change multi-line import to single-line

docs/docs/providers/agents/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Agents
 
-    APIs for creating and interacting with agentic systems."
+APIs for creating and interacting with agentic systems."
 sidebar_label: Agents
 title: Agents
 ---
@@ -12,6 +12,6 @@ title: Agents
 
 Agents
 
-    APIs for creating and interacting with agentic systems.
+APIs for creating and interacting with agentic systems.
 
 This section contains documentation for all available providers for the **agents** API.

docs/docs/providers/batches/index.mdx

@@ -1,14 +1,14 @@
 ---
 description: "The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
+particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
+This API provides the following extensions:
  - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes."
+Note: This API is currently under active development and may undergo changes."
 sidebar_label: Batches
 title: Batches
 ---
@@ -18,14 +18,14 @@ title: Batches
 ## Overview
 
 The Batches API enables efficient processing of multiple requests in a single operation,
-    particularly useful for processing large datasets, batch evaluation workflows, and
+particularly useful for processing large datasets, batch evaluation workflows, and
-    cost-effective inference at scale.
+cost-effective inference at scale.
 
-    The API is designed to allow use of openai client libraries for seamless integration.
+The API is designed to allow use of openai client libraries for seamless integration.
 
-    This API provides the following extensions:
+This API provides the following extensions:
  - idempotent batch creation
 
-    Note: This API is currently under active development and may undergo changes.
+Note: This API is currently under active development and may undergo changes.
 
 This section contains documentation for all available providers for the **batches** API.

docs/docs/providers/files/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs."
+This API is used to upload documents that can be used with other Llama Stack APIs."
 sidebar_label: Files
 title: Files
 ---
@@ -12,6 +12,6 @@ title: Files
 
 Files
 
-    This API is used to upload documents that can be used with other Llama Stack APIs.
+This API is used to upload documents that can be used with other Llama Stack APIs.
 
 This section contains documentation for all available providers for the **files** API.

docs/docs/providers/inference/index.mdx

@@ -1,11 +1,11 @@
 ---
 description: "Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Two kinds of models are supported:
+This API provides the raw interface to the underlying models. Two kinds of models are supported:
-    - LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
+- LLM models: these models generate \"raw\" and \"chat\" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search."
+- Embedding models: these models generate embeddings to be used for semantic search."
 sidebar_label: Inference
 title: Inference
 ---
@@ -16,10 +16,10 @@ title: Inference
 
 Inference
 
-    Llama Stack Inference API for generating completions, chat completions, and embeddings.
+Llama Stack Inference API for generating completions, chat completions, and embeddings.
 
-    This API provides the raw interface to the underlying models. Two kinds of models are supported:
+This API provides the raw interface to the underlying models. Two kinds of models are supported:
-    - LLM models: these models generate "raw" and "chat" (conversational) completions.
+- LLM models: these models generate "raw" and "chat" (conversational) completions.
-    - Embedding models: these models generate embeddings to be used for semantic search.
+- Embedding models: these models generate embeddings to be used for semantic search.
 
 This section contains documentation for all available providers for the **inference** API.

docs/docs/providers/safety/index.mdx

@@ -1,7 +1,7 @@
 ---
 description: "Safety
 
-    OpenAI-compatible Moderations API."
+OpenAI-compatible Moderations API."
 sidebar_label: Safety
 title: Safety
 ---
@@ -12,6 +12,6 @@ title: Safety
 
 Safety
 
-    OpenAI-compatible Moderations API.
+OpenAI-compatible Moderations API.
 
 This section contains documentation for all available providers for the **safety** API.

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

@@ -22,22 +22,16 @@ from llama_stack.apis.vector_io import (
 )
 from llama_stack.log import get_logger
 from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
-from llama_stack.providers.inline.vector_io.chroma import (
+from llama_stack.providers.inline.vector_io.chroma import ChromaVectorIOConfig as InlineChromaVectorIOConfig
-    ChromaVectorIOConfig as InlineChromaVectorIOConfig,
-)
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.kvstore.api import KVStore
-from llama_stack.providers.utils.memory.openai_vector_store_mixin import (
+from llama_stack.providers.utils.memory.openai_vector_store_mixin import OpenAIVectorStoreMixin
-    OpenAIVectorStoreMixin,
-)
 from llama_stack.providers.utils.memory.vector_store import (
     ChunkForDeletion,
     EmbeddingIndex,
     VectorDBWithIndex,
 )
-from llama_stack.providers.utils.vector_io.vector_utils import (
+from llama_stack.providers.utils.vector_io.vector_utils import WeightedInMemoryAggregator
-    WeightedInMemoryAggregator,
-)
 
 from .config import ChromaVectorIOConfig as RemoteChromaVectorIOConfig