build: format codebase imports using ruff linter (#1028)

# What does this PR do?

- Configured ruff linter to automatically fix import sorting issues.
- Set --exit-non-zero-on-fix to ensure non-zero exit code when fixes are
applied.
- Enabled the 'I' selection to focus on import-related linting rules.
- Ran the linter, and formatted all codebase imports accordingly.
- Removed the black dep from the "dev" group since we use ruff

Signed-off-by: Sébastien Han <seb@redhat.com>

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)

Signed-off-by: Sébastien Han <seb@redhat.com>

llama_stack/providers/utils/common/data_schema_validator.py

@@ -12,7 +12,6 @@ from llama_stack.apis.common.type_system import (
     CompletionInputType,
     StringType,
 )
-
 from llama_stack.distribution.datatypes import Api
 
 

llama_stack/providers/utils/datasetio/url_utils.py

@@ -11,7 +11,6 @@ from urllib.parse import unquote
 import pandas
 
 from llama_stack.apis.common.content_types import URL
-
 from llama_stack.providers.utils.memory.vector_store import parse_data_url
 
 

llama_stack/providers/utils/inference/model_registry.py

@@ -11,7 +11,6 @@ from llama_models.sku_list import all_registered_models
 
 from llama_stack.apis.models.models import ModelType
 from llama_stack.providers.datatypes import Model, ModelsProtocolPrivate
-
 from llama_stack.providers.utils.inference import (
     ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR,
 )

llama_stack/providers/utils/inference/openai_compat.py

@@ -13,7 +13,6 @@ from llama_models.datatypes import (
     TopKSamplingStrategy,
     TopPSamplingStrategy,
 )
-
 from llama_models.llama3.api.chat_format import ChatFormat
 from llama_models.llama3.api.datatypes import StopReason, ToolCall
 from openai.types.chat import ChatCompletionMessageToolCall
@@ -26,7 +25,6 @@ from llama_stack.apis.common.content_types import (
     ToolCallDelta,
     ToolCallParseStatus,
 )
-
 from llama_stack.apis.inference import (
     ChatCompletionRequest,
     ChatCompletionResponse,
@@ -39,7 +37,6 @@ from llama_stack.apis.inference import (
     Message,
     TokenLogProbs,
 )
-
 from llama_stack.providers.utils.inference.prompt_adapter import (
     convert_image_content_to_url,
 )

llama_stack/providers/utils/inference/prompt_adapter.py

@@ -13,7 +13,7 @@ import re
 from typing import List, Optional, Tuple, Union
 
 import httpx
-from llama_models.datatypes import is_multimodal, ModelFamily
+from llama_models.datatypes import ModelFamily, is_multimodal
 from llama_models.llama3.api.chat_format import ChatFormat
 from llama_models.llama3.api.datatypes import (
     RawContent,
@@ -47,9 +47,9 @@ from llama_stack.apis.inference import (
     ResponseFormat,
     ResponseFormatType,
     SystemMessage,
+    SystemMessageBehavior,
     ToolChoice,
     UserMessage,
-    SystemMessageBehavior,
 )
 from llama_stack.providers.utils.inference import supported_inference_models
 

llama_stack/providers/utils/kvstore/sqlite/sqlite.py

@@ -5,7 +5,6 @@
 # the root directory of this source tree.
 
 import os
-
 from datetime import datetime
 from typing import List, Optional
 

llama_stack/providers/utils/memory/vector_store.py

@@ -15,13 +15,14 @@ from urllib.parse import unquote
 import chardet
 import httpx
 import numpy as np
-
 from llama_models.llama3.api.tokenizer import Tokenizer
+from numpy.typing import NDArray
+from pypdf import PdfReader
 
 from llama_stack.apis.common.content_types import (
+    URL,
     InterleavedContent,
     TextContentItem,
-    URL,
 )
 from llama_stack.apis.tools import RAGDocument
 from llama_stack.apis.vector_dbs import VectorDB
@@ -30,9 +31,6 @@ from llama_stack.providers.datatypes import Api
 from llama_stack.providers.utils.inference.prompt_adapter import (
     interleaved_content_as_str,
 )
-from numpy.typing import NDArray
-
-from pypdf import PdfReader
 
 log = logging.getLogger(__name__)