fix: forward strict mode to Anthropic and Bedrock providers

The OpenAI-format tool schema sets strict: true but this was dropped
during conversion to Anthropic/Bedrock formats, so neither provider
used constrained decoding. Without it, the model can return string
"None" instead of JSON null for nullable fields, causing Pydantic
validation failures.

lib/crewai/pyproject.toml

@@ -74,8 +74,8 @@ qdrant = [
     "qdrant-client[fastembed]~=1.14.3",
 ]
 aws = [
-    "boto3~=1.40.38",
-    "aiobotocore~=2.25.2",
+    "boto3~=1.42.79",
+    "aiobotocore~=3.4.0",
 ]
 watson = [
     "ibm-watsonx-ai~=1.3.39",
@@ -87,7 +87,7 @@ litellm = [
     "litellm~=1.83.0",
 ]
 bedrock = [
-    "boto3~=1.40.45",
+    "boto3~=1.42.79",
 ]
 google-genai = [
     "google-genai~=1.65.0",

lib/crewai/src/crewai/llms/providers/anthropic/completion.py

@@ -494,6 +494,10 @@ class AnthropicCompletion(BaseLLM):
                     "required": [],
                 }
 
+            func_info = tool.get("function", {})
+            if func_info.get("strict"):
+                anthropic_tool["strict"] = True
+
             anthropic_tools.append(anthropic_tool)
 
         return anthropic_tools

lib/crewai/src/crewai/llms/providers/bedrock/completion.py

@@ -169,6 +169,7 @@ class ToolSpec(TypedDict, total=False):
     name: Required[str]
     description: Required[str]
     inputSchema: ToolInputSchema
+    strict: bool
 
 
 class ConverseToolTypeDef(TypedDict):
@@ -1965,6 +1966,10 @@ class BedrockCompletion(BaseLLM):
                     input_schema: ToolInputSchema = {"json": parameters}
                     tool_spec["inputSchema"] = input_schema
 
+                func_info = tool.get("function", {})
+                if func_info.get("strict"):
+                    tool_spec["strict"] = True
+
                 converse_tool: ConverseToolTypeDef = {"toolSpec": tool_spec}
 
                 converse_tools.append(converse_tool)