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fix(bedrock_mantle): normalize Codex agent message inputs
This commit is contained in:
Luis Gallego Ledesma
parent
b0fac57fe4
commit
be9ae8f3ab
2 changed files with 184 additions and 1 deletions
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@ -49,6 +49,9 @@ _BEDROCK_MANTLE_SUPPORTED_RESPONSE_TOOL_TYPES = frozenset({"function", "mcp", "c
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_BEDROCK_MANTLE_SUPPORTED_SERVICE_TIERS: Final = frozenset({"auto", "default"})
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_CODEX_ADDITIONAL_TOOLS_INPUT_ITEM_TYPE: Final = "additional_tools"
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_CODEX_AGENT_MESSAGE_INPUT_ITEM_TYPE: Final = "agent_message"
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_CODEX_AGENT_MESSAGE_INPUT_TEXT_CONTENT_TYPE: Final = "input_text"
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_CODEX_AGENT_MESSAGE_ENCRYPTED_CONTENT_TYPE: Final = "encrypted_content"
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class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPIConfig):
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@ -155,6 +158,7 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI
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headers: dict,
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) -> dict:
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remaining_input, hoisted_tools = self._hoist_codex_additional_tools(input)
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normalized_input: Final = self._normalize_codex_agent_messages(remaining_input)
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request_params: Final = (
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{
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**response_api_optional_request_params,
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@ -168,7 +172,7 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI
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)
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return super().transform_responses_api_request(
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model=model,
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input=remaining_input,
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input=normalized_input,
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response_api_optional_request_params=request_params,
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litellm_params=litellm_params,
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headers=headers,
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@ -210,6 +214,74 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI
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)
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return remaining_input, cls._filter_unsupported_tools(hoisted_tools)
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@staticmethod
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def _is_codex_agent_message_item(item: object) -> bool:
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return isinstance(item, dict) and item.get("type") == _CODEX_AGENT_MESSAGE_INPUT_ITEM_TYPE
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@staticmethod
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def _encrypted_content_block_count(item: "dict[str, Any]") -> int:
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content: Final = item.get("content")
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if not isinstance(content, list):
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return 0
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return sum(
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isinstance(block, dict) and block.get("type") == _CODEX_AGENT_MESSAGE_ENCRYPTED_CONTENT_TYPE
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for block in content
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)
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@staticmethod
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def _normalize_codex_agent_message_item(item: "dict[str, Any]") -> "dict[str, Any] | None":
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content: Final = item.get("content")
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if not isinstance(content, list):
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return None
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text_parts: Final = [
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block["text"]
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for block in content
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if isinstance(block, dict)
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and block.get("type") == _CODEX_AGENT_MESSAGE_INPUT_TEXT_CONTENT_TYPE
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and isinstance(block.get("text"), str)
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]
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if not text_parts:
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return None
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return {
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"type": "message",
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"role": "assistant",
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"content": [{"type": _CODEX_AGENT_MESSAGE_INPUT_TEXT_CONTENT_TYPE, "text": "\n".join(text_parts)}],
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}
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@classmethod
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def _normalize_codex_agent_messages(
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cls,
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input: "str | ResponseInputParam",
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) -> "str | ResponseInputParam":
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if not isinstance(input, list):
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return input
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agent_message_items: Final = [item for item in input if cls._is_codex_agent_message_item(item)]
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if not agent_message_items:
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return input
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normalized_items: Final = tuple(
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cls._normalize_codex_agent_message_item(item) if cls._is_codex_agent_message_item(item) else item
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for item in input
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)
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normalized_agent_message_items: Final = tuple(
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cls._normalize_codex_agent_message_item(item) for item in agent_message_items
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)
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normalized_input: Final = [item for item in normalized_items if item is not None]
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dropped_item_count: Final = sum(item is None for item in normalized_agent_message_items)
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encrypted_content_block_count: Final = sum(
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cls._encrypted_content_block_count(item) for item in agent_message_items
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)
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verbose_logger.warning(
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"Bedrock Mantle Responses API: converted %d unsupported Codex 'agent_message' item(s) to "
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"'message'; dropped %d item(s) without readable text and %d encrypted_content block(s) Mantle "
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"cannot process.",
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len(agent_message_items) - dropped_item_count,
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dropped_item_count,
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encrypted_content_block_count,
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)
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return normalized_input
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def map_openai_params(
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self,
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response_api_optional_params: ResponsesAPIOptionalRequestParams,
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@ -632,6 +632,117 @@ class TestBedrockMantleCodexAdditionalTools:
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assert "additional_tools" in str(mock_debug.call_args)
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class TestBedrockMantleCodexAgentMessages:
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_USER_MESSAGE = {
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"type": "message",
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"role": "user",
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"content": [{"type": "input_text", "text": "Continue the task."}],
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}
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def _transform(self, input):
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cfg = BedrockMantleResponsesAPIConfig()
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return cfg.transform_responses_api_request(
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model="openai.gpt-5.6-terra",
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input=input,
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response_api_optional_request_params={},
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litellm_params=GenericLiteLLMParams(),
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headers={},
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)
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def test_plain_agent_message_is_normalized_to_assistant_message(self):
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body = self._transform(
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input=[
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self._USER_MESSAGE,
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{
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"type": "agent_message",
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"id": "amsg_123",
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"author": "worker",
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"recipient": "parent",
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"content": [{"type": "input_text", "text": "The subtask is complete."}],
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},
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]
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)
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assert body["input"] == [
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self._USER_MESSAGE,
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{
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"type": "message",
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"role": "assistant",
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"content": [{"type": "input_text", "text": "The subtask is complete."}],
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},
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]
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def test_encrypted_agent_message_keeps_readable_text_only(self):
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body = self._transform(
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input=[
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{
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"type": "agent_message",
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"author": "worker",
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"recipient": "parent",
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"content": [
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{"type": "input_text", "text": "Message Type: MESSAGE\nSender: worker\nPayload:\n"},
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{"type": "encrypted_content", "encrypted_content": "opaque-payload"},
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],
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}
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]
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)
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assert body["input"] == [
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{
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"type": "message",
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"role": "assistant",
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"content": [
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{"type": "input_text", "text": "Message Type: MESSAGE\nSender: worker\nPayload:\n"}
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],
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}
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]
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def test_agent_message_without_readable_text_is_removed(self):
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body = self._transform(
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input=[
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self._USER_MESSAGE,
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{
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"type": "agent_message",
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"author": "worker",
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"recipient": "parent",
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"content": [{"type": "encrypted_content", "encrypted_content": "opaque-payload"}],
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},
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]
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)
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assert body["input"] == [self._USER_MESSAGE]
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def test_agent_message_normalization_is_logged_at_warning_level(self):
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from unittest.mock import patch
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with patch(
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"litellm.llms.bedrock_mantle.responses.transformation.verbose_logger.warning"
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) as mock_warning:
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self._transform(
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input=[
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{
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"type": "agent_message",
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"content": [{"type": "input_text", "text": "Done."}],
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}
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]
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)
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assert mock_warning.call_count == 1
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assert "agent_message" in str(mock_warning.call_args)
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def test_non_agent_items_remain_unchanged(self):
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input_items = [
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self._USER_MESSAGE,
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{"type": "reasoning", "summary": [], "encrypted_content": "gAAAA=="},
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{"type": "function_call", "name": "wait", "arguments": "{}", "call_id": "call_1"},
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{"type": "function_call_output", "call_id": "call_1", "output": "done"},
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]
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body = self._transform(input=input_items)
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assert body["input"] == input_items
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class TestBedrockMantleResponsesRegistry:
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def test_registry_returns_config_for_gpt_5_5(self, local_cost_map):
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# gpt-5.x advertises /v1/responses in supported_endpoints (capability)
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