Merge pull request #38997 from BerriAI/litellm_add_responses_input_tokens_endpoint

feat(proxy): add /v1/responses/input_tokens token counting endpoint

litellm/litellm_core_utils/token_counter.py

@@ -693,6 +693,26 @@ def _count_document_tokens(
     )
 
 
+def _count_file_tokens(
+    file_value: object,
+    count_function: TokenCounterFunction,
+    use_default_image_token_count: bool,
+) -> int:
+    """An OpenAI `file` block is the chat-completions spelling of a document, so it prices like one."""
+    if not isinstance(file_value, Mapping):
+        return 0
+    filename: Final = file_value.get("filename")
+    file_data: Final = file_value.get("file_data")
+    name_tokens: Final = count_function(filename) if isinstance(filename, str) and filename else 0
+    if not isinstance(file_data, str) or not file_data:
+        return name_tokens
+    return name_tokens + calculate_img_tokens(
+        data=file_data,
+        mode="auto",
+        use_default_image_token_count=use_default_image_token_count,
+    )
+
+
 def _count_anthropic_content(
     content: Mapping[str, Any],
     count_function: TokenCounterFunction,
@@ -778,6 +798,12 @@ def _count_content_list(
                     use_default_image_token_count,
                     default_token_count,
                 )
+            elif c["type"] == "file":
+                num_tokens += _count_file_tokens(
+                    c.get("file"),
+                    count_function,
+                    use_default_image_token_count,
+                )
             elif c["type"] in ("tool_use", "tool_result"):
                 num_tokens += _count_anthropic_content(
                     c,
@@ -807,7 +833,7 @@ def _count_content_list(
                 raise ValueError(
                     f"Invalid content item type: {content_type}. "
                     f"Expected str or dict with 'type' field "
-                    f"(text, image_url, image, document, tool_use, tool_result, thinking, tool_reference)."
+                    f"(text, image_url, image, document, file, tool_use, tool_result, thinking, tool_reference)."
                 )
         return num_tokens
     except Exception as e:

litellm/llms/openai/responses/count_tokens/transformation.py

@@ -4,7 +4,100 @@ OpenAI Responses API token counting transformation logic.
 This module handles the transformation of requests to OpenAI's /v1/responses/input_tokens endpoint.
 """
 
-from typing import Any, Final
+from collections.abc import Mapping, Sequence
+from typing import Any, Final, Literal
+
+from typing_extensions import ReadOnly, TypedDict
+
+
+class ResponsesInputTextPart(TypedDict):
+    type: ReadOnly[Literal["input_text"]]
+    text: ReadOnly[str]
+
+
+class ResponsesInputImagePart(TypedDict):
+    type: ReadOnly[Literal["input_image"]]
+    image_url: ReadOnly[str]
+    detail: ReadOnly[str]
+
+
+class ResponsesInputFilePart(TypedDict):
+    type: ReadOnly[Literal["input_file"]]
+    filename: ReadOnly[str]
+    file_data: ReadOnly[str]
+
+
+ResponsesInputPart = ResponsesInputTextPart | ResponsesInputImagePart | ResponsesInputFilePart
+
+ResponsesContentRole = Literal["user", "assistant"]
+
+
+def _chat_image_block_to_responses_part(image_url: object) -> ResponsesInputImagePart | None:
+    url: Final = image_url.get("url") if isinstance(image_url, Mapping) else image_url
+    if not isinstance(url, str) or not url:
+        return None
+    detail: Final = image_url.get("detail") if isinstance(image_url, Mapping) else None
+    part: Final[ResponsesInputImagePart] = {
+        "type": "input_image",
+        "image_url": url,
+        "detail": detail if isinstance(detail, str) and detail else "auto",
+    }
+    return part
+
+
+def _chat_file_block_to_responses_part(file_value: object) -> ResponsesInputFilePart | None:
+    """Only an inline file round trips: OpenAI rejects `file_data` without the `filename` beside it."""
+    if not isinstance(file_value, Mapping):
+        return None
+    filename: Final = file_value.get("filename")
+    file_data: Final = file_value.get("file_data")
+    if not isinstance(filename, str) or not filename or not isinstance(file_data, str) or not file_data:
+        return None
+    part: Final[ResponsesInputFilePart] = {
+        "type": "input_file",
+        "filename": filename,
+        "file_data": file_data,
+    }
+    return part
+
+
+def _chat_block_to_responses_part(block: object, role: ResponsesContentRole) -> ResponsesInputPart | None:
+    if isinstance(block, str):
+        bare: Final[ResponsesInputTextPart] = {"type": "input_text", "text": block}
+        return bare
+    if not isinstance(block, Mapping):
+        return None
+    match block.get("type"):
+        case "text":
+            text_value: Final = block.get("text")
+            text: Final[ResponsesInputTextPart] = {
+                "type": "input_text",
+                "text": text_value if isinstance(text_value, str) else "",
+            }
+            return text
+        case "image_url" if role == "user":
+            return _chat_image_block_to_responses_part(block.get("image_url"))
+        case "file" if role == "user":
+            return _chat_file_block_to_responses_part(block.get("file"))
+        case _:
+            return None
+
+
+def chat_content_blocks_to_responses_content(
+    content: Sequence[object],
+    role: ResponsesContentRole,
+) -> str | tuple[ResponsesInputPart, ...]:
+    """Text-only content collapses to a joined string, which every role accepts and counts identically.
+
+    Only a user turn may carry an image or file part: the Responses API rejects any part but
+    output_text and refusal inside an assistant turn.
+    """
+    parts: Final = tuple(
+        part for part in (_chat_block_to_responses_part(block, role) for block in content) if part is not None
+    )
+    if any(part["type"] != "input_text" for part in parts):
+        return parts
+    return "\n".join(part["text"] for part in parts if part["type"] == "input_text")
 
 
 class OpenAICountTokensConfig:
@@ -120,18 +213,13 @@ class OpenAICountTokensConfig:
                     instructions_parts.append("\n".join(text_parts))
             elif role == "user":
                 if isinstance(content, list):
-                    # Extract text from content blocks for Responses API
-                    text_parts = []
-                    for block in content:
-                        if isinstance(block, dict) and block.get("type") == "text":
-                            text_parts.append(block.get("text", ""))
-                        elif isinstance(block, str):
-                            text_parts.append(block)
-                    content = "\n".join(text_parts)
+                    content = chat_content_blocks_to_responses_content(content, "user")
                 input_items.append({"role": "user", "content": content})
             elif role == "assistant":
                 # Map tool_calls to Responses API function_call items
                 tool_calls = msg.get("tool_calls")
+                if isinstance(content, list):
+                    content = chat_content_blocks_to_responses_content(content, "assistant")
                 if content:
                     input_items.append({"role": "assistant", "content": content})
                 if tool_calls:

litellm/proxy/_types.py

@@ -422,6 +422,9 @@ class LiteLLMRoutes(enum.Enum):
         "/responses/{response_id}/cancel",
         "/v1/responses/{response_id}/cancel",
         "/openai/v1/responses/{response_id}/cancel",
+        "/responses/input_tokens",
+        "/v1/responses/input_tokens",
+        "/openai/v1/responses/input_tokens",
         # vector stores
         "/vector_stores",
         "/v1/vector_stores",

litellm/proxy/response_api_endpoints/endpoints.py

@@ -1,14 +1,18 @@
 import asyncio
 import json
 import time
-from collections.abc import AsyncIterator, Mapping
+from collections.abc import AsyncIterator, Awaitable, Mapping
+from enum import Enum
 from types import MappingProxyType
-from typing import TYPE_CHECKING, Any, Final, NamedTuple, cast, get_args
+from typing import TYPE_CHECKING, Any, Final, NamedTuple, Protocol, cast, get_args
 from uuid import uuid4
 
 import fastapi
 from fastapi import APIRouter, Depends, HTTPException, Request, Response
+from fastapi.responses import JSONResponse
+from openai.types.responses.response_create_params import ResponseInputParam
 from starlette.websockets import WebSocket, WebSocketDisconnect
+from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
 from litellm.integrations.custom_guardrail import ModifyResponseException
@@ -26,8 +30,13 @@ from litellm.proxy.common_utils.http_parsing_utils import (
     _read_request_body,
     _safe_set_request_parsed_body,
 )
-from litellm.types.llms.openai import REASONING_EFFORT, ResponsesAPIResponse
+from litellm.types.llms.openai import (
+    REASONING_EFFORT,
+    ResponsesAPIOptionalRequestParams,
+    ResponsesAPIResponse,
+)
 from litellm.types.responses.main import DeleteResponseResult
+from litellm.types.utils import TokenCountResponse
 
 if TYPE_CHECKING:
     from litellm.router import Router
@@ -35,7 +44,7 @@ if TYPE_CHECKING:
 router: Final = APIRouter()
 
 _user_api_key_auth_dep: Final = Depends(user_api_key_auth)
-_RESPONSES_TAGS: Final = ["responses"]  # mutable-ok: fastapi's route signature requires List[str] tags
+_RESPONSES_TAGS: Final[list[str | Enum]] = ["responses"]  # mutable-ok: fastapi's route signature requires list tags
 
 _TOOL_PAYLOAD_KEYS: Final[Mapping[str, tuple[str, ...]]] = MappingProxyType(
     {
@@ -1017,6 +1026,152 @@ async def compact_response(
         )
 
 
+class _ResponsesApiErrorDetail(TypedDict):
+    message: ReadOnly[str]
+    type: ReadOnly[str]
+    param: ReadOnly[str | None]
+    code: ReadOnly[str | None]
+
+
+class _ResponsesApiErrorBody(TypedDict):
+    error: ReadOnly[_ResponsesApiErrorDetail]
+
+
+class _ResponsesInputTokensResult(TypedDict):
+    object: ReadOnly[str]
+    input_tokens: ReadOnly[int]
+
+
+class _TokenCountPayload(TypedDict):
+    model: ReadOnly[str]
+    messages: ReadOnly[tuple[Mapping[str, object], ...]]
+    tools: ReadOnly[object]
+
+
+class _TokenCounter(Protocol):
+    def __call__(self, request: TokenCountRequest, call_endpoint: bool) -> Awaitable[TokenCountResponse]: ...
+
+
+def _proxy_token_counter() -> _TokenCounter:
+    from litellm.proxy.proxy_server import token_counter
+
+    return token_counter
+
+
+_token_counter_dep: Final = Depends(_proxy_token_counter)
+
+
+def _responses_invalid_request_response(message: str, param: str | None, code: str | None) -> JSONResponse:
+    body: Final[_ResponsesApiErrorBody] = {
+        "error": {
+            "message": message,
+            "type": "invalid_request_error",
+            "param": param,
+            "code": code,
+        }
+    }
+    return JSONResponse(status_code=400, content=body)
+
+
+def _missing_responses_param_response(param: str) -> JSONResponse:
+    return _responses_invalid_request_response(
+        message=f"Missing required parameter: '{param}'.",
+        param=param,
+        code="missing_required_parameter",
+    )
+
+
+def _responses_input_as_token_count_messages(
+    input_value: str | ResponseInputParam,
+    instructions: str | None,
+) -> tuple[Mapping[str, object], ...]:
+    from litellm.responses.litellm_completion_transformation.transformation import (
+        LiteLLMCompletionResponsesConfig,
+    )
+
+    request_params: Final[ResponsesAPIOptionalRequestParams] = {"instructions": instructions}
+    transformed: Final = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages(
+        input=input_value,
+        responses_api_request=request_params,
+    )
+    return tuple(
+        message if isinstance(message, dict) else message.model_dump(exclude_none=True) for message in transformed
+    )
+
+
+@router.post(
+    "/v1/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+@router.post(
+    "/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+@router.post(
+    "/openai/v1/responses/input_tokens",
+    dependencies=(_user_api_key_auth_dep,),
+    tags=_RESPONSES_TAGS,
+)
+async def responses_input_tokens(
+    request: Request,
+    token_counter: _TokenCounter = _token_counter_dep,
+):
+    """
+    Count the input tokens of a Responses API request without calling the model.
+
+    Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+
+    ```bash
+    curl -X POST http://localhost:4000/v1/responses/input_tokens \
+    -H "Content-Type: application/json" \
+    -H "Authorization: Bearer sk-1234" \
+    -d '{
+        "model": "gpt-4o",
+        "input": "Hello, how are you?"
+    }'
+    ```
+
+    Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+    """
+    data: Final = await _read_request_body(request=request)
+    model_name: Final = data.get("model")
+    input_value: Final = data.get("input")
+    if not isinstance(model_name, str) or not model_name:
+        return _missing_responses_param_response("model")
+    if input_value is None:
+        return _missing_responses_param_response("input")
+    if isinstance(input_value, (str, list)) and not input_value:
+        return _responses_invalid_request_response(
+            message="""One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""",
+            param=None,
+            code="missing_required_parameter",
+        )
+
+    try:
+        payload: Final[_TokenCountPayload] = {
+            "model": model_name,
+            "messages": _responses_input_as_token_count_messages(
+                input_value=input_value,
+                instructions=data.get("instructions"),
+            ),
+            "tools": data.get("tools"),
+        }
+        token_request: Final = TokenCountRequest.model_validate(payload)
+    except Exception as e:
+        return _responses_invalid_request_response(
+            message=f"Invalid request for token counting: {e}", param=None, code=None
+        )
+
+    token_response: Final = await token_counter(request=token_request, call_endpoint=True)
+    result: Final[_ResponsesInputTokensResult] = {
+        "object": "response.input_tokens",
+        "input_tokens": token_response.total_tokens,
+    }
+    return result
+
+
 @router.post(
     "/v1/responses/{response_id}/cancel",
     dependencies=[Depends(user_api_key_auth)],

litellm/proxy/spend_tracking/budget_reservation.py

@@ -172,7 +172,14 @@ async def reserve_budget_for_request(
 ) -> dict | None:
     if valid_token is None or not RouteChecks.is_llm_api_route(route=route):
         return None
-    if route in {"/models", "/v1/models", "/utils/token_counter"}:
+    if route in {
+        "/models",
+        "/v1/models",
+        "/utils/token_counter",
+        "/responses/input_tokens",
+        "/v1/responses/input_tokens",
+        "/openai/v1/responses/input_tokens",
+    }:
         return None
     if get_model_from_request(request_body, route, llm_router=llm_router) is None:
         return None

litellm/responses/litellm_completion_transformation/transformation.py

@@ -1629,6 +1629,8 @@ class LiteLLMCompletionResponsesConfig:
             file_dict["file_id"] = file_id
         if item.get("file_data"):
             file_dict["file_data"] = item["file_data"]
+        if item.get("filename"):
+            file_dict["filename"] = item["filename"]
 
         new_item: Final[dict[str, object]] = {"type": "file", "file": file_dict}
         if "cache_control" in item:

tests/test_litellm/litellm_core_utils/test_token_counter.py

@@ -1377,3 +1377,38 @@ def test_anthropic_document_title_and_context_add_their_tokens():
             {"type": "document", "source": source},
         ]
     )
+
+
+def test_openai_file_block_prices_like_the_equivalent_anthropic_document():
+    """An inline `file` is a `document` in the chat-completions dialect, so it must price identically, not raise.
+
+    Before the fix `file` was missing from the content-block match even though `ChatCompletionFileObject`
+    is in the union this counter accepts, so every local count of a Responses `input_file` raised
+    `Invalid content item type: file` and surfaced as a 500 on /v1/responses/input_tokens.
+    """
+    prompt = {"type": "text", "text": "Summarize this file."}
+    inline_file = {
+        "type": "file",
+        "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0xLjQK"},
+    }
+    document = {
+        "type": "document",
+        "title": "report.pdf",
+        "source": {"type": "base64", "media_type": "application/pdf", "data": "JVBERi0xLjQK"},
+    }
+
+    assert _count_user_content([prompt, inline_file]) == _count_user_content([prompt, document])
+    assert _count_user_content([prompt, inline_file]) > _count_user_content([prompt])
+
+
+def test_openai_file_block_without_inline_bytes_counts_what_it_carries():
+    """A `file` block naming an uploaded file has no bytes to price, so it adds only the filename's tokens."""
+    prompt = {"type": "text", "text": "Summarize this file."}
+
+    by_id = {"type": "file", "file": {"file_id": "file-abc123"}}
+    assert _count_user_content([prompt, by_id]) == _count_user_content([prompt])
+
+    named = {"type": "file", "file": {"file_id": "file-abc123", "filename": "report.pdf"}}
+    assert _count_user_content([prompt, named]) == _count_user_content(
+        [prompt, {"type": "text", "text": "report.pdf"}]
+    )

tests/test_litellm/llms/openai/responses/test_openai_count_tokens_transformation.py

@@ -163,6 +163,240 @@ def test_messages_to_responses_input_with_tool():
     }
 
 
+def test_messages_to_responses_input_preserves_images():
+    """An image block must survive the round trip, or OpenAI counts only the text.
+
+    A 256x256 image is worth 255 tokens to OpenAI's counting API; dropping it
+    turned a 268-token request into a 13-token one.
+    """
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this image?"},
+                {
+                    "type": "image_url",
+                    "image_url": {"url": "data:image/png;base64,iVBORw0KGgo=", "detail": "high"},
+                },
+            ],
+        }
+    ]
+
+    input_items, instructions = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert instructions is None
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "What is in this image?"},
+                {
+                    "type": "input_image",
+                    "image_url": "data:image/png;base64,iVBORw0KGgo=",
+                    "detail": "high",
+                },
+            ),
+        }
+    ]
+
+
+def test_messages_to_responses_input_image_without_detail_defaults_to_auto():
+    messages = [
+        {
+            "role": "user",
+            "content": [{"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}}],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_bare_string_image_url_is_preserved():
+    messages = [{"role": "user", "content": [{"type": "image_url", "image_url": "https://example.com/cat.png"}]}]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_text_only_blocks_stay_a_joined_string():
+    """Text-only content must keep collapsing to a string so existing counts do not shift."""
+    messages = [
+        {
+            "role": "user",
+            "content": [{"type": "text", "text": "first"}, {"type": "text", "text": "second"}],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "user", "content": "first\nsecond"}]
+
+
+def test_messages_to_responses_input_drops_unmappable_blocks():
+    """A block with no Responses API equivalent is skipped, never forwarded verbatim."""
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "hi"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+                {"type": "input_audio", "input_audio": {"data": "AAAA", "format": "wav"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items[0]["content"] == (
+        {"type": "input_text", "text": "hi"},
+        {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+    )
+
+
+def test_messages_to_responses_input_assistant_blocks_collapse_to_a_string():
+    """An assistant turn must never forward chat `text` blocks.
+
+    The Responses API only accepts output_text and refusal inside an assistant turn, so
+    forwarding them 400s the whole request and silently drops the count back to the local
+    tokenizer, which is exactly what defeats the image fix above.
+    """
+    messages = [
+        {"role": "user", "content": [{"type": "text", "text": "What is the capital of France?"}]},
+        {"role": "assistant", "content": [{"type": "text", "text": "Paris."}]},
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {"role": "user", "content": "What is the capital of France?"},
+        {"role": "assistant", "content": "Paris."},
+    ]
+
+
+def test_messages_to_responses_input_assistant_image_block_is_dropped():
+    """An image part is illegal inside an assistant turn, so it must not reach the provider."""
+    messages = [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "Here it is"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "assistant", "content": "Here it is"}]
+
+
+def test_messages_to_responses_input_keeps_user_image_alongside_an_assistant_turn():
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "What is in this image?"},
+                {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
+            ],
+        },
+        {"role": "assistant", "content": [{"type": "text", "text": "A cat."}]},
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "What is in this image?"},
+                {"type": "input_image", "image_url": "https://example.com/cat.png", "detail": "auto"},
+            ),
+        },
+        {"role": "assistant", "content": "A cat."},
+    ]
+
+
+def test_messages_to_responses_input_preserves_inline_files():
+    """An inline file must survive the round trip, or the count silently drops the file.
+
+    A small PDF is worth 36 tokens to OpenAI's counting API; dropping it left the same
+    request counting 13, the text-only total.
+    """
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Summarize this file."},
+                {
+                    "type": "file",
+                    "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0="},
+                },
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [
+        {
+            "role": "user",
+            "content": (
+                {"type": "input_text", "text": "Summarize this file."},
+                {
+                    "type": "input_file",
+                    "filename": "report.pdf",
+                    "file_data": "data:application/pdf;base64,JVBERi0=",
+                },
+            ),
+        }
+    ]
+
+
+def test_messages_to_responses_input_drops_a_file_with_no_inline_data():
+    """OpenAI rejects `file_data` without a `filename`, and a rejected request loses the whole count."""
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Summarize this file."},
+                {"type": "file", "file": {"file_data": "data:application/pdf;base64,JVBERi0="}},
+                {"type": "file", "file": {"file_id": "file-abc123"}},
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "user", "content": "Summarize this file."}]
+
+
+def test_messages_to_responses_input_assistant_file_block_is_dropped():
+    """A file part is illegal inside an assistant turn, so it must not reach the provider."""
+    messages = [
+        {
+            "role": "assistant",
+            "content": [
+                {"type": "text", "text": "Here it is"},
+                {
+                    "type": "file",
+                    "file": {"filename": "report.pdf", "file_data": "data:application/pdf;base64,JVBERi0="},
+                },
+            ],
+        }
+    ]
+
+    input_items, _ = OpenAICountTokensConfig.messages_to_responses_input(messages)
+
+    assert input_items == [{"role": "assistant", "content": "Here it is"}]
+
+
 def test_validate_request_valid():
     """Test that valid requests pass validation."""
     config = OpenAICountTokensConfig()

tests/test_litellm/proxy/response_api_endpoints/test_endpoints.py

@@ -3,10 +3,12 @@ Test for response_api_endpoints/endpoints.py
 """
 
 import unittest
+from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 from fastapi.testclient import TestClient
+from httpx import Response
 
 import litellm
 from litellm.proxy.proxy_server import app
@@ -82,11 +84,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
                 ResponseOutputMessage(
                     type="message",
                     role="assistant",
-                    content=[
-                        ResponseOutputText(
-                            type="output_text", text="Hello from Cursor!"
-                        )
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="Hello from Cursor!")],
                 )
             ],
         )
@@ -121,9 +119,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
     @pytest.mark.asyncio
     @patch("litellm.proxy.proxy_server.llm_router")
     @patch("litellm.proxy.proxy_server.user_api_key_auth")
-    async def test_responses_api_key_spend_header_includes_response_cost(
-        self, mock_auth, mock_router
-    ):
+    async def test_responses_api_key_spend_header_includes_response_cost(self, mock_auth, mock_router):
         """
         Test that x-litellm-key-spend header includes the current request's response_cost
         for /v1/responses endpoint.
@@ -159,9 +155,7 @@ class TestResponsesAPIEndpoints(unittest.TestCase):
                 ResponseOutputMessage(
                     type="message",
                     role="assistant",
-                    content=[
-                        ResponseOutputText(type="output_text", text="Test response")
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="Test response")],
                 )
             ],
         )
@@ -356,6 +350,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "model": "gpt-4o", "input": "hello"}
         assert _extract_model_from_first_ws_event(event) == "gpt-4o"
 
@@ -363,6 +358,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "response": {"model": "gpt-4o", "input": "hello"}}
         assert _extract_model_from_first_ws_event(event) == "gpt-4o"
 
@@ -370,6 +366,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {
             "type": "response.create",
             "model": "flat-model",
@@ -381,6 +378,7 @@ class TestWSModelExtraction:
         from litellm.proxy.response_api_endpoints.endpoints import (
             _extract_model_from_first_ws_event,
         )
+
         event = {"type": "response.create", "input": "hello"}
         assert _extract_model_from_first_ws_event(event) is None
 
@@ -400,9 +398,7 @@ class TestResponsesWSFirstFrameValidation:
         )
 
         ws = MagicMock()
-        ws.receive_text = AsyncMock(
-            return_value=json.dumps({"type": "session.update", "model": "gpt-4o"})
-        )
+        ws.receive_text = AsyncMock(return_value=json.dumps({"type": "session.update", "model": "gpt-4o"}))
         ws.send_text = AsyncMock()
         ws.close = AsyncMock()
 
@@ -412,10 +408,7 @@ class TestResponsesWSFirstFrameValidation:
         ws.send_text.assert_awaited_once()
         ws.close.assert_awaited_once_with(code=1008, reason="Invalid first message")
         error_payload = json.loads(ws.send_text.await_args.args[0])
-        assert (
-            error_payload["error"]["message"]
-            == "First message must be a response.create JSON object."
-        )
+        assert error_payload["error"]["message"] == "First message must be a response.create JSON object."
 
     @pytest.mark.asyncio
     async def test_rejects_non_object_json_first_frame(self):
@@ -484,16 +477,12 @@ class TestResponsesWSFirstFrameModelAuth:
         ws.url = "ws://testserver/v1/responses"
         ws.accept = AsyncMock()
         ws.receive_text = AsyncMock(
-            return_value=json.dumps(
-                {"type": "response.create", "model": "gpt-4o-mini", "input": []}
-            )
+            return_value=json.dumps({"type": "response.create", "model": "gpt-4o-mini", "input": []})
         )
         ws.close = AsyncMock()
 
         processor = MagicMock()
-        processor.common_processing_pre_call_logic = AsyncMock(
-            return_value=({"model": "gpt-4o-mini"}, MagicMock())
-        )
+        processor.common_processing_pre_call_logic = AsyncMock(return_value=({"model": "gpt-4o-mini"}, MagicMock()))
 
         async def fake_llm_call():
             return None
@@ -529,9 +518,7 @@ class TestResponsesWSFirstFrameModelAuth:
             _enforce_responses_ws_first_frame_model_auth,
         )
 
-        request = Request(
-            {"type": "http", "method": "POST", "path": "/v1/responses", "headers": []}
-        )
+        request = Request({"type": "http", "method": "POST", "path": "/v1/responses", "headers": []})
         user_api_key_dict = MagicMock()
         llm_router = MagicMock()
 
@@ -593,9 +580,7 @@ class TestReadWSModelFromFirstFrameErrors:
 
         assert result is None
         ws.send_text.assert_not_awaited()
-        ws.close.assert_awaited_once_with(
-            code=1008, reason="Timed out waiting for first message"
-        )
+        ws.close.assert_awaited_once_with(code=1008, reason="Timed out waiting for first message")
 
     @pytest.mark.asyncio
     async def test_invalid_json_sends_error_and_closes(self):
@@ -613,9 +598,7 @@ class TestReadWSModelFromFirstFrameErrors:
         assert result is None
         payload = json.loads(ws.send_text.await_args.args[0])
         assert payload["error"]["message"] == "First message is not valid JSON."
-        ws.close.assert_awaited_once_with(
-            code=1008, reason="Invalid JSON in first message"
-        )
+        ws.close.assert_awaited_once_with(code=1008, reason="Invalid JSON in first message")
 
     @pytest.mark.asyncio
     async def test_missing_model_sends_error_and_closes(self):
@@ -624,9 +607,7 @@ class TestReadWSModelFromFirstFrameErrors:
         )
 
         ws = MagicMock()
-        ws.receive_text = AsyncMock(
-            return_value=json.dumps({"type": "response.create", "input": []})
-        )
+        ws.receive_text = AsyncMock(return_value=json.dumps({"type": "response.create", "input": []}))
         ws.send_text = AsyncMock()
         ws.close = AsyncMock()
 
@@ -679,10 +660,7 @@ class TestManagedResponsesSameProvider:
         assert self._handler("gpt-4o")._same_provider("gpt-4o-mini") is True
 
     def test_different_provider_is_not_same(self):
-        assert (
-            self._handler("gpt-4o")._same_provider("vertex_ai/gemini-2.0-flash")
-            is False
-        )
+        assert self._handler("gpt-4o")._same_provider("vertex_ai/gemini-2.0-flash") is False
 
     def test_inject_credentials_keeps_provider_for_same_provider_model(self):
         handler = self._handler("gpt-4o", custom_llm_provider="openai")
@@ -697,18 +675,14 @@ class TestManagedResponsesSameProvider:
         assert "custom_llm_provider" not in call_kwargs
 
     def test_unresolvable_connection_model_falls_back_to_custom_provider(self):
-        handler = self._handler(
-            "my-custom-deployment", custom_llm_provider="openai"
-        )
+        handler = self._handler("my-custom-deployment", custom_llm_provider="openai")
         assert handler._same_provider("gpt-4o-mini") is True
         call_kwargs: dict = {}
         handler._inject_credentials(call_kwargs, model="gpt-4o-mini")
         assert call_kwargs["custom_llm_provider"] == "openai"
 
     def test_unresolvable_connection_model_still_drops_cross_provider(self):
-        handler = self._handler(
-            "my-custom-deployment", custom_llm_provider="openai"
-        )
+        handler = self._handler("my-custom-deployment", custom_llm_provider="openai")
         call_kwargs: dict = {}
         handler._inject_credentials(call_kwargs, model="vertex_ai/gemini-2.0-flash")
         assert "custom_llm_provider" not in call_kwargs
@@ -840,9 +814,7 @@ def test_cursor_chat_completions_input_body_uses_responses_pipeline_and_strips_s
                     type="message",
                     role="assistant",
                     status="completed",
-                    content=[
-                        ResponseOutputText(type="output_text", text="agent reply", annotations=[])
-                    ],
+                    content=[ResponseOutputText(type="output_text", text="agent reply", annotations=[])],
                 )
             ],
         )
@@ -851,9 +823,12 @@ def test_cursor_chat_completions_input_body_uses_responses_pipeline_and_strips_s
 
     app.dependency_overrides[user_api_key_auth] = _auth_override
     try:
-        with patch.object(ps, "llm_router", mock_router), patch(
-            "litellm.proxy.response_api_endpoints.endpoints._read_request_body",
-            side_effect=capturing_read_request_body,
+        with (
+            patch.object(ps, "llm_router", mock_router),
+            patch(
+                "litellm.proxy.response_api_endpoints.endpoints._read_request_body",
+                side_effect=capturing_read_request_body,
+            ),
         ):
             client = TestClient(app)
             response = client.post(
@@ -1488,8 +1463,8 @@ def _router_serving_only(base_model: str) -> MagicMock:
     mock_router.router_general_settings.pass_through_all_models = False
     mock_router.default_deployment = None
     mock_router.pattern_router.patterns = {base_model: ["anthropic/*"]}
-    mock_router.pattern_router.get_pattern.side_effect = (
-        lambda model: [{"model_name": "anthropic/*"}] if model == base_model else None
+    mock_router.pattern_router.get_pattern.side_effect = lambda model: (
+        [{"model_name": "anthropic/*"}] if model == base_model else None
     )
     return mock_router
 
@@ -1739,9 +1714,7 @@ class TestCursorGateRecognizesRoutingGroups:
         from litellm.proxy.response_api_endpoints.endpoints import _resolve_cursor_model_variant
 
         router = Router(
-            model_list=[
-                {"model_name": "member-fast", "litellm_params": {"model": "openai/gpt-4o", "api_key": "fake"}}
-            ],
+            model_list=[{"model_name": "member-fast", "litellm_params": {"model": "openai/gpt-4o", "api_key": "fake"}}],
             routing_groups=[
                 {"group_name": "grouped-thinking-high", "models": ["member-fast"], "routing_strategy": "simple-shuffle"}
             ],
@@ -1836,3 +1809,153 @@ class TestGuardrailBlockedResponsesUsage:
         assert usage["input_tokens"] == 0
         assert usage["output_tokens"] == 0
         assert usage["total_tokens"] == 0
+
+
+class TestResponsesInputTokens:
+    """Regression tests for POST /v1/responses/input_tokens.
+
+    The docs promise OpenAI-format token counting on the proxy, but the route was
+    never registered, so the POST fell through to the GET/DELETE-only
+    /v1/responses/{response_id} route and returned 405."""
+
+    def _post_input_tokens(
+        self,
+        body: dict[str, Any],
+        path: str = "/v1/responses/input_tokens",
+        counter: AsyncMock | None = None,
+    ) -> tuple[Response, AsyncMock]:
+        from litellm.proxy._types import UserAPIKeyAuth
+        from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
+        from litellm.proxy.response_api_endpoints.endpoints import _proxy_token_counter
+        from litellm.types.utils import TokenCountResponse
+
+        token_counter_mock = (
+            counter
+            if counter is not None
+            else AsyncMock(
+                return_value=TokenCountResponse(
+                    total_tokens=13,
+                    request_model=body.get("model", ""),
+                    model_used=body.get("model", ""),
+                    tokenizer_type="openai_api",
+                )
+            )
+        )
+        app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth(api_key="sk-test", request_route=path)
+        app.dependency_overrides[_proxy_token_counter] = lambda: token_counter_mock
+        try:
+            client = TestClient(app)
+            response = client.post(path, json=body, headers={"Authorization": "Bearer sk-1234"})
+            return response, token_counter_mock
+        finally:
+            app.dependency_overrides.pop(user_api_key_auth, None)
+            app.dependency_overrides.pop(_proxy_token_counter, None)
+
+    def test_string_input_returns_openai_input_tokens_shape(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": "Hello, how are you?"})
+
+        assert response.status_code == 200, response.text
+        assert response.json() == {"object": "response.input_tokens", "input_tokens": 13}
+        counter.assert_awaited_once()
+        assert counter.call_args.kwargs["call_endpoint"] is True
+        token_request = counter.call_args.kwargs["request"]
+        assert token_request.model == "gpt-4o"
+        assert token_request.messages == [{"role": "user", "content": "Hello, how are you?"}]
+
+    def test_every_route_alias_is_registered(self):
+        for path in ("/v1/responses/input_tokens", "/responses/input_tokens", "/openai/v1/responses/input_tokens"):
+            response, _ = self._post_input_tokens({"model": "gpt-4o", "input": "hi"}, path=path)
+            assert response.status_code == 200, f"{path}: {response.status_code} {response.text}"
+
+    def test_input_items_instructions_and_tools_are_forwarded(self):
+        tools = [
+            {
+                "type": "function",
+                "name": "get_weather",
+                "description": "Get weather for a city",
+                "parameters": {"type": "object", "properties": {"city": {"type": "string"}}},
+            }
+        ]
+        response, counter = self._post_input_tokens(
+            {
+                "model": "gpt-4o",
+                "input": [{"role": "user", "content": "What is the weather in Paris?"}],
+                "instructions": "You are terse.",
+                "tools": tools,
+            }
+        )
+
+        assert response.status_code == 200, response.text
+        token_request = counter.call_args.kwargs["request"]
+        assert token_request.messages == [
+            {"role": "system", "content": "You are terse."},
+            {"role": "user", "content": "What is the weather in Paris?"},
+        ]
+        assert token_request.tools == tools
+
+    def test_missing_model_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"input": "Hello"})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": "Missing required parameter: 'model'.",
+                "type": "invalid_request_error",
+                "param": "model",
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    def test_missing_input_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o"})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": "Missing required parameter: 'input'.",
+                "type": "invalid_request_error",
+                "param": "input",
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    @pytest.mark.parametrize("empty_input", ["", []])
+    def test_empty_input_returns_openai_400(self, empty_input):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": empty_input})
+
+        assert response.status_code == 400, response.text
+        assert response.json() == {
+            "error": {
+                "message": """One of "input" or "previous_response_id" or 'prompt' or 'conversation' must be provided.""",
+                "type": "invalid_request_error",
+                "param": None,
+                "code": "missing_required_parameter",
+            }
+        }
+        counter.assert_not_awaited()
+
+    def test_invalid_tools_returns_openai_400(self):
+        response, counter = self._post_input_tokens({"model": "gpt-4o", "input": "hi", "tools": "not-a-list"})
+
+        assert response.status_code == 400, response.text
+        error = response.json()["error"]
+        assert error["type"] == "invalid_request_error"
+        counter.assert_not_awaited()
+
+    def test_provider_error_maps_status_code(self):
+        from litellm.proxy._types import ProxyException
+
+        failing_counter = AsyncMock(
+            side_effect=ProxyException(
+                message="rate limited",
+                type="token_counting_error",
+                param="model",
+                code="429",
+            )
+        )
+        response, _ = self._post_input_tokens({"model": "gpt-4o", "input": "hi"}, counter=failing_counter)
+
+        assert response.status_code == 429, response.text
+        assert response.json()["error"]["message"] == "rate limited"

tests/test_litellm/proxy/spend_tracking/test_budget_reservation.py

@@ -0,0 +1,48 @@
+from typing import Final
+
+import pytest
+
+from litellm.caching import DualCache
+from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache
+from litellm.proxy.spend_tracking.budget_reservation import reserve_budget_for_request
+from litellm.proxy.utils import ProxyLogging
+
+TOKEN_COUNTING_ROUTES: Final = (
+    "/responses/input_tokens",
+    "/v1/responses/input_tokens",
+    "/openai/v1/responses/input_tokens",
+    "/utils/token_counter",
+)
+
+
+def _budgeted_token() -> UserAPIKeyAuth:
+    return UserAPIKeyAuth(api_key="sk-test", token="hashed-token", max_budget=100.0, spend=0.0)
+
+
+async def _reserve(route: str) -> dict | None:
+    return await reserve_budget_for_request(
+        request_body={"model": "gpt-4o", "input": "hello"},
+        route=route,
+        llm_router=None,
+        valid_token=_budgeted_token(),
+        team_object=None,
+        user_object=None,
+        prisma_client=None,
+        user_api_key_cache=UserApiKeyCache(),
+        proxy_logging_obj=ProxyLogging(user_api_key_cache=DualCache()),
+    )
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("route", TOKEN_COUNTING_ROUTES)
+async def test_token_counting_routes_are_exempt_from_budget_reservation(route):
+    assert await _reserve(route) is None
+
+
+@pytest.mark.asyncio
+async def test_non_exempt_llm_route_still_reserves_budget():
+    reservation: Final = await _reserve("/v1/responses")
+
+    assert reservation is not None
+    assert reservation["reserved_cost"] > 0

tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py

@@ -124,6 +124,25 @@ class TestLiteLLMCompletionResponsesConfig:
         assert "extra_field" not in result["file"]
         assert "another_field" not in result["file"]
 
+    def test_transform_input_file_item_to_file_item_keeps_filename(self):
+        """OpenAI rejects file_data with no filename beside it, so dropping it 400s the request"""
+        result = (
+            LiteLLMCompletionResponsesConfig._transform_input_file_item_to_file_item(
+                {
+                    "type": "input_file",
+                    "filename": "report.pdf",
+                    "file_data": "data:application/pdf;base64,JVBERi0=",
+                }
+            )
+        )
+        assert result == {
+            "type": "file",
+            "file": {
+                "file_data": "data:application/pdf;base64,JVBERi0=",
+                "filename": "report.pdf",
+            },
+        }
+
     def test_transform_input_file_item_to_file_item_with_file_url(self):
         """file_url should be mapped to file_id for downstream URL handling"""
         result = (

ui/litellm-dashboard/src/lib/http/schema.d.ts

@@ -9700,6 +9700,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/openai/v1/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_openai_v1_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/openai/v1/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -12619,6 +12650,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -19194,6 +19256,37 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/v1/responses/input_tokens": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        put?: never;
+        /**
+         * Responses Input Tokens
+         * @description Count the input tokens of a Responses API request without calling the model.
+         *
+         *     Follows the OpenAI Responses API spec: https://platform.openai.com/docs/api-reference/responses/input-tokens
+         *
+         *     ```bash
+         *     curl -X POST http://localhost:4000/v1/responses/input_tokens     -H "Content-Type: application/json"     -H "Authorization: Bearer sk-1234"     -d '{
+         *         "model": "gpt-4o",
+         *         "input": "Hello, how are you?"
+         *     }'
+         *     ```
+         *
+         *     Returns: `{"object": "response.input_tokens", "input_tokens": <count>}`
+         */
+        post: operations["responses_input_tokens_v1_responses_input_tokens_post"];
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/v1/responses/{response_id}": {
         parameters: {
             query?: never;
@@ -51496,6 +51589,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_openai_v1_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_openai_v1_responses__response_id__get: {
         parameters: {
             query?: never;
@@ -54460,6 +54573,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_responses__response_id__get: {
         parameters: {
             query?: never;
@@ -62882,6 +63015,26 @@ export interface operations {
             };
         };
     };
+    responses_input_tokens_v1_responses_input_tokens_post: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": unknown;
+                };
+            };
+        };
+    };
     get_response_v1_responses__response_id__get: {
         parameters: {
             query?: never;