fix: formatting issues

adalflow/adalflow/components/model_client/bedrock_client.py

@@ -302,7 +302,9 @@ def convert_inputs_to_api_kwargs(
             api_kwargs = self._validate_and_process_config_keys(api_kwargs)
 
             # Separate inference config and additional model request fields
-            api_kwargs, inference_config, additional_model_request_fields = self._separate_parameters(api_kwargs)
+            api_kwargs, inference_config, additional_model_request_fields = (
+                self._separate_parameters(api_kwargs)
+            )
 
             api_kwargs["messages"] = [
                 {"role": "user", "content": [{"text": input}]},

docs/source/integrations/aws_bedrock.rst

@@ -11,7 +11,7 @@ AWS Bedrock API Client
 Getting Credentials
 -------------------
 
-You need to have an AWS account and an access key and secret key to use AWS Bedrock services. Moreover, the account associated with the access key must have 
+You need to have an AWS account and an access key and secret key to use AWS Bedrock services. Moreover, the account associated with the access key must have
 the necessary permissions to access Bedrock services. Refer to the `AWS documentation <https://docs.aws.amazon.com/singlesignon/latest/userguide/howtogetcredentials.html>`_ for more information on obtaining credentials.
 
 Enabling Foundation Models
@@ -32,9 +32,9 @@ Steps for enabling model access:
 Note:
 
 1. Avoid enabling high-cost models to prevent accidental high charges due to incorrect usage.
-2. As of Nov 2024, a cost-effective option is the Llama-3.2 1B model, with model ID: ``meta.llama3-2-1b-instruct-v1:0`` in the ``us-east-1`` region. 
+2. As of Nov 2024, a cost-effective option is the Llama-3.2 1B model, with model ID: ``meta.llama3-2-1b-instruct-v1:0`` in the ``us-east-1`` region.
 3. AWS tags certain models with `inferenceTypesSupported` = `INFERENCE_PROFILE` and in UI it might appear with a tooltip as `This model can only be used through an inference profile.` In such cases you may need to use the Model ARN: ``arn:aws:bedrock:us-east-1:306093656765:inference-profile/us.meta.llama3-2-1b-instruct-v1:0`` in the model ID field when using Adalflow.
-4. Ensure (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION_NAME) or AWS_DEFAULT_PROFILE is set in the ``.env`` file. Mention exact key names in ``.env`` file for example access key id is ``AWS_ACCESS_KEY_ID`` 
+4. Ensure (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION_NAME) or AWS_DEFAULT_PROFILE is set in the ``.env`` file. Mention exact key names in ``.env`` file for example access key id is ``AWS_ACCESS_KEY_ID``
 
 .. code-block:: python
 

tutorials/bedrock_client_simple_qa.py

@@ -1,5 +1,3 @@
-import os
-
 from adalflow.components.model_client import BedrockAPIClient
 from adalflow.core.types import ModelType
 from adalflow.utils import setup_env