> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.twelvelabs.io/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.twelvelabs.io/_mcp/server. # Create async embeddings > Create embeddings asynchronously for audio, video, images, and documents. The `EmbedClient.V2Client.TasksClient` class provides methods to create embeddings asynchronously for audio, video, images, and documents. Creating embeddings asynchronously requires three steps: 1. Create a task using the `create` method. The platform returns a task ID. 2. Poll for the status of the task using the `retrieve` method. Wait until the status is `ready`. 3. Retrieve the embeddings from the response when the status is `ready` using the `retrieve` method. # Methods ## List embedding tasks **Description**: This method returns a list of the async embedding tasks in your account. The platform returns your async embedding tasks sorted by creation date, with the newest at the top of the list. > **Notes** > > * Embeddings are stored for seven days. > * When you invoke this method without specifying the `started_at` and `ended_at` parameters, the platform returns all the async embedding tasks created within the last seven days. **Function signature and example**: **`Function signature`** ```python Function signature def list( self, *, started_at: typing.Optional[str] = None, ended_at: typing.Optional[str] = None, status: typing.Optional[str] = None, page: typing.Optional[int] = None, page_limit: typing.Optional[int] = None, request_options: typing.Optional[RequestOptions] = None, ) -> SyncPager[MediaEmbeddingTask] ``` **`List embedding tasks`** ```python List embedding tasks from twelvelabs import TwelveLabs response = client.embed.v_2.tasks.list( page=1, page_limit=10, ) print("Embedding tasks:") for task in response: print(f" Task ID: {task.id}") print(f" Model: {task.model_name}") print(f" Status: {task.status}") print(f" Created: {task.created_at}") ``` ### Parameters | Name | Type | Required | Description | | ----------------- | ---------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------- | | `started_at` | `str` | No | Retrieve the embedding tasks that were created after the specified date and time, expressed in the RFC 3339 format ("YYYY-MM-DDTHH:mm:ssZ"). | | `ended_at` | `str` | No | Retrieve the embedding tasks that were created before the specified date and time, expressed in the RFC 3339 format ("YYYY-MM-DDTHH:mm:ssZ"). | | `status` | `str` | No | Filter the embedding tasks by their current status. Values: `processing`, `ready`, or `failed`. | | `page` | `int` | No | A number that identifies the page to retrieve. Default: `1`. | | `page_limit` | `int` | No | The number of items to return on each page. Default: `10`. Max: `50`. | | `request_options` | `RequestOptions` | No | Request-specific configuration. | ### Return value Returns a `SyncPager[MediaEmbeddingTask]` object that allows you to iterate through the paginated task results. The `SyncPager[T]` class contains the following properties and methods: | Name | Type | Description | | -------------- | ------------------------------------------------ | ---------------------------------------------------------------------- | | `items` | `Optional[List[T]]` | A list containing the current page of items. Can be `None`. | | `has_next` | `bool` | Indicates whether there is a next page to load. | | `get_next` | `Optional[Callable[[], Optional[SyncPager[T]]]]` | A callable function that retrieves the next page. Can be `None`. | | `response` | `Optional[BaseHttpResponse]` | The HTTP response object. Can be `None`. | | `next_page()` | `Optional[SyncPager[T]]` | Calls `get_next()` if available and returns the next page object. | | `__iter__()` | `Iterator[T]` | Allows iteration through all items across all pages using `for` loops. | | `iter_pages()` | `Iterator[SyncPager[T]]` | Allows iteration through page objects themselves. | The `MediaEmbeddingTask` class contains the following properties: | Name | Type | Description | | -------------------- | ----------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | `Optional[str]` | The unique identifier of the embedding task. | | `model_name` | `Optional[str]` | The name of the video understanding model the platform used to create the embedding. | | `status` | `Optional[str]` | A string indicating the status of the embedding task. It can take one of the following values: `processing`, `ready` or `failed`. | | `created_at` | `Optional[datetime]` | The date and time when the task was created. | | `updated_at` | `Optional[datetime]` | The date and time when the task was last updated. | | `video_embedding` | `Optional[MediaEmbeddingTaskVideoEmbedding]` | An object containing the metadata associated with the embedding. See [VideoEmbeddingMetadata](#videoembeddingmetadata) for details. | | `audio_embedding` | `Optional[MediaEmbeddingTaskAudioEmbedding]` | An object containing the metadata associated with the embedding. See [AudioEmbeddingMetadata](#audioembeddingmetadata) for details. | | `document_embedding` | `Optional[MediaEmbeddingTaskDocumentEmbedding]` | An object containing the metadata associated with the embedding. Present only for `document` tasks created with Marengo 3.5. See [DocumentEmbeddingMetadata](#documentembeddingmetadata) for details. | | `image_embedding` | `Optional[MediaEmbeddingTaskImageEmbedding]` | An object containing the metadata associated with the embedding. Present only for `image` tasks created with Marengo 3.5. See [ImageEmbeddingMetadata](#imageembeddingmetadata) for details. | Each of the four objects above wraps a single `metadata` field. All four metadata classes inherit the following properties: | Name | Type | Description | | ---------------- | --------------- | --------------------------------------------------------------------------------------------------------- | | `input_url` | `Optional[str]` | The URL of the media file used to generate the embedding. Present if a URL was provided in the request. | | `input_filename` | `Optional[str]` | The name of the media file used to generate the embedding. Present if a file was provided in the request. | #### VideoEmbeddingMetadata The `VideoEmbeddingMetadata` class contains the metadata associated with the embedding. | Name | Type | Description | | ------------------------ | --------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `video_clip_length` | `Optional[float]` | The duration for each clip in seconds, as specified in the request. Note that the platform automatically truncates video segments shorter than 2 seconds. For a 31-second video divided into 6-second segments, the final 1-second segment will be truncated. This truncation only applies to the last segment if it does not meet the minimum length requirement of 2 seconds. | | `video_embedding_scope` | `Optional[List[str]]` | The scope you've specified in the request. | | `video_embedding_option` | `Optional[List[str]]` | The `embedding_option` values used to generate the embedding. | | `duration` | `Optional[float]` | The total duration of the video in seconds. | #### AudioEmbeddingMetadata The `AudioEmbeddingMetadata` class contains the metadata associated with the embedding. | Name | Type | Description | | ------------------------ | --------------------- | ------------------------------------------------------------------------------------------------------- | | `audio_embedding_option` | `Optional[List[str]]` | The type of the embedding. It can take one of the following values: `["audio"]` or `["transcription"]`. | | `audio_embedding_scope` | `Optional[List[str]]` | The scope you've specified in the request. | | `duration` | `Optional[float]` | The total duration of the audio in seconds. | | `start_offset_sec` | `Optional[float]` | The start offset in seconds from the beginning of the audio where processing should begin. | | `end_offset_sec` | `Optional[float]` | The end offset in seconds from the beginning of the audio where processing should end. | #### DocumentEmbeddingMetadata The `DocumentEmbeddingMetadata` class contains the metadata associated with the embedding. Only Marengo 3.5 returns this object. | Name | Type | Description | | --------------------------- | --------------------- | ------------------------------------------------------------- | | `document_embedding_option` | `Optional[List[str]]` | The `embedding_option` values used to generate the embedding. | | `document_embedding_scope` | `Optional[List[str]]` | The `embedding_scope` values used to generate the embedding. | #### ImageEmbeddingMetadata The `ImageEmbeddingMetadata` class contains the metadata associated with the embedding. Only Marengo 3.5 returns this object. | Name | Type | Description | | ------------------------ | --------------------- | ---------------------------------------------------------------------------------- | | `image_embedding_option` | `Optional[List[str]]` | The `embedding_option` values used to generate the embedding. Always `["visual"]`. | | `image_embedding_scope` | `Optional[List[str]]` | The `embedding_scope` values used to generate the embedding. Always `["asset"]`. | ### API Reference [List async embedding tasks](/v1.3/api-reference/create-embeddings-v2/list-async-embedding-tasks) ## Create an async embedding task **Description**: This method creates embeddings for audio, video, images, and documents asynchronously. Use this method to embed content at scale, such as long files or the media files you want to make searchable. For a query, or for results you need in the same request, use the [Create embeddings](/v1.3/sdk-reference/python/embed-v2/sync) class instead. The content this method accepts depends on the model. Both models embed audio and video. Marengo 3.5 also embeds images and documents. For the formats, resolutions, file sizes, and duration limits each model accepts, see the input requirements for [Marengo 3.5](/v1.3/docs/concepts/models/marengo/marengo-3-5#input-requirements) or [Marengo 3.0](/v1.3/docs/concepts/models/marengo/marengo-3-0#input-requirements). > **Notes** > > * Creating a task validates only basic metadata and playability, not the full file. A file can pass this check but still fail later during embedding. When you retrieve the results, check the `status` field. If it is `failed`, the `error.message` field contains the reason. > * This method is rate-limited. With Marengo 3.5, the platform counts input tokens for each type of content. A task can exceed a limit before you see an error. For details, see [Input token limits for embedding](/v1.3/docs/get-started/rate-limits#input-token-limits-for-embedding). > * Embeddings are stored for seven days. **Function signature and example**: **`Function signature`** ```python Function signature def create( self, *, input_type: CreateAsyncEmbeddingRequestInputType, model_name: CreateAsyncEmbeddingRequestModelName, embedding_uncertainty: typing.Optional[bool] = OMIT, embedding_dimension: typing.Optional[int] = OMIT, audio: typing.Optional[AsyncAudioInputRequest] = OMIT, video: typing.Optional[AsyncVideoInputRequest] = OMIT, document: typing.Optional[AsyncDocumentInputRequest] = OMIT, image: typing.Optional[AsyncImageInputRequest] = OMIT, request_options: typing.Optional[RequestOptions] = None, ) -> TasksCreateResponse ``` **`Video with fixed segmentation`** ```python Video with fixed segmentation from twelvelabs import ( TwelveLabs, AsyncVideoInputRequest, AsyncTemporalSegmentation, TemporalSegmentation_Fixed, TemporalSegmentationFixedFixed, MediaSource, ) task = client.embed.v_2.tasks.create( input_type="video", model_name="marengo3.5", video=AsyncVideoInputRequest( media_source=MediaSource( url="", ), start_sec=0.0, end_sec=50.0, segmentation=AsyncTemporalSegmentation( temporal=TemporalSegmentation_Fixed( fixed=TemporalSegmentationFixedFixed( duration_sec=10, ), ), ), embedding_option=["visual", "audio"], embedding_scope=["clip", "asset"], embedding_type=["separate_embedding"], ), ) print(f"Task ID: {task.id}") print(f"Status: {task.status}") ``` **`Video fused with time-based metadata`** ```python Video fused with time-based metadata from twelvelabs import ( TwelveLabs, AsyncVideoInputRequest, MediaSource, TimeBasedMetadataEntry, ) task = client.embed.v_2.tasks.create( input_type="video", model_name="marengo3.5", video=AsyncVideoInputRequest( media_source=MediaSource( asset_id="", ), embedding_option=["visual", "audio"], embedding_type=["separate_embedding", "fused_embedding"], embedding_scope=["clip"], time_based_metadata=[ TimeBasedMetadataEntry( start=42.3, end=42.3, text="Shot made. LeBron James dunk. Assist: D'Angelo Russell. +2 LAL. 88-84.", ), ], ), embedding_uncertainty=True, ) print(f"Task ID: {task.id}") print(f"Status: {task.status}") ``` **`PDF document, page-level and whole-asset embeddings`** ```python PDF document, page-level and whole-asset embeddings from twelvelabs import TwelveLabs, AsyncDocumentInputRequest, MediaSource task = client.embed.v_2.tasks.create( input_type="document", model_name="marengo3.5", document=AsyncDocumentInputRequest( media_source=MediaSource( asset_id="", ), embedding_option=["visual"], embedding_type=["separate_embedding"], embedding_scope=["local", "asset"], ), embedding_uncertainty=True, ) print(f"Task ID: {task.id}") print(f"Status: {task.status}") ``` **`Image with single asset-scope visual embedding`** ```python Image with single asset-scope visual embedding from twelvelabs import TwelveLabs, AsyncImageInputRequest, MediaSource task = client.embed.v_2.tasks.create( input_type="image", model_name="marengo3.5", image=AsyncImageInputRequest( media_source=MediaSource( asset_id="", ), ), embedding_uncertainty=True, ) print(f"Task ID: {task.id}") print(f"Status: {task.status}") ``` ### Parameters | Name | Type | Required | Description | | ----------------------- | -------------------------------------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `input_type` | `CreateAsyncEmbeddingRequestInputType` | Yes | The type of content for the embeddings. Values: - `audio`: An audio file. - `video`: A video file. - `document`: A PDF, plain text, or Markdown file. Requires Marengo 3.5. - `image`: An image file. Requires Marengo 3.5. | | `model_name` | `CreateAsyncEmbeddingRequestModelName` | Yes | The embedding model to use. **Values**: - `marengo3.5`: For details about this version, see the [Marengo 3.5](/v1.3/docs/concepts/models/marengo/marengo-3-5) page. - `marengo3.0`: For details about this version, see the [Marengo 3.0](/v1.3/docs/concepts/models/marengo/marengo-3-0) page. | | `audio` | `AsyncAudioInputRequest` | No | Audio input configuration. Required when `input_type` is `audio`. See [AsyncAudioInputRequest](#asyncaudioinputrequest) for details. | | `video` | `AsyncVideoInputRequest` | No | Video input configuration. Required when `input_type` is `video`. See [AsyncVideoInputRequest](#asyncvideoinputrequest) for details. | | `document` | `AsyncDocumentInputRequest` | No | Document input configuration. Required when `input_type` is `document`. Requires Marengo 3.5. See [AsyncDocumentInputRequest](#asyncdocumentinputrequest) for details. | | `image` | `AsyncImageInputRequest` | No | Image input configuration. Required when `input_type` is `image`. Requires Marengo 3.5. See [AsyncImageInputRequest](#asyncimageinputrequest) for details. | | `embedding_uncertainty` | `Optional[bool]` | No | Set this parameter to `True` to include a per-dimension uncertainty vector in the `data[].embedding_uncertainty` field of the result. The vector has the same length as the `embedding` array. A higher value indicates lower confidence in that dimension. Requires Marengo 3.5. **Requirements**: - For audio or video input, set the `embedding_scope` field to exclude `asset`. For example, set the `video.embedding_scope` field to `["clip"]`. The field defaults to `["clip", "asset"]`, so the platform returns a `400` error if you keep the default. This requirement does not apply to image input. - For a PDF document, the platform returns a `400` error regardless of the `document.embedding_scope` value. - For a plain text or Markdown document, set the `document.embedding_scope` field to `["local"]`. Any other value returns a `400` error. | | `embedding_dimension` | `Optional[int]` | No | The number of dimensions for each embedding that the task produces, including the [`data[].embedding_uncertainty`](/v1.3/api-reference/create-embeddings-v2/retrieve-embeddings#response.body.data.embedding-uncertainty) vector. Marengo 3.5 produces Matryoshka embeddings: a shorter embedding consists of the first values of the full-length embedding. A 256-dimension embedding, for example, is the first 256 values of a 512-dimension embedding of the same content. Shorter embeddings reduce index size and speed up similarity search; longer embeddings produce higher retrieval quality. **Requirements**: - Requires Marengo 3.5. Setting this parameter when `model_name` is `marengo3.0` returns a `400` error. - Applies to the entire task: you cannot set it for a single input type or embedding. - Set it once, when you create the task. To use a different value, create a new task. - Use the same value across an index. **Default**: 512 | | `request_options` | `RequestOptions` | No | Request-specific configuration. | #### AsyncAudioInputRequest The `AsyncAudioInputRequest` class specifies the configuration for processing audio content. Required when `input_type` is `audio`. Base64-encoded audio can be up to 36 MB decoded. For a larger file, provide a URL or an asset identifier. | Name | Type | Required | Description | | --------------------- | ---------------------------------------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `media_source` | `MediaSource` | Yes | Specifies the source of the audio file. See [MediaSource](#mediasource) for details. | | `start_sec` | `float` | No | The start time in seconds for processing the audio file. Use this parameter to process a portion of the audio file starting from a specific time. **Default**: 0 (start from the beginning). | | `end_sec` | `float` | No | The end time in seconds for processing the audio file. Use this parameter to process a portion of the audio file ending at a specific time. The end time must be greater than the start time. **Default**: End of the audio file | | `segmentation` | `AsyncAudioInputRequestSegmentation` | No | Specifies how the platform divides the audio into segments. The structure of this object depends on the model version: - **With Marengo 3.5**: Place your settings in the `temporal` object. Both strategies are available: `dynamic` divides the audio into variable-length segments that follow scene changes, and `fixed` divides it into equal-length segments. Default: `temporal.dynamic`, `min_duration_sec: 2`. - **With Marengo 3.0**: Provide the settings directly in this object. Only `fixed` segmentation is available. Default: `fixed`, `duration_sec: 6`. If you use a structure that does not match your model version, the platform returns a `400` error. See [AudioSegmentation](#audiosegmentation) and [AsyncTemporalSegmentation](#asynctemporalsegmentation) for details. | | `embedding_option` | `List[str]` | No | The types of embeddings you wish to generate. **Values**: - `audio`: Generates embeddings based on audio content (sounds, music, effects). With Marengo 3.5, this value includes speech, music, and non-dialog audio. - `transcription`: Generates embeddings based on transcribed speech. Requires Marengo 3.0. You can specify multiple values to generate different types of embeddings for the same audio. **Default**: `["audio", "transcription"]` for Marengo 3.0; `["audio"]` for Marengo 3.5. | | `embedding_scope` | `List[str]` | No | The scope for which you wish to generate embeddings. **Values**: - `clip`: Generates one embedding for each segment. Works with both Marengo 3.0 and Marengo 3.5. - `local`: Generates one embedding for each segment. Equivalent to `clip` when using Marengo 3.5. - `asset`: Generates one embedding for the entire audio file You can specify multiple scopes to generate embeddings at different levels. **Default**: `["clip", "asset"]` | | `embedding_type` | `List[str]` | No | Specifies how to structure the embedding. Include this parameter only when the `embedding_option` parameter contains at least two values. **Values**: - `separate_embedding`: Returns separate embeddings for each modality specified in the `embedding_option` parameter. - `fused_embedding`: Returns a single combined embedding that integrates all modalities into one vector. With Marengo 3.5, this value requires the `time_based_metadata` field. Specify both values to receive separate and fused embeddings in the same response. **Default**: `separate_embedding`. | | `time_based_metadata` | `Optional[List[TimeBasedMetadataEntry]]` | No | Your own time-aligned text, such as a stats feed or scene descriptions. The platform folds each entry into the fused embedding of the segments it overlaps in time, and it affects only that embedding. Requires the `fused_embedding` value in the `embedding_type` field. This field is supported only with Marengo 3.5. See [TimeBasedMetadataEntry](#timebasedmetadataentry) for details. | #### AsyncVideoInputRequest The `AsyncVideoInputRequest` class specifies the configuration for processing video content. Required when `input_type` is `video`. Base64-encoded video can be up to 36 MB decoded. For a larger file, provide a URL or an asset identifier. | Name | Type | Required | Description | | --------------------- | ---------------------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `media_source` | `MediaSource` | Yes | Specifies the source of the video file. See [MediaSource](#mediasource) for details. | | `start_sec` | `float` | No | The start time in seconds for processing the video file. Use this parameter to process a portion of the video file starting from a specific time. **Default**: 0 (start from the beginning) | | `end_sec` | `float` | No | The end time in seconds for processing the video file. Use this parameter to process a portion of the video file ending at a specific time. The end time must be greater than the start time. **Default**: End of the video file | | `segmentation` | `AsyncVideoInputRequestSegmentation` | No | Specifies how the platform divides the video into segments. The structure of this object depends on the model version: - **With Marengo 3.5**: Place your settings in the `temporal` object. Both strategies are available: `dynamic` divides the video into variable-length segments that follow scene changes, and `fixed` divides it into equal-length segments. Default: `temporal.dynamic`, `min_duration_sec: 2`. - **With Marengo 3.0**: Provide the settings directly in this object. Default: `dynamic`, `min_duration_sec: 4`. If you use a structure that does not match your model version, the platform returns a `400` error. See [VideoSegmentation](#videosegmentation) and [AsyncTemporalSegmentation](#asynctemporalsegmentation) for details. | | `embedding_option` | `List[str]` | No | The types of embeddings to generate for the video. **Values**: - `visual`: Generates embeddings based on visual content (scenes, objects, actions) - `audio`: Generates embeddings based on audio content (sounds, music, effects). With Marengo 3.5, this value includes speech, music, and non-dialog audio. - `transcription`: Generates embeddings based on transcribed speech. Requires Marengo 3.0. You can specify multiple values to generate different types of embeddings for the same video. **Default**: `["visual", "audio", "transcription"]` for Marengo 3.0; `["visual", "audio"]` for Marengo 3.5. | | `embedding_scope` | `List[str]` | No | The scope for which you wish to generate embeddings. **Values**: - `clip`: Generates one embedding for each segment. Works with both Marengo 3.0 and Marengo 3.5. - `local`: Generates one embedding for each segment. Equivalent to `clip` when using Marengo 3.5. - `asset`: Generates one embedding for the entire video file. Use this scope for videos up to 10-30 seconds to maintain optimal performance. You can specify multiple scopes to generate embeddings at different levels. **Default**: `["clip", "asset"]` | | `embedding_type` | `List[str]` | No | Specifies how to structure the embedding. Include this parameter only when the `embedding_option` parameter contains at least two values. **Values**: - `separate_embedding`: Returns separate embeddings for each modality specified in the `embedding_option` parameter. - `fused_embedding`: Returns a single combined embedding that integrates all modalities into one vector. With Marengo 3.5, this value requires the `time_based_metadata` field. Specify both values to receive separate and fused embeddings in the same response. **Default**: `separate_embedding`. | | `time_based_metadata` | `Optional[List[TimeBasedMetadataEntry]]` | No | Your own time-aligned text, such as a stats feed or scene descriptions, which you can generate by [segmenting a video with Pegasus](/v1.3/docs/guides/segment-videos). The platform folds each entry into the fused embedding of the segments it overlaps in time, and it affects only that embedding. Requires the `fused_embedding` value in the `embedding_type` field. This field is supported only with Marengo 3.5. See [TimeBasedMetadataEntry](#timebasedmetadataentry) for details. | #### TimeBasedMetadataEntry One time-aligned metadata entry. The platform folds the text of the entry into the fused embedding of every segment that overlaps the time range of the entry. Used by the `AsyncAudioInputRequest.time_based_metadata` and `AsyncVideoInputRequest.time_based_metadata` fields. Not applicable to the `AsyncDocumentInputRequest` class. Requires Marengo 3.5. | Name | Type | Required | Description | | ------- | ------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `start` | `float` | Yes | The start time of the entry in seconds, measured from the beginning of the asset. Set the same value in the `end` field for an event that happens at a single point in time, such as one entry in a stats feed. | | `end` | `float` | Yes | The end time of the entry in seconds, measured from the beginning of the asset. | | `text` | `str` | Yes | The text to fold into the fused embedding of the overlapping segments. | #### AsyncDocumentInputRequest The `AsyncDocumentInputRequest` class specifies the configuration for processing documents. Requires Marengo 3.5. The platform accepts PDF (`.pdf`), plain text (`.txt`), and Markdown (`.md`) files. The decoded file can be up to 512 MB. It embeds a PDF file from its rendered pages or from its extracted text, and a plain text or Markdown file from its text. A PDF file also has a page allowance: 64 pages for each MB of file size. A 0.5 MB file is allowed 64 pages, and a 4 MB file is allowed 256 pages. The `quadrants` strategy counts each page five times against this allowance. The platform checks the page count of the file against the allowance before processing the file. If the file exceeds the allowance, the platform creates the task and sets its `status` field to the `failed` value. The `error.message` field contains the page count and the allowance. Plain text and Markdown files have no page allowance. The `embedding_option` and `embedding_scope` fields combine, and the platform supports the following combinations. | File type | `embedding_option` | `embedding_scope` | Result | | -------------------- | ------------------ | ----------------- | ---------------------------------------------------------------------------------------------- | | PDF | `visual` | `local` | One embedding for each rendered page. The default for PDF files. | | PDF | `visual` | `asset` | One embedding for the entire file. | | PDF | `text` | `asset` | One embedding for the extracted text of the entire file. | | Plain text, Markdown | `text` | `asset` | One embedding for the entire file. The default for plain text and Markdown files. | | Plain text, Markdown | `text` | `local` | One embedding for each chunk of whole sentences. Requires the `segmentation.sequential` field. | You can request more than one combination at a time. For example, `embedding_scope: ["local", "asset"]` on a PDF file returns the per-page embeddings and the whole-file embedding together. The platform pairs each value in one field with each value in the other. Each pair must appear in this table; if you send a pair outside it, the platform returns a `400` error. If you omit a field, the platform uses its default value. If you embed a PDF file with the `embedding_option` field set to `["text"]`, also set the `embedding_scope` field to `["asset"]`. For PDF files, the default `["local"]` pairs with only the `visual` option. | Name | Type | Required | Description | | ------------------ | -------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `media_source` | `MediaSource` | Yes | Specifies the source of the document file. See [MediaSource](#mediasource) for details. | | `segmentation` | `Optional[DocumentSegmentation]` | No | Specifies how the platform divides your document before it generates embeddings. Use the `spatial` field to divide each rendered page of a PDF file. Use the `sequential` field to divide a plain text or Markdown file into chunks. See [DocumentSegmentation](#documentsegmentation) for details. | | `embedding_option` | `Optional[List[str]]` | No | The types of embeddings to generate for the document. **Values**: - `visual`: Generates embeddings from the rendered pages. Valid for PDF files. - `text`: Generates embeddings from the text content. Valid for PDF, plain text, and Markdown files. **Default**: `["visual"]` for PDF files; `["text"]` for plain text and Markdown files. | | `embedding_type` | `Optional[List[str]]` | No | Specifies how to structure the embedding. **Values**: - `separate_embedding`: Returns one embedding per requested `embedding_scope`. - `fused_embedding`: The platform returns a `400` error if you set this value. Documents have a single modality. **Default**: `separate_embedding`. | | `embedding_scope` | `Optional[List[str]]` | No | The scope for which you wish to generate embeddings. **Values**: - `local`: Returns one embedding for each part of the file. For a PDF file, each part is a rendered page, and you can divide each page further with the `segmentation.spatial` field. For a plain text or Markdown file, each part is a chunk of whole sentences, and the `segmentation.sequential` field is required. - `asset`: Returns one embedding for the entire file. **Default**: `["local"]` for PDF files; `["asset"]` for plain text and Markdown files. | #### DocumentSegmentation The `DocumentSegmentation` class specifies how the platform divides your document before it generates embeddings. Requires Marengo 3.5. Use the `spatial` field to divide each rendered page of a PDF file. Use the `sequential` field to divide a plain text or Markdown file into chunks. Provide the field that matches your file. If you provide neither field, the platform returns a `400` error. | Name | Type | Required | Description | | ------------ | ------------------------------------------ | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `spatial` | `Optional[DocumentSpatialSegmentation]` | No | Specifies how the platform divides each rendered page of a PDF file. See [DocumentSpatialSegmentation](#documentspatialsegmentation) for details. | | `sequential` | `Optional[DocumentSequentialSegmentation]` | No | Specifies how the platform divides a plain text or Markdown file into chunks. See [DocumentSequentialSegmentation](#documentsequentialsegmentation) for details. | #### DocumentSpatialSegmentation The `DocumentSpatialSegmentation` class specifies how the platform divides each rendered page of a PDF file. Plain text and Markdown files have no rendered pages, so the platform returns a `400` error if you include this object. This object requires the `visual` value in the `embedding_option` field and the `local` value in the `embedding_scope` field. | Name | Type | Required | Description | | ---------- | ----------------------------------------------- | -------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `Optional[DocumentSpatialSegmentationStrategy]` | No | The strategy for dividing each page. **Values**: - `standard`: Returns one embedding for each page. - `quadrants`: Divides each page into a 2×2 grid. Returns five embeddings: one for the whole page, and one for each quarter. The `data[].quadrant` field identifies which quarter each embedding represents. This field is `null` on the whole-page embedding. This strategy uses five times as many tokens as the `standard` strategy. It also counts each page five times against the page allowance of the file. **Default**: `standard` | #### DocumentSequentialSegmentation The `DocumentSequentialSegmentation` class specifies how the platform divides a plain text or Markdown file into chunks. For a PDF file, the platform divides by page instead and returns a `400` error if you include this object. This object requires the `text` value in the `embedding_option` field and the `local` value in the `embedding_scope` field. | Name | Type | Required | Description | | ------------------- | ---------------------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `DocumentSequentialSegmentationStrategy` | Yes | The strategy for dividing the text into chunks. Always `sentence`, which groups whole sentences into each chunk, up to the number of sentences in the `max_sentences` field. | | `max_sentences` | `int` | Yes | The maximum number of sentences in each chunk. This field has no default. Choose a value small enough that every chunk fits in the context window of the model. If a chunk exceeds that window, the task fails, and the platform does not truncate it. How many sentences fit depends on the length of the sentences in your file. | | `overlap_sentences` | `Optional[int]` | No | The number of sentences at the end of one chunk that the platform repeats at the start of the next. The overlap preserves the context of the previous chunk. This value must be less than the `max_sentences` value. **Default**: 0 | #### AsyncImageInputRequest The `AsyncImageInputRequest` class specifies the configuration for processing image content. Required when `input_type` is `image`. Requires Marengo 3.5. The decoded file can be up to 32 MB. For an image, the `embedding_option`, `embedding_type`, and `embedding_scope` fields each accept a single value; the platform returns a `400` error if you send any other value. | Name | Type | Required | Description | | ------------------ | --------------------- | -------- | -------------------------------------------------------------------------------------------------------------- | | `media_source` | `MediaSource` | Yes | Specifies the source of the image file. See [MediaSource](#mediasource) for details. | | `embedding_option` | `Optional[List[str]]` | No | The type of embedding to generate for the image. Always `visual`. | | `embedding_type` | `Optional[List[str]]` | No | Specifies how to structure the embedding. Always `separate_embedding`. | | `embedding_scope` | `Optional[List[str]]` | No | The scope for which to generate embeddings. Always `asset`, which produces one embedding for the entire image. | #### MediaSource The `MediaSource` class specifies the source of the media file. Provide exactly one of the following: | Name | Type | Required | Description | | ---------------- | ----- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `base_64_string` | `str` | No | The base64-encoded media data. Encoding grows the payload by about a third, so the string you send is larger than the original file. The maximum size depends on the input type and the model. The description of the field that contains this media source states the limit where it differs; for the formats and sizes each model accepts, see the input requirements for [Marengo 3.5](/v1.3/docs/concepts/models/marengo/marengo-3-5#input-requirements) or [Marengo 3.0](/v1.3/docs/concepts/models/marengo/marengo-3-0#input-requirements). | | `url` | `str` | No | The publicly accessible URL of the media file. Use direct links to raw media files. Video hosting platforms and cloud storage sharing links are not supported. | | `asset_id` | `str` | No | The unique identifier of an asset from a [direct](/v1.3/sdk-reference/python/upload-content/direct-uploads) or [multipart](/v1.3/sdk-reference/python/upload-content/multipart-uploads) upload. The asset status must be `ready`. Use [`assets.retrieve`](/v1.3/sdk-reference/python/manage-assets#retrieve-an-asset) to check the status. | #### AudioSegmentation The `AudioSegmentation` class specifies how the platform divides the audio into segments using fixed-length intervals. | Name | Type | Required | Description | | ---------- | --------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `AudioSegmentationStrategy` | Yes | The segmentation strategy. Value: `fixed`. | | `fixed` | `AudioSegmentationFixed` | Yes | Configuration for fixed segmentation. This object is required when the `strategy` field is `fixed`. See [AudioSegmentationFixed](#audiosegmentationfixed) for details. | #### AudioSegmentationFixed The `AudioSegmentationFixed` class configures fixed-length segmentation for audio. | Name | Type | Required | Description | | -------------- | ----- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `duration_sec` | `int` | Yes | The duration in seconds for each segment. The platform divides the audio into segments of this exact length. The final segment may be shorter if the audio duration is not evenly divisible. **Min**: `2`. **Max**: `10`. **Example**: With `duration_sec: 5`, a 12-second audio file produces segments: \[0-5s], \[5-10s], \[10-12s]. | #### VideoSegmentation The `VideoSegmentation` type specifies how the platform divides the video into segments. Use one of the following: **Fixed segmentation**: Divides the video into equal-length segments: | Name | Type | Required | Description | | ---------- | ----------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------ | | `strategy` | `Literal["fixed"]` | Yes | The segmentation strategy. Value: `fixed`. | | `fixed` | `VideoSegmentationFixedFixed` | Yes | Configuration for fixed segmentation. See [VideoSegmentationFixedFixed](#videosegmentationfixedfixed) for details. | **Dynamic segmentation**: Divides the video into adaptive segments based on scene changes: | Name | Type | Required | Description | | ---------- | --------------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `Literal["dynamic"]` | Yes | The segmentation strategy. Value: `dynamic`. | | `dynamic` | `VideoSegmentationDynamicDynamic` | Yes | Configuration for dynamic segmentation. See [VideoSegmentationDynamicDynamic](#videosegmentationdynamicdynamic) for details. | #### VideoSegmentationFixedFixed The `VideoSegmentationFixedFixed` class configures fixed-length segmentation for video. | Name | Type | Required | Description | | -------------- | ----- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `duration_sec` | `int` | Yes | The duration in seconds for each segment. The platform divides the video into segments of this exact length. The final segment may be shorter if the video duration is not evenly divisible. **Min**: `2`. **Max**: `10`. **Example**: With `duration_sec: 5`, a 12-second video produces segments: \[0-5s], \[5-10s], \[10-12s]. | #### VideoSegmentationDynamicDynamic The `VideoSegmentationDynamicDynamic` class configures dynamic segmentation for video based on scene changes. | Name | Type | Required | Description | | ------------------ | ----- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `min_duration_sec` | `int` | Yes | The minimum duration in seconds for each segment. The platform divides the video into segments that are at least this long. Segments adapt to scene changes and content boundaries and may be longer than the minimum. **Min**: `2`. **Max**: `5`. **Example**: With `min_duration_sec: 3`, segments might be: \[0-3.2s], \[3.2-7.8s], \[7.8-12.1s] | #### AsyncTemporalSegmentation The `AsyncTemporalSegmentation` class wraps your settings in a `temporal` object. Use with Marengo 3.5. | Name | Type | Required | Description | | ---------- | ---------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------- | | `temporal` | `TemporalSegmentation` | Yes | Specifies how the platform divides the file into segments. See [TemporalSegmentation](#temporalsegmentation) for details. | #### TemporalSegmentation The `TemporalSegmentation` type specifies how the platform divides the file into segments. The `strategy` field selects one variant: **Dynamic segmentation**: Creates variable-length segments that align with scene or content boundaries. Use this for content-aware segmentation. | Name | Type | Required | Description | | ---------- | ------------------------------------ | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `Literal["dynamic"]` | Yes | Must be `dynamic`. Identifies this as the content-aware segmentation variant. | | `dynamic` | `TemporalSegmentationDynamicDynamic` | Yes | Configuration for dynamic segmentation. This object is required when `strategy` is `dynamic`. See [TemporalSegmentationDynamicDynamic](#temporalsegmentationdynamicdynamic) for details. | **Fixed segmentation**: Creates equal-length segments. Use this for consistent timing. | Name | Type | Required | Description | | ---------- | -------------------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `strategy` | `Literal["fixed"]` | Yes | Must be `fixed`. Identifies this as the equal-length segmentation variant. | | `fixed` | `TemporalSegmentationFixedFixed` | Yes | Configuration for fixed segmentation. This object is required when `strategy` is `fixed`. See [TemporalSegmentationFixedFixed](#temporalsegmentationfixedfixed) for details. | #### TemporalSegmentationDynamicDynamic The `TemporalSegmentationDynamicDynamic` class configures dynamic segmentation. This object is required when `strategy` is `dynamic`. | Name | Type | Required | Description | | ------------------ | ----- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `min_duration_sec` | `int` | Yes | The minimum duration in seconds for each segment. The platform divides the file into segments that are at least this long. Segments adapt to scene changes and content boundaries and may be longer than the minimum. **Min**: `2`. **Max**: `5`. | #### TemporalSegmentationFixedFixed The `TemporalSegmentationFixedFixed` class configures fixed segmentation. This object is required when `strategy` is `fixed`. | Name | Type | Required | Description | | -------------- | ----- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `duration_sec` | `int` | Yes | The duration in seconds for each segment. The platform divides the file into segments of this exact length. The final segment may be shorter if the duration is not evenly divisible. **Min**: `2`. **Max**: `10`. | ### Return value Returns a `TasksCreateResponse` object containing the task details. The `TasksCreateResponse` class contains the following properties: | Name | Type | Description | | ---------- | --------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | `str` | The unique identifier of the embedding task. | | `status` | `Literal["processing"]` | The initial status of the embedding task. Value: `processing`. | | `data` | `Optional[List[EmbeddingData]]` | Array of embedding results. Present when `status` is `ready`; `null` when `status` is `processing` or `failed`. | | `metadata` | `Optional[TasksCreateResponseMetadata]` | Metadata about the task you created. The platform sets the length of your embeddings when it creates the task, and the `embedding_dimension` field contains that length. Only Marengo 3.5 returns this object. | The `TasksCreateResponseMetadata` class contains the following properties: | Name | Type | Description | | --------------------- | ------------------------------ | -------------------------------------------------------------------------------------------------- | | `embedding_dimension` | `Optional[EmbeddingDimension]` | The number of dimensions for each embedding in this response. Only Marengo 3.5 returns this field. | ### API Reference [Create an async embedding task](/v1.3/api-reference/create-embeddings-v2/create-async-embedding-task) ### Related guide * [Audio embeddings](/v1.3/docs/guides/create-embeddings/at-scale/audio) * [Video embeddings](/v1.3/docs/guides/create-embeddings/at-scale/video) ## Retrieve task status and results **Description**: This method retrieves the status and the results of an async embedding task. Invoke this method repeatedly until the `status` field is `ready` or `failed`. When the status is `ready`, use the embeddings from the response. When the status is `failed`, the `error.message` field contains the reason. > **Note** > > Embeddings are stored for seven days. **Function signature and example**: **`Function signature`** ```python Function signature def retrieve( self, task_id: str, *, request_options: typing.Optional[RequestOptions] = None ) -> EmbeddingTaskResponse ``` **`Poll for task completion`** ```python Poll for task completion from twelvelabs import TwelveLabs import time while True: task = client.embed.v_2.tasks.retrieve(task_id="") print(f"Task Status: {task.status}") if task.status == "ready": print(f"Task completed!") break elif task.status == "failed": print("Task failed") break else: print("Task still processing, waiting...") time.sleep(5) ``` **`Retrieve embeddings`** ```python Retrieve embeddings from twelvelabs import TwelveLabs task = client.embed.v_2.tasks.retrieve( task_id="", ) print(f"Task ID: {task.id}") print(f"Status: {task.status}") if task.status == "ready" and task.data: print(f"\nNumber of embeddings: {len(task.data)}") for embedding_data in task.data: print(f"Type: {embedding_data.embedding_option}, Scope: {embedding_data.embedding_scope}") if embedding_data.start_sec is not None: print(f"Time range: {embedding_data.start_sec}s - {embedding_data.end_sec}s") print(f"Embedding dimensions: {len(embedding_data.embedding)}") print(f"First 10 values: {embedding_data.embedding[:10]}") ``` ### Parameters | Name | Type | Required | Description | | ----------------- | ---------------- | -------- | -------------------------------------------- | | `task_id` | `str` | Yes | The unique identifier of the embedding task. | | `request_options` | `RequestOptions` | No | Request-specific configuration. | ### Return value Returns an `EmbeddingTaskResponse` object containing the task status and results. The `EmbeddingTaskResponse` class contains the following properties: | Name | Type | Description | | ------------ | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | `str` | The unique identifier of the embedding task. | | `status` | `EmbeddingTaskResponseStatus` | The current status of the task. **Values**: - `processing`: The platform is creating the embeddings - `ready`: Processing is complete. Embeddings are available in the `data` field - `failed`: The task failed. The `data` field is `null`, and the `error.message` field contains the reason | | `created_at` | `Optional[datetime]` | The date and time when the task was created. | | `updated_at` | `Optional[datetime]` | The date and time when the task was last updated. | | `data` | `Optional[List[EmbeddingData]]` | An object containing the embedding results, or `null` otherwise. | | `usage` | `Optional[EmbeddingUsage]` | Token counts for the request. Only Marengo 3.5 returns this field. See [EmbeddingUsage](#embeddingusage) for details. | | `metadata` | `Optional[EmbeddingTaskMediaMetadata]` | Metadata for the media input. See [EmbeddingTaskMediaMetadata](#embeddingtaskmediametadata) for details. | | `error` | `Optional[EmbeddingTaskResponseError]` | An object describing why the embedding task failed. Present only when `status` is `failed`. Omitted otherwise. | The `EmbeddingData` class contains the following properties: | Name | Type | Description | | ----------------------- | ---------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `embedding` | `List[float]` | The embedding vector for the content. | | `embedding_uncertainty` | `Optional[List[float]]` | A per-dimension uncertainty vector with the same length as the `embedding` array. A higher value indicates lower confidence in that dimension. Present when the request sets `embedding_uncertainty: true`. Only Marengo 3.5 returns this field. | | `embedding_option` | `Optional[EmbeddingDataEmbeddingOption]` | The type of the embedding. **Values**: - `visual`: Embedding based on visual content (a video, a page of a PDF file, or an image embedded asynchronously). - `audio`: Embedding based on audio content. - `transcription`: Embedding based on transcribed speech. Returned only for content embedded with Marengo 3.0. - `text`: Embedding based on the text content of a PDF, plain text, or Markdown file embedded asynchronously. - `fused`: Embedding based on a combination of the modalities specified in the request. The platform returns this embedding only for video and audio input, and only when the `embedding_type` parameter includes the `fused_embedding` value. - `null`: For text embeddings and images embedded synchronously. | | `embedding_scope` | `Optional[EmbeddingDataEmbeddingScope]` | The scope for which the embedding was generated. **Values**: - `clip`: Embedding for a segment. For video and audio input, one embedding per detected segment. - `page`: Embedding for one page of a PDF file embedded asynchronously, or for one quadrant of a page when the request sets the `document.segmentation.spatial.strategy` field to the `quadrants` strategy. With that strategy, five entries share the same scope and page numbers, so read the `quadrant` field to tell them apart: the whole-page entry has no `quadrant` value. - `chunk`: Embedding for one chunk of whole sentences of a plain text or Markdown file embedded asynchronously. Read the `chunk_index` field for the position of the chunk in the file. - `asset`: Embedding for the entire file. For video and audio input, use this scope for content up to 10-30 seconds to maintain optimal performance. - `null`: For text embeddings and images embedded synchronously. When you request the `local` scope, the platform returns `clip` for audio and video, `page` for PDF files, and `chunk` for plain text and Markdown files. For audio, video, and document input, the `metadata.embedding_scopes` field contains the scopes you requested. | | `start_sec` | `Optional[float]` | The start time in seconds for this segment. This field is `null` for text and image embeddings. | | `end_sec` | `Optional[float]` | The end time in seconds for this segment. This field is `null` for text and image embeddings. | | `start_page_number` | `Optional[int]` | The first page this embedding covers, counting from 1. The platform returns this field only for page-level embeddings of a PDF file, and `null` in every other case. | | `quadrant` | `Optional[str]` | The quarter of the page this embedding covers. The platform returns this field only when the request sets the `document.segmentation.spatial.strategy` field to the `quadrants` strategy, and only on the four quadrant embeddings of a page. This field is `null` on the whole-page embedding and in every other case. | | `chunk_index` | `Optional[int]` | The position of this chunk in the file, counting from 0. The platform returns this field only on `chunk`-scope embeddings of a plain text or Markdown file, and `null` in every other case. Read this field rather than the position of the entry in the `data` array, which provides no ordering guarantee. | | `end_page_number` | `Optional[int]` | The last page this embedding covers, counting from 1 and including that page. This field matches the `start_page_number` field when the embedding covers a single page. The platform returns this field only for page-level embeddings of a PDF file, and `null` in every other case. | #### EmbeddingUsage The `EmbeddingUsage` class provides token counts for the request. Only Marengo 3.5 returns this object. | Name | Type | Description | | ------------------- | --------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | `input_tokens` | `Dict[str, int]` | The number of tokens the request used. Each key names a type of content the request processed, and each value is the token count for that content. The platform reports the content types your request actually used. Each key is one of the following: `video`, `audio`, `image`, `document`, or `text`. Read the keys the response returns rather than assuming a fixed set. | | `truncated` | `bool` | Whether the input was truncated to fit within the token limit. | | `truncation_reason` | `Literal["model_context_window"]` | The reason the input was truncated. Present only when the `truncated` field is `true`. **Values**: - `model_context_window`: The input exceeded the context window of the model. | #### EmbeddingTaskMediaMetadata The `EmbeddingTaskMediaMetadata` type provides metadata for the media input. The `input_type` field selects one variant: **Audio**: Metadata for audio embeddings. | Name | Type | Description | | --------------------- | ------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | `input_type` | `Literal["audio"]` | The type of the input content. Value: `audio`. | | `input_url` | `Optional[str]` | The publicly accessible URL for the audio file. | | `input_filename` | `Optional[str]` | The name of the audio file. | | `embedding_options` | `List[str]` | The `embedding_option` values used to generate the embedding. | | `embedding_scopes` | `List[EmbeddingAudioMetadataEmbeddingScopesItem]` | The `embedding_scope` values used to generate the embedding. | | `embedding_dimension` | `Optional[int]` | The number of dimensions for each embedding in this response. Only Marengo 3.5 returns this field. | | `duration` | `float` | The duration of the audio in seconds. | | `start_offset_sec` | `Optional[float]` | The start offset in seconds. | | `end_offset_sec` | `Optional[float]` | The end offset in seconds. | **Video**: Metadata for video embeddings. | Name | Type | Description | | --------------------- | ------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | `input_type` | `Literal["video"]` | The type of the input content. Value: `video`. | | `input_url` | `Optional[str]` | The publicly accessible URL for the video file. | | `input_filename` | `Optional[str]` | The name of the video file. | | `clip_length` | `Optional[int]` | Length of each video clip in seconds. Only available for fixed segmentation. | | `embedding_scopes` | `List[EmbeddingVideoMetadataEmbeddingScopesItem]` | The `embedding_scope` values used to generate the embedding. | | `embedding_dimension` | `Optional[int]` | The number of dimensions for each embedding in this response. Only Marengo 3.5 returns this field. | | `embedding_options` | `List[str]` | The `embedding_option` values used to generate the embedding. | | `duration` | `float` | The duration of the video in seconds. | | `start_offset_sec` | `Optional[float]` | The start offset in seconds. | | `end_offset_sec` | `Optional[float]` | The end offset in seconds. | **Document**: Metadata for document embeddings. Only Marengo 3.5 returns this object. | Name | Type | Description | | --------------------- | ---------------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | `input_type` | `Literal["document"]` | The type of the input content. Value: `document`. | | `input_url` | `Optional[str]` | The publicly accessible URL for the document file. | | `input_filename` | `Optional[str]` | The name of the document file. | | `embedding_options` | `Optional[List[str]]` | The `embedding_option` values used to generate the embedding. | | `embedding_scopes` | `Optional[List[AsyncDocumentMetadataEmbeddingScopesItem]]` | The `embedding_scope` values used to generate the embedding. | | `embedding_dimension` | `Optional[int]` | The number of dimensions for each embedding in this response. Only Marengo 3.5 returns this field. | **Image**: Metadata for image embeddings. Only Marengo 3.5 returns this object. | Name | Type | Description | | --------------------- | ------------------------------------------------------- | -------------------------------------------------------------------------------------------------- | | `input_type` | `Literal["image"]` | The type of the input content. Value: `image`. | | `input_url` | `Optional[str]` | The publicly accessible URL for the image file. | | `input_filename` | `Optional[str]` | The name of the image file. | | `embedding_options` | `Optional[List[str]]` | The `embedding_option` values used to generate the embedding. Always `["visual"]`. | | `embedding_scopes` | `Optional[List[AsyncImageMetadataEmbeddingScopesItem]]` | The `embedding_scope` values used to generate the embedding. Always `["asset"]`. | | `embedding_dimension` | `Optional[int]` | The number of dimensions for each embedding in this response. Only Marengo 3.5 returns this field. | The `EmbeddingTaskResponseError` class contains the following property: | Name | Type | Description | | --------- | ----- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `message` | `str` | A human-readable message that describes why the task failed. Possible values: - "The embedding service is temporarily unstable. Please try again later." - "The embedding task failed. Please try again later." - "The embedding task could not complete processing." - "The embedding request was invalid." - "The media exceeds the maximum allowed size for embedding." - "Content exceeds the model’s context window." - "The embedding result is no longer available and cannot be retrieved." - "failed to fetch or materialize source media" - "We could not process your media for embedding. Please verify the input file and try again." For the steps to fix the file, see the [How do I fix a file that could not be processed for embedding?](/v1.3/docs/resources/frequently-asked-questions#how-do-i-fix-a-file-that-could-not-be-processed-for-embedding) section on the **Frequently asked questions** page. When the platform can measure the overage in pages, bytes, or seconds, the message includes those numbers in place of the fixed sentence for that limit. For example: "Document (17 pages) exceeds maximum limit of 6 pages", "File size (33.6 MB) exceeds maximum limit of 32 MB", or "Duration (35.0 seconds) exceeds maximum limit of 30 seconds (0 minutes)". | ### API Reference [Retrieve task status and results](/v1.3/api-reference/create-embeddings-v2/retrieve-embeddings)