The video content understanding operator supports using the Doubao model to understand video files, including parsing video content and generating natural language descriptions.
Details | Caution and prerequisites |
|---|---|
Costs | Before calling an operator, you need to understand the model invocation costs associated with using the operator. For details, see Large model invocation billing. |
Authentication (API Key) | Before calling an operator, you need to generate an API Key for operator invocation. It is recommended to configure the API Key as an environment variable to ensure safer operator calls. For details, see Obtain and configure API Key. |
BaseURL | Before calling an operator, you need to determine the BaseURL for operator invocation based on the region where your current LAS service is deployed. This is used to configure the path parameter values for operator calls. |
Billing standards
Sub-item | Billing standard description |
|---|---|
Billing item | There are two billing items: Inference service (input) and Inference service (output). The total fee payable is the sum of all billing items. |
Billing type | Pay-as-you-go, unit: |
Unit price |
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Billing details
Billing formula: Total cost = Total price of billing item 1 + Total price of billing item 2 = (Unit price of billing item 1 * usage) + (Unit price of billing item 2 * usage)
Model type | Sub-scenario (Input video link type) | Condition (thousand tokens) | Unit price: Billing item 1 Inference service (input) | Unit price: Billing item 2 Inference service (output) |
|---|---|---|---|---|
| Video link: Public network link | Input length [0, 128] | 4.7 CNY per million tokens | 20 CNY per million tokens |
Input length (128, 256] | 5.9 CNY per million tokens | 30 CNY per million tokens | ||
Video link: TOS path | Input length [0, 128] | 2.6 CNY per million tokens | 20 CNY per million tokens | |
Input length (128, 256] | 3.8 CNY per million tokens | 30 CNY per million tokens | ||
| Video link: Public network link | Input length [0, 32] | 8.6 CNY per million tokens | 28.9 CNY per million tokens |
Input length (32, 128] | 11.3 CNY per million tokens | 42.4 CNY per million tokens | ||
Input length (128, 256] | 19.3 CNY per million tokens | 82.8 CNY per million tokens | ||
Video link: TOS path | Input length [0, 32] | 6.6 CNY per million tokens | 27 CNY per million tokens | |
Input length (32, 128] | 9.3 CNY per million Tokens | 40.4 CNY per million Tokens | ||
Input length (128, 256] | 17.4 CNY per million Tokens | 80.8 CNY per million Tokens |
Billing estimation
LAS provides you with the capability for "online experience" and offers a certain amount of free usage quota. No configuration is required to experience the data processing effect of the LAS operator online.
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The current operator's online experience allows free usage of up to 500,000 tokens for model consumption. Any excess will be billed according to the operator's billing metrics. For details on billing metrics and logic for each operator, please refer to Large model invocation billing.
After logging in and entering LAS console , locate the current operator card, hover the mouse over the operator card, and click the "online experience" button.
Invoke the las_vlm_video operator for video understanding via the Chat interface.
Parameter name | Type | Required | Example | Description |
|---|---|---|---|---|
las_extra_params | las_extra_params | Yes | Additional operator-specific parameters. | |
model | string | Yes | doubao-seed-1-8-251228 | Specifies the model used for video understanding. Supported model names:
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messages | list of chat_message | Yes | A list of messages that make up the conversation so far. Different models support different message types, such as text, images, and videos. For usage of this field, refer to the messages parameter in the request body of the Chat API. Video URLs support public HTTP links and TOS paths. | |
max_tokens | integer | No | 10000 | Value range: varies by model. For details, see Model List. Maximum length of the model response (unit: token).
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max_completion_tokens | integer | No | 10000 | > For models that support this field and usage instructions, see Documentation. Value range: [0, 64k]. Controls the maximum length of the model output, including both the model response and reasoning content (unit: token). After this parameter is configured, the model can output ultra-long content, max_tokens (default value: 4k) becomes invalid, and the model outputs content (response and reasoning content) as needed until it reaches the value configured for max_completion_tokens.Cannot be set together with max_tokens; otherwise, an error is returned. |
stop | list of string | No | Default value: null. The model stops generating when it encounters any string specified in the stop field, and the string itself is not output. Up to 4 strings are supported.> Models with deep thinking capabilities do not support this field. | |
frequency_penalty | float | No | 1.0 | Value range: [-2.0, 2.0]. Frequency penalty coefficient. If the value is positive, new tokens are penalized based on their frequency in the text, reducing the likelihood of verbatim repetition. |
presence_penalty | float | No | 1.0 | Value range: [-2.0, 2.0]. Presence penalty coefficient. If the value is positive, new tokens are penalized based on whether they have appeared in the text so far, increasing the likelihood that the model discusses new topics. |
temperature | float | No | 1 | Value range: [0, 2]. Sampling temperature. Controls how much smoothing is applied to the probability distribution of each candidate token during text generation. When set to 0, the model only considers the token with the highest log probability. Higher values, such as 0.8, make the output more random; lower values, such as 0.2, make the output more focused and deterministic. It is generally recommended to adjust only one of temperature or top_p, not both. |
top_p | float | No | 0.5 | Value range: [0, 1]. Nucleus sampling probability threshold. The model considers token results whose probability mass falls within top_p. When set to 0, the model only considers the token with the highest log probability. A value of 0.1 means only the top 10% tokens by probability mass are considered. Larger values increase randomness, while smaller values increase determinism. It is generally recommended to adjust only one of temperature or top_p, not both. |
logprobs | boolean | No | true | > Models with deep thinking capabilities do not support this field. Whether to return log probabilities of output tokens:
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top_logprobs | integer | No | 10 | > Models with deep thinking capabilities do not support this field. Value range: [0, 20]. Specifies the number of most likely tokens to return at each output token position, each associated with a log probability. The top_logprobs parameter can be set only when logprobs is true. |
logit_bias | map[str,int] | No | > Models with deep thinking capabilities do not support this field. Adjusts the probability that specified tokens appear in the model output, making the generated content better align with specific preferences. The logit_bias field accepts a map where each key is a token ID in the vocabulary (obtained by using the tokenization interface), and each value is the bias value for that token. Value range: [-100, 100]. -1 reduces the likelihood of selection, 1 increases the likelihood, -100 completely prohibits selecting the token, and 100 makes only that token selectable. The actual effect may vary by model. | |
thinking | request_thinking | No | Controls whether deep thinking mode is enabled for the model. Deep thinking mode is enabled by default and can be manually disabled. For usage of this field, refer to the thinking parameter in the request body of the Chat API. | |
response_format | request_response_format | No | The model output content must follow the format specified here. For usage of this field, refer to the response_format parameter in the request body of the Chat API. | |
tools | list of chat_tool | No | List of tools to be called, which may be included in the model response. Configure this structure when you need the model to return tools to be called. For usage of this field, refer to the tools parameter in the request body of the Chat API. | |
tool_choice | string or object | No | > Only doubao-seed-1-6-* and later-generation models support this field.Specifies whether the model response for this request contains tools to be called. When no tools are specified, none is the default value. If tools exist, auto is the default value.Tool selection mode (string)
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Parameter name | Type | Example | Description |
|---|---|---|---|
id | string | 0217426318107460cfa43dc3f3683b1de1c09624ff49085a456ac | Unique identifier of this request. |
model | string | Name and version of the model actually used for this request. | |
created | integer | Unix timestamp, in seconds, when this request was created. | |
object | string | chat.completion | Fixed as chat.completion. |
choices | list of choice | Model output content for this request. | |
usage | usage | Token usage for this request. | |
las_extra_result | las_extra_result | Additional operator-specific return attributes. |
curl --location "https://operator.las.ap-southeast-1.volces.com/api/v1/chat/completions" \ --header "Content-Type: application/json" \ --header "Authorization: Bearer $LAS_API_KEY" \ --data '{ "operator_id": "las_vlm_video", "operator_version": "v1", "data": { "las_extra_params": { "operator_id": "las_vlm_video", "operator_version": "v1" }, "model_name":"doubao-seed-1-8-251228", "messages": [ { "content": [ { "video_url": { "url": "https://las-ai-cn-beijing-baseline.tos-cn-beijing.volces.com/operator_cards_serving/public/baseline/las_vlm_video/v1/eating_56.mp4" }, "type": "video_url" }, { "text": "", "type": "text" } ], "role": "user" } ] } }'
{ "metadata": { "task_status": "COMPLETED", "business_code": "0", "error_msg": "", "request_id": "7517a8d9fa003a570777e2a390977f73" }, "data": { "vlm_result": { "id": "0217610362616819fc4dc47d27ebf7239e22958e08dac0b3c4dd9", "object": "chat.completion", "created": 1761036294, "model": "doubao-seed-1.8", "serviceTier": "default", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "The video unfolds with a brightly colored two-layer cake as the core, and the overall atmosphere is fantastical and with a sense of humor. Here is the specific analysis:\ n\ n\ n ###** 1. Scene and object details **\ n- ** Main cake **: The bottom layer is dark red, and the surface is covered with smooth red frosting; the top layer is light yellow, decorated with red wavy stripes, and the top is covered with thick red frosting. The frosting is stacked with beige cream flowers, and the top of the cream is inserted with a red cherry. The bottom edge of the cake is decorated with yellow stars, and the overall shape is exquisite and inviting.\ n- ** Background Environment **: The background is a blue carved window. The window frame lines are smooth, and the dark purple light is revealed, creating a mysterious atmosphere. The visible part on the left is a red bookshelf, with faint outlines of books; on the right hangs a painting of a hand holding a blue magic wand with pink stars twinkling at the end, suggesting that the scene may be related to "magic".\ n\ n ###** 2. Core characters and dynamics **\ n The key twist in the video is the green creature that suddenly appears at the top of the cake:\ n- ** Initial state **: The creature "emerges" from the cream of the top cake, initially showing only its head, eyes closed, mouth raised, revealing two sharp teeth, with a sly complacent expression (as if snickering or planning something). \ n- ** Expression Change **: Then the creature suddenly opens its eyes, the eyeballs instantly become big and round (highlighting surprise or excitement), the mouth opens, revealing more fangs, and the smile is exaggerated, changing from "sly" to "ecstasy" or "surprise", as if it has just finished a prank or discovered something interesting.\ n- ** Interactive Details **: When the creature appears, the cream flower is slightly pushed up but not scattered, and the red cherry at the top remains in place, suggesting that the creature is "drilled" from the inside of the cream, with light and fantastical movements.\ n\ n ###** 3. Ambience and underlying narrative **\ n- ** Fantastic tone **: The magic wand hanging on the right echoes the sudden appearance of the creature, suggesting that there may be a magical element in the scene - the cake may be enchanted, or the creature itself has magical powers that can be hidden in the food.\ n- ** Humor and mischievousness **: The expression of the green creature ranges from "bad laugh" to "exaggerated excitement", and the character image is mischievous and intelligent, contrasting with the delicate cake (the "sweetness" of the cake and the "cunning" of the creature), creating a relaxed and humorous atmosphere, possibly in the moment of a mischievous character's "surprise appearance". The video builds a short and vivid scene through vibrant color contrasts (red, yellow cakes and green creatures), fantastical elements (magic paintings, creatures that suddenly appear), and quick changes in the characters' expressions (sly → ecstatic): a mischievous green creature hidden in a cake suddenly appears in a magical environment, with the excitement of a successful mischief, and the overall delivery is relaxed and fantastical fun.", "reasoning_content": "\ nThe user now needs me to analyze this video. First, I need to look carefully at the video content and describe all the elements I see. The video starts with a two-layer cake with a red bottom layer and a yellow top layer with red wavy stripes, topped with cream and cherries. The background is a blue window with a bookshelf on the left and a painting on the right with a magic wand and stars.\ n\ nThen, a green creature suddenly appears from the cream on the top of the cake. At first, it closes its eyes and shows a bad smile. Then the eyes open and become very large. The mouth opens and shows teeth. The expression changes from complacency to surprise or excitement? Need to pay attention to the process of biological change. \ n\ nNext, to analyze the atmosphere of the scene, the blue windows and bookshelves may be in a room, and the magic wand painting on the right may suggest that there are magic elements. The cake looks very tempting, and the green creature appears from the cake. It may appear suddenly, with a feeling of surprise or mischief.\ n\ nThe expression of the creature changes: first close the eyes and smile, then open the eyes, the eyes become larger, the mouth is open, and the teeth are exposed. It may be that you find yourself on the cake, or the reaction to the surrounding environment. You need to pay attention to details, such as the state of the cream, whether the cream changes when the creature appears, such as being pushed up.\ n\ nAlso consider the chronological order. The video is very short, about 3 seconds. The action ranges from static cake to creature appearance to expression change. The possible intention is to show a character who has suddenly appeared, with a humorous or fantastical color, because there is a background of magic painting, which may be related to magic, and the creature may have appeared through magic?\ n\ nSummary elements: cake (red bottom layer, yellow top layer, red frosting, cream, cherry), background (blue window, bookshelf, magic painting), green creature (expression change: closed eyes smirk → open eyes surprise/excitement), action (creature emerges from the top of the cake).\ n\ nPossible scene setting: a room with magic, the cake may be enchanted, or the creature is hidden in the cake and suddenly appears. The green of the creature contrasts with the bright color of the cake, highlighting the character. \ n\ nNeed to confirm if there are other details, such as the yellow decoration on the bottom of the cake, possibly stars or petals? There is a yellow shape on the bottom of the cake at the beginning of the video, which may be decoration. When the creature appears, the cherry on the top is still there, and the cream is jacked up, but the cherry is not dropped, indicating that the creature is drilled out of the cream.\ n\ nKey to the change of expression: When the eyes are closed, the corners of the mouth are raised, there is a smug smile, and it may be planning something; After opening the eyes, the eyes are round, the mouth is open, and the teeth are exposed. It may be surprised by their successful appearance, or the reaction after seeing the surrounding environment, they appear more lively.\ n\ nOverall atmosphere: Fantasy, humorous, with a little naughty feeling, because the creature's expression ranges from bad laugh to excitement, and may be a naugh" }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 4903, "completion_tokens": 1133, "total_tokens": 6036, "prompt_tokens_details": { "cached_tokens": 0 }, "completion_tokens_details": { "reasoning_tokens": 554 } } }, "compress_result": [ { "video_url": "https://las-ai-cn-beijing-baseline.tos-cn-beijing.volces.com/operator_cards_serving/public/qa/las_vlm_video/v1/eating_56.mp4", "compression_details": { "original_info": { "original_path": "https://las-ai-cn-beijing-baseline.tos-cn-beijing.volces.com/operator_cards_serving/public/qa/las_vlm_video/v1/eating_56.mp4", "original_size_mb": 0.35, "original_width": 640, "original_height": 360, "original_fps": 25, "original_duration": 2.9, "original_format": "mp4" }, "compression_process": { "step_0_format_conversion": { "executed": false }, "step_1_fps_reduction": { "executed": false }, "step_2_resolution_reduction": { "executed": false }, "step_3_bitrate_compression": { "executed": false } }, "final_result": { "final_width": 640, "final_height": 360, "final_fps": 25, "final_duration": 2.9, "final_size_mb": 0.35, "final_format": "mp4" }, "timing_info": { "total_processing_time_seconds": 0.23 } } } ] } }
HttpCode | Error code | Error message | Description |
|---|---|---|---|
401 | Authorization.Missing | Missing Authorization. | Authentication missing |
401 | ApiKey.Invalid | The api key is invalid. | API key is invalid |
400 | Url.Invalid | The url is invalid. | Video URL is invalid |