[Bedrock] ValidationException: "Thinking may not be enabled when tool_choice forces tool use" with interleaved thinking on Sonnet 4.5

[sharon8811]

Initial Checks

• I confirm that I'm using the latest version of Pydantic AI
• I confirm that I searched for my issue in https://github.com/pydantic/pydantic-ai/issues before opening this issue

Description

Bug Description

When using AWS Bedrock Claude Sonnet 4.5 with interleaved thinking enabled, the agent fails when attempting to use tools after the initial call. This appears to be a regression introduced between versions 1.0.1 and 1.0.15.

Error Message

botocore.errorfactory.ValidationException: An error occurred (ValidationException) when calling the ConverseStream operation: The model returned the following errors: Thinking may not be enabled when tool_choice forces tool use.

Configuration

PydanticAI Version: 1.0.15
Model: Claude Sonnet 4.5 via AWS Bedrock
Provider: bedrock

Model Settings:

{
  "max_tokens": 63000,
  "temperature": 1.0,
  "timeout": 300,
  "parallel_tool_calls": true,
  "bedrock_additional_model_requests_fields": {
    "anthropic_beta": [
      "token-efficient-tools-2025-02-19",
      "interleaved-thinking-2025-05-14"
    ],
    "thinking": {
      "type": "enabled",
      "budget_tokens": 4096
    }
  }
}

Steps to Reproduce

1. Configure agent with AWS Bedrock Sonnet 4.5 and thinking enabled (settings above)
2. Call agent with structured output: agent.iter(prompt, output_type=MyOutputType)
3. Agent responds to first call with the error

Stack Trace

File ".venv/lib/python3.12/site-packages/pydantic_ai/models/instrumented.py", line 381, in request_stream
  async with self.wrapped.request_stream(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/homebrew/anaconda3/lib/python3.12/contextlib.py", line 210, in __aenter__
  return await anext(self.gen)
         ^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/pydantic_ai/models/bedrock.py", line 289, in request_stream
  response = await self._messages_create(messages, True, settings, model_request_parameters)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/pydantic_ai/models/bedrock.py", line 412, in _messages_create
  model_response = await anyio.to_thread.run_sync(functools.partial(self.client.converse_stream, **params))
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/anyio/to_thread.py", line 56, in run_sync
  return await get_async_backend().run_sync_in_worker_thread(
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 2470, in run_sync_in_worker_thread
  return await future
         ^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/anyio/_backends/_asyncio.py", line 967, in run
  result = context.run(func, *args)
           ^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/botocore/client.py", line 602, in _api_call
  return self._make_api_call(operation_name, kwargs)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/botocore/context.py", line 123, in wrapper
  return func(*args, **kwargs)
         ^^^^^^^^^^^^^^^^^^^^^
File ".venv/lib/python3.12/site-packages/botocore/client.py", line 1078, in _make_api_call
  raise error_class(parsed_response, operation_name)
botocore.errorfactory.ValidationException: An error occurred (ValidationException) when calling the ConverseStream operation: The model returned the following errors: Thinking may not be enabled when tool_choice forces tool use.

Expected Behavior

The agent should successfully use tools even when thinking is enabled, as it did in version 1.0.1.

Additional Context

• Regression: This worked correctly in PydanticAI version 1.0.1
• Consistent: Error occurs on every attempt with these settings
• Timing: Fails specifically when tools are required after the initial response

The error suggests that when PydanticAI forces tool usage (likely due to output_type requiring structured output or tool selection), it conflicts with Bedrock's thinking feature. This may be related to how tool_choice is set in the Bedrock API call when thinking is enabled.

Example Code

import asyncio
from pydantic import BaseModel
from pydantic_ai import Agent
from pydantic_ai.models.anthropic import AnthropicModelSettings
from pydantic_ai.models.bedrock import BedrockConverseModel


# Define a simple tool
def get_current_time() -> str:
    """Get the current time."""
    from datetime import datetime
    return datetime.now().isoformat()


# Define a simple structured output type for this example
class SimpleOutput(BaseModel):
    """Simple structured output."""
    summary: str
    timestamp: str


# Model settings that trigger the bug
model_settings = {
    "max_tokens": 63000,
    "temperature": 1.0,
    "timeout": 300,
    "parallel_tool_calls": True,
    "bedrock_additional_model_requests_fields": {
        "anthropic_beta": [
            "token-efficient-tools-2025-02-19",
            "interleaved-thinking-2025-05-14"
        ],
        "thinking": {
            "type": "enabled",
            "budget_tokens": 4096
        }
    }
}

# Create the Bedrock model
model = BedrockConverseModel(
    model_name="us.anthropic.claude-sonnet-4-5-20250929-v1:0",
    settings=AnthropicModelSettings(**model_settings)
)

# Create agent with tool
agent = Agent(
    model=model,
    tools=[get_current_time],
    system_prompt="You are a helpful assistant. Use the get_current_time tool to provide accurate timestamps."
)


async def main():
    """Run the agent and trigger the error."""

    # This prompt should trigger tool usage
    prompt = "What is the current time?"
    nodes = []
    # Using iter() with output_type triggers the bug when tools are needed
    async with agent.iter(prompt, output_type=SimpleOutput) as agent_run:
        async for node in agent_run:
            nodes.append(node)

    result = agent_run.result.output
    print("\n\nResult:", result)


if __name__ == "__main__":
    asyncio.run(main())

Python, Pydantic AI & LLM client version

- **Python:** 3.12.7
- **Pydantic:** 2.11.7
- **PydanticAI:** 1.0.15
- **boto3:** 1.40.38
- **botocore:** 1.40.38
- **anthropic:** 0.69.0