Python: Improve Bedrock service setup docs

python/.cspell.json

@@ -51,6 +51,7 @@
         "nopep",
         "NOSQL",
         "ollama",
+        "Onnx",
         "onyourdatatest",
         "OPENAI",
         "opentelemetry",

python/samples/concepts/agents/bedrock_agent/README.md

@@ -5,6 +5,37 @@
 1. You need to have an AWS account and [access to the foundation models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-permissions.html)
 2. [AWS CLI installed](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) and [configured](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration)
 
+### Configuration
+
+Follow this [guide](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration) to configure your environment to use the Bedrock API.
+
+Please configure the `aws_access_key_id`, `aws_secret_access_key`, and `region` otherwise you will need to create custom clients for the services. For example:
+
+```python
+runtime_client=boto.client(
+    "bedrock-runtime",
+    aws_access_key_id="your_access_key",
+    aws_secret_access_key="your_secret_key",
+    region_name="your_region",
+    [...other parameters you may need...]
+)
+client=boto.client(
+    "bedrock",
+    aws_access_key_id="your_access_key",
+    aws_secret_access_key="your_secret_key",
+    region_name="your_region",
+    [...other parameters you may need...]
+)
+
+bedrock_agent = BedrockAgent.create_and_prepare_agent(
+    name="your_agent_name",
+    instructions="your_instructions",
+    runtime_client=runtime_client,
+    client=client,
+    [...other parameters you may need...]
+)
+```
+
 ## Samples
 
 | Sample | Description |

python/samples/concepts/setup/ALL_SETTINGS.md

@@ -1,4 +1,6 @@
-## AI Service Settings used across SK:
+# Semantic Kernel Settings
+
+## AI Service Settings used across SK
 
 | Provider | Service | Constructor Settings | Environment Variable | Required? | Settings Class |
 | --- | --- | --- | --- | --- | --- |
@@ -36,7 +38,7 @@
 | Onnx | [OnnxGenAIChatCompletion](../../../semantic_kernel/connectors/ai/onnx/services/onnx_gen_ai_chat_completion.py) | template, <br> ai_model_path | N/A, <br> ONNX_GEN_AI_CHAT_MODEL_FOLDER | Yes, <br> Yes | [OnnxGenAISettings](../../../semantic_kernel/connectors/ai/onnx/onnx_gen_ai_settings.py) |
 |  | [OnnxGenAITextCompletion](../../../semantic_kernel/connectors/ai/onnx/services/onnx_gen_ai_text_completion.py) | ai_model_path | ONNX_GEN_AI_TEXT_MODEL_FOLDER | Yes |  |
 
-## Memory Service Settings used across SK:
+## Memory Service Settings used across SK
 
 | Provider | Service | Constructor Settings | Environment Variable | Required? | Settings Class |
 | --- | --- | --- | --- | --- | --- |
@@ -49,7 +51,7 @@
 | Redis | [RedisMemoryService](../../../semantic_kernel/connectors/memory/redis/redis_memory_store.py) | connection_string | REDIS_CONNECTION_STRING | Yes | [RedisSettings](../../../semantic_kernel/connectors/memory/redis/redis_settings.py) |
 | Weaviate | [WeaviateMemoryService](../../../semantic_kernel/connectors/memory/weaviate/weaviate_memory_store.py) | url, <br> api_key, <br> use_embed | WEAVIATE_URL, <br> WEAVIATE_API_KEY, <br> WEAVIATE_USE_EMBED | No, <br> No, <br> No | [WeaviateSettings](../../../semantic_kernel/connectors/memory/weaviate/weaviate_settings.py) |
 
-## Other settings used:
+## Other settings used
 
 | Provider | Service | Constructor Settings | Environment Variable | Required? | Settings Class |
 | --- | --- | --- | --- | --- | --- |

python/semantic_kernel/connectors/ai/README.md

@@ -3,14 +3,14 @@
 This directory contains the implementation of the AI connectors (aka AI services) that are used to interact with AI models.
 
 Depending on the modality, the AI connector can inherit from one of the following classes:
+
 - [`ChatCompletionClientBase`](./chat_completion_client_base.py) for chat completion tasks.
 - [`TextCompletionClientBase`](./text_completion_client_base.py) for text completion tasks.
 - [`AudioToTextClientBase`](./audio_to_text_client_base.py) for audio to text tasks.
 - [`TextToAudioClientBase`](./text_to_audio_client_base.py) for text to audio tasks.
 - [`TextToImageClientBase`](./text_to_image_client_base.py) for text to image tasks.
 - [`EmbeddingGeneratorBase`](./embeddings/embedding_generator_base.py) for text embedding tasks.
 
-
 All base clients inherit from the [`AIServiceClientBase`](../../services/ai_service_client_base.py) class.
 
 ## Existing AI connectors

python/semantic_kernel/connectors/ai/bedrock/README.md

@@ -11,6 +11,27 @@
 
 Follow this [guide](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html#configuration) to configure your environment to use the Bedrock API.
 
+Please configure the `aws_access_key_id`, `aws_secret_access_key`, and `region` otherwise you will need to create custom clients for the services. For example:
+
+```python
+runtime_client=boto.client(
+    "bedrock-runtime",
+    aws_access_key_id="your_access_key",
+    aws_secret_access_key="your_secret_key",
+    region_name="your_region",
+    [...other parameters you may need...]
+)
+client=boto.client(
+    "bedrock",
+    aws_access_key_id="your_access_key",
+    aws_secret_access_key="your_secret_key",
+    region_name="your_region",
+    [...other parameters you may need...]
+)
+
+bedrock_chat_completion_service = BedrockChatCompletion(runtime_client=runtime_client, client=client)
+```
+
 ## Supports
 
 ### Region

python/semantic_kernel/connectors/ai/bedrock/services/bedrock_base.py

@@ -4,6 +4,8 @@
 from functools import partial
 from typing import Any, ClassVar
 
+import boto3
+
 from semantic_kernel.kernel_pydantic import KernelBaseModel
 from semantic_kernel.utils.async_utils import run_in_executor
 
@@ -19,6 +21,26 @@ class BedrockBase(KernelBaseModel, ABC):
     # Client: Use for model management
     bedrock_client: Any
 
+    def __init__(
+        self,
+        *,
+        runtime_client: Any | None = None,
+        client: Any | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """Initialize the Amazon Bedrock Base Class.
+
+        Args:
+            runtime_client: The Amazon Bedrock runtime client to use.
+            client: The Amazon Bedrock client to use.
+            **kwargs: Additional keyword arguments.
+        """
+        super().__init__(
+            bedrock_runtime_client=runtime_client or boto3.client("bedrock-runtime"),
+            bedrock_client=client or boto3.client("bedrock"),
+            **kwargs,
+        )
+
     async def get_foundation_model_info(self, model_id: str) -> dict[str, Any]:
         """Get the foundation model information."""
         response = await run_in_executor(

python/semantic_kernel/connectors/ai/bedrock/services/bedrock_chat_completion.py

@@ -5,8 +5,6 @@
 from functools import partial
 from typing import TYPE_CHECKING, Any, ClassVar
 
-import boto3
-
 if sys.version_info >= (3, 12):
     from typing import override  # pragma: no cover
 else:
@@ -95,8 +93,8 @@ def __init__(
         super().__init__(
             ai_model_id=bedrock_settings.chat_model_id,
             service_id=service_id or bedrock_settings.chat_model_id,
-            bedrock_runtime_client=runtime_client or boto3.client("bedrock-runtime"),
-            bedrock_client=client or boto3.client("bedrock"),
+            runtime_client=runtime_client,
+            client=client,
         )
 
     # region Overriding base class methods

python/semantic_kernel/connectors/ai/bedrock/services/bedrock_text_completion.py

@@ -6,7 +6,6 @@
 from functools import partial
 from typing import TYPE_CHECKING, Any
 
-import boto3
 from pydantic import ValidationError
 
 if sys.version_info >= (3, 12):
@@ -73,8 +72,8 @@ def __init__(
         super().__init__(
             ai_model_id=bedrock_settings.text_model_id,
             service_id=service_id or bedrock_settings.text_model_id,
-            bedrock_runtime_client=runtime_client or boto3.client("bedrock-runtime"),
-            bedrock_client=client or boto3.client("bedrock"),
+            runtime_client=runtime_client,
+            client=client,
         )
 
     # region Overriding base class methods

python/semantic_kernel/connectors/ai/bedrock/services/bedrock_text_embedding.py

@@ -6,7 +6,6 @@
 from functools import partial
 from typing import TYPE_CHECKING, Any
 
-import boto3
 from numpy import array, ndarray
 from pydantic import ValidationError
 
@@ -70,8 +69,8 @@ def __init__(
         super().__init__(
             ai_model_id=bedrock_settings.embedding_model_id,
             service_id=service_id or bedrock_settings.embedding_model_id,
-            bedrock_runtime_client=runtime_client or boto3.client("bedrock-runtime"),
-            bedrock_client=client or boto3.client("bedrock"),
+            runtime_client=runtime_client,
+            client=client,
         )
 
     @override

python/tests/integration/completions/chat_completion_test_base.py

@@ -67,8 +67,6 @@
     ["ONNX_GEN_AI_CHAT_MODEL_FOLDER"], raise_if_not_set=False
 )  # Tests are optional for ONNX
 anthropic_setup: bool = is_service_setup_for_testing(["ANTHROPIC_API_KEY", "ANTHROPIC_CHAT_MODEL_ID"])
-# When testing Bedrock, after logging into AWS CLI this has been set, so we can use it to check if the service is setup
-bedrock_setup: bool = is_service_setup_for_testing(["AWS_DEFAULT_REGION"], raise_if_not_set=False)
 
 
 # A mock plugin that contains a function that returns a complex object.
@@ -90,7 +88,7 @@ class ChatCompletionTestBase(CompletionTestBase):
     """Base class for testing completion services."""
 
     @override
-    @pytest.fixture(scope="function")
+    @pytest.fixture(scope="class")
     def services(self) -> dict[str, tuple[ServiceType | None, type[PromptExecutionSettings] | None]]:
         azure_openai_setup = True
         azure_openai_settings = AzureOpenAISettings.create()
@@ -152,27 +150,27 @@ def services(self) -> dict[str, tuple[ServiceType | None, type[PromptExecutionSe
                 OnnxGenAIPromptExecutionSettings,
             ),
             "bedrock_amazon_titan": (
-                BedrockChatCompletion(model_id="amazon.titan-text-premier-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("amazon.titan-text-premier-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
             "bedrock_ai21labs": (
-                BedrockChatCompletion(model_id="ai21.jamba-1-5-mini-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("ai21.jamba-1-5-mini-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
             "bedrock_anthropic_claude": (
-                BedrockChatCompletion(model_id="anthropic.claude-3-5-sonnet-20240620-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("anthropic.claude-3-5-sonnet-20240620-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
             "bedrock_cohere_command": (
-                BedrockChatCompletion(model_id="cohere.command-r-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("cohere.command-r-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
             "bedrock_meta_llama": (
-                BedrockChatCompletion(model_id="meta.llama3-70b-instruct-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("meta.llama3-70b-instruct-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
             "bedrock_mistralai": (
-                BedrockChatCompletion(model_id="mistral.mistral-small-2402-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_chat_completion_client("mistral.mistral-small-2402-v1:0"),
                 BedrockChatPromptExecutionSettings,
             ),
         }
@@ -218,3 +216,13 @@ async def get_chat_completion_response(
         if parts:
             return sum(parts[1:], parts[0])
         raise AssertionError("No response")
+
+    def _try_create_bedrock_chat_completion_client(self, model_id: str) -> BedrockChatCompletion | None:
+        try:
+            return BedrockChatCompletion(model_id=model_id)
+        except Exception as ex:
+            from conftest import logger
+
+            logger.warning(ex)
+            # Returning None so that the test that uses this service will be skipped
+            return None

python/tests/integration/completions/test_chat_completions.py

@@ -18,7 +18,6 @@
 from tests.integration.completions.chat_completion_test_base import (
     ChatCompletionTestBase,
     anthropic_setup,
-    bedrock_setup,
     mistral_ai_setup,
     ollama_setup,
     onnx_setup,
@@ -190,7 +189,6 @@ class Reasoning(KernelBaseModel):
                 ChatMessageContent(role=AuthorRole.USER, items=[TextContent(text="How are you today?")]),
             ],
             {},
-            marks=pytest.mark.skipif(not bedrock_setup, reason="Bedrock Environment Variables not set"),
             id="bedrock_amazon_titan_text_input",
         ),
         pytest.param(

python/tests/integration/completions/test_text_completion.py

@@ -45,7 +45,6 @@
 onnx_setup: bool = is_service_setup_for_testing(
     ["ONNX_GEN_AI_TEXT_MODEL_FOLDER"], raise_if_not_set=False
 )  # Tests are optional for ONNX
-bedrock_setup = is_service_setup_for_testing(["AWS_DEFAULT_REGION"], raise_if_not_set=False)
 
 pytestmark = pytest.mark.parametrize(
     "service_id, execution_settings_kwargs, inputs, kwargs",
@@ -138,7 +137,6 @@
             {},
             ["Repeat the word Hello once"],
             {},
-            marks=pytest.mark.skipif(not bedrock_setup, reason="Not setup"),
             id="bedrock_amazon_titan_text_completion",
         ),
         pytest.param(
@@ -255,27 +253,27 @@ def services(self) -> dict[str, tuple[ServiceType | None, type[PromptExecutionSe
             # Amazon Bedrock supports models from multiple providers but requests to and responses from the models are
             # inconsistent. So we need to test each model separately.
             "bedrock_amazon_titan": (
-                BedrockTextCompletion(model_id="amazon.titan-text-premier-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("amazon.titan-text-premier-v1:0"),
                 BedrockTextPromptExecutionSettings,
             ),
             "bedrock_anthropic_claude": (
-                BedrockTextCompletion(model_id="anthropic.claude-v2") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("anthropic.claude-v2"),
                 BedrockTextPromptExecutionSettings,
             ),
             "bedrock_cohere_command": (
-                BedrockTextCompletion(model_id="cohere.command-text-v14") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("cohere.command-text-v14"),
                 BedrockTextPromptExecutionSettings,
             ),
             "bedrock_ai21labs": (
-                BedrockTextCompletion(model_id="ai21.j2-mid-v1") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("ai21.j2-mid-v1"),
                 BedrockTextPromptExecutionSettings,
             ),
             "bedrock_meta_llama": (
-                BedrockTextCompletion(model_id="meta.llama3-70b-instruct-v1:0") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("meta.llama3-70b-instruct-v1:0"),
                 BedrockTextPromptExecutionSettings,
             ),
             "bedrock_mistralai": (
-                BedrockTextCompletion(model_id="mistral.mistral-7b-instruct-v0:2") if bedrock_setup else None,
+                self._try_create_bedrock_text_completion_client("mistral.mistral-7b-instruct-v0:2"),
                 BedrockTextPromptExecutionSettings,
             ),
         }
@@ -373,3 +371,13 @@ async def _test_helper(
                 name="text completions",
             )
             self.evaluate(response)
+
+    def _try_create_bedrock_text_completion_client(self, model_id: str) -> BedrockTextCompletion | None:
+        try:
+            return BedrockTextCompletion(model_id=model_id)
+        except Exception as ex:
+            from conftest import logger
+
+            logger.warning(ex)
+            # Returning None so that the test that uses this service will be skipped
+            return None