nemo_gym.responses_converter

Shared Responses API ↔ Chat Completions converter.

This module contains the translation logic between OpenAI’s Responses API format and the Chat Completions API format. It is used by model servers that need to convert between the two formats (e.g. vllm_model, inference_provider).

Module Contents

Classes

Name	Description
`ResponsesConverter`	Converts between OpenAI Responses API and Chat Completions API formats.
`ResponsesConverterState`	-

Functions

Name	Description
`_message_content_to_text`	Plain text of a chat message content (a string, or a list of text parts).
`_optional_token_count`	Return a provider-reported token count without coercing missing/invalid values to zero.
`_token_information_from_mapping`	Return validated token metadata when the mapping contains it.
`_usage_detail`	Read one canonical nested token detail, then named provider aliases.
`split_responses_input_output_items`	-

Data

VLLMConverter

VLLMConverterResponsesToChatCompletionsState

_RESPONSE_NON_BOUNDARY_TYPES

_RESPONSE_OUTPUT_BOUNDARY_TYPES

API

class nemo_gym.responses_converter.ResponsesConverter()

Bases: BaseModel

Converts between OpenAI Responses API and Chat Completions API formats.

THINK_TAG_PATTERN

ClassVar = re.compile('<think>(.*?)</think>', re.DOTALL)

return_token_id_information

bool

uses_reasoning_parser

bool = True

nemo_gym.responses_converter.ResponsesConverter._chat_completion_to_responses_tools(
    chat_completions_tools: typing.Optional[typing.List[nemo_gym.openai_utils.NeMoGymChatCompletionToolParam]]
) -> typing.List[nemo_gym.openai_utils.NeMoGymFunctionToolParam]

nemo_gym.responses_converter.ResponsesConverter._extract_reasoning_from_content(
    content: str
) -> typing.Tuple[typing.List[str], str]

nemo_gym.responses_converter.ResponsesConverter._format_function_call(
    m: dict,
    state: nemo_gym.responses_converter.ResponsesConverterState
) -> None

nemo_gym.responses_converter.ResponsesConverter._format_function_call_output(
    m: dict,
    state: nemo_gym.responses_converter.ResponsesConverterState
) -> None

nemo_gym.responses_converter.ResponsesConverter._format_message(
    m: dict,
    state: nemo_gym.responses_converter.ResponsesConverterState
) -> None

nemo_gym.responses_converter.ResponsesConverter._format_reasoning(
    m: dict,
    state: nemo_gym.responses_converter.ResponsesConverterState
) -> None

Collects text from ‘reasoning’ messages in responses api and appends it to a buffer.

This is done to group together one (or multiple) reasoning message(s) into a single, cohesive block, later prepending it to a subsequent assistant message. See: https://docs.nvidia.com/nemo/gym/main/infrastructure/engineering-notes/responses-api-evolution for background on reasoning in the Responses API.

nemo_gym.responses_converter.ResponsesConverter._parse_think_tags(
    content: str
) -> typing.Tuple[typing.List[str], str]

classmethod

nemo_gym.responses_converter.ResponsesConverter._wrap_reasoning_in_think_tags(
    texts: typing.List[str]
) -> str

staticmethod

nemo_gym.responses_converter.ResponsesConverter.chat_completion_to_response(
    responses_create_params: nemo_gym.openai_utils.NeMoGymResponseCreateParamsNonStreaming,
    chat_completion: nemo_gym.openai_utils.NeMoGymChatCompletion
) -> nemo_gym.openai_utils.NeMoGymResponse

nemo_gym.responses_converter.ResponsesConverter.chat_completion_to_responses_create_params(
    chat_completion_create_params: nemo_gym.openai_utils.NeMoGymChatCompletionCreateParamsNonStreaming
) -> nemo_gym.openai_utils.NeMoGymResponseCreateParamsNonStreaming

nemo_gym.responses_converter.ResponsesConverter.chat_completions_messages_to_responses_items(
    messages: typing.List[typing.Dict[str, typing.Any]]
) -> typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem]

nemo_gym.responses_converter.ResponsesConverter.postprocess_assistant_message_dict(
    message_dict: typing.Dict[str, typing.Any]
) -> typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem]

nemo_gym.responses_converter.ResponsesConverter.postprocess_chat_response(
    choice: nemo_gym.openai_utils.NeMoGymChoice
) -> typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem]

nemo_gym.responses_converter.ResponsesConverter.responses_to_chat_completion_create_params(
    responses_create_params: nemo_gym.openai_utils.NeMoGymResponseCreateParamsNonStreaming
) -> nemo_gym.openai_utils.NeMoGymChatCompletionCreateParamsNonStreaming

class nemo_gym.responses_converter.ResponsesConverterState()

Bases: BaseModel

assistant_item_buffered

bool = False

content_buffer

str = ''

messages

List[NeMoGymChatCompletionMessageParam] = Field(default_factory=list)

return_token_id_information

bool

token_information

Optional[TokenIDLogProbMixin] = None

tool_calls_buffer

List[NeMoGymChatCompletionMessageToolCallParam] = Field(default_factory=list)

nemo_gym.responses_converter.ResponsesConverterState.flush_assistant() -> None

nemo_gym.responses_converter._message_content_to_text(
    content: typing.Any
) -> str

Plain text of a chat message content (a string, or a list of text parts).

nemo_gym.responses_converter._optional_token_count(
    value: typing.Any
) -> typing.Optional[int]

Return a provider-reported token count without coercing missing/invalid values to zero.

nemo_gym.responses_converter._token_information_from_mapping(
    value: typing.Dict[str, typing.Any]
) -> typing.Optional[nemo_gym.openai_utils.TokenIDLogProbMixin]

Return validated token metadata when the mapping contains it.

nemo_gym.responses_converter._usage_detail(
    usage: typing.Any,
    detail_group: str,
    detail_name: str,
    top_level_aliases: str = ()
) -> typing.Optional[int]

Read one canonical nested token detail, then named provider aliases.

nemo_gym.responses_converter.split_responses_input_output_items(
    items: typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem]
) -> typing.Tuple[typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem], typing.List[nemo_gym.openai_utils.NeMoGymResponseOutputItem]]

nemo_gym.responses_converter.VLLMConverter = ResponsesConverter

nemo_gym.responses_converter.VLLMConverterResponsesToChatCompletionsState = ResponsesConverterState

nemo_gym.responses_converter._RESPONSE_NON_BOUNDARY_TYPES: frozenset[str] = frozenset({'computer_call_output', 'custom_tool_call_output', 'function_call_out...

nemo_gym.responses_converter._RESPONSE_OUTPUT_BOUNDARY_TYPES = frozenset({'code_interpreter_call', 'computer_call', 'custom_tool_call', 'file_s...