.py

@@ -22,7 +22,7 @@ from llama_stack.providers.utils.memory.vector_store import (
     VectorDBWithIndex,
 )
 
-from .config import PGVectorConfig
+from .config import PGVectorVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -121,8 +121,8 @@ class PGVectorIndex(EmbeddingIndex):
             cur.execute(f"DROP TABLE IF EXISTS {self.table_name}")
 
 
-class PGVectorVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: PGVectorConfig, inference_api: Api.inference) -> None:
+class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
+    def __init__(self, config: PGVectorVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
         self.conn = None

llama_stack/providers/remote/vector_io/qdrant/__init__.py

@@ -8,12 +8,12 @@ from typing import Dict
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import QdrantConfig
+from .config import QdrantVectorIOConfig
 
 
-async def get_adapter_impl(config: QdrantConfig, deps: Dict[Api, ProviderSpec]):
-    from .qdrant import QdrantVectorDBAdapter
+async def get_adapter_impl(config: QdrantVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .qdrant import QdrantVectorIOAdapter
 
-    impl = QdrantVectorDBAdapter(config, deps[Api.inference])
+    impl = QdrantVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/qdrant/config.py

@@ -11,7 +11,7 @@ from pydantic import BaseModel
 
 
 @json_schema_type
-class QdrantConfig(BaseModel):
+class QdrantVectorIOConfig(BaseModel):
     location: Optional[str] = None
     url: Optional[str] = None
     port: Optional[int] = 6333

llama_stack/providers/remote/vector_io/qdrant/qdrant.py

@@ -21,7 +21,7 @@ from llama_stack.providers.utils.memory.vector_store import (
     VectorDBWithIndex,
 )
 
-from .config import QdrantConfig
+from .config import QdrantVectorIOConfig
 
 log = logging.getLogger(__name__)
 CHUNK_ID_KEY = "_chunk_id"
@@ -98,8 +98,8 @@ class QdrantIndex(EmbeddingIndex):
         await self.client.delete_collection(collection_name=self.collection_name)
 
 
-class QdrantVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
-    def __init__(self, config: QdrantConfig, inference_api: Api.inference) -> None:
+class QdrantVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
+    def __init__(self, config: QdrantVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.client = AsyncQdrantClient(**self.config.model_dump(exclude_none=True))
         self.cache = {}

llama_stack/providers/remote/vector_io/sample/__init__.py

@@ -6,12 +6,12 @@
 
 from typing import Any
 
-from .config import SampleConfig
+from .config import SampleVectorIOConfig
 
 
-async def get_adapter_impl(config: SampleConfig, _deps) -> Any:
-    from .sample import SampleMemoryImpl
+async def get_adapter_impl(config: SampleVectorIOConfig, _deps) -> Any:
+    from .sample import SampleVectorIOImpl
 
-    impl = SampleMemoryImpl(config)
+    impl = SampleVectorIOImpl(config)
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/sample/config.py

@@ -7,6 +7,6 @@
 from pydantic import BaseModel
 
 
-class SampleConfig(BaseModel):
+class SampleVectorIOConfig(BaseModel):
     host: str = "localhost"
     port: int = 9999

llama_stack/providers/remote/vector_io/sample/sample.py

@@ -7,11 +7,11 @@
 from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.apis.vector_io import VectorIO
 
-from .config import SampleConfig
+from .config import SampleVectorIOConfig
 
 
-class SampleMemoryImpl(VectorIO):
-    def __init__(self, config: SampleConfig):
+class SampleVectorIOImpl(VectorIO):
+    def __init__(self, config: SampleVectorIOConfig):
         self.config = config
 
     async def register_vector_db(self, vector_db: VectorDB) -> None:

llama_stack/providers/remote/vector_io/weaviate/__init__.py

@@ -8,12 +8,12 @@ from typing import Dict
 
 from llama_stack.providers.datatypes import Api, ProviderSpec
 
-from .config import WeaviateConfig, WeaviateRequestProviderData  # noqa: F401
+from .config import WeaviateRequestProviderData, WeaviateVectorIOConfig  # noqa: F401
 
 
-async def get_adapter_impl(config: WeaviateConfig, deps: Dict[Api, ProviderSpec]):
-    from .weaviate import WeaviateMemoryAdapter
+async def get_adapter_impl(config: WeaviateVectorIOConfig, deps: Dict[Api, ProviderSpec]):
+    from .weaviate import WeaviateVectorIOAdapter
 
-    impl = WeaviateMemoryAdapter(config, deps[Api.inference])
+    impl = WeaviateVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl

llama_stack/providers/remote/vector_io/weaviate/config.py

@@ -12,5 +12,5 @@ class WeaviateRequestProviderData(BaseModel):
     weaviate_cluster_url: str
 
 
-class WeaviateConfig(BaseModel):
+class WeaviateVectorIOConfig(BaseModel):
     pass

llama_stack/providers/remote/vector_io/weaviate/weaviate.py

@@ -23,7 +23,7 @@ from llama_stack.providers.utils.memory.vector_store import (
     VectorDBWithIndex,
 )
 
-from .config import WeaviateConfig, WeaviateRequestProviderData
+from .config import WeaviateRequestProviderData, WeaviateVectorIOConfig
 
 log = logging.getLogger(__name__)
 
@@ -85,12 +85,12 @@ class WeaviateIndex(EmbeddingIndex):
         collection.data.delete_many(where=Filter.by_property("id").contains_any(chunk_ids))
 
 
-class WeaviateMemoryAdapter(
+class WeaviateVectorIOAdapter(
     VectorIO,
     NeedsRequestProviderData,
     VectorDBsProtocolPrivate,
 ):
-    def __init__(self, config: WeaviateConfig, inference_api: Api.inference) -> None:
+    def __init__(self, config: WeaviateVectorIOConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
         self.client_cache = {}