Merge branch 'main' into main

Author: dbschmigelski

pyproject.toml

@@ -29,7 +29,7 @@ dependencies = [
     "boto3>=1.26.0,<2.0.0",
     "botocore>=1.29.0,<2.0.0",
     "docstring_parser>=0.15,<1.0",
-    "mcp>=1.8.0,<2.0.0",
+    "mcp>=1.11.0,<2.0.0",
     "pydantic>=2.0.0,<3.0.0",
     "typing-extensions>=4.13.2,<5.0.0",
     "watchdog>=6.0.0,<7.0.0",
@@ -89,8 +89,14 @@ writer = [
     "writer-sdk>=2.2.0,<3.0.0"
 ]
 
+sagemaker = [
+    "boto3>=1.26.0,<2.0.0",
+    "botocore>=1.29.0,<2.0.0",
+    "boto3-stubs[sagemaker-runtime]>=1.26.0,<2.0.0"
+]
+
 a2a = [
-    "a2a-sdk[sql]>=0.2.16,<1.0.0",
+    "a2a-sdk[sql]>=0.2.11,<1.0.0",
     "uvicorn>=0.34.2,<1.0.0",
     "httpx>=0.28.1,<1.0.0",
     "fastapi>=0.115.12,<1.0.0",
@@ -136,7 +142,7 @@ all = [
     "opentelemetry-exporter-otlp-proto-http>=1.30.0,<2.0.0",
 
     # a2a
-    "a2a-sdk[sql]>=0.2.16,<1.0.0",
+    "a2a-sdk[sql]>=0.2.11,<1.0.0",
     "uvicorn>=0.34.2,<1.0.0",
     "httpx>=0.28.1,<1.0.0",
     "fastapi>=0.115.12,<1.0.0",
@@ -148,7 +154,7 @@ all = [
 source = "vcs"
 
 [tool.hatch.envs.hatch-static-analysis]
-features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer", "a2a"]
+features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer", "a2a", "sagemaker"]
 dependencies = [
   "mypy>=1.15.0,<2.0.0",
   "ruff>=0.11.6,<0.12.0",
@@ -171,7 +177,7 @@ lint-fix = [
 ]
 
 [tool.hatch.envs.hatch-test]
-features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer", "a2a"]
+features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer", "a2a", "sagemaker"]
 extra-dependencies = [
     "moto>=5.1.0,<6.0.0",
     "pytest>=8.0.0,<9.0.0",
@@ -187,7 +193,7 @@ extra-args = [
 
 [tool.hatch.envs.dev]
 dev-mode = true
-features = ["dev", "docs", "anthropic", "litellm", "llamaapi", "ollama", "otel", "mistral", "writer", "a2a"]
+features = ["dev", "docs", "anthropic", "litellm", "llamaapi", "ollama", "otel", "mistral", "writer", "a2a", "sagemaker"]
 
 [[tool.hatch.envs.hatch-test.matrix]]
 python = ["3.13", "3.12", "3.11", "3.10"]
@@ -315,4 +321,4 @@ style = [
     ["instruction", ""],
     ["text", ""],
     ["disabled", "fg:#858585 italic"]
-]
+]

src/strands/models/anthropic.py

@@ -414,7 +414,7 @@ async def structured_output(
         stop_reason, messages, _, _ = event["stop"]
 
         if stop_reason != "tool_use":
-            raise ValueError("No valid tool use or tool use input was found in the Anthropic response.")
+            raise ValueError(f"Model returned stop_reason: {stop_reason} instead of \"tool_use\".")
 
         content = messages["content"]
         output_response: dict[str, Any] | None = None

src/strands/models/bedrock.py

@@ -17,10 +17,10 @@
 
 from ..event_loop import streaming
 from ..tools import convert_pydantic_to_tool_spec
-from ..types.content import Messages
+from ..types.content import ContentBlock, Message, Messages
 from ..types.exceptions import ContextWindowOverflowException, ModelThrottledException
 from ..types.streaming import StreamEvent
-from ..types.tools import ToolSpec
+from ..types.tools import ToolResult, ToolSpec
 from .model import Model
 
 logger = logging.getLogger(__name__)
@@ -181,7 +181,7 @@ def format_request(
         """
         return {
             "modelId": self.config["model_id"],
-            "messages": messages,
+            "messages": self._format_bedrock_messages(messages),
             "system": [
                 *([{"text": system_prompt}] if system_prompt else []),
                 *([{"cachePoint": {"type": self.config["cache_prompt"]}}] if self.config.get("cache_prompt") else []),
@@ -246,6 +246,53 @@ def format_request(
             ),
         }
 
+    def _format_bedrock_messages(self, messages: Messages) -> Messages:
+        """Format messages for Bedrock API compatibility.
+
+        This function ensures messages conform to Bedrock's expected format by:
+        - Cleaning tool result content blocks by removing additional fields that may be
+          useful for retaining information in hooks but would cause Bedrock validation
+          exceptions when presented with unexpected fields
+        - Ensuring all message content blocks are properly formatted for the Bedrock API
+
+        Args:
+            messages: List of messages to format
+
+        Returns:
+            Messages formatted for Bedrock API compatibility
+
+        Note:
+            Bedrock will throw validation exceptions when presented with additional
+            unexpected fields in tool result blocks.
+            https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ToolResultBlock.html
+        """
+        cleaned_messages = []
+
+        for message in messages:
+            cleaned_content: list[ContentBlock] = []
+
+            for content_block in message["content"]:
+                if "toolResult" in content_block:
+                    # Create a new content block with only the cleaned toolResult
+                    tool_result: ToolResult = content_block["toolResult"]
+
+                    # Keep only the required fields for Bedrock
+                    cleaned_tool_result = ToolResult(
+                        content=tool_result["content"], toolUseId=tool_result["toolUseId"], status=tool_result["status"]
+                    )
+
+                    cleaned_block: ContentBlock = {"toolResult": cleaned_tool_result}
+                    cleaned_content.append(cleaned_block)
+                else:
+                    # Keep other content blocks as-is
+                    cleaned_content.append(content_block)
+
+            # Create new message with cleaned content
+            cleaned_message: Message = Message(content=cleaned_content, role=message["role"])
+            cleaned_messages.append(cleaned_message)
+
+        return cleaned_messages
+
     def _has_blocked_guardrail(self, guardrail_data: dict[str, Any]) -> bool:
         """Check if guardrail data contains any blocked policies.
 
@@ -584,7 +631,7 @@ async def structured_output(
         stop_reason, messages, _, _ = event["stop"]
 
         if stop_reason != "tool_use":
-            raise ValueError("No valid tool use or tool use input was found in the Bedrock response.")
+            raise ValueError(f"Model returned stop_reason: {stop_reason} instead of \"tool_use\".")
 
         content = messages["content"]
         output_response: dict[str, Any] | None = None