{ "version_module": true, "baseUrl": "https://firebaseml.googleapis.com/", "id": "firebaseml:v2beta", "rootUrl": "https://firebaseml.googleapis.com/", "servicePath": "", "basePath": "", "description": "Access custom machine learning models hosted via Firebase ML.", "fullyEncodeReservedExpansion": true, "documentationLink": "https://firebase.google.com", "revision": "20260809", "schemas": { "GoogleCloudAiplatformV1beta1EnterpriseWebSearch": { "type": "object", "properties": { "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.", "items": { "type": "string" }, "type": "array" }, "blockingConfidence": { "type": "string", "enum": [ "PHISH_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_HIGH_AND_ABOVE", "BLOCK_HIGHER_AND_ABOVE", "BLOCK_VERY_HIGH_AND_ABOVE", "BLOCK_ONLY_EXTREMELY_HIGH" ], "enumDescriptions": [ "Defaults to unspecified.", "Blocks Low and above confidence URL that is risky.", "Blocks Medium and above confidence URL that is risky.", "Blocks High and above confidence URL that is risky.", "Blocks Higher and above confidence URL that is risky.", "Blocks Very high and above confidence URL that is risky.", "Blocks Extremely high confidence URL that is risky." ], "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results." } }, "id": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch", "description": "Tool to search public web data, powered by Vertex AI Search and Sec4 compliance." }, "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams": { "description": "The search parameters to use for the ELASTIC_SEARCH spec.", "type": "object", "properties": { "index": { "description": "The ElasticSearch index to use.", "type": "string" }, "searchTemplate": { "description": "The ElasticSearch search template to use.", "type": "string" }, "numHits": { "description": "Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams" }, "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig", "type": "object", "properties": { "mode": { "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ], "type": "string", "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ], "description": "The mode of the predictor to be used in dynamic retrieval." }, "dynamicThreshold": { "description": "Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.", "format": "float", "type": "number" } }, "description": "Describes the options to customize dynamic retrieval." }, "GoogleCloudAiplatformV1beta1GenerationConfig": { "description": "Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output.", "type": "object", "properties": { "temperature": { "description": "Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].", "format": "float", "type": "number" }, "seed": { "type": "integer", "description": "Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the \"random\" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.", "format": "int32" }, "mediaResolution": { "type": "string", "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ], "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low (64 tokens).", "Media resolution set to medium (256 tokens).", "Media resolution set to high (zoomed reframing with 256 tokens)." ], "description": "Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model." }, "topP": { "type": "number", "description": "Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.", "format": "float" }, "routingConfig": { "description": "Optional. Routing configuration.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig" }, "responseSchema": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1Schema", "description": "Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead." }, "thinkingConfig": { "description": "Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig" }, "frequencyPenalty": { "description": "Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].", "format": "float", "type": "number" }, "responseFormat": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ResponseFormat" }, "description": "Optional. New response format field for the model to configure output formatting and delivery." }, "responseLogprobs": { "description": "Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.", "type": "boolean" }, "responseMimeType": { "type": "string", "deprecated": true, "description": "Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead." }, "imageConfig": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1ImageConfig", "description": "Optional. Config for image generation features. Deprecated: Use `response_format.image` instead." }, "speechConfig": { "description": "Optional. The speech generation config.", "$ref": "GoogleCloudAiplatformV1beta1SpeechConfig" }, "responseJsonSchema": { "description": "Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.", "deprecated": true, "type": "any" }, "stopSequences": { "description": "Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use [\"\\n\", \"###\"] to stop generation at a new line or a specific marker.", "type": "array", "items": { "type": "string" } }, "topK": { "description": "Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.", "format": "float", "type": "number" }, "responseModalities": { "type": "array", "items": { "enumDescriptions": [ "Unspecified modality. Will be processed as text.", "Text modality.", "Image modality.", "Audio modality.", "Video modality." ], "type": "string", "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO", "VIDEO" ] }, "description": "Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image." }, "maxOutputTokens": { "description": "Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.", "format": "int32", "type": "integer" }, "enableAffectiveDialog": { "description": "Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.", "type": "boolean" }, "audioTimestamp": { "description": "Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.", "type": "boolean" }, "audioTranscriptionConfig": { "description": "Optional. Configuration for audio transcription (speech recognition).", "$ref": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfig" }, "presencePenalty": { "description": "Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].", "format": "float", "type": "number" }, "logprobs": { "type": "integer", "description": "Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.", "format": "int32" }, "modelConfig": { "description": "Optional. Config for model selection.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig" }, "candidateCount": { "description": "Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "GoogleCloudAiplatformV1beta1PartialArg": { "description": "Partial argument value of the function call.", "id": "GoogleCloudAiplatformV1beta1PartialArg", "type": "object", "properties": { "jsonPath": { "description": "Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. \"$.foo.bar[0].data\".", "type": "string" }, "numberValue": { "description": "Optional. Represents a double value.", "format": "double", "type": "number" }, "stringValue": { "description": "Optional. Represents a string value.", "type": "string" }, "willContinue": { "description": "Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.", "type": "boolean" }, "nullValue": { "description": "Optional. Represents a null value.", "type": "string", "enum": [ "NULL_VALUE" ], "enumDescriptions": [ "Null value." ] }, "boolValue": { "description": "Optional. Represents a boolean value.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec": { "description": "Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec", "type": "object", "properties": { "filter": { "description": "Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)", "type": "string" }, "dataStore": { "description": "Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec" }, "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams", "description": "The search parameters to use for SIMPLE_SEARCH spec." }, "GoogleCloudAiplatformV1beta1GenerateContentRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateContentRequest", "type": "object", "properties": { "safetySettings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" }, "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates." }, "cachedContent": { "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`", "type": "string" }, "modelArmorConfig": { "description": "Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied.", "$ref": "GoogleCloudAiplatformV1beta1ModelArmorConfig" }, "contents": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request." }, "toolConfig": { "description": "Optional. Tool config. This config is shared for all tools provided in the request.", "$ref": "GoogleCloudAiplatformV1beta1ToolConfig" }, "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "generationConfig": { "description": "Optional. Generation config.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" }, "tools": { "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "type": "array", "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model." }, "labels": { "type": "object", "additionalProperties": { "type": "string" }, "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter." } }, "description": "Request message for [PredictionService.GenerateContent]." }, "GoogleCloudAiplatformV1beta1CountTokensResponse": { "description": "Response message for PredictionService.CountTokens.", "id": "GoogleCloudAiplatformV1beta1CountTokensResponse", "type": "object", "properties": { "totalTokens": { "description": "The total number of tokens counted across all instances from the request.", "format": "int32", "type": "integer" }, "totalBillableCharacters": { "description": "The total number of billable characters counted across all instances from the request.", "format": "int32", "type": "integer" }, "promptTokensDetails": { "readOnly": true, "description": "Output only. List of modalities that were processed in the request input.", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "type": "array" } } }, "GoogleCloudAiplatformV1beta1FileData": { "type": "object", "properties": { "fileUri": { "description": "Required. The URI of the file in Google Cloud Storage.", "type": "string" }, "displayName": { "description": "Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FileData", "description": "URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage." }, "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri": { "type": "object", "properties": { "sourceId": { "description": "The ID of the place or review.", "type": "string" }, "flagContentUri": { "description": "The URI that can be used to flag the content.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri", "description": "A URI that can be used to flag a place or review for inappropriate content. This is populated only when the grounding source is Google Maps." }, "GoogleCloudAiplatformV1beta1ImageResponseFormat": { "type": "object", "properties": { "aspectRatio": { "description": "Optional. The aspect ratio for the image output.", "type": "string", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_ONE_BY_ONE", "ASPECT_RATIO_TWO_BY_THREE", "ASPECT_RATIO_THREE_BY_TWO", "ASPECT_RATIO_THREE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_THREE", "ASPECT_RATIO_FOUR_BY_FIVE", "ASPECT_RATIO_FIVE_BY_FOUR", "ASPECT_RATIO_NINE_BY_SIXTEEN", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_TWENTY_ONE_BY_NINE", "ASPECT_RATIO_ONE_BY_EIGHT", "ASPECT_RATIO_EIGHT_BY_ONE", "ASPECT_RATIO_ONE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_ONE" ], "enumDescriptions": [ "Default value. This value is unused.", "1:1 aspect ratio.", "2:3 aspect ratio.", "3:2 aspect ratio.", "3:4 aspect ratio.", "4:3 aspect ratio.", "4:5 aspect ratio.", "5:4 aspect ratio.", "9:16 aspect ratio.", "16:9 aspect ratio.", "21:9 aspect ratio.", "1:8 aspect ratio.", "8:1 aspect ratio.", "1:4 aspect ratio.", "4:1 aspect ratio." ] }, "mimeType": { "description": "Optional. The MIME type of the image output.", "type": "string", "enum": [ "MIME_TYPE_UNSPECIFIED", "IMAGE_JPEG" ], "enumDescriptions": [ "Default value. This value is unused.", "JPEG image format." ] }, "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ], "type": "string", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "Optional. Delivery mode for the generated content." }, "imageSize": { "type": "string", "enum": [ "IMAGE_SIZE_UNSPECIFIED", "IMAGE_SIZE_FIVE_TWELVE", "IMAGE_SIZE_ONE_K", "IMAGE_SIZE_TWO_K", "IMAGE_SIZE_FOUR_K" ], "enumDescriptions": [ "Default value. This value is unused.", "512px image size.", "1K image size.", "2K image size.", "4K image size." ], "description": "Optional. The size of the image output." } }, "id": "GoogleCloudAiplatformV1beta1ImageResponseFormat", "description": "Configuration for image-specific output formatting." }, "GoogleCloudAiplatformV1beta1GroundingChunkImage": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkImage", "type": "object", "properties": { "imageUri": { "description": "The URI of the image.", "type": "string" }, "title": { "description": "The title of the image search result page.", "type": "string" }, "domain": { "description": "The domain of the image search result page.", "type": "string" }, "sourceUri": { "description": "The URI of the image search result page.", "type": "string" } }, "description": "An `Image` chunk is a piece of evidence that comes from an image search result. It contains the URI of the image search result and the URI of the image. This is used to provide the user with a link to the source of the information." }, "GoogleCloudAiplatformV1beta1GroundingChunkMaps": { "description": "A `Maps` chunk is a piece of evidence that comes from Google Maps, containing information about places or routes. This is used to provide the user with rich, location-based information.", "type": "object", "properties": { "placeAnswerSources": { "description": "The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources" }, "text": { "description": "The text of the place answer.", "type": "string" }, "title": { "description": "The title of the place.", "type": "string" }, "placeId": { "description": "This Place's resource name, in `places/{place_id}` format. This can be used to look up the place in the Google Maps API.", "type": "string" }, "route": { "readOnly": true, "description": "Output only. Route information.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute" }, "uri": { "description": "The URI of the place.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkMaps" }, "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig": { "description": "The configuration for the replicated voice to use.", "id": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig", "type": "object", "properties": { "mimeType": { "description": "Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.", "type": "string" }, "voiceSampleAudio": { "type": "string", "description": "Optional. The sample of the custom voice.", "format": "byte" } } }, "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", "type": "object", "properties": { "serviceAccount": { "description": "Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.", "type": "string" } }, "description": "Config for Google Service Account Authentication." }, "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig": { "description": "Config for user oauth.", "type": "object", "properties": { "serviceAccount": { "description": "The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.", "type": "string" }, "accessToken": { "description": "Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig" }, "GoogleCloudAiplatformV1beta1ImageConfig": { "id": "GoogleCloudAiplatformV1beta1ImageConfig", "type": "object", "properties": { "imageSize": { "description": "Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.", "type": "string" }, "prominentPeople": { "enumDescriptions": [ "Unspecified value. The model will proceed with the default behavior, which is to allow generation of prominent people.", "Allows the model to generate images of prominent people.", "Prevents the model from generating images of prominent people." ], "type": "string", "enum": [ "PROMINENT_PEOPLE_UNSPECIFIED", "ALLOW_PROMINENT_PEOPLE", "BLOCK_PROMINENT_PEOPLE" ], "description": "Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people." }, "aspectRatio": { "description": "Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: \"1:1\" \"2:3\", \"3:2\" \"3:4\", \"4:3\" \"4:5\", \"5:4\" \"9:16\", \"16:9\" \"21:9\"", "type": "string" }, "imageOutputOptions": { "description": "Optional. The image output format for generated images.", "$ref": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions" }, "personGeneration": { "type": "string", "enum": [ "PERSON_GENERATION_UNSPECIFIED", "ALLOW_ALL", "ALLOW_ADULT", "ALLOW_NONE" ], "enumDescriptions": [ "The default behavior is unspecified. The model will decide whether to generate images of people.", "Allows the model to generate images of people, including adults and children.", "Allows the model to generate images of adults, but not children.", "Prevents the model from generating images of people." ], "description": "Optional. Controls whether the model can generate people." } }, "description": "Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people." }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet", "type": "object", "properties": { "googleMapsUri": { "description": "A link to show the review on Google Maps.", "type": "string" }, "reviewId": { "description": "The ID of the review that is being referenced.", "type": "string" }, "title": { "description": "The title of the review.", "type": "string" } }, "description": "A review snippet that is used to generate the answer." }, "GoogleCloudAiplatformV1beta1VertexAISearch": { "description": "Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder", "id": "GoogleCloudAiplatformV1beta1VertexAISearch", "type": "object", "properties": { "engine": { "description": "Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`", "type": "string" }, "dataStoreSpecs": { "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec" }, "type": "array", "description": "Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used." }, "filter": { "description": "Optional. Filter strings to be passed to the search API.", "type": "string" }, "datastore": { "description": "Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" }, "maxResults": { "description": "Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes", "type": "object", "properties": { "webSearch": { "description": "Optional. Setting this field enables web search. Only text results are returned.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch" }, "imageSearch": { "description": "Optional. Setting this field enables image search. Image bytes are returned.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch" } }, "description": "Different types of search that can be enabled on the GoogleSearch tool." }, "GoogleCloudAiplatformV1beta1LogprobsResultCandidate": { "id": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate", "type": "object", "properties": { "token": { "description": "The token's string representation.", "type": "string" }, "tokenId": { "type": "integer", "description": "The token's numerical ID. While the `token` field provides the string representation of the token, the `token_id` is the numerical representation that the model uses internally. This can be useful for developers who want to build custom logic based on the model's vocabulary.", "format": "int32" }, "logProbability": { "description": "The log probability of this token. A higher value indicates that the model was more confident in this token. The log probability can be used to assess the relative likelihood of different tokens and to identify when the model is uncertain.", "format": "float", "type": "number" } }, "description": "A single token and its associated log probability." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfig", "type": "object", "properties": { "topK": { "description": "Optional. The number of contexts to retrieve.", "format": "int32", "type": "integer" }, "ranking": { "description": "Optional. Config for ranking and reranking.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking" }, "hybridSearch": { "description": "Optional. Config for Hybrid Search.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch" }, "filter": { "description": "Optional. Config for filters.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter" } }, "description": "Specifies the context retrieval config." }, "GoogleCloudAiplatformV1beta1Retrieval": { "description": "Defines a retrieval tool that model can call to access external knowledge.", "id": "GoogleCloudAiplatformV1beta1Retrieval", "type": "object", "properties": { "vertexRagStore": { "description": "Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.", "$ref": "GoogleCloudAiplatformV1beta1VertexRagStore" }, "disableAttribution": { "type": "boolean", "deprecated": true, "description": "Optional. Deprecated. This option is no longer supported." }, "vertexAiSearch": { "description": "Set to use data source powered by Vertex AI Search.", "$ref": "GoogleCloudAiplatformV1beta1VertexAISearch" }, "externalApi": { "description": "Use data source powered by external API for grounding.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApi" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking": { "type": "object", "properties": { "rankService": { "description": "Optional. Config for Rank Service.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService" }, "llmRanker": { "description": "Optional. Config for LlmRanker.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker" } }, "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking", "description": "Config for ranking and reranking." }, "GoogleCloudAiplatformV1beta1CitationMetadata": { "description": "A collection of citations that apply to a piece of generated content.", "type": "object", "properties": { "citations": { "readOnly": true, "description": "Output only. A list of citations for the content.", "items": { "$ref": "GoogleCloudAiplatformV1beta1Citation" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1beta1CitationMetadata" }, "GoogleCloudAiplatformV1beta1TextResponseFormat": { "description": "Configuration for text-specific output formatting.", "id": "GoogleCloudAiplatformV1beta1TextResponseFormat", "type": "object", "properties": { "mimeType": { "enumDescriptions": [ "Default value. This value is unused.", "JSON output format.", "Plain text output format." ], "type": "string", "enum": [ "MIME_TYPE_UNSPECIFIED", "APPLICATION_JSON", "TEXT_PLAIN" ], "description": "Optional. The IANA standard MIME type of the response." }, "schema": { "description": "Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.", "type": "any" } } }, "GoogleCloudAiplatformV1beta1Blob": { "id": "GoogleCloudAiplatformV1beta1Blob", "type": "object", "properties": { "data": { "type": "string", "description": "Required. The raw bytes of the data.", "format": "byte" }, "displayName": { "description": "Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" } }, "description": "A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video." }, "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions": { "id": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions", "type": "object", "properties": { "mimeType": { "description": "Optional. The image format that the output should be saved as.", "type": "string" }, "compressionQuality": { "type": "integer", "description": "Optional. The compression quality of the output image.", "format": "int32" } }, "description": "The image output format for generated images." }, "GoogleCloudAiplatformV1beta1GroundingSupport": { "description": "A collection of supporting references for a segment or part of the model's response.", "type": "object", "properties": { "confidenceScores": { "description": "The confidence scores for the support references. This list is parallel to the `grounding_chunk_indices` list. A score is a value between 0.0 and 1.0, with a higher score indicating a higher confidence that the reference supports the claim. For Gemini 2.0 and before, this list has the same size as `grounding_chunk_indices`. For Gemini 2.5 and later, this list is empty and should be ignored.", "type": "array", "items": { "type": "number", "format": "float" } }, "groundingChunkIndices": { "description": "A list of indices into the `grounding_chunks` field of the `GroundingMetadata` message. These indices specify which grounding chunks support the claim made in the content segment. For example, if this field has the values `[1, 3]`, it means that `grounding_chunks[1]` and `grounding_chunks[3]` are the sources for the claim in the content segment.", "items": { "type": "integer", "format": "int32" }, "type": "array" }, "renderedParts": { "description": "Indices into the `rendered_parts` field of the `GroundingMetadata` message. These indices specify which rendered parts are associated with this support message.", "type": "array", "items": { "type": "integer", "format": "int32" } }, "segment": { "description": "The content segment that this support message applies to.", "$ref": "GoogleCloudAiplatformV1beta1Segment" } }, "id": "GoogleCloudAiplatformV1beta1GroundingSupport" }, "GoogleCloudAiplatformV1beta1SearchEntryPoint": { "id": "GoogleCloudAiplatformV1beta1SearchEntryPoint", "type": "object", "properties": { "renderedContent": { "description": "Optional. An HTML snippet that can be embedded in a web page or an application's webview. This snippet displays a search result, including the title, URL, and a brief description of the search result.", "type": "string" }, "sdkBlob": { "type": "string", "description": "Optional. A base64-encoded JSON object that contains a list of search queries and their corresponding search URLs. This information can be used to build a custom search UI.", "format": "byte" } }, "description": "An entry point for displaying Google Search results. A `SearchEntryPoint` is populated when the grounding source for a model's response is Google Search. It provides information that you can use to display the search results in your application." }, "GoogleCloudAiplatformV1beta1SafetyRating": { "description": "A safety rating for a piece of content. The safety rating contains the harm category and the harm probability level.", "id": "GoogleCloudAiplatformV1beta1SafetyRating", "type": "object", "properties": { "category": { "type": "string", "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY", "HARM_CATEGORY_IMAGE_HATE", "HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT", "HARM_CATEGORY_IMAGE_HARASSMENT", "HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT", "HARM_CATEGORY_JAILBREAK" ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "description": "Output only. The harm category of this rating.", "enumDescriptions": [ "Default value. This value is unused.", "Content that promotes violence or incites hatred against individuals or groups based on certain attributes.", "Content that promotes, facilitates, or enables dangerous activities.", "Abusive, threatening, or content intended to bully, torment, or ridicule.", "Content that contains sexually explicit material.", "Deprecated: Election filter is not longer supported. The harm category is civic integrity.", "Images that contain hate speech.", "Images that contain dangerous content.", "Images that contain harassment.", "Images that contain sexually explicit content.", "Prompts designed to bypass safety filters." ], "readOnly": true }, "severityScore": { "type": "number", "description": "Output only. The severity score of harm for this category.", "format": "float", "readOnly": true }, "blocked": { "type": "boolean", "description": "Output only. Indicates whether the content was blocked because of this rating.", "readOnly": true }, "probabilityScore": { "type": "number", "readOnly": true, "description": "Output only. The probability score of harm for this category.", "format": "float" }, "overwrittenThreshold": { "description": "Output only. The overwritten threshold for the safety category of Gemini 2.0 image out. If minors are detected in the output image, the threshold of each safety category will be overwritten if user sets a lower threshold.", "type": "string", "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "readOnly": true, "enumDescriptions": [ "The harm block threshold is unspecified.", "Block content with a low harm probability or higher.", "Block content with a medium harm probability or higher.", "Block content with a high harm probability.", "Do not block any content, regardless of its harm probability.", "Turn off the safety filter entirely." ] }, "probability": { "enumDescriptions": [ "The harm probability is unspecified.", "The harm probability is negligible.", "The harm probability is low.", "The harm probability is medium.", "The harm probability is high." ], "readOnly": true, "type": "string", "enum": [ "HARM_PROBABILITY_UNSPECIFIED", "NEGLIGIBLE", "LOW", "MEDIUM", "HIGH" ], "description": "Output only. The probability of harm for this category." }, "severity": { "description": "Output only. The severity of harm for this category.", "type": "string", "enum": [ "HARM_SEVERITY_UNSPECIFIED", "HARM_SEVERITY_NEGLIGIBLE", "HARM_SEVERITY_LOW", "HARM_SEVERITY_MEDIUM", "HARM_SEVERITY_HIGH" ], "readOnly": true, "enumDescriptions": [ "The harm severity is unspecified.", "The harm severity is negligible.", "The harm severity is low.", "The harm severity is medium.", "The harm severity is high." ] } } }, "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig": { "type": "object", "properties": { "featureSelectionPreference": { "enumDescriptions": [ "Unspecified feature selection preference.", "Prefer higher quality over lower cost.", "Balanced feature selection preference.", "Prefer lower cost over higher quality." ], "type": "string", "enum": [ "FEATURE_SELECTION_PREFERENCE_UNSPECIFIED", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ], "description": "Required. Feature selection preference." } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig", "description": "Config for model selection." }, "GoogleCloudAiplatformV1beta1GenerateContentResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateContentResponse", "type": "object", "properties": { "modelVersion": { "description": "Output only. The model version used to generate the response.", "readOnly": true, "type": "string" }, "responseId": { "readOnly": true, "description": "Output only. response_id is used to identify each response. It is the encoding of the event_id.", "type": "string" }, "promptFeedback": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback", "description": "Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations.", "readOnly": true }, "createTime": { "description": "Output only. Timestamp when the request is made to the server.", "format": "google-datetime", "readOnly": true, "type": "string" }, "usageMetadata": { "description": "Usage metadata about the response(s).", "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata" }, "candidates": { "description": "Output only. Generated candidates.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Candidate" } } }, "description": "Response message for [PredictionService.GenerateContent]." }, "GoogleCloudAiplatformV1beta1RetrievalMetadata": { "id": "GoogleCloudAiplatformV1beta1RetrievalMetadata", "type": "object", "properties": { "googleSearchDynamicRetrievalScore": { "description": "Optional. A score indicating how likely it is that a Google Search query could help answer the prompt. The score is in the range of `[0, 1]`. A score of 1 means the model is confident that a search will be helpful, and 0 means it is not. This score is populated only when Google Search grounding and dynamic retrieval are enabled. The score is used to determine whether to trigger a search.", "format": "float", "type": "number" } }, "description": "Metadata related to the retrieval grounding source. This is part of the `GroundingMetadata` returned when grounding is enabled." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter": { "type": "object", "properties": { "vectorDistanceThreshold": { "description": "Optional. Only returns contexts with vector distance smaller than the threshold.", "format": "double", "type": "number" }, "metadataFilter": { "description": "Optional. String for metadata filtering.", "type": "string" }, "vectorSimilarityThreshold": { "type": "number", "description": "Optional. Only returns contexts with vector similarity larger than the threshold.", "format": "double" } }, "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter", "description": "Config for filters." }, "GoogleCloudAiplatformV1beta1ToolComputerUse": { "description": "Tool to support computer use.", "type": "object", "properties": { "environment": { "enumDescriptions": [ "Defaults to browser.", "Operates in a web browser.", "Operates in a mobile environment.", "Operates in a desktop environment." ], "type": "string", "enum": [ "ENVIRONMENT_UNSPECIFIED", "ENVIRONMENT_BROWSER", "ENVIRONMENT_MOBILE", "ENVIRONMENT_DESKTOP" ], "description": "Required. The environment being operated." }, "excludedPredefinedFunctions": { "description": "Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.", "items": { "type": "string" }, "type": "array" }, "enablePromptInjectionDetection": { "description": "Optional. Enables the prompt injection detection check on computer-use request.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1ToolComputerUse" }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig": { "description": "The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name.", "type": "object", "properties": { "autoMode": { "description": "In this mode, the model is selected automatically based on the content of the request.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode" }, "manualMode": { "description": "In this mode, the model is specified manually.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode" } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig" }, "GoogleCloudAiplatformV1beta1SafetySetting": { "description": "A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category.", "id": "GoogleCloudAiplatformV1beta1SafetySetting", "type": "object", "properties": { "category": { "enumDescriptions": [ "Default value. This value is unused.", "Content that promotes violence or incites hatred against individuals or groups based on certain attributes.", "Content that promotes, facilitates, or enables dangerous activities.", "Abusive, threatening, or content intended to bully, torment, or ridicule.", "Content that contains sexually explicit material.", "Deprecated: Election filter is not longer supported. The harm category is civic integrity.", "Images that contain hate speech.", "Images that contain dangerous content.", "Images that contain harassment.", "Images that contain sexually explicit content.", "Prompts designed to bypass safety filters." ], "description": "Required. The harm category to be blocked.", "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "type": "string", "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_CIVIC_INTEGRITY", "HARM_CATEGORY_IMAGE_HATE", "HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT", "HARM_CATEGORY_IMAGE_HARASSMENT", "HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT", "HARM_CATEGORY_JAILBREAK" ] }, "threshold": { "description": "Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked.", "enumDescriptions": [ "The harm block threshold is unspecified.", "Block content with a low harm probability or higher.", "Block content with a medium harm probability or higher.", "Block content with a high harm probability.", "Do not block any content, regardless of its harm probability.", "Turn off the safety filter entirely." ], "type": "string", "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ] }, "method": { "description": "Optional. The method for blocking content. If not specified, the default behavior is to use the probability score.", "type": "string", "enum": [ "HARM_BLOCK_METHOD_UNSPECIFIED", "SEVERITY", "PROBABILITY" ], "enumDescriptions": [ "The harm block method is unspecified.", "The harm block method uses both probability and severity scores.", "The harm block method uses the probability score." ] } } }, "GoogleCloudAiplatformV1beta1PartMediaResolution": { "id": "GoogleCloudAiplatformV1beta1PartMediaResolution", "type": "object", "properties": { "level": { "type": "string", "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH", "MEDIA_RESOLUTION_ULTRA_HIGH" ], "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low.", "Media resolution set to medium.", "Media resolution set to high.", "Media resolution set to ultra high. This is for image only." ], "description": "The tokenization quality used for given media." } }, "description": "per part media resolution. Media resolution for the input media." }, "GoogleCloudAiplatformV1beta1VertexRagStore": { "description": "Retrieve from Vertex RAG Store for grounding.", "type": "object", "properties": { "similarityTopK": { "description": "Optional. Number of top k results to return from the selected corpora.", "format": "int32", "deprecated": true, "type": "integer" }, "storeContext": { "description": "Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.", "type": "boolean" }, "ragCorpora": { "deprecated": true, "items": { "type": "string" }, "type": "array", "description": "Optional. Deprecated. Please use rag_resources instead." }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the Rag query.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfig" }, "ragResources": { "description": "Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.", "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource" }, "type": "array" }, "vectorDistanceThreshold": { "deprecated": true, "type": "number", "description": "Optional. Only return results with vector distance smaller than the threshold.", "format": "double" } }, "id": "GoogleCloudAiplatformV1beta1VertexRagStore" }, "LatLng": { "description": "An object that represents a latitude/longitude pair. This is expressed as a pair of doubles to represent degrees latitude and degrees longitude. Unless specified otherwise, this object must conform to the WGS84 standard. Values must be within normalized ranges.", "type": "object", "properties": { "longitude": { "type": "number", "description": "The longitude in degrees. It must be in the range [-180.0, +180.0].", "format": "double" }, "latitude": { "type": "number", "description": "The latitude in degrees. It must be in the range [-90.0, +90.0].", "format": "double" } }, "id": "LatLng" }, "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig": { "description": "Config for user OIDC auth.", "id": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig", "type": "object", "properties": { "serviceAccount": { "description": "The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).", "type": "string" }, "idToken": { "description": "OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata": { "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.", "id": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata", "type": "object", "properties": { "candidatesTokenCount": { "type": "integer", "description": "The total number of tokens in the generated candidates.", "format": "int32" }, "toolUsePromptTokenCount": { "readOnly": true, "description": "Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.", "format": "int32", "type": "integer" }, "cacheTokensDetails": { "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "type": "array", "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the cached content." }, "toolUsePromptTokensDetails": { "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "promptTokensDetails": { "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "type": "array", "readOnly": true, "description": "Output only. A detailed breakdown of the token count for each modality in the prompt." }, "totalTokenCount": { "type": "integer", "description": "The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`.", "format": "int32" }, "candidatesTokensDetails": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.", "readOnly": true }, "thoughtsTokenCount": { "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "format": "int32", "readOnly": true, "type": "integer" }, "cachedContentTokenCount": { "description": "Output only. The number of tokens in the cached content that was used for this request.", "format": "int32", "readOnly": true, "type": "integer" }, "promptTokenCount": { "description": "The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content.", "format": "int32", "type": "integer" }, "trafficType": { "description": "Output only. The traffic type for this request.", "type": "string", "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "ON_DEMAND_OFFPEAK", "PROVISIONED_THROUGHPUT" ], "readOnly": true, "enumDescriptions": [ "Unspecified request traffic type.", "The request was processed using Pay-As-You-Go quota.", "Type for Priority Pay-As-You-Go traffic.", "Type for Flex traffic.", "Type for Off-Peak Pay-As-You-Go traffic.", "Type for Provisioned Throughput traffic." ] } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch", "type": "object", "properties": {}, "description": "Standard web search for grounding and related configurations. Only text results are returned." }, "GoogleCloudAiplatformV1beta1FunctionCallingConfig": { "id": "GoogleCloudAiplatformV1beta1FunctionCallingConfig", "type": "object", "properties": { "mode": { "enumDescriptions": [ "Unspecified function calling mode. This value should not be used.", "Default model behavior, model decides to predict either function calls or natural language response.", "Model is constrained to always predicting function calls only. If \"allowed_function_names\" are set, the predicted function calls will be limited to any one of \"allowed_function_names\", else the predicted function calls will be any one of the provided \"function_declarations\".", "Model will not predict any function calls. Model behavior is same as when not passing any function declarations.", "Model is constrained to predict either function calls or natural language response. If \"allowed_function_names\" are set, the predicted function calls will be limited to any one of \"allowed_function_names\", else the predicted function calls will be any one of the provided \"function_declarations\"." ], "type": "string", "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ], "description": "Optional. Function calling mode." }, "allowedFunctionNames": { "description": "Optional. Function names to call. Only set when the Mode is ANY. Function names should match FunctionDeclaration.name. With mode set to ANY, model will predict a function call from the set of function names provided.", "items": { "type": "string" }, "type": "array" }, "streamFunctionCallArguments": { "description": "Optional. When set to true, arguments of a single function call will be streamed out in multiple parts/contents/responses. Partial parameter results will be returned in the `FunctionCall.partial_args` field.", "type": "boolean" } }, "description": "Function calling config." }, "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageAuto": { "deprecated": true, "description": "Deprecated: Use top-level `language_codes` instead. Indicates the language of the audio should be automatically detected.", "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageAuto" }, "GoogleCloudAiplatformV1beta1FunctionResponse": { "id": "GoogleCloudAiplatformV1beta1FunctionResponse", "type": "object", "properties": { "response": { "description": "Required. The function response in JSON object format. Use \"output\" key to specify function output and \"error\" key to specify error details (if any). If \"output\" and \"error\" keys are not specified, then whole \"response\" is treated as function output.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parts": { "description": "Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.", "items": { "$ref": "GoogleCloudAiplatformV1beta1FunctionResponsePart" }, "type": "array" }, "id": { "description": "Optional. The id of the function call this response is for. Populated by the client to match the corresponding function call `id`.", "type": "string" }, "name": { "description": "Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.", "type": "string" }, "scheduling": { "description": "Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.", "type": "string", "enum": [ "SCHEDULING_UNSPECIFIED", "SILENT", "WHEN_IDLE", "INTERRUPT" ], "enumDescriptions": [ "This value is unused.", "Only add the result to the conversation context, do not interrupt or trigger generation.", "Add the result to the conversation context, and prompt to generate output without interrupting ongoing generation.", "Add the result to the conversation context, interrupt ongoing generation and prompt to generate output." ] } }, "description": "The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction." }, "Date": { "id": "Date", "type": "object", "properties": { "year": { "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", "format": "int32", "type": "integer" }, "month": { "type": "integer", "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.", "format": "int32" }, "day": { "type": "integer", "description": "Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn't significant.", "format": "int32" } }, "description": "Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values. * A month and day, with a zero year (for example, an anniversary). * A year on its own, with a zero month and a zero day. * A year and month, with a zero day (for example, a credit card expiration date). Related types: * google.type.TimeOfDay * google.type.DateTime * google.protobuf.Timestamp" }, "GoogleCloudAiplatformV1beta1GroundingMetadata": { "description": "Information about the sources that support the content of a response. When grounding is enabled, the model returns citations for claims in the response. This object contains the retrieved sources.", "id": "GoogleCloudAiplatformV1beta1GroundingMetadata", "type": "object", "properties": { "retrievalMetadata": { "$ref": "GoogleCloudAiplatformV1beta1RetrievalMetadata", "description": "Optional. Output only. Metadata related to the retrieval grounding source.", "readOnly": true }, "imageSearchQueries": { "description": "Optional. The image search queries that were used to generate the content. This field is populated only when the grounding source is Google Search with the Image Search search_type enabled.", "type": "array", "items": { "type": "string" } }, "retrievalQueries": { "description": "Optional. The queries that were executed by the retrieval tools. This field is populated only when the grounding source is a retrieval tool, such as Vertex AI Search.", "items": { "type": "string" }, "type": "array" }, "groundingSupports": { "description": "Optional. A list of grounding supports that connect the generated content to the grounding chunks. This field is populated when the grounding source is Google Search or Vertex AI Search.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingSupport" } }, "googleMapsWidgetContextToken": { "readOnly": true, "description": "Optional. Output only. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and will no longer be populated once removed. A token that can be used to render a Google Maps widget with the contextual data. This field is populated only when the grounding source is Google Maps.", "deprecated": true, "type": "string" }, "webSearchQueries": { "description": "Optional. The web search queries that were used to generate the content. This field is populated only when the grounding source is Google Search.", "type": "array", "items": { "type": "string" } }, "searchEntryPoint": { "description": "Optional. A web search entry point that can be used to display search results. This field is populated only when the grounding source is Google Search.", "$ref": "GoogleCloudAiplatformV1beta1SearchEntryPoint" }, "sourceFlaggingUris": { "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri" }, "type": "array", "readOnly": true, "description": "Optional. Output only. A list of URIs that can be used to flag a place or review for inappropriate content. This field is populated only when the grounding source is Google Maps." }, "groundingChunks": { "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunk" }, "type": "array", "description": "A list of supporting references retrieved from the grounding source. This field is populated when the grounding source is Google Search, Vertex AI Search, or Google Maps." } } }, "ModelOperationMetadata": { "id": "ModelOperationMetadata", "type": "object", "properties": { "name": { "description": "The name of the model we are creating/updating The name must have the form `projects/{project_id}/models/{model_id}`", "type": "string" }, "basicOperationStatus": { "enumDescriptions": [ "The status is unspecified", "The model file is being uploaded", "The model file is being verified" ], "type": "string", "enum": [ "BASIC_OPERATION_STATUS_UNSPECIFIED", "BASIC_OPERATION_STATUS_UPLOADING", "BASIC_OPERATION_STATUS_VERIFYING" ] } }, "description": "This is returned in the longrunning operations for create/update." }, "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig", "type": "object", "properties": { "voiceName": { "description": "The name of the prebuilt voice to use.", "type": "string" } }, "description": "Configuration for a prebuilt voice." }, "GoogleCloudAiplatformV1beta1AudioTranscriptionConfig": { "type": "object", "properties": { "languageCodes": { "items": { "type": "string" }, "type": "array", "description": "Optional. BCP-47 language codes providing hints about the languages present in the audio. If omitted or empty, defaults to automatic language detection." }, "adaptationPhrases": { "description": "Optional. Deprecated: Use `custom_vocabulary` instead. A list of phrases to bias the speech recognition model towards.", "deprecated": true, "items": { "type": "string" }, "type": "array" }, "wordTimestamp": { "description": "Optional. Configures word-level timestamp generation.", "type": "boolean" }, "customVocabulary": { "description": "Optional. A list of custom vocabulary phrases to bias the speech recognition model toward recognizing specific terms.", "items": { "type": "string" }, "type": "array" }, "diarization": { "description": "Optional. Configures speaker diarization.", "type": "boolean" }, "languageHints": { "$ref": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageHints", "deprecated": true, "description": "Optional. Deprecated: Use top-level `language_codes` instead. Specifies one or more languages in the audio." }, "languageAuto": { "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageAuto", "description": "Optional. Deprecated: Use top-level `language_codes` instead. The model will detect the language automatically." } }, "id": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfig", "description": "Configuration for speech recognition (transcription)." }, "GoogleCloudAiplatformV1beta1RagChunk": { "id": "GoogleCloudAiplatformV1beta1RagChunk", "type": "object", "properties": { "text": { "description": "The content of the chunk.", "type": "string" }, "pageSpan": { "description": "If populated, represents where the chunk starts and ends in the document.", "$ref": "GoogleCloudAiplatformV1beta1RagChunkPageSpan" }, "chunkId": { "description": "The ID of the chunk.", "type": "string" }, "fileId": { "description": "The ID of the file that the chunk belongs to.", "type": "string" } }, "description": "A RagChunk includes the content of a chunk of a RagFile, and associated metadata." }, "GoogleCloudAiplatformV1beta1SpeechConfig": { "id": "GoogleCloudAiplatformV1beta1SpeechConfig", "type": "object", "properties": { "multiSpeakerVoiceConfig": { "description": "The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.", "$ref": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig" }, "languageCode": { "description": "Optional. The language code (ISO 639-1) for the speech synthesis.", "type": "string" }, "voiceConfig": { "description": "The configuration for the voice to use.", "$ref": "GoogleCloudAiplatformV1beta1VoiceConfig" } }, "description": "Configuration for speech generation." }, "GoogleCloudAiplatformV1beta1Candidate": { "description": "A response candidate generated from the model.", "type": "object", "properties": { "citationMetadata": { "$ref": "GoogleCloudAiplatformV1beta1CitationMetadata", "readOnly": true, "description": "Output only. A collection of citations that apply to the generated content." }, "index": { "description": "Output only. The 0-based index of this candidate in the list of generated responses. This is useful for distinguishing between multiple candidates when `candidate_count` \u003e 1.", "format": "int32", "readOnly": true, "type": "integer" }, "avgLogprobs": { "readOnly": true, "description": "Output only. The average log probability of the tokens in this candidate. This is a length-normalized score that can be used to compare the quality of candidates of different lengths. A higher average log probability suggests a more confident and coherent response.", "format": "double", "type": "number" }, "groundingMetadata": { "readOnly": true, "description": "Output only. Metadata returned when grounding is enabled. It contains the sources used to ground the generated content.", "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadata" }, "urlContextMetadata": { "$ref": "GoogleCloudAiplatformV1beta1UrlContextMetadata", "readOnly": true, "description": "Output only. Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL." }, "content": { "$ref": "GoogleCloudAiplatformV1beta1Content", "description": "Output only. The content of the candidate.", "readOnly": true }, "finishReason": { "readOnly": true, "enumDescriptions": [ "The finish reason is unspecified.", "The model reached a natural stopping point or a configured stop sequence.", "The model generated the maximum number of tokens allowed by the `max_output_tokens` parameter.", "The model stopped generating because the content potentially violates safety policies. NOTE: When streaming, the `content` field is empty if content filters block the output.", "The model stopped generating because the content may be a recitation from a source.", "The model stopped generating for a reason not otherwise specified.", "The model stopped generating because the content contains a term from a configured blocklist.", "The model stopped generating because the content may be prohibited.", "The model stopped generating because the content may contain sensitive personally identifiable information (SPII).", "The model generated a function call that is syntactically invalid and can't be parsed.", "The model response was blocked by Model Armor.", "The generated image potentially violates safety policies.", "The generated image may contain prohibited content.", "The generated image may be a recitation from a source.", "The image generation stopped for a reason not otherwise specified.", "The model generated a function call that is semantically invalid. This can happen, for example, if function calling is not enabled or the generated function is not in the function declaration.", "The model was expected to generate an image, but didn't." ], "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating.", "type": "string", "enum": [ "FINISH_REASON_UNSPECIFIED", "STOP", "MAX_TOKENS", "SAFETY", "RECITATION", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "SPII", "MALFORMED_FUNCTION_CALL", "MODEL_ARMOR", "IMAGE_SAFETY", "IMAGE_PROHIBITED_CONTENT", "IMAGE_RECITATION", "IMAGE_OTHER", "UNEXPECTED_TOOL_CALL", "NO_IMAGE" ] }, "safetyRatings": { "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" }, "type": "array", "readOnly": true, "description": "Output only. A list of ratings for the safety of a response candidate. There is at most one rating per category." }, "finishMessage": { "description": "Output only. Describes the reason the model stopped generating tokens in more detail. This field is returned only when `finish_reason` is set.", "readOnly": true, "type": "string" }, "logprobsResult": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResult", "description": "Output only. The detailed log probability information for the tokens in this candidate. This is useful for debugging, understanding model uncertainty, and identifying potential \"hallucinations\".", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1Candidate" }, "GoogleCloudAiplatformV1beta1Schema": { "id": "GoogleCloudAiplatformV1beta1Schema", "type": "object", "properties": { "example": { "description": "Optional. Example of an instance of this schema.", "type": "any" }, "title": { "description": "Optional. Title for the schema.", "type": "string" }, "minLength": { "type": "string", "description": "Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.", "format": "int64" }, "minItems": { "type": "string", "description": "Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.", "format": "int64" }, "additionalProperties": { "description": "Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.", "type": "any" }, "minProperties": { "description": "Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.", "format": "int64", "type": "string" }, "default": { "description": "Optional. Default value to use if the field is not specified.", "type": "any" }, "maximum": { "type": "number", "description": "Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.", "format": "double" }, "ref": { "description": "Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named \"Pet\": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the \"pet\" property is a reference to the schema node named \"Pet\". See details in https://json-schema.org/understanding-json-schema/structuring", "type": "string" }, "items": { "description": "Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "propertyOrdering": { "description": "Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.", "items": { "type": "string" }, "type": "array" }, "enum": { "description": "Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:[\"EAST\", \"NORTH\", \"SOUTH\", \"WEST\"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:[\"101\", \"201\", \"301\"]}`", "type": "array", "items": { "type": "string" } }, "format": { "description": "Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.", "type": "string" }, "required": { "description": "Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.", "type": "array", "items": { "type": "string" } }, "anyOf": { "description": "Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.", "items": { "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "type": "array" }, "pattern": { "description": "Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.", "type": "string" }, "type": { "enumDescriptions": [ "Not specified, should not be used.", "OpenAPI string type", "OpenAPI number type", "OpenAPI integer type", "OpenAPI boolean type", "OpenAPI array type", "OpenAPI object type", "Null type" ], "type": "string", "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ], "description": "Optional. Data type of the schema field." }, "nullable": { "description": "Optional. Indicates if the value of this field can be null.", "type": "boolean" }, "maxItems": { "description": "Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.", "format": "int64", "type": "string" }, "properties": { "description": "Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" } }, "maxLength": { "type": "string", "description": "Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.", "format": "int64" }, "minimum": { "type": "number", "description": "Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.", "format": "double" }, "maxProperties": { "description": "Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.", "format": "int64", "type": "string" }, "defs": { "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "description": "Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema." }, "description": { "description": "Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.", "type": "string" } }, "description": "Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object)." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService": { "type": "object", "properties": { "modelName": { "description": "Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService", "description": "Config for Rank Service." }, "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig": { "description": "Config for authentication with API key.", "id": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig", "type": "object", "properties": { "apiKeySecret": { "description": "Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" }, "apiKeyString": { "description": "Optional. The API key to be used in the request directly.", "type": "string" }, "httpElementLocation": { "description": "Optional. The location of the API key.", "enumDescriptions": [ "", "Element is in the HTTP request query.", "Element is in the HTTP request header.", "Element is in the HTTP request path.", "Element is in the HTTP request body.", "Element is in the HTTP request cookie." ], "type": "string", "enum": [ "HTTP_IN_UNSPECIFIED", "HTTP_IN_QUERY", "HTTP_IN_HEADER", "HTTP_IN_PATH", "HTTP_IN_BODY", "HTTP_IN_COOKIE" ] }, "name": { "description": "Optional. The parameter name of the API key. E.g. If the API request is \"https://example.com/act?api_key=\", \"api_key\" would be the parameter name.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1VideoResponseFormat": { "description": "Configuration for video-specific output formatting.", "id": "GoogleCloudAiplatformV1beta1VideoResponseFormat", "type": "object", "properties": { "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ], "type": "string", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "Optional. Delivery mode for the generated content." }, "aspectRatio": { "enumDescriptions": [ "Default value. This value is unused.", "16:9 aspect ratio.", "9:16 aspect ratio." ], "type": "string", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_NINE_BY_SIXTEEN" ], "description": "The aspect ratio for the video output." }, "gcsUri": { "description": "Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.", "type": "string" }, "resolution": { "description": "Optional. The video output resolution. Supported values: \"360p\", \"720p\", \"1080p\", \"4k\".", "type": "string" }, "duration": { "type": "string", "description": "Optional. The duration for the video output.", "format": "google-duration" } } }, "GoogleCloudAiplatformV1beta1ModalityTokenCount": { "description": "Represents a breakdown of token usage by modality. This message is used in CountTokensResponse and GenerateContentResponse.UsageMetadata to provide a detailed view of how many tokens are used by each modality (e.g., text, image, video) in a request. This is particularly useful for multimodal models, allowing you to track and manage token consumption for billing and quota purposes.", "type": "object", "properties": { "modality": { "enumDescriptions": [ "When a modality is not specified, it is treated as `TEXT`.", "The `Part` contains plain text.", "The `Part` contains an image.", "The `Part` contains a video.", "The `Part` contains audio.", "The `Part` contains a document, such as a PDF." ], "type": "string", "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ], "description": "The modality that this token count applies to." }, "tokenCount": { "description": "The number of tokens counted for this modality.", "format": "int32", "type": "integer" } }, "id": "GoogleCloudAiplatformV1beta1ModalityTokenCount" }, "GoogleCloudAiplatformV1beta1LogprobsResult": { "type": "object", "properties": { "topCandidates": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates" }, "description": "A list of the top candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps." }, "chosenCandidates": { "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" }, "type": "array", "description": "A list of the chosen candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps. Note that the chosen candidate might not be in `top_candidates`." } }, "id": "GoogleCloudAiplatformV1beta1LogprobsResult", "description": "The log probabilities of the tokens generated by the model. This is useful for understanding the model's confidence in its predictions and for debugging. For example, you can use log probabilities to identify when the model is making a less confident prediction or to explore alternative responses that the model considered. A low log probability can also indicate that the model is \"hallucinating\" or generating factually incorrect information." }, "GoogleCloudAiplatformV1beta1ToolConfig": { "description": "Tool config. This config is shared for all tools provided in the request.", "id": "GoogleCloudAiplatformV1beta1ToolConfig", "type": "object", "properties": { "functionCallingConfig": { "description": "Optional. Function calling config.", "$ref": "GoogleCloudAiplatformV1beta1FunctionCallingConfig" }, "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "GoogleCloudAiplatformV1beta1RetrievalConfig" } } }, "GoogleCloudAiplatformV1beta1UrlContextMetadata": { "description": "Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "type": "object", "properties": { "urlMetadata": { "readOnly": true, "description": "Output only. A list of URL metadata, with one entry for each URL retrieved by the tool.", "items": { "$ref": "GoogleCloudAiplatformV1beta1UrlMetadata" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1beta1UrlContextMetadata" }, "GoogleCloudAiplatformV1beta1GoogleMapsPlaces": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1GoogleMapsPlaces", "description": "Grounding with Google Maps Places data (e.g. QueryPlaces). This is the default Google Maps grounding type when no other type is specified." }, "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageHints": { "id": "GoogleCloudAiplatformV1beta1AudioTranscriptionConfigLanguageHints", "type": "object", "properties": { "languageCodes": { "description": "Required. Deprecated: Use top-level `language_codes` instead. BCP-47 language codes. At least one must be specified.", "deprecated": true, "items": { "type": "string" }, "type": "array" } }, "description": "Deprecated: Use top-level `language_codes` instead. Provides hints to the model about possible languages present in the audio.", "deprecated": true }, "GoogleCloudAiplatformV1beta1FunctionCall": { "description": "A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values.", "type": "object", "properties": { "id": { "description": "Optional. The unique id of the function call. If populated, the client to execute the `function_call` and return the response with the matching `id`.", "type": "string" }, "name": { "description": "Optional. The name of the function to call. Matches FunctionDeclaration.name.", "type": "string" }, "args": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details." }, "partialArgs": { "description": "Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1PartialArg" } }, "willContinue": { "description": "Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.", "type": "boolean" } }, "id": "GoogleCloudAiplatformV1beta1FunctionCall" }, "GoogleCloudAiplatformV1beta1ApiAuth": { "type": "object", "properties": { "apiKeyConfig": { "description": "The API secret.", "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig" } }, "id": "GoogleCloudAiplatformV1beta1ApiAuth", "description": "The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead." }, "GoogleCloudAiplatformV1beta1Part": { "id": "GoogleCloudAiplatformV1beta1Part", "type": "object", "properties": { "inlineData": { "description": "Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.", "$ref": "GoogleCloudAiplatformV1beta1Blob" }, "videoMetadata": { "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", "$ref": "GoogleCloudAiplatformV1beta1VideoMetadata" }, "text": { "description": "Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.", "type": "string" }, "mediaResolution": { "description": "per part media resolution. Media resolution for the input media.", "$ref": "GoogleCloudAiplatformV1beta1PartMediaResolution" }, "codeExecutionResult": { "description": "Optional. The result of executing the ExecutableCode.", "$ref": "GoogleCloudAiplatformV1beta1CodeExecutionResult" }, "thought": { "description": "Optional. Indicates whether the `part` represents the model's thought process or reasoning.", "type": "boolean" }, "functionCall": { "description": "Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.", "$ref": "GoogleCloudAiplatformV1beta1FunctionCall" }, "executableCode": { "description": "Optional. Code generated by the model that is intended to be executed.", "$ref": "GoogleCloudAiplatformV1beta1ExecutableCode" }, "thoughtSignature": { "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests.", "format": "byte", "type": "string" }, "audioTranscription": { "description": "Optional. Audio (input or output) transcription. This is only set when this `Part` contains audio data.", "$ref": "GoogleCloudAiplatformV1beta1AudioTranscription" }, "functionResponse": { "description": "Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponse" }, "fileData": { "description": "Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.", "$ref": "GoogleCloudAiplatformV1beta1FileData" } }, "description": "A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes." }, "GoogleCloudAiplatformV1beta1CountTokensRequest": { "type": "object", "properties": { "contents": { "description": "Optional. Input content.", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" }, "type": "array" }, "model": { "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", "type": "string" }, "tools": { "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" }, "type": "array", "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model." }, "instances": { "type": "array", "items": { "type": "any" }, "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model." }, "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "generationConfig": { "description": "Optional. Generation config that the model will use to generate the response.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" } }, "id": "GoogleCloudAiplatformV1beta1CountTokensRequest", "description": "Request message for PredictionService.CountTokens." }, "GoogleCloudAiplatformV1beta1Citation": { "description": "A citation for a piece of generatedcontent.", "id": "GoogleCloudAiplatformV1beta1Citation", "type": "object", "properties": { "title": { "description": "Output only. The title of the source of the citation.", "readOnly": true, "type": "string" }, "publicationDate": { "$ref": "Date", "description": "Output only. The publication date of the source of the citation.", "readOnly": true }, "startIndex": { "description": "Output only. The start index of the citation in the content.", "format": "int32", "readOnly": true, "type": "integer" }, "license": { "type": "string", "readOnly": true, "description": "Output only. The license of the source of the citation." }, "endIndex": { "description": "Output only. The end index of the citation in the content.", "format": "int32", "readOnly": true, "type": "integer" }, "uri": { "description": "Output only. The URI of the source of the citation.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1FunctionDeclaration": { "id": "GoogleCloudAiplatformV1beta1FunctionDeclaration", "type": "object", "properties": { "description": { "description": "Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.", "type": "string" }, "parameters": { "description": "Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "responseJsonSchema": { "description": "Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.", "type": "any" }, "parametersJsonSchema": { "description": "Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { \"type\": \"object\", \"properties\": { \"name\": { \"type\": \"string\" }, \"age\": { \"type\": \"integer\" } }, \"additionalProperties\": false, \"required\": [\"name\", \"age\"], \"propertyOrdering\": [\"name\", \"age\"] } ``` This field is mutually exclusive with `parameters`.", "type": "any" }, "name": { "description": "Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.", "type": "string" }, "response": { "description": "Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "behavior": { "description": "Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.", "enumDescriptions": [ "This value is unspecified.", "If set, the system will wait to receive the function response before continuing the conversation.", "If set, the system will not wait to receive the function response. Instead, it will attempt to handle function responses as they become available while maintaining the conversation between the user and the model." ], "type": "string", "enum": [ "UNSPECIFIED", "BLOCKING", "NON_BLOCKING" ] } }, "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client." }, "GoogleCloudAiplatformV1beta1ExternalApi": { "id": "GoogleCloudAiplatformV1beta1ExternalApi", "type": "object", "properties": { "apiSpec": { "enumDescriptions": [ "Unspecified API spec. This value should not be used.", "Simple search API spec.", "Elastic search API spec." ], "type": "string", "enum": [ "API_SPEC_UNSPECIFIED", "SIMPLE_SEARCH", "ELASTIC_SEARCH" ], "description": "The API spec that the external API implements." }, "endpoint": { "description": "The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search", "type": "string" }, "apiAuth": { "description": "The authentication config to access the API. Deprecated. Please use auth_config instead.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1ApiAuth" }, "simpleSearchParams": { "description": "Parameters for the simple search API.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams" }, "elasticSearchParams": { "description": "Parameters for the elastic search API.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams" }, "authConfig": { "description": "The authentication config to access the API.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfig" } }, "description": "Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec." }, "GoogleCloudAiplatformV1beta1ModelArmorConfig": { "description": "Configuration for Model Armor. Model Armor is a Google Cloud service that provides safety and security filtering for prompts and responses. It helps protect your AI applications from risks such as harmful content, sensitive data leakage, and prompt injection attacks.", "type": "object", "properties": { "promptTemplateName": { "description": "Optional. The resource name of the Model Armor template to use for prompt screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the user's prompt for safety and security risks before it is sent to the model. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`.", "type": "string" }, "responseTemplateName": { "description": "Optional. The resource name of the Model Armor template to use for response screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the model's response for safety and security risks before it is returned to the user. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1ModelArmorConfig" }, "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates": { "id": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates", "type": "object", "properties": { "candidates": { "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" }, "type": "array", "description": "The list of candidate tokens, sorted by log probability in descending order." } }, "description": "A list of the top candidate tokens and their log probabilities at each decoding step. This can be used to see what other tokens the model considered." }, "GoogleCloudAiplatformV1beta1ToolCodeExecution": { "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1ToolCodeExecution", "description": "Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch": { "type": "object", "properties": { "alpha": { "description": "Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.", "format": "float", "type": "number" } }, "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch", "description": "Config for Hybrid Search." }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch": { "description": "Image search for grounding and related configurations.", "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext": { "type": "object", "properties": { "text": { "description": "The content of the retrieved data source.", "type": "string" }, "title": { "description": "The title of the retrieved data source.", "type": "string" }, "documentName": { "type": "string", "description": "Output only. The full resource name of the referenced Vertex AI Search document. This is used to identify the specific document that was retrieved. The format is `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/branches/{branch}/documents/{document}`.", "readOnly": true }, "ragChunk": { "description": "Additional context for a Retrieval-Augmented Generation (RAG) retrieval result. This is populated only when the RAG retrieval tool is used.", "$ref": "GoogleCloudAiplatformV1beta1RagChunk" }, "uri": { "description": "The URI of the retrieved data source.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext", "description": "Context retrieved from a data source to ground the model's response. This is used when a retrieval tool fetches information from a user-provided corpus or a public dataset." }, "GoogleCloudAiplatformV1beta1UrlContext": { "description": "Tool to support URL context.", "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1UrlContext" }, "GoogleCloudAiplatformV1beta1VideoMetadata": { "type": "object", "properties": { "endOffset": { "description": "Optional. The end offset of the video.", "format": "google-duration", "type": "string" }, "fps": { "description": "Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].", "format": "double", "type": "number" }, "startOffset": { "type": "string", "description": "Optional. The start offset of the video.", "format": "google-duration" } }, "id": "GoogleCloudAiplatformV1beta1VideoMetadata", "description": "Provides metadata for a video, including the start and end offsets for clipping and the frame rate." }, "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig", "type": "object", "properties": { "speakerVoiceConfigs": { "description": "Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.", "items": { "$ref": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig" }, "type": "array" } }, "description": "Configuration for a multi-speaker text-to-speech request." }, "GoogleCloudAiplatformV1beta1GroundingChunk": { "type": "object", "properties": { "image": { "description": "A grounding chunk from an image search result. See the `Image` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkImage" }, "retrievedContext": { "description": "A grounding chunk from a data source retrieved by a retrieval tool, such as Vertex AI Search. See the `RetrievedContext` message for details", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext" }, "web": { "description": "A grounding chunk from a web page, typically from Google Search. See the `Web` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkWeb" }, "maps": { "description": "A grounding chunk from Google Maps. See the `Maps` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMaps" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunk", "description": "A piece of evidence that supports a claim made by the model. This is used to show a citation for a claim made by the model. When grounding is enabled, the model returns a `GroundingChunk` that contains a reference to the source of the information." }, "GoogleCloudAiplatformV1beta1FunctionResponsePart": { "description": "A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.", "id": "GoogleCloudAiplatformV1beta1FunctionResponsePart", "type": "object", "properties": { "fileData": { "description": "URI based data.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseFileData" }, "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseBlob" } } }, "GoogleCloudAiplatformV1beta1ToolParallelAiSearch": { "description": "ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding.", "type": "object", "properties": { "enableZeroDataRetention": { "description": "Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is \"false\" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is \"true\", the Parallel Web Search for Grounding - ZDR subscription will be used.", "type": "boolean" }, "apiKey": { "description": "Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.", "type": "string" }, "enableDataRetention": { "description": "Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is \"false\" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is \"true\", the Parallel Web Search for Grounding - ZDR subscription will be used.", "deprecated": true, "type": "boolean" }, "customConfigs": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { \"source_policy\": { \"include_domains\": [\"google.com\", \"wikipedia.org\"], \"exclude_domains\": [\"example.com\"] }, \"fetch_policy\": { \"max_age_seconds\": 3600 } }" } }, "id": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch" }, "GoogleCloudAiplatformV1beta1GroundingChunkWeb": { "type": "object", "properties": { "uri": { "description": "The URI of the web page that contains the evidence.", "type": "string" }, "title": { "description": "The title of the web page that contains the evidence.", "type": "string" }, "domain": { "description": "The domain of the web page that contains the evidence. This can be used to filter out low-quality sources.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkWeb", "description": "A `Web` chunk is a piece of evidence that comes from a web page. It contains the URI of the web page, the title of the page, and the domain of the page. This is used to provide the user with a link to the source of the information." }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute": { "description": "Route information from Google Maps.", "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute", "type": "object", "properties": { "duration": { "type": "string", "description": "The total duration of the route.", "format": "google-duration" }, "distanceMeters": { "description": "The total distance of the route, in meters.", "format": "int32", "type": "integer" }, "encodedPolyline": { "description": "An encoded polyline of the route. See https://developers.google.com/maps/documentation/utilities/polylinealgorithm", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GoogleMaps": { "description": "Tool to retrieve public maps data for grounding, powered by Google.", "type": "object", "properties": { "enableWidget": { "description": "Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.", "deprecated": true, "type": "boolean" }, "groundingTypes": { "description": "Optional. Specifies the types of Google Maps grounding to enable. Defaults to `places` when unset.", "$ref": "GoogleCloudAiplatformV1beta1GoogleMapsGroundingTypes" } }, "id": "GoogleCloudAiplatformV1beta1GoogleMaps" }, "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback": { "type": "object", "properties": { "blockReason": { "type": "string", "enum": [ "BLOCKED_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "MODEL_ARMOR", "IMAGE_SAFETY", "JAILBREAK" ], "description": "Output only. The reason why the prompt was blocked.", "enumDescriptions": [ "The blocked reason is unspecified.", "The prompt was blocked for safety reasons.", "The prompt was blocked for other reasons. For example, it may be due to the prompt's language, or because it contains other harmful content.", "The prompt was blocked because it contains a term from the terminology blocklist.", "The prompt was blocked because it contains prohibited content.", "The prompt was blocked by Model Armor.", "The prompt was blocked because it contains content that is unsafe for image generation.", "The prompt was blocked as a jailbreak attempt." ], "readOnly": true }, "safetyRatings": { "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" }, "description": "Output only. A list of safety ratings for the prompt. There is one rating per category.", "readOnly": true }, "blockReasonMessage": { "type": "string", "description": "Output only. A readable message that explains the reason why the prompt was blocked.", "readOnly": true } }, "id": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback", "description": "Content filter results for a prompt sent in the request. Note: This is sent only in the first stream chunk and only if no candidates were generated due to content violations." }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker": { "description": "Config for LlmRanker.", "type": "object", "properties": { "modelName": { "description": "Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker" }, "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig", "type": "object", "properties": { "thinkingBudget": { "description": "Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.", "format": "int32", "type": "integer" }, "thinkingLevel": { "description": "Optional. The number of thoughts tokens that the model should generate.", "type": "string", "enum": [ "THINKING_LEVEL_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "MINIMAL" ], "enumDescriptions": [ "Unspecified thinking level.", "Low thinking level.", "Medium thinking level.", "High thinking level.", "MINIMAL thinking level." ] }, "includeThoughts": { "description": "Optional. If true, the model will include its thoughts in the response. \"Thoughts\" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.", "type": "boolean" } }, "description": "Configuration for the model's thinking features. \"Thinking\" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response." }, "GoogleCloudAiplatformV1beta1AuthConfig": { "description": "Auth configuration to run the extension.", "id": "GoogleCloudAiplatformV1beta1AuthConfig", "type": "object", "properties": { "authType": { "description": "Type of auth scheme.", "enumDescriptions": [ "", "No Auth.", "API Key Auth.", "HTTP Basic Auth.", "Google Service Account Auth.", "OAuth auth.", "OpenID Connect (OIDC) Auth." ], "type": "string", "enum": [ "AUTH_TYPE_UNSPECIFIED", "NO_AUTH", "API_KEY_AUTH", "HTTP_BASIC_AUTH", "GOOGLE_SERVICE_ACCOUNT_AUTH", "OAUTH", "OIDC_AUTH" ] }, "googleServiceAccountConfig": { "description": "Config for Google Service Account auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig" }, "oauthConfig": { "description": "Config for user oauth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig" }, "oidcConfig": { "description": "Config for user OIDC auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig" }, "apiKeyConfig": { "description": "Config for API key auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig" }, "httpBasicAuthConfig": { "description": "Config for HTTP Basic auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig" } } }, "GoogleCloudAiplatformV1beta1ToolExaAiSearch": { "description": "ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding.", "id": "GoogleCloudAiplatformV1beta1ToolExaAiSearch", "type": "object", "properties": { "apiKey": { "description": "Required. The API key for ExaAiSearch.", "type": "string" }, "customConfigs": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. This field can be used to pass any parameter from the Exa.ai Search API." } } }, "GoogleCloudAiplatformV1beta1UrlMetadata": { "description": "The metadata for a single URL retrieval.", "type": "object", "properties": { "retrievedUrl": { "description": "The URL retrieved by the tool.", "type": "string" }, "urlRetrievalStatus": { "description": "The status of the URL retrieval.", "type": "string", "enum": [ "URL_RETRIEVAL_STATUS_UNSPECIFIED", "URL_RETRIEVAL_STATUS_SUCCESS", "URL_RETRIEVAL_STATUS_ERROR" ], "enumDescriptions": [ "Default value. This value is unused.", "The URL was retrieved successfully.", "The URL retrieval failed." ] } }, "id": "GoogleCloudAiplatformV1beta1UrlMetadata" }, "GoogleCloudAiplatformV1beta1Content": { "id": "GoogleCloudAiplatformV1beta1Content", "type": "object", "properties": { "role": { "description": "Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.", "type": "string" }, "parts": { "description": "Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Part" } } }, "description": "The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message." }, "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig": { "description": "Configuration for a single speaker in a multi-speaker setup.", "id": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig", "type": "object", "properties": { "speaker": { "description": "Required. The name of the speaker. This should be the same as the speaker name used in the prompt.", "type": "string" }, "voiceConfig": { "description": "Required. The configuration for the voice of this speaker.", "$ref": "GoogleCloudAiplatformV1beta1VoiceConfig" } } }, "GoogleCloudAiplatformV1beta1AudioTranscription": { "description": "The transcription of an audio part. For multi-speaker audio, each speaker segment is a separate `Part` with its own `AudioTranscription` carrying the `speaker_label`.", "id": "GoogleCloudAiplatformV1beta1AudioTranscription", "type": "object", "properties": { "text": { "description": "Required. The transcription text of this audio segment.", "type": "string" }, "speakerLabel": { "description": "Optional. A label identifying the speaker of this audio segment (e.g. `spk_1`, `spk_2`). Present when `diarization` is set.", "type": "string" }, "words": { "description": "Optional. Detailed word-level transcriptions and timing details. Present when `word_timestamp` is set.", "items": { "$ref": "GoogleCloudAiplatformV1beta1AudioTranscriptionWordInfo" }, "type": "array" } } }, "GoogleCloudAiplatformV1beta1RetrievalConfig": { "description": "Retrieval config.", "type": "object", "properties": { "languageCode": { "description": "The language code of the user.", "type": "string" }, "latLng": { "description": "The location of the user.", "$ref": "LatLng" } }, "id": "GoogleCloudAiplatformV1beta1RetrievalConfig" }, "GoogleCloudAiplatformV1beta1VoiceConfig": { "type": "object", "properties": { "prebuiltVoiceConfig": { "description": "The configuration for a prebuilt voice.", "$ref": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig" }, "replicatedVoiceConfig": { "description": "Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.", "$ref": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig" } }, "id": "GoogleCloudAiplatformV1beta1VoiceConfig", "description": "Configuration for a voice." }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources": { "description": "The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content.", "type": "object", "properties": { "reviewSnippets": { "description": "Snippets of reviews that were used to generate the answer.", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet" }, "type": "array" } }, "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources" }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode": { "description": "The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference.", "type": "object", "properties": { "modelRoutingPreference": { "type": "string", "enum": [ "UNKNOWN", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ], "enumDescriptions": [ "Unspecified model routing preference.", "The model will be selected to prioritize the quality of the response.", "The model will be selected to balance quality and cost.", "The model will be selected to prioritize the cost of the request." ], "description": "The model routing preference." } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode" }, "GoogleCloudAiplatformV1beta1AudioResponseFormat": { "description": "Configuration for audio-specific output formatting.", "type": "object", "properties": { "bitRate": { "type": "integer", "description": "Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).", "format": "int32" }, "mimeType": { "enumDescriptions": [ "Default value. This value is unused.", "MP3 audio format.", "OGG Opus audio format.", "Raw PCM (L16) audio format.", "WAV audio format.", "A-law audio format.", "Mu-law audio format." ], "type": "string", "enum": [ "MIME_TYPE_UNSPECIFIED", "AUDIO_MP3", "AUDIO_OGG_OPUS", "AUDIO_L16", "AUDIO_WAV", "AUDIO_ALAW", "AUDIO_MULAW" ], "description": "Optional. The MIME type of the audio output." }, "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Generated bytes are returned inline in the response.", "Generated content is stored and a URI is returned." ], "type": "string", "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "Optional. Delivery mode for the generated content." }, "sampleRate": { "type": "integer", "description": "Optional. Sample rate for the generated audio in Hertz.", "format": "int32" } }, "id": "GoogleCloudAiplatformV1beta1AudioResponseFormat" }, "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig", "type": "object", "properties": { "credentialSecret": { "description": "Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.", "type": "string" } }, "description": "Config for HTTP Basic Authentication." }, "GoogleCloudAiplatformV1beta1GoogleMapsRouting": { "description": "Grounding with Google Maps Routing APIs (ComputeRoutes and SearchAlongRoute).", "type": "object", "properties": {}, "id": "GoogleCloudAiplatformV1beta1GoogleMapsRouting" }, "GoogleCloudAiplatformV1beta1ExecutableCode": { "type": "object", "properties": { "code": { "description": "Required. The code to be executed.", "type": "string" }, "id": { "description": "Optional. Unique identifier of the `ExecutableCode` part. The server returns the `CodeExecutionResult` with the matching `id`.", "type": "string" }, "language": { "description": "Required. Programming language of the `code`.", "type": "string", "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ], "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ] } }, "id": "GoogleCloudAiplatformV1beta1ExecutableCode", "description": "Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated." }, "GoogleCloudAiplatformV1beta1GoogleMapsGroundingTypes": { "type": "object", "properties": { "places": { "description": "Optional. Enables grounding with Google Maps Places. This is the default grounding type when no `GroundingTypes` are specified.", "$ref": "GoogleCloudAiplatformV1beta1GoogleMapsPlaces" }, "routing": { "description": "Optional. Enables grounding with Google Maps Routing APIs (ComputeRoutes and SearchAlongRoute).", "$ref": "GoogleCloudAiplatformV1beta1GoogleMapsRouting" } }, "id": "GoogleCloudAiplatformV1beta1GoogleMapsGroundingTypes", "description": "Defines the types of Google Maps grounding that can be enabled and their configurations." }, "GoogleCloudAiplatformV1beta1CodeExecutionResult": { "id": "GoogleCloudAiplatformV1beta1CodeExecutionResult", "type": "object", "properties": { "outcome": { "description": "Required. Outcome of the code execution.", "enumDescriptions": [ "Unspecified status. This value should not be used.", "Code execution completed successfully. `output` contains the stdout, if any.", "Code execution failed. `output` contains the stderr and stdout, if any.", "Code execution ran for too long, and was cancelled. There may or may not be a partial `output` present." ], "type": "string", "enum": [ "OUTCOME_UNSPECIFIED", "OUTCOME_OK", "OUTCOME_FAILED", "OUTCOME_DEADLINE_EXCEEDED" ] }, "output": { "description": "Optional. Contains stdout when code execution is successful, stderr or other description otherwise.", "type": "string" }, "id": { "description": "Optional. The identifier of the `ExecutableCode` part this result is for. Only populated if the corresponding `ExecutableCode` has an id.", "type": "string" } }, "description": "Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used." }, "GoogleCloudAiplatformV1beta1ResponseFormat": { "description": "Configuration for the model to configure output formatting and delivery.", "id": "GoogleCloudAiplatformV1beta1ResponseFormat", "type": "object", "properties": { "audio": { "description": "Audio output format.", "$ref": "GoogleCloudAiplatformV1beta1AudioResponseFormat" }, "text": { "description": "Text output format.", "$ref": "GoogleCloudAiplatformV1beta1TextResponseFormat" }, "video": { "description": "Video output format.", "$ref": "GoogleCloudAiplatformV1beta1VideoResponseFormat" }, "image": { "description": "Image output format.", "$ref": "GoogleCloudAiplatformV1beta1ImageResponseFormat" } } }, "GoogleCloudAiplatformV1beta1FunctionResponseBlob": { "id": "GoogleCloudAiplatformV1beta1FunctionResponseBlob", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "description": "Required. Raw bytes.", "format": "byte", "type": "string" }, "displayName": { "description": "Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.", "type": "string" } }, "description": "Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field." }, "GoogleCloudAiplatformV1beta1Tool": { "id": "GoogleCloudAiplatformV1beta1Tool", "type": "object", "properties": { "parallelAiSearch": { "description": "Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation", "$ref": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch" }, "exaAiSearch": { "description": "Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation", "$ref": "GoogleCloudAiplatformV1beta1ToolExaAiSearch" }, "codeExecution": { "description": "Optional. CodeExecution tool type. Enables the model to execute code as part of generation.", "$ref": "GoogleCloudAiplatformV1beta1ToolCodeExecution" }, "retrieval": { "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.", "$ref": "GoogleCloudAiplatformV1beta1Retrieval" }, "functionDeclarations": { "description": "Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration" } }, "googleMaps": { "description": "Optional. GoogleMaps tool type. Tool to support Google Maps in Model.", "$ref": "GoogleCloudAiplatformV1beta1GoogleMaps" }, "computerUse": { "description": "Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.", "$ref": "GoogleCloudAiplatformV1beta1ToolComputerUse" }, "googleSearchRetrieval": { "$ref": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval", "deprecated": true, "description": "Optional. Specialized retrieval tool that is powered by Google Search." }, "enterpriseWebSearch": { "description": "Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.", "$ref": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch" }, "urlContext": { "description": "Optional. Tool to support URL context retrieval.", "$ref": "GoogleCloudAiplatformV1beta1UrlContext" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearch" } }, "description": "Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval)." }, "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval": { "description": "Tool to retrieve public web data for grounding, powered by Google.", "type": "object", "properties": { "dynamicRetrievalConfig": { "description": "Specifies the dynamic retrieval configuration for the given source.", "$ref": "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig" } }, "id": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval" }, "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig": { "id": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", "type": "object", "properties": { "apiKeySecretVersion": { "description": "Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}", "type": "string" }, "apiKeyString": { "description": "The API key string. Either this or `api_key_secret_version` must be set.", "type": "string" } }, "description": "The API secret." }, "GoogleCloudAiplatformV1beta1RagChunkPageSpan": { "description": "Represents where the chunk starts and ends in the document.", "id": "GoogleCloudAiplatformV1beta1RagChunkPageSpan", "type": "object", "properties": { "firstPage": { "type": "integer", "description": "Page where chunk starts in the document. Inclusive. 1-indexed.", "format": "int32" }, "lastPage": { "description": "Page where chunk ends in the document. Inclusive. 1-indexed.", "format": "int32", "type": "integer" } } }, "GoogleCloudAiplatformV1beta1Segment": { "description": "A segment of the content.", "type": "object", "properties": { "partIndex": { "readOnly": true, "description": "Output only. The index of the `Part` object that this segment belongs to. This is useful for associating the segment with a specific part of the content.", "format": "int32", "type": "integer" }, "endIndex": { "type": "integer", "readOnly": true, "description": "Output only. The end index of the segment in the `Part`, measured in bytes. This marks the end of the segment and is exclusive, meaning the segment includes content up to, but not including, the byte at this index.", "format": "int32" }, "startIndex": { "type": "integer", "readOnly": true, "description": "Output only. The start index of the segment in the `Part`, measured in bytes. This marks the beginning of the segment and is inclusive, meaning the byte at this index is the first byte of the segment.", "format": "int32" }, "text": { "readOnly": true, "description": "Output only. The text of the segment.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1Segment" }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode": { "description": "The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided.", "type": "object", "properties": { "modelName": { "description": "The name of the model to use. Only public LLM models are accepted.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode" }, "GoogleCloudAiplatformV1beta1AudioTranscriptionWordInfo": { "id": "GoogleCloudAiplatformV1beta1AudioTranscriptionWordInfo", "type": "object", "properties": { "endOffset": { "description": "Optional. End offset in time of the word relative to the start of the audio.", "format": "google-duration", "type": "string" }, "word": { "description": "Required. Transcript of the word.", "type": "string" }, "startOffset": { "description": "Optional. Start offset in time of the word relative to the start of the audio.", "format": "google-duration", "type": "string" } }, "description": "Information about a single recognized word." }, "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource": { "description": "The definition of the Rag resource.", "id": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource", "type": "object", "properties": { "ragFileIds": { "items": { "type": "string" }, "type": "array", "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field." }, "ragCorpus": { "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearch": { "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearch", "type": "object", "properties": { "excludeDomains": { "items": { "type": "string" }, "type": "array", "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: [\"amazon.com\", \"facebook.com\"]." }, "searchTypes": { "description": "Optional. The set of search types to enable. If not set, web search is enabled by default.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes" }, "blockingConfidence": { "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "enumDescriptions": [ "Defaults to unspecified.", "Blocks Low and above confidence URL that is risky.", "Blocks Medium and above confidence URL that is risky.", "Blocks High and above confidence URL that is risky.", "Blocks Higher and above confidence URL that is risky.", "Blocks Very high and above confidence URL that is risky.", "Blocks Extremely high confidence URL that is risky." ], "type": "string", "enum": [ "PHISH_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_HIGH_AND_ABOVE", "BLOCK_HIGHER_AND_ABOVE", "BLOCK_VERY_HIGH_AND_ABOVE", "BLOCK_ONLY_EXTREMELY_HIGH" ] } } }, "GoogleCloudAiplatformV1beta1FunctionResponseFileData": { "type": "object", "properties": { "fileUri": { "description": "Required. URI.", "type": "string" }, "displayName": { "description": "Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.", "type": "string" }, "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" } }, "id": "GoogleCloudAiplatformV1beta1FunctionResponseFileData", "description": "URI based data for function response." } }, "name": "firebaseml", "kind": "discovery#restDescription", "batchPath": "batch", "canonicalName": "Firebase ML", "ownerName": "Google", "auth": { "oauth2": { "scopes": { "https://www.googleapis.com/auth/cloud-platform": { "description": "See, edit, configure, and delete your Google Cloud data and see the email address for your Google Account." } } } }, "icons": { "x32": "http://www.google.com/images/icons/product/search-32.gif", "x16": "http://www.google.com/images/icons/product/search-16.gif" }, "version": "v2beta", "title": "Firebase ML API", "parameters": { "access_token": { "type": "string", "description": "OAuth access token.", "location": "query" }, "quotaUser": { "description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.", "location": "query", "type": "string" }, "callback": { "type": "string", "location": "query", "description": "JSONP" }, "upload_protocol": { "type": "string", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", "location": "query" }, "uploadType": { "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", "location": "query", "type": "string" }, "$.xgafv": { "enumDescriptions": [ "v1 error format", "v2 error format" ], "location": "query", "description": "V1 error format.", "type": "string", "enum": [ "1", "2" ] }, "key": { "location": "query", "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.", "type": "string" }, "alt": { "default": "json", "type": "string", "enum": [ "json", "media", "proto" ], "location": "query", "description": "Data format for response.", "enumDescriptions": [ "Responses with Content-Type of application/json", "Media download with context-dependent Content-Type", "Responses with Content-Type of application/x-protobuf" ] }, "oauth_token": { "location": "query", "description": "OAuth 2.0 token for the current user.", "type": "string" }, "fields": { "type": "string", "location": "query", "description": "Selector specifying which fields to include in a partial response." }, "prettyPrint": { "type": "boolean", "default": "true", "description": "Returns response with indentations and line breaks.", "location": "query" } }, "ownerDomain": "google.com", "protocol": "rest", "discoveryVersion": "v1", "mtlsRootUrl": "https://firebaseml.mtls.googleapis.com/", "resources": { "projects": { "resources": { "locations": { "resources": { "publishers": { "resources": { "models": { "methods": { "generateContent": { "parameterOrder": [ "model" ], "parameters": { "model": { "location": "path", "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "type": "string", "required": true } }, "path": "v2beta/{+model}:generateContent", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "httpMethod": "POST", "id": "firebaseml.projects.locations.publishers.models.generateContent", "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "description": "Generate content with multimodal inputs.", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "flatPath": "v2beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent" }, "streamGenerateContent": { "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "description": "Generate content with multimodal inputs with streaming support.", "id": "firebaseml.projects.locations.publishers.models.streamGenerateContent", "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "flatPath": "v2beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", "parameters": { "model": { "required": true, "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$" } }, "parameterOrder": [ "model" ], "httpMethod": "POST", "path": "v2beta/{+model}:streamGenerateContent", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ] }, "countTokens": { "httpMethod": "POST", "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "path": "v2beta/{+endpoint}:countTokens", "parameters": { "endpoint": { "type": "string", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "location": "path", "required": true } }, "parameterOrder": [ "endpoint" ], "flatPath": "v2beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens", "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "description": "Perform a token counting.", "id": "firebaseml.projects.locations.publishers.models.countTokens" } } } } } } } } } } }