feat(minimax): add MiniMax-H3 and H3-Max video generation via /v1/videos

MinimaxVideoConfig maps litellm's OpenAI Videos API onto MiniMax's V2 task
API. Create, status, list, content and delete hit /v2/video_generation and
/v2/query/video_generation. Remix is not exposed: MiniMax's
/v2/video_regeneration only upscales a finished 768P task to 2K and ignores any
prompt, so it raises instead of returning a video that silently drops the edit

OpenAI params translate to MiniMax's contract: seconds becomes duration, size
reduces via gcd to a valid ratio, and text-to-video requests default to ratio
16:9, resolution 768P and duration 5 when unset. input_reference becomes a
first_frame content item, base64 encoded into a data URI for file inputs, and
multimodal reference media passes through a content array in extra_body. Caller
content is validated strictly as image, video or audio items, and the scanned
prompt is always the one text item sent, so text can't reach MiniMax past the
guardrails; anything else in content returns a 400. api_base
shares MINIMAX_API_BASE with the chat config (a trailing /v1 or /v2 is stripped
because the video API carries its own version). The list endpoint pages by
number with no cursor or sort, so after and an ascending order are rejected
with a 400 rather than ignored, and page_num passes through extra_query. Responses
validate into frozen pydantic models at the boundary, video ids are
provider-encoded so status and content route back to MiniMax, and create
reports duration_seconds and video_resolution in usage for cost tracking

End-to-end tests drive the real avideo_generation() entrypoint through an httpx
MockTransport and assert on the encoded request body, which is what catches a
mapper that drops input_reference before the request is built

Both model_prices maps gain minimax/MiniMax-H3 and minimax/MiniMax-H3-Max,
priced per output second by resolution tier from MiniMax's pay-as-you-go list
(H3 $0.08 at 768P and $0.13 at 2K, H3-Max $0.05 at 480P and $0.08 at 768P).
MiniMax also bills input images beyond a per-model free allowance (5 for H3, 2
for H3-Max), so each entry carries input_cost_per_image and
provider_specific_entry.minimax_free_input_images, and the create response
reports the full charge as provider_reported_cost_usd. Reference video input is
rejected with a 400, because MiniMax bills its duration only after the create
call that litellm bills

Co-authored-by: AaronHowell <237895480@qq.com>

litellm/llms/minimax/videos/transformation.py

@@ -0,0 +1,692 @@
+"""
+MiniMax V2 video task API: create, poll, list, download and delete. Regeneration (/v2/video_regeneration)
+only upscales a finished 768P task to 2K and ignores the prompt, so it is not exposed as an OpenAI remix.
+"""
+
+import base64
+from collections.abc import Mapping, Sequence
+from io import BufferedReader, BytesIO
+from math import gcd
+from types import MappingProxyType
+from typing import TYPE_CHECKING, Final, Literal
+
+import httpx
+from httpx._types import RequestFiles
+from pydantic import BaseModel, TypeAdapter, ValidationError
+
+import litellm
+from litellm.exceptions import UnsupportedParamsError
+from litellm.images.utils import ImageEditRequestUtils
+from litellm.litellm_core_utils.url_utils import encode_url_path_segment
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.llms.base_llm.videos.transformation import BaseVideoConfig
+from litellm.llms.custom_httpx.http_handler import (
+    _get_httpx_client,  # pyright: ignore[reportPrivateUsage, reportUnknownVariableType]  # house cached-client factory has no public alias and its stub leaves params untyped
+    get_async_httpx_client,  # pyright: ignore[reportUnknownVariableType]  # factory stub leaves params untyped
+)
+from litellm.llms.openai.cost_calculation import video_generation_cost
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.videos.main import VideoCreateOptionalRequestParams, VideoObject
+from litellm.types.videos.utils import (
+    encode_video_id_with_provider,
+    extract_original_video_id,
+)
+from litellm.utils import get_model_info
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging
+    from litellm.llms.custom_httpx.http_handler import HTTPHandler
+
+
+class MinimaxVideoError(BaseLLMException):
+    pass
+
+
+class _TaskError(BaseModel, frozen=True):
+    code: str | None = None
+    message: str | None = None
+
+
+class _TaskUsage(BaseModel, frozen=True):
+    total_seconds: int | None = None
+    input_seconds: int | None = None
+    output_seconds: int | None = None
+    input_image_count: int | None = None
+    input_audio_seconds: int | None = None
+    total_tokens: int | None = None
+    prompt_tokens: int | None = None
+    completion_tokens: int | None = None
+
+
+class _TaskContent(BaseModel, frozen=True):
+    url: str | None = None
+    prompt: str | None = None
+
+
+class _ContentItem(BaseModel, frozen=True):
+    type: str = ""
+    text: str | None = None
+    role: str | None = None
+
+
+class _MediaUrl(BaseModel, frozen=True, extra="forbid"):
+    url: str
+
+
+class _CallerMediaItem(BaseModel, frozen=True, extra="forbid"):
+    type: Literal["image_url", "video_url", "audio_url"]
+    image_url: _MediaUrl | None = None
+    video_url: _MediaUrl | None = None
+    audio_url: _MediaUrl | None = None
+    role: Literal["first_frame", "last_frame", "reference_image", "reference_video", "reference_audio"] | None = None
+
+
+class _MiniMaxTask(BaseModel, frozen=True):
+    id: str = ""
+    model: str | None = None
+    status: str = ""
+    error: _TaskError | None = None
+    created_at: int | None = None
+    updated_at: int | None = None
+    content: _TaskContent | None = None
+    resolution: str | None = None
+    duration: int | None = None
+    usage: _TaskUsage | None = None
+    ratio: str | None = None
+    task_type: str | None = None
+    modality: str | None = None
+
+
+class _TaskIdResponse(BaseModel, frozen=True):
+    task_id: str = ""
+
+
+class _TaskResponse(BaseModel, frozen=True):
+    task: _MiniMaxTask | None = None
+
+
+class _ListResponse(BaseModel, frozen=True):
+    items: Sequence[_MiniMaxTask] | None = None
+    total: int | None = None
+
+
+class _DeleteResponse(BaseModel, frozen=True):
+    task_id: str = ""
+    status: str = ""
+
+
+MINIMAX_VIDEO_DEFAULT_API_BASE: Final = "https://api.minimax.io"
+MINIMAX_VIDEO_DEFAULT_RESOLUTION: Final = "768P"
+MINIMAX_VIDEO_DEFAULT_DURATION_SECONDS: Final = 5
+MINIMAX_TEXT_TO_VIDEO_DEFAULT_RATIO: Final = "16:9"
+
+_EMPTY_PARAMS: Final[dict[str, object]] = {}  # mutable-ok: BaseVideoConfig contract empty params
+
+_RESPONSE_ADAPTER: Final = TypeAdapter(dict[str, object])
+_TASK_ID_RESPONSE_ADAPTER: Final = TypeAdapter(_TaskIdResponse)
+_TASK_RESPONSE_ADAPTER: Final = TypeAdapter(_TaskResponse)
+_LIST_RESPONSE_ADAPTER: Final = TypeAdapter(_ListResponse)
+_DELETE_RESPONSE_ADAPTER: Final = TypeAdapter(_DeleteResponse)
+_CONTENT_ITEMS_ADAPTER: Final = TypeAdapter(list[_ContentItem])
+_CALLER_MEDIA_ADAPTER: Final = TypeAdapter(list[_CallerMediaItem])
+
+_STATUS_MAP: Final = MappingProxyType(
+    {
+        "queued": "queued",
+        "running": "in_progress",
+        "succeeded": "completed",
+        "failed": "failed",
+        "cancelled": "cancelled",
+    }
+)
+
+_DROP_FROM_CREATE_BODY: Final = frozenset(
+    {
+        "model",
+        "prompt",
+        "user",
+        "characters",
+        "image",
+        "extra_headers",
+        "extra_query",
+        "extra_body",
+    }
+)
+
+_CREATE_BODY_KEYS: Final = (
+    "resolution",
+    "duration",
+    "ratio",
+    "callback_url",
+    "aigc_watermark",
+    "extra",
+)
+
+
+def _parse_task_response(raw_response: httpx.Response) -> _MiniMaxTask:
+    return _TASK_RESPONSE_ADAPTER.validate_python(raw_response.json()).task or _MiniMaxTask()
+
+
+def _parse_task_id_response(raw_response: httpx.Response) -> str:
+    return _TASK_ID_RESPONSE_ADAPTER.validate_python(raw_response.json()).task_id
+
+
+def _parse_delete_response(raw_response: httpx.Response) -> tuple[str, str]:
+    deleted: Final = _DELETE_RESPONSE_ADAPTER.validate_python(raw_response.json())
+    return deleted.task_id, deleted.status
+
+
+MINIMAX_SURFACE_SUFFIXES: Final = ("/v1", "/v2", "/anthropic")
+
+
+def _normalized_api_base(api_base: str) -> str:
+    """
+    A MiniMax key covers the chat surfaces (``/v1``, ``/anthropic``) and video (``/v2``), so strip whichever
+    surface suffix a shared api_base carries back to the host.
+    """
+    trimmed: Final = api_base.rstrip("/")
+    matched: Final = next((suffix for suffix in MINIMAX_SURFACE_SUFFIXES if trimmed.endswith(suffix)), None)
+    return trimmed[: -len(matched)] if matched else trimmed
+
+
+def _ratio_from_size(size: str) -> str | None:
+    if ":" in size:
+        return size
+    width_str, separator, height_str = size.partition("x")
+    if not separator or not (width_str.isdigit() and height_str.isdigit()):
+        return None
+    width: Final = int(width_str)
+    height: Final = int(height_str)
+    divisor: Final = gcd(width, height)
+    return f"{width // divisor}:{height // divisor}"
+
+
+def _duration_param(seconds: object) -> int | None:
+    if isinstance(seconds, bool):
+        return None
+    if isinstance(seconds, int):
+        return seconds
+    if not isinstance(seconds, str):
+        return None
+    try:
+        return int(float(seconds))
+    except ValueError:
+        return None
+
+
+def _read_all_bytes(file_obj: object) -> bytes:
+    if isinstance(file_obj, (BytesIO, BufferedReader)):
+        current_position: Final = file_obj.tell()
+        file_obj.seek(0)
+        content: Final = file_obj.read()
+        file_obj.seek(current_position)
+        return content
+    if isinstance(file_obj, bytes):
+        return file_obj
+    if isinstance(file_obj, bytearray):
+        return bytes(file_obj)
+    read: Final = getattr(file_obj, "read", None)
+    if callable(read):
+        data: Final = read()
+        if isinstance(data, bytes):
+            return data
+    raise ValueError("input_reference must be a URL string, bytes, or a file object")
+
+
+def _image_url(image: object) -> str:
+    if isinstance(image, str):
+        return image
+    content_type: Final = ImageEditRequestUtils.get_image_content_type(image)
+    encoded: Final = base64.b64encode(_read_all_bytes(image)).decode("utf-8")
+    return f"data:{content_type};base64,{encoded}"
+
+
+def _first_frame_content_item(
+    image: object,
+) -> dict[str, object]:  # mutable-ok: content items are JSON request-body fragments
+    return {  # mutable-ok: request-body content item serialized to JSON by the handler
+        "type": "image_url",
+        "image_url": {"url": _image_url(image)},  # mutable-ok: request-body content item field
+        "role": "first_frame",
+    }
+
+
+def _content_items(content: object) -> tuple[_ContentItem, ...]:
+    if not isinstance(content, Sequence) or isinstance(content, (str, bytes)):
+        return ()
+    try:
+        return tuple(_CONTENT_ITEMS_ADAPTER.validate_python(content))
+    except ValidationError:
+        return ()
+
+
+def _is_text_only_content(content: object) -> bool:
+    if not isinstance(content, Sequence) or isinstance(content, (str, bytes)) or not content:
+        return False
+    try:
+        items: Final = _CONTENT_ITEMS_ADAPTER.validate_python(content)
+    except ValidationError:
+        return False
+    return all(item.type == "text" for item in items)
+
+
+def _video_object_from_task(task: _MiniMaxTask) -> VideoObject:
+    status: Final = _STATUS_MAP.get(task.status, "queued")
+    usage_dump: Final = task.usage.model_dump(exclude_none=True) if task.usage is not None else None
+    return VideoObject(
+        id=task.id,
+        object="video",
+        status=status,
+        created_at=task.created_at,
+        completed_at=task.updated_at if status == "completed" else None,
+        error=task.error.model_dump(exclude_none=True) if task.error is not None else None,
+        seconds=str(task.duration) if task.duration is not None else None,
+        model=task.model,
+        usage=usage_dump or None,
+    )
+
+
+def _create_cost_usd(model: str, duration: float, resolution: str | None, input_image_count: int) -> float | None:
+    """
+    MiniMax bills input images beyond a per-model free allowance on top of output seconds, and the create
+    call is the only billed one, so the whole charge is reported for the cost calculator to use as is.
+    """
+    try:
+        info: Final = get_model_info(model=model, custom_llm_provider="minimax")
+    except Exception:
+        return None
+    provider_specific: Final = info.get("provider_specific_entry")
+    free_images: Final = (
+        provider_specific.get("minimax_free_input_images") if isinstance(provider_specific, Mapping) else None
+    )
+    image_rate: Final = info.get("input_cost_per_image")
+    if not isinstance(free_images, (int, float)) or not isinstance(image_rate, (int, float)):
+        return None
+    output_cost: Final = video_generation_cost(
+        model=model, duration_seconds=duration, custom_llm_provider="minimax", video_resolution=resolution
+    )
+    return output_cost + max(0, input_image_count - int(free_images)) * image_rate
+
+
+def _video_url_from_task(task: _MiniMaxTask) -> str:
+    if task.content is not None and task.content.url:
+        return task.content.url
+
+    if task.status in ("queued", "running"):
+        raise ValueError(f"Video is still processing (status: {task.status}). Please wait and try again.")
+    if task.error is not None:
+        raise ValueError(f"Video generation failed: {task.error.message or 'unknown error'}")
+    raise ValueError("Video URL not found in task response. The task may not have succeeded yet.")
+
+
+class MinimaxVideoConfig(BaseVideoConfig):
+    def get_supported_openai_params(self, model: str) -> list[str]:  # mutable-ok: BaseVideoConfig contract returns list
+        return [  # mutable-ok: BaseVideoConfig contract returns list
+            "model",
+            "prompt",
+            "input_reference",
+            "seconds",
+            "size",
+            "resolution",
+            "user",
+            "extra_headers",
+            "duration",
+            "ratio",
+            "content",
+            "callback_url",
+            "aigc_watermark",
+            "extra",
+            "parameters",
+        ]
+
+    def map_openai_params(
+        self,
+        video_create_optional_params: VideoCreateOptionalRequestParams,
+        model: str,
+        drop_params: bool,
+    ) -> dict[str, object]:  # mutable-ok: BaseVideoConfig contract
+        mapped_params: Final[dict[str, object]] = {}  # mutable-ok: BaseVideoConfig contract; extra_body merges into it
+        for key, value in video_create_optional_params.items():
+            if value is None or key in _DROP_FROM_CREATE_BODY:
+                continue
+            if key == "seconds":
+                duration = _duration_param(value)
+                if duration is not None:
+                    mapped_params["duration"] = duration
+            elif key == "size":
+                ratio = _ratio_from_size(value) if isinstance(value, str) else None
+                if ratio is not None:
+                    mapped_params.setdefault("ratio", ratio)
+            elif key == "parameters":
+                try:
+                    mapped_params.update(_RESPONSE_ADAPTER.validate_python(value))
+                except ValidationError as e:
+                    raise ValueError("parameters must be an object of MiniMax request fields") from e
+            else:
+                mapped_params[key] = value
+        return mapped_params
+
+    def validate_environment(
+        self,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract; handler expects a mutable headers dict
+        model: str,
+        api_key: str | None = None,
+        litellm_params: GenericLiteLLMParams | None = None,
+    ) -> dict[str, str]:  # mutable-ok: BaseVideoConfig contract
+        resolved_api_key: Final = (
+            api_key
+            or (litellm_params.api_key if litellm_params is not None and litellm_params.api_key else None)
+            or litellm.api_key
+            or get_secret_str("MINIMAX_API_KEY")
+        )
+
+        if resolved_api_key is None:
+            raise ValueError(
+                "MiniMax API key is required. Set MINIMAX_API_KEY environment variable or pass api_key parameter."
+            )
+
+        auth_headers: Final[dict[str, str]] = {  # mutable-ok: httpx request headers are a mutable dict
+            "Authorization": f"Bearer {resolved_api_key}",
+            "Content-Type": "application/json",
+        }
+        headers.update(auth_headers)
+        return headers
+
+    def get_complete_url(
+        self,
+        model: str,
+        api_base: str | None,
+        litellm_params: dict[str, object],  # mutable-ok: BaseVideoConfig contract
+    ) -> str:
+        resolved_api_base: Final = api_base or get_secret_str("MINIMAX_API_BASE") or MINIMAX_VIDEO_DEFAULT_API_BASE
+        return _normalized_api_base(resolved_api_base)
+
+    def transform_video_create_request(
+        self,
+        model: str,
+        prompt: str,
+        api_base: str,
+        video_create_optional_request_params: dict[str, object],  # mutable-ok: BaseVideoConfig contract
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+    ) -> tuple[dict[str, object], RequestFiles, str]:  # mutable-ok: BaseVideoConfig contract
+        content: Final = self._content_param(video_create_optional_request_params, prompt)
+        if any(item.type == "video_url" for item in _content_items(content)):
+            raise UnsupportedParamsError(
+                message=(
+                    "Reference video input is not supported through litellm: MiniMax bills its duration, which is only "
+                    "known after the task is created and billed. Use image or audio references instead."
+                ),
+                model=model,
+                llm_provider="minimax",
+            )
+        request_data: Final[dict[str, object]] = {  # mutable-ok: request body dict, JSON-serialized by the handler
+            "model": model,
+            "content": content,
+        }
+        for key in _CREATE_BODY_KEYS:
+            if video_create_optional_request_params.get(key) is not None:
+                request_data[key] = video_create_optional_request_params[key]
+
+        request_data.setdefault("resolution", MINIMAX_VIDEO_DEFAULT_RESOLUTION)
+        request_data.setdefault("duration", MINIMAX_VIDEO_DEFAULT_DURATION_SECONDS)
+        if "ratio" not in request_data and _is_text_only_content(content):
+            request_data["ratio"] = MINIMAX_TEXT_TO_VIDEO_DEFAULT_RATIO
+
+        return request_data, (), f"{api_base}/v2/video_generation"
+
+    @staticmethod
+    def _content_param(video_create_optional_request_params: Mapping[str, object], prompt: str) -> object:
+        """
+        ``prompt`` is what guardrails scanned, so it is always the one text item MiniMax takes; a caller's
+        ``content`` array only contributes media, never text that would bypass that check.
+        """
+        explicit_content: Final = video_create_optional_request_params.get("content")
+        if explicit_content is not None:
+            try:
+                media: Final = _CALLER_MEDIA_ADAPTER.validate_python(explicit_content)
+            except ValidationError as e:
+                raise UnsupportedParamsError(
+                    message=(
+                        "content must be a list of MiniMax image_url, video_url or audio_url items; pass the text of "
+                        f"the request as prompt. {e.error_count()} invalid item field(s)."
+                    ),
+                    llm_provider="minimax",
+                ) from e
+            return [  # mutable-ok: JSON request-body content
+                {"type": "text", "text": prompt},
+                *(item.model_dump(exclude_none=True) for item in media),
+            ]
+
+        content_items: Final[list[dict[str, object]]] = [  # mutable-ok: JSON request-body content items
+            {"type": "text", "text": prompt}  # mutable-ok: JSON request-body content item
+        ]
+        input_reference: Final = video_create_optional_request_params.get("input_reference")
+        if input_reference is not None:
+            content_items.append(_first_frame_content_item(input_reference))
+        return content_items
+
+    def transform_video_create_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+        custom_llm_provider: str | None = None,
+        request_data: dict[str, object] | None = None,  # mutable-ok: BaseVideoConfig contract
+    ) -> VideoObject:
+        task_id: Final = _parse_task_id_response(raw_response)
+        request_mapping: Final[Mapping[str, object]] = request_data if request_data is not None else _EMPTY_PARAMS
+        duration: Final = request_mapping.get("duration")
+        resolution: Final = request_mapping.get("resolution")
+        input_image_count: Final = sum(
+            1 for item in _content_items(request_mapping.get("content")) if item.type == "image_url"
+        )
+
+        video_obj: Final = VideoObject(
+            id=task_id,
+            object="video",
+            status="queued",
+            model=model,
+            seconds=str(duration) if duration is not None else None,
+        )
+        if custom_llm_provider and video_obj.id:
+            video_obj.id = encode_video_id_with_provider(video_obj.id, custom_llm_provider, model)
+
+        usage: Final[dict[str, object]] = {}  # mutable-ok: VideoObject.usage is a mutable dict field
+        if isinstance(duration, (int, float)):
+            usage["duration_seconds"] = float(duration)
+        if isinstance(resolution, str):
+            usage["video_resolution"] = resolution.strip().lower()
+        if input_image_count:
+            usage["input_image_count"] = input_image_count
+        create_cost: Final = (
+            _create_cost_usd(model, float(duration), resolution.strip().lower(), input_image_count)
+            if isinstance(duration, (int, float)) and isinstance(resolution, str)
+            else None
+        )
+        if create_cost is not None:
+            usage["provider_reported_cost_usd"] = create_cost
+        video_obj.usage = usage
+
+        return video_obj
+
+    def transform_video_status_retrieve_request(
+        self,
+        video_id: str,
+        api_base: str,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+    ) -> tuple[str, dict[str, object]]:  # mutable-ok: BaseVideoConfig contract
+        original_task_id: Final = extract_original_video_id(video_id)
+        encoded_task_id: Final = encode_url_path_segment(original_task_id, field_name="video_id")
+        return f"{api_base}/v2/query/video_generation/{encoded_task_id}", _EMPTY_PARAMS
+
+    def transform_video_status_retrieve_response(
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+        custom_llm_provider: str | None = None,
+        client: "HTTPHandler | None" = None,
+    ) -> VideoObject:
+        task: Final = _parse_task_response(raw_response)
+        video_obj: Final = _video_object_from_task(task)
+        if custom_llm_provider and video_obj.id:
+            video_obj.id = encode_video_id_with_provider(video_obj.id, custom_llm_provider, task.model)
+        return video_obj
+
+    def transform_video_content_request(
+        self,
+        video_id: str,
+        api_base: str,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+        variant: str | None = None,
+    ) -> tuple[str, dict[str, object]]:  # mutable-ok: BaseVideoConfig contract
+        original_task_id: Final = extract_original_video_id(video_id)
+        encoded_task_id: Final = encode_url_path_segment(original_task_id, field_name="video_id")
+        return f"{api_base}/v2/query/video_generation/{encoded_task_id}", _EMPTY_PARAMS
+
+    def transform_video_content_response(
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+    ) -> bytes:
+        task: Final = _parse_task_response(raw_response)
+        video_url: Final = _video_url_from_task(task)
+
+        httpx_client: Final = _get_httpx_client()
+        video_response: Final = httpx_client.get(video_url)  # pyright: ignore[reportUnknownMemberType]  # HTTPHandler.get stub leaves params/headers untyped
+        video_response.raise_for_status()
+
+        return video_response.content
+
+    async def async_transform_video_content_response(
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+    ) -> bytes:
+        task: Final = _parse_task_response(raw_response)
+        video_url: Final = _video_url_from_task(task)
+
+        async_httpx_client: Final = get_async_httpx_client(
+            llm_provider=litellm.LlmProviders.MINIMAX,
+        )
+        video_response: Final = await async_httpx_client.get(video_url)  # pyright: ignore[reportUnknownMemberType]  # HTTPHandler.get stub leaves params/headers untyped
+        video_response.raise_for_status()
+
+        return video_response.content
+
+    def transform_video_remix_request(
+        self,
+        video_id: str,
+        prompt: str,
+        api_base: str,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+        extra_body: dict[str, object] | None = None,  # mutable-ok: BaseVideoConfig contract
+    ) -> tuple[str, dict[str, object]]:  # mutable-ok: BaseVideoConfig contract
+        raise NotImplementedError(
+            "Video remix is not supported by MiniMax. Its regeneration endpoint only upscales a finished 768P "
+            "MiniMax-H3 task to 2K and ignores the prompt; send a new video_generation() request with the edited "
+            "prompt instead."
+        )
+
+    def transform_video_remix_response(
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+        custom_llm_provider: str | None = None,
+    ) -> VideoObject:
+        raise NotImplementedError("Video remix is not supported by MiniMax.")
+
+    def transform_video_list_request(
+        self,
+        api_base: str,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+        after: str | None = None,
+        limit: int | None = None,
+        order: str | None = None,
+        extra_query: dict[str, object] | None = None,  # mutable-ok: BaseVideoConfig contract
+    ) -> tuple[str, dict[str, object]]:  # mutable-ok: BaseVideoConfig contract
+        if after is not None:
+            raise UnsupportedParamsError(
+                message=(
+                    "MiniMax video list does not support cursor pagination via 'after'. "
+                    "Pass extra_query={'page_num': N} to request a later page."
+                ),
+                llm_provider="minimax",
+            )
+        if order is not None and order != "desc":
+            raise UnsupportedParamsError(
+                message="MiniMax video list only returns newest first; order must be 'desc' or omitted.",
+                llm_provider="minimax",
+            )
+        params: Final[dict[str, object]] = {}  # mutable-ok: query params dict consumed by the http handler
+        if limit is not None:
+            params["page_size"] = str(limit)
+        if extra_query:
+            params.update(extra_query)
+        return f"{api_base}/v2/query/video_generation", params
+
+    def transform_video_list_response(  # pyright: ignore[reportIncompatibleMethodOverride]  # base declares dict[str, str] but the payload is a heterogeneous list body
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+        custom_llm_provider: str | None = None,
+    ) -> dict[str, object]:  # mutable-ok: OpenAI list body served as JSON by the proxy
+        list_payload: Final = _LIST_RESPONSE_ADAPTER.validate_python(raw_response.json())
+        total: Final = list_payload.total
+
+        data: Final[list[dict[str, object]]] = []  # mutable-ok: OpenAI list body served as JSON by the proxy
+        for task in list_payload.items or ():
+            video_obj = _video_object_from_task(task)
+            if custom_llm_provider and video_obj.id:
+                video_obj.id = encode_video_id_with_provider(video_obj.id, custom_llm_provider, video_obj.model)
+            data.append(video_obj.model_dump())
+
+        list_response: Final[dict[str, object]] = {  # mutable-ok: OpenAI list body served as JSON by the proxy
+            "object": "list",
+            "data": data,
+            "total": total if isinstance(total, int) and not isinstance(total, bool) else len(data),
+        }
+        if data:
+            list_response["first_id"] = data[0]["id"]
+            list_response["last_id"] = data[-1]["id"]
+        return list_response
+
+    def transform_video_delete_request(
+        self,
+        video_id: str,
+        api_base: str,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict[str, str],  # mutable-ok: BaseVideoConfig contract
+    ) -> tuple[str, dict[str, object]]:  # mutable-ok: BaseVideoConfig contract
+        original_task_id: Final = extract_original_video_id(video_id)
+        encoded_task_id: Final = encode_url_path_segment(original_task_id, field_name="video_id")
+        return f"{api_base}/v2/video_generation/{encoded_task_id}", _EMPTY_PARAMS
+
+    def transform_video_delete_response(
+        self,
+        raw_response: httpx.Response,
+        logging_obj: "Logging",
+    ) -> VideoObject:
+        task_id, status = _parse_delete_response(raw_response)
+        return VideoObject(
+            id=task_id,
+            object="video",
+            status=status,
+        )
+
+    def get_error_class(
+        self,
+        error_message: str,
+        status_code: int,
+        headers: dict[str, str] | httpx.Headers,  # mutable-ok: BaseVideoConfig contract
+    ) -> BaseLLMException:
+        return MinimaxVideoError(
+            status_code=status_code,
+            message=error_message,
+            headers=headers,
+        )

litellm/model_prices_and_context_window_backup.json

@@ -37986,6 +37986,60 @@
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000
     },
+    "minimax/MiniMax-H3": {
+        "litellm_provider": "minimax",
+        "mode": "video_generation",
+        "source": "https://platform.minimax.io/docs/guides/pricing-paygo",
+        "output_cost_per_second": 0.08,
+        "output_cost_per_second_768p": 0.08,
+        "output_cost_per_second_2k": 0.13,
+        "input_cost_per_image": 0.04,
+        "provider_specific_entry": {
+            "minimax_free_input_images": 5
+        },
+        "supported_modalities": [
+            "text",
+            "image",
+            "video",
+            "audio"
+        ],
+        "supported_output_modalities": [
+            "video"
+        ],
+        "supported_endpoints": [
+            "/v1/videos"
+        ],
+        "metadata": {
+            "comment": "V2 async task API. Pay-as-you-go list price $0.08/s at 768P and $0.13/s at 2K, plus $0.04 per input image beyond the first 5. Audio input is free. Reference video input is rejected, since MiniMax bills its duration only after the create call."
+        }
+    },
+    "minimax/MiniMax-H3-Max": {
+        "litellm_provider": "minimax",
+        "mode": "video_generation",
+        "source": "https://platform.minimax.io/docs/guides/pricing-paygo",
+        "output_cost_per_second": 0.08,
+        "output_cost_per_second_480p": 0.05,
+        "output_cost_per_second_768p": 0.08,
+        "input_cost_per_image": 0.074,
+        "provider_specific_entry": {
+            "minimax_free_input_images": 2
+        },
+        "supported_modalities": [
+            "text",
+            "image",
+            "video",
+            "audio"
+        ],
+        "supported_output_modalities": [
+            "video"
+        ],
+        "supported_endpoints": [
+            "/v1/videos"
+        ],
+        "metadata": {
+            "comment": "V2 async task API, fast tier. Pay-as-you-go list price $0.05/s at 480P and $0.08/s at 768P; no 2K. Plus $0.074 per input image beyond the first 2. Audio input is free. Reference video input is rejected, since MiniMax bills its duration only after the create call."
+        }
+    },
     "mistral.devstral-2-123b": {
         "input_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_converse",

litellm/utils.py

@@ -9638,6 +9638,10 @@ class ProviderConfigManager:
             from litellm.llms.hosted_vllm.videos import get_hosted_vllm_video_config
 
             return get_hosted_vllm_video_config(model)
+        elif LlmProviders.MINIMAX == provider:
+            from litellm.llms.minimax.videos.transformation import MinimaxVideoConfig
+
+            return MinimaxVideoConfig()
         elif LlmProviders.EDENAI == provider:
             return litellm.EdenAIVideoConfig()
         return None

model_prices_and_context_window.json

@@ -37986,6 +37986,60 @@
         "max_input_tokens": 1000000,
         "max_output_tokens": 128000
     },
+    "minimax/MiniMax-H3": {
+        "litellm_provider": "minimax",
+        "mode": "video_generation",
+        "source": "https://platform.minimax.io/docs/guides/pricing-paygo",
+        "output_cost_per_second": 0.08,
+        "output_cost_per_second_768p": 0.08,
+        "output_cost_per_second_2k": 0.13,
+        "input_cost_per_image": 0.04,
+        "provider_specific_entry": {
+            "minimax_free_input_images": 5
+        },
+        "supported_modalities": [
+            "text",
+            "image",
+            "video",
+            "audio"
+        ],
+        "supported_output_modalities": [
+            "video"
+        ],
+        "supported_endpoints": [
+            "/v1/videos"
+        ],
+        "metadata": {
+            "comment": "V2 async task API. Pay-as-you-go list price $0.08/s at 768P and $0.13/s at 2K, plus $0.04 per input image beyond the first 5. Audio input is free. Reference video input is rejected, since MiniMax bills its duration only after the create call."
+        }
+    },
+    "minimax/MiniMax-H3-Max": {
+        "litellm_provider": "minimax",
+        "mode": "video_generation",
+        "source": "https://platform.minimax.io/docs/guides/pricing-paygo",
+        "output_cost_per_second": 0.08,
+        "output_cost_per_second_480p": 0.05,
+        "output_cost_per_second_768p": 0.08,
+        "input_cost_per_image": 0.074,
+        "provider_specific_entry": {
+            "minimax_free_input_images": 2
+        },
+        "supported_modalities": [
+            "text",
+            "image",
+            "video",
+            "audio"
+        ],
+        "supported_output_modalities": [
+            "video"
+        ],
+        "supported_endpoints": [
+            "/v1/videos"
+        ],
+        "metadata": {
+            "comment": "V2 async task API, fast tier. Pay-as-you-go list price $0.05/s at 480P and $0.08/s at 768P; no 2K. Plus $0.074 per input image beyond the first 2. Audio input is free. Reference video input is rejected, since MiniMax bills its duration only after the create call."
+        }
+    },
     "mistral.devstral-2-123b": {
         "input_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_converse",

tests/unit/llms/minimax/videos/test_minimax_video_transformation.py

@@ -0,0 +1,697 @@
+"""
+Tests for MiniMax (Hailuo-03) video generation transformation.
+"""
+
+import base64
+import io
+import json
+from typing import Final
+from unittest.mock import Mock
+
+import httpx
+import pytest
+
+from litellm.exceptions import UnsupportedParamsError
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler
+from litellm.llms.minimax.videos.transformation import (
+    _MiniMaxTask,
+    _TaskContent,
+    _TaskError,
+    _video_url_from_task,
+    MinimaxVideoConfig,
+)
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.videos.utils import (
+    decode_video_id_with_provider,
+    encode_video_id_with_provider,
+)
+from litellm.videos.main import avideo_generation
+
+PNG_BYTES = base64.b64decode(
+    "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8BQDwAEhQGAhKmMIQAAAABJRU5ErkJggg=="
+)
+
+API_BASE = "https://api.minimax.io"
+
+
+def _mock_response(payload: dict) -> Mock:
+    mock_response = Mock(spec=httpx.Response)
+    mock_response.json.return_value = payload
+    return mock_response
+
+
+def _query_response(task: dict) -> Mock:
+    return _mock_response({"task": task})
+
+
+class TestMinimaxVideoCreateRequest:
+    def test_text_to_video_defaults(self):
+        """A prompt-only request must build the content array and apply
+        MiniMax's required resolution/duration/ratio when the caller omits them."""
+        data, files, url = MinimaxVideoConfig().transform_video_create_request(
+            model="MiniMax-H3",
+            prompt="A cinematic shot of a lighthouse at dusk",
+            api_base=API_BASE,
+            video_create_optional_request_params={},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert url == f"{API_BASE}/v2/video_generation"
+        assert files == ()
+        assert data["model"] == "MiniMax-H3"
+        assert data["content"] == [{"type": "text", "text": "A cinematic shot of a lighthouse at dusk"}]
+        assert data["resolution"] == "768P"
+        assert data["duration"] == 5
+        assert data["ratio"] == "16:9"
+
+    def test_explicit_params_beat_defaults(self):
+        data, _, _ = MinimaxVideoConfig().transform_video_create_request(
+            model="MiniMax-H3-Max",
+            prompt="prompt",
+            api_base=API_BASE,
+            video_create_optional_request_params={"resolution": "480P", "duration": 9, "ratio": "9:16"},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert data["model"] == "MiniMax-H3-Max"
+        assert data["resolution"] == "480P"
+        assert data["duration"] == 9
+        assert data["ratio"] == "9:16"
+
+    def test_map_openai_params_converts_seconds_and_size(self):
+        """OpenAI ``seconds``/``size`` must become MiniMax ``duration``/``ratio``
+        (1280x720 reduces to 16:9), not be forwarded verbatim."""
+        mapped = MinimaxVideoConfig().map_openai_params(
+            video_create_optional_params={"seconds": "5", "size": "1280x720", "resolution": "2K"},
+            model="MiniMax-H3",
+            drop_params=False,
+        )
+
+        assert mapped["duration"] == 5
+        assert mapped["ratio"] == "16:9"
+        assert mapped["resolution"] == "2K"
+        assert "seconds" not in mapped
+        assert "size" not in mapped
+
+    def test_map_openai_params_drops_fields_minimax_rejects(self):
+        mapped = MinimaxVideoConfig().map_openai_params(
+            video_create_optional_params={"user": "u1", "characters": [{"id": "c"}], "prompt": "p"},
+            model="MiniMax-H3",
+            drop_params=False,
+        )
+
+        assert mapped == {}
+
+    def test_map_openai_params_explicit_ratio_wins_over_size(self):
+        mapped = MinimaxVideoConfig().map_openai_params(
+            video_create_optional_params={"size": "1280x720", "ratio": "4:3"},
+            model="MiniMax-H3",
+            drop_params=False,
+        )
+
+        assert mapped["ratio"] == "4:3"
+
+    def test_map_openai_params_merges_parameters_block(self):
+        mapped = MinimaxVideoConfig().map_openai_params(
+            video_create_optional_params={"parameters": {"callback_url": "https://cb.example/hook", "ratio": "1:1"}},
+            model="MiniMax-H3",
+            drop_params=False,
+        )
+
+        assert mapped == {"callback_url": "https://cb.example/hook", "ratio": "1:1"}
+
+    def test_image_reference_file_becomes_first_frame_data_uri(self):
+        """A file input_reference must arrive as a first_frame content item
+        carrying a base64 data URI, and text-only ratio defaults must not apply."""
+        data, _, _ = MinimaxVideoConfig().transform_video_create_request(
+            model="MiniMax-H3",
+            prompt="Pull focus to the people in the background",
+            api_base=API_BASE,
+            video_create_optional_request_params={"input_reference": io.BytesIO(PNG_BYTES)},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        image_item = data["content"][1]
+        assert image_item["type"] == "image_url"
+        assert image_item["role"] == "first_frame"
+        assert image_item["image_url"]["url"].startswith("data:image/png;base64,")
+        encoded = image_item["image_url"]["url"].split(",", 1)[1]
+        assert base64.b64decode(encoded) == PNG_BYTES
+        assert "ratio" not in data
+
+    def test_image_reference_url_passthrough(self):
+        data, _, _ = MinimaxVideoConfig().transform_video_create_request(
+            model="MiniMax-H3",
+            prompt="Add more steam to the ramen bowl",
+            api_base=API_BASE,
+            video_create_optional_request_params={"input_reference": "https://cdn.example.com/frame.png"},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert data["content"][1] == {
+            "type": "image_url",
+            "image_url": {"url": "https://cdn.example.com/frame.png"},
+            "role": "first_frame",
+        }
+
+    def test_explicit_media_content_follows_the_prompt(self):
+        """Multimodal-reference (r2va) callers supply the media items; they pass
+        through after the prompt and suppress the text-only ratio default."""
+        media = [
+            {"type": "image_url", "image_url": {"url": "https://cdn.example.com/ref.png"}, "role": "reference_image"},
+            {"type": "audio_url", "audio_url": {"url": "https://cdn.example.com/ref.mp3"}, "role": "reference_audio"},
+        ]
+        data, _, _ = MinimaxVideoConfig().transform_video_create_request(
+            model="MiniMax-H3",
+            prompt="Character speaking",
+            api_base=API_BASE,
+            video_create_optional_request_params={"content": media},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert data["content"] == [{"type": "text", "text": "Character speaking"}, *media]
+        assert "ratio" not in data
+
+    @pytest.mark.parametrize(
+        "content",
+        [
+            [{"type": "text", "text": "unscanned text"}, {"type": "image_url"}],
+            [{"type": "image_url", "image_url": {"url": "https://x/a.png"}, "text": "unscanned text"}],
+            [{"type": "image_url", "image_url": {"url": "https://x/a.png", "text": "unscanned text"}}],
+            [{"type": "text", "text": "unscanned text"}, "not an item"],
+            "unscanned text",
+        ],
+    )
+    def test_malformed_content_cannot_smuggle_unscanned_text(self, content):
+        """A text item hidden behind a malformed sibling, or text on a media
+        item, must be rejected rather than let through by a lenient parse."""
+        with pytest.raises(UnsupportedParamsError) as raised:
+            MinimaxVideoConfig().transform_video_create_request(
+                model="MiniMax-H3",
+                prompt="a calm lake",
+                api_base=API_BASE,
+                video_create_optional_request_params={"content": content},
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+            )
+
+        assert raised.value.status_code == 400
+
+    def test_text_inside_content_is_rejected_so_guardrails_cannot_be_bypassed(self):
+        """Guardrails scan prompt; a text item smuggled into content would reach
+        MiniMax unscanned while a harmless prompt passed the check."""
+        with pytest.raises(UnsupportedParamsError, match="as prompt") as raised:
+            MinimaxVideoConfig().transform_video_create_request(
+                model="MiniMax-H3",
+                prompt="a calm lake",
+                api_base=API_BASE,
+                video_create_optional_request_params={"content": [{"type": "text", "text": "unscanned text"}]},
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+            )
+
+        assert raised.value.status_code == 400
+
+    @pytest.mark.parametrize(
+        "configured_api_base",
+        (
+            "https://api.minimax.cn/v1/",
+            "https://api.minimax.cn/v1",
+            "https://api.minimax.cn/anthropic",
+            "https://api.minimax.cn/anthropic/",
+            "https://api.minimax.cn",
+            "https://api.minimax.cn/",
+            "https://api.minimax.cn/v2",
+        ),
+    )
+    def test_any_published_surface_base_reaches_video(self, configured_api_base):
+        """A MiniMax key works across that host's API surfaces, so an existing
+        chat credential must reach video whichever base it was configured with:
+        MiniMax publishes .../v1 (OpenAI-compatible) and .../anthropic
+        (Anthropic Messages) alongside the /v2 video API, and users also
+        configure the bare host."""
+        config = MinimaxVideoConfig()
+        api_base = config.get_complete_url(model="MiniMax-H3", api_base=configured_api_base, litellm_params={})
+
+        _, _, url = config.transform_video_create_request(
+            model="MiniMax-H3",
+            prompt="p",
+            api_base=api_base,
+            video_create_optional_request_params={},
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert url == "https://api.minimax.cn/v2/video_generation"
+
+    @pytest.mark.parametrize(
+        ("configured_api_base", "expected"),
+        (
+            ("https://anthropic.example.com/v1", "https://anthropic.example.com"),
+            ("https://api.minimax.cn/v1/proxy", "https://api.minimax.cn/v1/proxy"),
+            ("https://gateway.internal/anthropic/shim", "https://gateway.internal/anthropic/shim"),
+        ),
+    )
+    def test_surface_suffix_is_only_stripped_from_the_end(self, configured_api_base, expected):
+        """Only a trailing surface segment marks the protocol. One appearing
+        anywhere else is part of the address: cutting it out of the middle sends
+        the request to a different path than the operator configured."""
+        config = MinimaxVideoConfig()
+
+        assert config.get_complete_url(model="MiniMax-H3", api_base=configured_api_base, litellm_params={}) == expected
+
+    def test_get_complete_url_defaults_to_international_host(self):
+        assert MinimaxVideoConfig().get_complete_url(model="MiniMax-H3", api_base=None, litellm_params={}) == (
+            "https://api.minimax.io"
+        )
+
+
+class TestMinimaxVideoCreateResponse:
+    def test_task_id_is_encoded_with_provider_and_model(self):
+        """The create response only carries task_id; litellm must wrap it so
+        later status/content/remix calls can route back to minimax."""
+        video_obj = MinimaxVideoConfig().transform_video_create_response(
+            model="MiniMax-H3",
+            raw_response=_mock_response({"task_id": "424010985738629"}),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+            request_data={"model": "MiniMax-H3", "content": [], "resolution": "2K", "duration": 5, "ratio": "16:9"},
+        )
+
+        assert video_obj.status == "queued"
+        assert video_obj.model == "MiniMax-H3"
+        assert video_obj.seconds == "5"
+        decoded = decode_video_id_with_provider(video_obj.id)
+        assert decoded["custom_llm_provider"] == "minimax"
+        assert decoded["model_id"] == "MiniMax-H3"
+        assert decoded["video_id"] == "424010985738629"
+
+    def test_usage_carries_cost_inputs(self):
+        video_obj = MinimaxVideoConfig().transform_video_create_response(
+            model="MiniMax-H3",
+            raw_response=_mock_response({"task_id": "t1"}),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+            request_data={"resolution": "768P", "duration": 4},
+        )
+
+        assert video_obj.usage["duration_seconds"] == 4.0
+        assert video_obj.usage["video_resolution"] == "768p"
+        assert "input_image_count" not in video_obj.usage
+
+
+class TestMinimaxVideoStatus:
+    def test_succeeded_task_mapping(self):
+        video_obj = MinimaxVideoConfig().transform_video_status_retrieve_response(
+            raw_response=_query_response(
+                {
+                    "id": "424010985738629",
+                    "model": "MiniMax-H3",
+                    "status": "succeeded",
+                    "created_at": 1785125529,
+                    "updated_at": 1785125946,
+                    "content": {"url": "https://cdn.example.com/output.mp4"},
+                    "resolution": "2K",
+                    "duration": 5,
+                    "usage": {"total_seconds": 5, "input_seconds": 0, "output_seconds": 5, "input_image_count": 1},
+                    "ratio": "16:9",
+                    "task_type": "generation",
+                    "modality": "video",
+                }
+            ),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+        )
+
+        assert video_obj.status == "completed"
+        assert video_obj.created_at == 1785125529
+        assert video_obj.completed_at == 1785125946
+        assert video_obj.seconds == "5"
+        assert video_obj.model == "MiniMax-H3"
+        assert video_obj.usage["output_seconds"] == 5
+        decoded = decode_video_id_with_provider(video_obj.id)
+        assert decoded["custom_llm_provider"] == "minimax"
+        assert decoded["model_id"] == "MiniMax-H3"
+
+    def test_running_task_maps_to_in_progress_without_completion(self):
+        video_obj = MinimaxVideoConfig().transform_video_status_retrieve_response(
+            raw_response=_query_response({"id": "t1", "model": "MiniMax-H3", "status": "running", "created_at": 1}),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+        )
+
+        assert video_obj.status == "in_progress"
+        assert video_obj.completed_at is None
+        assert video_obj.usage is None
+
+    def test_failed_task_maps_error(self):
+        video_obj = MinimaxVideoConfig().transform_video_status_retrieve_response(
+            raw_response=_query_response(
+                {
+                    "id": "t1",
+                    "status": "failed",
+                    "error": {"code": "1026", "message": "video description contains sensitive content"},
+                    "created_at": 1,
+                }
+            ),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+        )
+
+        assert video_obj.status == "failed"
+        assert video_obj.error == {"code": "1026", "message": "video description contains sensitive content"}
+
+    def test_request_decodes_task_id_from_wrapped_video_id(self):
+        encoded_video_id = encode_video_id_with_provider("424010985738629", "minimax", "MiniMax-H3")
+        url, data = MinimaxVideoConfig().transform_video_status_retrieve_request(
+            video_id=encoded_video_id,
+            api_base=API_BASE,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert url == f"{API_BASE}/v2/query/video_generation/424010985738629"
+        assert data == {}
+
+    def test_content_request_hits_query_endpoint(self):
+        encoded_video_id = encode_video_id_with_provider("424010985738629", "minimax", "MiniMax-H3")
+        url, data = MinimaxVideoConfig().transform_video_content_request(
+            video_id=encoded_video_id,
+            api_base=API_BASE,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert url == f"{API_BASE}/v2/query/video_generation/424010985738629"
+
+    def test_video_url_from_task_pending_and_failed_raise(self):
+        with pytest.raises(ValueError, match="still processing"):
+            _video_url_from_task(_MiniMaxTask(status="running"))
+        with pytest.raises(ValueError, match="sensitive content"):
+            _video_url_from_task(_MiniMaxTask(status="failed", error=_TaskError(message="sensitive content")))
+
+
+class TestMinimaxVideoList:
+    def test_request_maps_limit_and_extra_query(self):
+        url, params = MinimaxVideoConfig().transform_video_list_request(
+            api_base=API_BASE,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+            limit=4,
+            extra_query={"filter.status": "succeeded", "page_num": 2},
+        )
+
+        assert url == f"{API_BASE}/v2/query/video_generation"
+        assert params == {"page_size": "4", "filter.status": "succeeded", "page_num": 2}
+
+    def test_after_cursor_is_rejected_instead_of_repeating_the_first_page(self):
+        with pytest.raises(UnsupportedParamsError, match="page_num") as raised:
+            MinimaxVideoConfig().transform_video_list_request(
+                api_base=API_BASE,
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+                after="video_abc",
+            )
+
+        assert raised.value.status_code == 400
+
+    def test_ascending_order_is_rejected(self):
+        with pytest.raises(UnsupportedParamsError, match="newest first") as raised:
+            MinimaxVideoConfig().transform_video_list_request(
+                api_base=API_BASE,
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+                order="asc",
+            )
+
+        assert raised.value.status_code == 400
+
+    def test_descending_order_is_what_minimax_already_returns(self):
+        _, params = MinimaxVideoConfig().transform_video_list_request(
+            api_base=API_BASE,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+            order="desc",
+        )
+
+        assert params == {}
+
+    def test_response_adopts_openai_list_shape_with_encoded_ids(self):
+        response = MinimaxVideoConfig().transform_video_list_response(
+            raw_response=_mock_response(
+                {
+                    "items": [
+                        {"id": "424635601932571", "model": "MiniMax-H3", "status": "succeeded", "duration": 5},
+                        {"id": "424635601932588", "model": "MiniMax-H3", "status": "running"},
+                    ],
+                    "total": 476,
+                }
+            ),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+        )
+
+        assert response["object"] == "list"
+        assert response["total"] == 476
+        assert [item["status"] for item in response["data"]] == ["completed", "in_progress"]
+        first_decoded = decode_video_id_with_provider(response["first_id"])
+        last_decoded = decode_video_id_with_provider(response["last_id"])
+        assert first_decoded["video_id"] == "424635601932571"
+        assert last_decoded["video_id"] == "424635601932588"
+        assert first_decoded["custom_llm_provider"] == "minimax"
+
+
+class TestMinimaxVideoRemix:
+    def test_remix_is_rejected_instead_of_silently_dropping_the_prompt(self):
+        """MiniMax regeneration only upscales to 2K and ignores any prompt, so
+        mapping remix onto it would return a video that ignores the edit."""
+        encoded_video_id = encode_video_id_with_provider("424010985738629", "minimax", "MiniMax-H3")
+
+        with pytest.raises(NotImplementedError, match="remix is not supported by MiniMax"):
+            MinimaxVideoConfig().transform_video_remix_request(
+                video_id=encoded_video_id,
+                prompt="a different ending",
+                api_base=API_BASE,
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+            )
+
+
+class TestMinimaxVideoDelete:
+    def test_delete_request_and_cancelled_response(self):
+        encoded_video_id = encode_video_id_with_provider("424010985738629", "minimax", "MiniMax-H3")
+        url, data = MinimaxVideoConfig().transform_video_delete_request(
+            video_id=encoded_video_id,
+            api_base=API_BASE,
+            litellm_params=GenericLiteLLMParams(),
+            headers={},
+        )
+
+        assert url == f"{API_BASE}/v2/video_generation/424010985738629"
+        assert data == {}
+
+        video_obj = MinimaxVideoConfig().transform_video_delete_response(
+            raw_response=_mock_response({"task_id": "424010985738629", "action": "cancelled", "status": "cancelled"}),
+            logging_obj=None,
+        )
+        assert video_obj.status == "cancelled"
+        assert video_obj.id == "424010985738629"
+
+
+class TestMinimaxVideoEnvironment:
+    def test_explicit_api_key_wins_over_litellm_params(self):
+        headers = MinimaxVideoConfig().validate_environment(
+            headers={},
+            model="MiniMax-H3",
+            api_key="explicit-key",
+            litellm_params=GenericLiteLLMParams(api_key="deployment-key"),
+        )
+
+        assert headers["Authorization"] == "Bearer explicit-key"
+        assert headers["Content-Type"] == "application/json"
+
+    def test_litellm_params_key_used_when_no_explicit_key(self):
+        headers = MinimaxVideoConfig().validate_environment(
+            headers={},
+            model="MiniMax-H3",
+            litellm_params=GenericLiteLLMParams(api_key="deployment-key"),
+        )
+
+        assert headers["Authorization"] == "Bearer deployment-key"
+
+    def test_missing_api_key_raises(self, monkeypatch):
+        monkeypatch.delenv("MINIMAX_API_KEY", raising=False)
+        monkeypatch.setattr("litellm.api_key", None)
+
+        with pytest.raises(ValueError, match="MINIMAX_API_KEY"):
+            MinimaxVideoConfig().validate_environment(
+                headers={},
+                model="MiniMax-H3",
+                litellm_params=GenericLiteLLMParams(),
+            )
+
+    def test_env_var_api_key_used(self, monkeypatch):
+        monkeypatch.setenv("MINIMAX_API_KEY", "env-key")
+        monkeypatch.setattr("litellm.api_key", None)
+
+        headers = MinimaxVideoConfig().validate_environment(
+            headers={},
+            model="MiniMax-H3",
+            litellm_params=GenericLiteLLMParams(),
+        )
+
+        assert headers["Authorization"] == "Bearer env-key"
+
+
+class TestMinimaxVideoEndToEndRequest:
+    """
+    Drive the real avideo_generation() entrypoint rather than the transform.
+
+    map_openai_params runs first and only its output reaches
+    transform_video_create_request, so a param the mapper drops never makes
+    it into the body even though the transform alone handles it.
+    """
+
+    @staticmethod
+    async def _wire_body(**kwargs) -> dict:
+        sent: Final[list[httpx.Request]] = []
+
+        def respond(request: httpx.Request) -> httpx.Response:
+            sent.append(request)
+            return httpx.Response(200, json={"task_id": "t1"})
+
+        async with httpx.AsyncClient(transport=httpx.MockTransport(respond)) as http_client:
+            handler: Final = AsyncHTTPHandler()
+            await handler.close()
+            handler.client = http_client
+            await avideo_generation(api_key="sk-test", api_base=API_BASE, client=handler, **kwargs)
+
+        (request,) = sent
+        return json.loads(request.content)
+
+    @pytest.mark.asyncio
+    async def test_input_reference_survives_param_mapping_into_the_body(self):
+        """Regression: map_openai_params dropped input_reference, so an
+        image-to-video call silently degraded to text-to-video."""
+        body = await self._wire_body(
+            model="minimax/MiniMax-H3",
+            prompt="make it move",
+            input_reference="https://cdn.example/first.png",
+        )
+
+        assert body["content"] == [
+            {"type": "text", "text": "make it move"},
+            {"type": "image_url", "image_url": {"url": "https://cdn.example/first.png"}, "role": "first_frame"},
+        ]
+        assert "input_reference" not in body
+        assert "ratio" not in body
+
+    @pytest.mark.asyncio
+    async def test_file_input_reference_reaches_the_body_as_a_data_uri(self):
+        body = await self._wire_body(
+            model="minimax/MiniMax-H3",
+            prompt="make it move",
+            input_reference=io.BytesIO(PNG_BYTES),
+        )
+
+        image_item = body["content"][1]
+        assert image_item["role"] == "first_frame"
+        assert image_item["image_url"]["url"] == f"data:image/png;base64,{base64.b64encode(PNG_BYTES).decode()}"
+
+
+@pytest.mark.usefixtures("local_model_cost_map")
+class TestMinimaxVideoPricing:
+    @pytest.mark.parametrize(
+        "model,resolutions",
+        [("MiniMax-H3", ("768p", "2k")), ("MiniMax-H3-Max", ("480p", "768p"))],
+    )
+    def test_every_supported_tier_bills_its_own_rate(self, model, resolutions):
+        """A tier with no rate of its own falls back to the base rate, so a 2K
+        video would silently bill at the 768P price."""
+        from litellm import get_model_info
+        from litellm.llms.openai.cost_calculation import video_generation_cost
+
+        info = get_model_info(model=model, custom_llm_provider="minimax")
+
+        for resolution in resolutions:
+            tier_rate = info[f"output_cost_per_second_{resolution}"]
+            assert tier_rate > 0
+            cost = video_generation_cost(
+                model=model, duration_seconds=5.0, custom_llm_provider="minimax", video_resolution=resolution
+            )
+            assert cost == pytest.approx(tier_rate * 5.0)
+
+    def test_higher_resolution_never_bills_less(self):
+        from litellm import get_model_info
+
+        h3 = get_model_info(model="MiniMax-H3", custom_llm_provider="minimax")
+        h3_max = get_model_info(model="MiniMax-H3-Max", custom_llm_provider="minimax")
+
+        assert h3["output_cost_per_second_2k"] > h3["output_cost_per_second_768p"]
+        assert h3_max["output_cost_per_second_768p"] > h3_max["output_cost_per_second_480p"]
+
+
+@pytest.mark.usefixtures("local_model_cost_map")
+class TestMinimaxVideoInputBilling:
+    @staticmethod
+    def _create_cost(model: str, image_count: int) -> float:
+        import litellm
+
+        content = [{"type": "text", "text": "p"}] + [
+            {"type": "image_url", "image_url": {"url": f"https://x/{i}.png"}, "role": "reference_image"}
+            for i in range(image_count)
+        ]
+        video_obj = MinimaxVideoConfig().transform_video_create_response(
+            model=model,
+            raw_response=_mock_response({"task_id": "t1"}),
+            logging_obj=None,
+            custom_llm_provider="minimax",
+            request_data={"model": model, "content": content, "duration": 5, "resolution": "768P"},
+        )
+        return litellm.completion_cost(
+            completion_response=video_obj,
+            model=f"minimax/{model}",
+            call_type="create_video",
+            custom_llm_provider="minimax",
+        )
+
+    @pytest.mark.parametrize("model", ["MiniMax-H3", "MiniMax-H3-Max"])
+    def test_images_beyond_the_free_allowance_are_billed_per_image(self, model):
+        """MiniMax charges for input images past a per-model free allowance;
+        billing only output seconds under-recorded those requests."""
+        from litellm import get_model_info
+
+        info = get_model_info(model=model, custom_llm_provider="minimax")
+        free_images = info["provider_specific_entry"]["minimax_free_input_images"]
+        image_rate = info["input_cost_per_image"]
+        output_only = self._create_cost(model, image_count=0)
+
+        assert self._create_cost(model, image_count=free_images) == pytest.approx(output_only)
+        assert self._create_cost(model, image_count=free_images + 3) == pytest.approx(output_only + 3 * image_rate)
+        assert output_only == pytest.approx(info["output_cost_per_second_768p"] * 5)
+
+    @pytest.mark.parametrize(
+        "content",
+        [
+            [{"type": "video_url", "video_url": {"url": "https://x/ref.mp4"}, "role": "reference_video"}],
+        ],
+    )
+    def test_reference_video_is_rejected_because_its_length_cannot_be_billed(self, content):
+        """MiniMax bills reference-video seconds, which are only reported after
+        the create call that litellm bills."""
+        with pytest.raises(UnsupportedParamsError, match="Reference video") as raised:
+            MinimaxVideoConfig().transform_video_create_request(
+                model="MiniMax-H3",
+                prompt="p",
+                api_base=API_BASE,
+                video_create_optional_request_params={"content": content},
+                litellm_params=GenericLiteLLMParams(),
+                headers={},
+            )
+
+        assert raised.value.status_code == 400