{ "kind": "discovery#restDescription", "revision": "20260511", "baseUrl": "https://firebasevertexai.googleapis.com/", "resources": { "projects": { "resources": { "locations": { "methods": { "getConfig": { "id": "firebasevertexai.projects.locations.getConfig", "path": "v1beta/{+name}", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/config", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The resource name of the config. Format: projects/{project}/locations/{location}/config", "pattern": "^projects/[^/]+/locations/[^/]+/config$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "Config" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Fetches the current configuration for the given project. Currently the only supported location is \"global\"." }, "updateConfig": { "id": "firebasevertexai.projects.locations.updateConfig", "path": "v1beta/{+name}", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/config", "httpMethod": "PATCH", "parameters": { "name": { "description": "Identifier. The resource name of the config. Format: projects/{project}/locations/{location}/config", "pattern": "^projects/[^/]+/locations/[^/]+/config$", "location": "path", "required": true, "type": "string" }, "updateMask": { "description": "Optional. A comma-separated list of names of fields in the DebugToken to update. Example: `telemetry_config.mode`.", "location": "query", "type": "string", "format": "google-fieldmask" } }, "parameterOrder": [ "name" ], "request": { "$ref": "Config" }, "response": { "$ref": "Config" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates the current configuration for the specified project. Currently the only supported location is \"global\"." } }, "resources": { "publishers": { "resources": { "models": { "methods": { "predict": { "id": "firebasevertexai.projects.locations.publishers.models.predict", "path": "v1beta/{+endpoint}:predict", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:predict", "httpMethod": "POST", "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1PredictRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform an online prediction." }, "countTokens": { "id": "firebasevertexai.projects.locations.publishers.models.countTokens", "path": "v1beta/{+endpoint}:countTokens", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:countTokens", "httpMethod": "POST", "parameters": { "endpoint": { "description": "Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "endpoint" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1CountTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform a token counting." }, "generateContent": { "id": "firebasevertexai.projects.locations.publishers.models.generateContent", "path": "v1beta/{+model}:generateContent", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:generateContent", "httpMethod": "POST", "parameters": { "model": { "description": "Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`", "pattern": "^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs." }, "streamGenerateContent": { "id": "firebasevertexai.projects.locations.publishers.models.streamGenerateContent", "path": "v1beta/{+model}:streamGenerateContent", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/publishers/{publishersId}/models/{modelsId}:streamGenerateContent", "httpMethod": "POST", "parameters": { "model": { "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/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs with streaming support." } } } } }, "templates": { "methods": { "templatePredict": { "id": "firebasevertexai.projects.locations.templates.templatePredict", "path": "v1beta/{+name}:templatePredict", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}:templatePredict", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1PredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform an online prediction using a server-side prompt template." }, "templateGenerateContent": { "id": "firebasevertexai.projects.locations.templates.templateGenerateContent", "path": "v1beta/{+name}:templateGenerateContent", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}:templateGenerateContent", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs using a server-side prompt template." }, "templateStreamGenerateContent": { "id": "firebasevertexai.projects.locations.templates.templateStreamGenerateContent", "path": "v1beta/{+name}:templateStreamGenerateContent", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}:templateStreamGenerateContent", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs and streaming outputs using a server-side prompt template." }, "get": { "id": "firebasevertexai.projects.locations.templates.get", "path": "v1beta/{+name}", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}", "httpMethod": "GET", "parameters": { "name": { "description": "Required. The name of the PromptTemplate resource. Format: projects/{project}/locations/{location}/templates/{prompt_template}", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "response": { "$ref": "PromptTemplate" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Gets a PromptTemplate." }, "list": { "id": "firebasevertexai.projects.locations.templates.list", "path": "v1beta/{+parent}/templates", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates", "httpMethod": "GET", "parameters": { "parent": { "description": "Required. The parent resource where this PromptTemplate will be created. Format: projects/{project}/locations/{location}", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "required": true, "type": "string" }, "pageSize": { "description": "Optional. The maximum number of PromptTemplates to return. The service may return fewer than this value. If unspecified, at most 50 PromptTemplates will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000.", "location": "query", "type": "integer", "format": "int32" }, "pageToken": { "description": "Optional. A page token, received from a previous `ListPromptTemplates` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListPromptTemplates` must match the call that provided the page token.", "location": "query", "type": "string" }, "filter": { "description": "Optional. The filter to apply to the list of PromptTemplates.", "location": "query", "type": "string" }, "view": { "description": "Optional. The view to return. If not specified, the default view is FULL.", "location": "query", "type": "string", "enumDescriptions": [ "The default / unset value. The API will default to the FULL view.", "Include all fields except template_string.", "Include all fields. This is the default view." ], "enum": [ "PROMPT_TEMPLATE_VIEW_UNSPECIFIED", "PROMPT_TEMPLATE_VIEW_BASIC", "PROMPT_TEMPLATE_VIEW_FULL" ] } }, "parameterOrder": [ "parent" ], "response": { "$ref": "ListPromptTemplatesResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Lists PromptTemplates." }, "create": { "id": "firebasevertexai.projects.locations.templates.create", "path": "v1beta/{+parent}/templates", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates", "httpMethod": "POST", "parameters": { "parent": { "description": "Required. The parent resource where this PromptTemplate will be created. Format: projects/{project}/locations/{location}", "pattern": "^projects/[^/]+/locations/[^/]+$", "location": "path", "required": true, "type": "string" }, "validateOnly": { "description": "Optional. If set to true, the request will be validated but not executed.", "location": "query", "type": "boolean" }, "promptTemplateId": { "description": "Optional. The unique ID to use for the PromptTemplate, which will become the final component of the PromptTemplate's resource name. It can contain only lowercase letters, numbers, and hyphens, with the first character a letter, the last a letter or a number, and a 63-character maximum. If not provided, a system-generated ID will be used.", "location": "query", "type": "string" }, "regionalPropagationDisabled": { "description": "Optional. For global endpoints only. If true, the PromptTemplate will be created in global only. Otherwise, the PromptTemplate will _also_ be replicated to all regions where applicable.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "parent" ], "request": { "$ref": "PromptTemplate" }, "response": { "$ref": "PromptTemplate" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Creates a new PromptTemplate." }, "patch": { "id": "firebasevertexai.projects.locations.templates.patch", "path": "v1beta/{+name}", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}", "httpMethod": "PATCH", "parameters": { "name": { "description": "Identifier. The resource name of the PromptTemplate. Format: projects/{project}/locations/{location}/templates/{prompt_template}", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" }, "updateMask": { "description": "Optional. The list of fields to update.", "location": "query", "type": "string", "format": "google-fieldmask" }, "validateOnly": { "description": "Optional. If set to true, the request will be validated but not executed.", "location": "query", "type": "boolean" }, "allowMissing": { "description": "Optional. If set to true and the PromptTemplate does not already exist, it will be created.", "location": "query", "type": "boolean" }, "regionalPropagationDisabled": { "description": "Optional. For global endpoints only. If true, the PromptTemplate will be updated in global only. Otherwise, the PromptTemplate will _also_ be updated in all regions where applicable.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "request": { "$ref": "PromptTemplate" }, "response": { "$ref": "PromptTemplate" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates a PromptTemplate." }, "delete": { "id": "firebasevertexai.projects.locations.templates.delete", "path": "v1beta/{+name}", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}", "httpMethod": "DELETE", "parameters": { "name": { "description": "Required. The name of the PromptTemplate resource to be deleted. Format: projects/{project}/locations/{location}/templates/{prompt_template}", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" }, "etag": { "description": "Optional. The etag of the PromptTemplate. If this is provided, it must match the server's etag for the operation to succeed.", "location": "query", "type": "string" }, "validateOnly": { "description": "Optional. If set to true, the request will be validated but not executed.", "location": "query", "type": "boolean" }, "allowMissing": { "description": "Optional. If set to true and the PromptTemplate does not exist, the method will still succeed.", "location": "query", "type": "boolean" }, "regionalPropagationDisabled": { "description": "Optional. For global endpoints only. If true, the PromptTemplate will be deleted in global only. Otherwise, the PromptTemplate will _also_ be deleted in all regions where applicable.", "location": "query", "type": "boolean" } }, "parameterOrder": [ "name" ], "response": { "$ref": "Empty" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Deletes a PromptTemplate." }, "modifyLock": { "id": "firebasevertexai.projects.locations.templates.modifyLock", "path": "v1beta/{+name}:modifyLock", "flatPath": "v1beta/projects/{projectsId}/locations/{locationsId}/templates/{templatesId}:modifyLock", "httpMethod": "POST", "parameters": { "name": { "description": "Required. The name of the PromptTemplate resource to update the lock on. Format: projects/{project}/locations/{location}/templates/{prompt_template}", "pattern": "^projects/[^/]+/locations/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "ModifyLockRequest" }, "response": { "$ref": "ModifyLockResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Updates the Lock state on a PromptTemplate" } } } } }, "models": { "methods": { "countTokens": { "id": "firebasevertexai.projects.models.countTokens", "path": "v1beta/{+model}:countTokens", "flatPath": "v1beta/projects/{projectsId}/models/{modelsId}:countTokens", "httpMethod": "POST", "parameters": { "model": { "description": "Required. The model's resource name. This serves as an ID for the Model to use. This name should match a model name returned by the `ListModels` method. Format: `models/{model}`", "pattern": "^projects/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleAiGenerativelanguageV1betaCountTokensRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaCountTokensResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform a token counting." }, "generateContent": { "id": "firebasevertexai.projects.models.generateContent", "path": "v1beta/{+model}:generateContent", "flatPath": "v1beta/projects/{projectsId}/models/{modelsId}:generateContent", "httpMethod": "POST", "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^projects/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs." }, "streamGenerateContent": { "id": "firebasevertexai.projects.models.streamGenerateContent", "path": "v1beta/{+model}:streamGenerateContent", "flatPath": "v1beta/projects/{projectsId}/models/{modelsId}:streamGenerateContent", "httpMethod": "POST", "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^projects/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs with streaming support." }, "predict": { "id": "firebasevertexai.projects.models.predict", "path": "v1beta/{+model}:predict", "flatPath": "v1beta/projects/{projectsId}/models/{modelsId}:predict", "httpMethod": "POST", "parameters": { "model": { "description": "Required. The name of the model for prediction. Format: `name=models/{model}`.", "pattern": "^projects/[^/]+/models/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "model" ], "request": { "$ref": "GoogleAiGenerativelanguageV1betaPredictRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaPredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform an online prediction." } } }, "templates": { "methods": { "templateGenerateContent": { "id": "firebasevertexai.projects.templates.templateGenerateContent", "path": "v1beta/{+name}:templateGenerateContent", "flatPath": "v1beta/projects/{projectsId}/templates/{templatesId}:templateGenerateContent", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs using a server-side prompt template." }, "templateStreamGenerateContent": { "id": "firebasevertexai.projects.templates.templateStreamGenerateContent", "path": "v1beta/{+name}:templateStreamGenerateContent", "flatPath": "v1beta/projects/{projectsId}/templates/{templatesId}:templateStreamGenerateContent", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Generate content with multimodal inputs and streaming outputs using a server-side prompt template." }, "templatePredict": { "id": "firebasevertexai.projects.templates.templatePredict", "path": "v1beta/{+name}:templatePredict", "flatPath": "v1beta/projects/{projectsId}/templates/{templatesId}:templatePredict", "httpMethod": "POST", "parameters": { "name": { "description": "Required. Name of the template to use in the request. projects/project-id/location/location-name/template/template-id", "pattern": "^projects/[^/]+/templates/[^/]+$", "location": "path", "required": true, "type": "string" } }, "parameterOrder": [ "name" ], "request": { "$ref": "TemplateGenerateContentRequest" }, "response": { "$ref": "GoogleAiGenerativelanguageV1betaPredictResponse" }, "scopes": [ "https://www.googleapis.com/auth/cloud-platform" ], "description": "Perform an online prediction using a server-side prompt template" } } } } } }, "batchPath": "batch", "icons": { "x16": "http://www.google.com/images/icons/product/search-16.gif", "x32": "http://www.google.com/images/icons/product/search-32.gif" }, "discoveryVersion": "v1", "ownerName": "Google", "name": "firebasevertexai", "canonicalName": "Firebase Vertex AI", "documentationLink": "https://firebase.google.com", "version": "v1beta", "rootUrl": "https://firebasevertexai.googleapis.com/", "basePath": "", "schemas": { "Config": { "id": "Config", "description": "Configuration for Firebase AI Logic.", "type": "object", "properties": { "name": { "description": "Identifier. The resource name of the config. Format: projects/{project}/locations/{location}/config", "type": "string" }, "telemetryConfig": { "description": "Optional. Configuration for telemetry.", "$ref": "TelemetryConfig" }, "generativeLanguageConfig": { "description": "Optional. Configuration for Gemini Developer API.", "$ref": "GenerativeLanguageConfig" }, "trafficFilter": { "description": "Optional. Configuration for traffic filtering.", "$ref": "TrafficFilter" } } }, "TelemetryConfig": { "id": "TelemetryConfig", "description": "Configuration for telemetry. Telemetry is the collection of metrics, logs, and traces recorded by the Firebase AI Logic backend.", "type": "object", "properties": { "mode": { "description": "Optional. The current monitoring mode used for this project.", "type": "string", "enumDescriptions": [ "Unspecified mode. Not intended for use.", "Telemetry is disabled by default.", "The collection of metrics, logs, and traces is enabled." ], "enum": [ "MODE_UNSPECIFIED", "NONE", "ALL" ] }, "samplingRate": { "description": "Optional. The percentage of requests to be sampled, expressed as a fraction in the range (0,1]. Note that the actual sampling rate may be lower than the specified value if the system is overloaded. Default is 1.0.", "type": "number", "format": "double" } } }, "GenerativeLanguageConfig": { "id": "GenerativeLanguageConfig", "description": "Configuration for using the Gemini Developer API via Firebase AI Logic. When using the Gemini Developer API via Firebase AI Logic, a separate Gemini API key is stored in this configuration *on the server* so that you do **not** add your Gemini API key directly into your app's codebase.", "type": "object", "properties": { "apiKey": { "description": "Input only. The value of the API key. The API key must have `generativelanguage.googleapis.com` in its \"API restrictions\" allowlist. Note that this API is sometimes called the *Generative Language API* in the Google Cloud console. Do **not** add this Gemini API key into your app's codebase", "type": "string" }, "obfuscatedApiKey": { "description": "Output only. The obfuscated value of the API key, showing only the last few characters of the API key to unique identify it within the project.", "readOnly": true, "type": "string" } } }, "TrafficFilter": { "id": "TrafficFilter", "description": "Configuration for traffic filter.", "type": "object", "properties": { "templateOnly": { "description": "Optional. Only allows users to use AI Logic via prompt templates for this project.", "type": "boolean" }, "firebaseAuthRequired": { "description": "Optional. Only allow requests that include a valid Firebase Auth credential. Use this setting to limit access to AI Logic to only requests from logged in users. For more details on how to integrate with Firebase Auth see https://firebase.google.com/docs/auth", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaCountTokensRequest": { "id": "GoogleAiGenerativelanguageV1betaCountTokensRequest", "description": "Counts the number of tokens in the `prompt` sent to a model. Models may tokenize text differently, so each model may return a different `token_count`.", "type": "object", "properties": { "contents": { "description": "Optional. The input given to the model as a prompt. This field is ignored when `generate_content_request` is set.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaContent" } }, "generateContentRequest": { "description": "Optional. The overall input given to the `Model`. This includes the prompt as well as other model steering information like [system instructions](https://ai.google.dev/gemini-api/docs/system-instructions), and/or function declarations for [function calling](https://ai.google.dev/gemini-api/docs/function-calling). `Model`s/`Content`s and `generate_content_request`s are mutually exclusive. You can either send `Model` + `Content`s or a `generate_content_request`, but never both.", "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentRequest" } } }, "GoogleAiGenerativelanguageV1betaContent": { "id": "GoogleAiGenerativelanguageV1betaContent", "description": "The base structured datatype containing multi-part content of a message. A `Content` includes a `role` field designating the producer of the `Content` and a `parts` field containing multi-part data that contains the content of the message turn.", "type": "object", "properties": { "parts": { "description": "Ordered `Parts` that constitute a single message. Parts may have different MIME types.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaPart" } }, "role": { "description": "Optional. The producer of the content. Must be either 'user' or 'model'. Useful to set for multi-turn conversations, otherwise can be left blank or unset.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaPart": { "id": "GoogleAiGenerativelanguageV1betaPart", "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`. A `Part` 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.", "type": "object", "properties": { "text": { "description": "Inline text.", "type": "string" }, "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleAiGenerativelanguageV1betaBlob" }, "functionCall": { "description": "A predicted `FunctionCall` returned from the model that contains a string representing the `FunctionDeclaration.name` with the arguments and their values.", "$ref": "GoogleAiGenerativelanguageV1betaFunctionCall" }, "functionResponse": { "description": "The result output of 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.", "$ref": "GoogleAiGenerativelanguageV1betaFunctionResponse" }, "fileData": { "description": "URI based data.", "$ref": "GoogleAiGenerativelanguageV1betaFileData" }, "executableCode": { "description": "Code generated by the model that is meant to be executed.", "$ref": "GoogleAiGenerativelanguageV1betaExecutableCode" }, "codeExecutionResult": { "description": "Result of executing the `ExecutableCode`.", "$ref": "GoogleAiGenerativelanguageV1betaCodeExecutionResult" }, "toolCall": { "description": "Server-side tool call. This field is populated when the model predicts a tool invocation that should be executed on the server. The client is expected to echo this message back to the API.", "$ref": "GoogleAiGenerativelanguageV1betaToolCall" }, "toolResponse": { "description": "The output from a server-side `ToolCall` execution. This field is populated by the client with the results of executing the corresponding `ToolCall`.", "$ref": "GoogleAiGenerativelanguageV1betaToolResponse" }, "videoMetadata": { "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", "$ref": "GoogleAiGenerativelanguageV1betaVideoMetadata" }, "thought": { "description": "Optional. Indicates if the part is thought from the model.", "type": "boolean" }, "thoughtSignature": { "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests.", "type": "string", "format": "byte" }, "partMetadata": { "description": "Custom metadata associated with the Part. Agents using genai.Part as content representation may need to keep track of the additional information. For example it can be name of a file/source from which the Part originates or a way to multiplex multiple Part streams.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "mediaResolution": { "description": "Optional. Media resolution for the input media.", "$ref": "MediaResolution" } } }, "GoogleAiGenerativelanguageV1betaBlob": { "id": "GoogleAiGenerativelanguageV1betaBlob", "description": "Raw media bytes. Text should not be sent as raw bytes, use the 'text' field.", "type": "object", "properties": { "mimeType": { "description": "The IANA standard MIME type of the source data. Examples of supported types: - Images: image/png, image/jpeg, image/jpg, image/webp, image/heic, image/heif, image/gif, image/avif - Audio: audio/*, video/audio/s16le, video/audio/wav - Video: video/* - Text: text/plain, text/html, text/css, text/javascript, text/x-typescript, text/csv, text/markdown, text/x-python, text/xml, text/rtf, video/text/timestamp - Applications: application/x-javascript, application/x-typescript, application/x-python-code, application/json, application/x-ipynb+json, application/rtf, application/pdf For additional context, see [Supported file formats](https://ai.google.dev/gemini-api/docs/file-input-methods#supported-content-types). //", "type": "string" }, "data": { "description": "Raw bytes for media formats.", "type": "string", "format": "byte" } } }, "GoogleAiGenerativelanguageV1betaFunctionCall": { "id": "GoogleAiGenerativelanguageV1betaFunctionCall", "description": "A predicted `FunctionCall` returned from the model that contains a string representing the `FunctionDeclaration.name` with the arguments and their values.", "type": "object", "properties": { "id": { "description": "Optional. Unique identifier 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": "Required. The name of the function to call. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 128.", "type": "string" }, "args": { "description": "Optional. The function parameters and values in JSON object format.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleAiGenerativelanguageV1betaFunctionResponse": { "id": "GoogleAiGenerativelanguageV1betaFunctionResponse", "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.", "type": "object", "properties": { "id": { "description": "Optional. The identifier 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. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 128.", "type": "string" }, "response": { "description": "Required. The function response in JSON object format. Callers can use any keys of their choice that fit the function's syntax to return the function output, e.g. \"output\", \"result\", etc. In particular, if the function call failed to execute, the response can have an \"error\" key to return error details to the model.", "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.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaFunctionResponsePart" } }, "willContinue": { "description": "Optional. Signals that function call continues, and more responses will be returned, turning the function call into a generator. Is only applicable to NON_BLOCKING function calls, is ignored otherwise. If set to false, future responses will not be considered. It is allowed to return empty `response` with `will_continue=False` to signal that the function call is finished. This may still trigger the model generation. To avoid triggering the generation and finish the function call, additionally set `scheduling` to `SILENT`.", "type": "boolean" }, "scheduling": { "description": "Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.", "type": "string", "enumDescriptions": [ "This value is unused.", "Only add the result to the conversation context, do not interrupt or trigger generation.", "Add the result to the conversation context, and prompt to generate output without interrupting ongoing generation.", "Add the result to the conversation context, interrupt ongoing generation and prompt to generate output." ], "enum": [ "SCHEDULING_UNSPECIFIED", "SILENT", "WHEN_IDLE", "INTERRUPT" ] } } }, "GoogleAiGenerativelanguageV1betaFunctionResponsePart": { "id": "GoogleAiGenerativelanguageV1betaFunctionResponsePart", "description": "A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.", "type": "object", "properties": { "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleAiGenerativelanguageV1betaFunctionResponseBlob" } } }, "GoogleAiGenerativelanguageV1betaFunctionResponseBlob": { "id": "GoogleAiGenerativelanguageV1betaFunctionResponseBlob", "description": "Raw media bytes for function response. Text should not be sent as raw bytes, use the 'FunctionResponse.response' field.", "type": "object", "properties": { "mimeType": { "description": "The IANA standard MIME type of the source data. Examples: - image/png - image/jpeg If an unsupported MIME type is provided, an error will be returned. For a complete list of supported types, see [Supported file formats](https://ai.google.dev/gemini-api/docs/prompting_with_media#supported_file_formats).", "type": "string" }, "data": { "description": "Raw bytes for media formats.", "type": "string", "format": "byte" } } }, "GoogleAiGenerativelanguageV1betaFileData": { "id": "GoogleAiGenerativelanguageV1betaFileData", "description": "URI based data.", "type": "object", "properties": { "mimeType": { "description": "Optional. The IANA standard MIME type of the source data.", "type": "string" }, "fileUri": { "description": "Required. URI.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaExecutableCode": { "id": "GoogleAiGenerativelanguageV1betaExecutableCode", "description": "Code generated by the model that is meant to be executed, and the result returned to the model. Only generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding `CodeExecutionResult` will also be generated.", "type": "object", "properties": { "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", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available. Python is the default language." ], "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ] }, "code": { "description": "Required. The code to be executed.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaCodeExecutionResult": { "id": "GoogleAiGenerativelanguageV1betaCodeExecutionResult", "description": "Result of executing the `ExecutableCode`. Generated only when the `CodeExecution` tool is used.", "type": "object", "properties": { "id": { "description": "Optional. The identifier of the `ExecutableCode` part this result is for. Only populated if the corresponding `ExecutableCode` has an id.", "type": "string" }, "outcome": { "description": "Required. Outcome of the code execution.", "type": "string", "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." ], "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" } } }, "GoogleAiGenerativelanguageV1betaToolCall": { "id": "GoogleAiGenerativelanguageV1betaToolCall", "description": "A predicted server-side `ToolCall` returned from the model. This message contains information about a tool that the model wants to invoke. The client is NOT expected to execute this `ToolCall`. Instead, the client should pass this `ToolCall` back to the API in a subsequent turn within a `Content` message, along with the corresponding `ToolResponse`.", "type": "object", "properties": { "id": { "description": "Optional. Unique identifier of the tool call. The server returns the tool response with the matching `id`.", "type": "string" }, "toolType": { "description": "Required. The type of tool that was called.", "type": "string", "enumDescriptions": [ "Unspecified tool type.", "Google search tool, maps to Tool.google_search.search_types.web_search.", "Image search tool, maps to Tool.google_search.search_types.image_search.", "URL context tool, maps to Tool.url_context.", "Google maps tool, maps to Tool.google_maps.", "File search tool, maps to Tool.file_search." ], "enum": [ "TOOL_TYPE_UNSPECIFIED", "GOOGLE_SEARCH_WEB", "GOOGLE_SEARCH_IMAGE", "URL_CONTEXT", "GOOGLE_MAPS", "FILE_SEARCH" ] }, "args": { "description": "Optional. The tool call arguments. Example: {\"arg1\" : \"value1\", \"arg2\" : \"value2\" , ...}", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleAiGenerativelanguageV1betaToolResponse": { "id": "GoogleAiGenerativelanguageV1betaToolResponse", "description": "The output from a server-side `ToolCall` execution. This message contains the results of a tool invocation that was initiated by a `ToolCall` from the model. The client should pass this `ToolResponse` back to the API in a subsequent turn within a `Content` message, along with the corresponding `ToolCall`.", "type": "object", "properties": { "id": { "description": "Optional. The identifier of the tool call this response is for.", "type": "string" }, "toolType": { "description": "Required. The type of tool that was called, matching the `tool_type` in the corresponding `ToolCall`.", "type": "string", "enumDescriptions": [ "Unspecified tool type.", "Google search tool, maps to Tool.google_search.search_types.web_search.", "Image search tool, maps to Tool.google_search.search_types.image_search.", "URL context tool, maps to Tool.url_context.", "Google maps tool, maps to Tool.google_maps.", "File search tool, maps to Tool.file_search." ], "enum": [ "TOOL_TYPE_UNSPECIFIED", "GOOGLE_SEARCH_WEB", "GOOGLE_SEARCH_IMAGE", "URL_CONTEXT", "GOOGLE_MAPS", "FILE_SEARCH" ] }, "response": { "description": "Optional. The tool response.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleAiGenerativelanguageV1betaVideoMetadata": { "id": "GoogleAiGenerativelanguageV1betaVideoMetadata", "deprecated": true, "description": "Deprecated: Use `GenerateContentRequest.processing_options` instead. Metadata describes the input video content.", "type": "object", "properties": { "startOffset": { "description": "Optional. The start offset of the video.", "type": "string", "format": "google-duration" }, "endOffset": { "description": "Optional. The end offset of the video.", "type": "string", "format": "google-duration" }, "fps": { "description": "Optional. The frame rate of the video sent to the model. If not specified, the default value will be 1.0. The fps range is (0.0, 24.0].", "type": "number", "format": "double" } } }, "MediaResolution": { "id": "MediaResolution", "description": "Media resolution for tokenization.", "type": "object", "properties": { "level": { "description": "The tokenization quality used for given media. for Gemini API support .", "type": "string", "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." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH", "MEDIA_RESOLUTION_ULTRA_HIGH" ] } } }, "GoogleAiGenerativelanguageV1betaGenerateContentRequest": { "id": "GoogleAiGenerativelanguageV1betaGenerateContentRequest", "description": "Request to generate a completion from the model.", "type": "object", "properties": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "type": "string" }, "systemInstruction": { "description": "Optional. Developer set [system instruction(s)](https://ai.google.dev/gemini-api/docs/system-instructions). Currently, text only.", "$ref": "GoogleAiGenerativelanguageV1betaContent" }, "contents": { "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries like [chat](https://ai.google.dev/gemini-api/docs/text-generation#chat), this is a repeated field that contains the conversation history and the latest request.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaContent" } }, "tools": { "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`. Supported `Tool`s are `Function` and `code_execution`. Refer to the [Function calling](https://ai.google.dev/gemini-api/docs/function-calling) and the [Code execution](https://ai.google.dev/gemini-api/docs/code-execution) guides to learn more.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaTool" } }, "toolConfig": { "description": "Optional. Tool configuration for any `Tool` specified in the request. Refer to the [Function calling guide](https://ai.google.dev/gemini-api/docs/function-calling#function_calling_mode) for a usage example.", "$ref": "GoogleAiGenerativelanguageV1betaToolConfig" }, "safetySettings": { "description": "Optional. A list of unique `SafetySetting` instances for blocking unsafe content. This will be enforced on the `GenerateContentRequest.contents` and `GenerateContentResponse.candidates`. There should not be more than one setting for each `SafetyCategory` type. The API will block any contents and responses that fail to meet the thresholds set by these settings. This list overrides the default settings for each `SafetyCategory` specified in the safety_settings. If there is no `SafetySetting` for a given `SafetyCategory` provided in the list, the API will use the default safety setting for that category. Harm categories HARM_CATEGORY_HATE_SPEECH, HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT, HARM_CATEGORY_HARASSMENT, HARM_CATEGORY_CIVIC_INTEGRITY are supported. Refer to the [guide](https://ai.google.dev/gemini-api/docs/safety-settings) for detailed information on available safety settings. Also refer to the [Safety guidance](https://ai.google.dev/gemini-api/docs/safety-guidance) to learn how to incorporate safety considerations in your AI applications.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaSafetySetting" } }, "generationConfig": { "description": "Optional. Configuration options for model generation and outputs.", "$ref": "GoogleAiGenerativelanguageV1betaGenerationConfig" }, "cachedContent": { "description": "Optional. The name of the content [cached](https://ai.google.dev/gemini-api/docs/caching) to use as context to serve the prediction. Format: `cachedContents/{cachedContent}`", "type": "string" }, "serviceTier": { "description": "Optional. The service tier of the request.", "type": "string", "enumDescriptions": [ "Default service tier, which is standard.", "Standard service tier.", "Flex service tier.", "Priority service tier." ], "enum": [ "unspecified", "standard", "flex", "priority" ] }, "store": { "description": "Optional. Configures the logging behavior for a given request. If set, it takes precedence over the project-level logging config.", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaTool": { "id": "GoogleAiGenerativelanguageV1betaTool", "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. Next ID: 16", "type": "object", "properties": { "functionDeclarations": { "description": "Optional. A list of `FunctionDeclarations` available to the model that can be used for function calling. The model or system does not execute the function. Instead the defined function may be returned as a FunctionCall with arguments to the client side for execution. The model may decide to call a subset of these functions by populating FunctionCall in the response. The next conversation turn may contain a FunctionResponse with the Content.role \"function\" generation context for the next model turn.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaFunctionDeclaration" } }, "googleSearchRetrieval": { "description": "Optional. Retrieval tool that is powered by Google search.", "$ref": "GoogleAiGenerativelanguageV1betaGoogleSearchRetrieval" }, "codeExecution": { "description": "Optional. Enables the model to execute code as part of generation.", "$ref": "GoogleAiGenerativelanguageV1betaCodeExecution" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleAiGenerativelanguageV1betaToolGoogleSearch" }, "computerUse": { "description": "Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.", "$ref": "GoogleAiGenerativelanguageV1betaToolComputerUse" }, "urlContext": { "description": "Optional. Tool to support URL context retrieval.", "$ref": "GoogleAiGenerativelanguageV1betaUrlContext" }, "fileSearch": { "description": "Optional. FileSearch tool type. Tool to retrieve knowledge from Semantic Retrieval corpora.", "$ref": "GoogleAiGenerativelanguageV1betaFileSearch" }, "mcpServers": { "description": "Optional. MCP Servers to connect to.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaToolMcpServer" } }, "googleMaps": { "description": "Optional. Tool that allows grounding the model's response with geospatial context related to the user's query.", "$ref": "GoogleAiGenerativelanguageV1betaGoogleMaps" } } }, "GoogleAiGenerativelanguageV1betaFunctionDeclaration": { "id": "GoogleAiGenerativelanguageV1betaFunctionDeclaration", "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.03 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.", "type": "object", "properties": { "name": { "description": "Required. The name of the function. Must be a-z, A-Z, 0-9, or contain underscores, colons, dots, and dashes, with a maximum length of 128.", "type": "string" }, "description": { "description": "Required. A brief description of the function.", "type": "string" }, "parameters": { "description": "Optional. Describes the parameters to this function. Reflects the Open API 3.03 Parameter Object string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter.", "$ref": "GoogleAiGenerativelanguageV1betaSchema" }, "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" }, "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": "GoogleAiGenerativelanguageV1betaSchema" }, "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" }, "behavior": { "description": "Optional. Specifies the function Behavior. Currently only supported by the BidiGenerateContent method.", "type": "string", "enumDescriptions": [ "This value is unused.", "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." ], "enum": [ "UNSPECIFIED", "BLOCKING", "NON_BLOCKING" ] } } }, "GoogleAiGenerativelanguageV1betaSchema": { "id": "GoogleAiGenerativelanguageV1betaSchema", "description": "The `Schema` object allows the definition of input and output data types. These types can be objects, but also primitives and arrays. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema).", "type": "object", "properties": { "type": { "description": "Required. Data type.", "type": "string", "enumDescriptions": [ "Not specified, should not be used.", "String type.", "Number type.", "Integer type.", "Boolean type.", "Array type.", "Object type.", "Null type." ], "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ] }, "format": { "description": "Optional. The format of the data. Any value is allowed, but most do not trigger any special functionality.", "type": "string" }, "title": { "description": "Optional. The title of the schema.", "type": "string" }, "description": { "description": "Optional. A brief description of the parameter. This could contain examples of use. Parameter description may be formatted as Markdown.", "type": "string" }, "nullable": { "description": "Optional. Indicates if the value may be null.", "type": "boolean" }, "enum": { "description": "Optional. Possible values of the element of Type.STRING with enum format. For example we can define an Enum Direction as : {type:STRING, format:enum, enum:[\"EAST\", NORTH\", \"SOUTH\", \"WEST\"]}", "type": "array", "items": { "type": "string" } }, "items": { "description": "Optional. Schema of the elements of Type.ARRAY.", "$ref": "GoogleAiGenerativelanguageV1betaSchema" }, "maxItems": { "description": "Optional. Maximum number of the elements for Type.ARRAY.", "type": "string", "format": "int64" }, "minItems": { "description": "Optional. Minimum number of the elements for Type.ARRAY.", "type": "string", "format": "int64" }, "properties": { "description": "Optional. Properties of Type.OBJECT.", "type": "object", "additionalProperties": { "$ref": "GoogleAiGenerativelanguageV1betaSchema" } }, "required": { "description": "Optional. Required properties of Type.OBJECT.", "type": "array", "items": { "type": "string" } }, "minProperties": { "description": "Optional. Minimum number of the properties for Type.OBJECT.", "type": "string", "format": "int64" }, "maxProperties": { "description": "Optional. Maximum number of the properties for Type.OBJECT.", "type": "string", "format": "int64" }, "minimum": { "description": "Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER", "type": "number", "format": "double" }, "maximum": { "description": "Optional. Maximum value of the Type.INTEGER and Type.NUMBER", "type": "number", "format": "double" }, "minLength": { "description": "Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING", "type": "string", "format": "int64" }, "maxLength": { "description": "Optional. Maximum length of the Type.STRING", "type": "string", "format": "int64" }, "pattern": { "description": "Optional. Pattern of the Type.STRING to restrict a string to a regular expression.", "type": "string" }, "example": { "description": "Optional. Example of the object. Will only populated when the object is the root.", "type": "any" }, "anyOf": { "description": "Optional. The value should be validated against any (one or more) of the subschemas in the list.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaSchema" } }, "propertyOrdering": { "description": "Optional. The order of the properties. Not a standard field in open api spec. Used to determine the order of the properties in the response.", "type": "array", "items": { "type": "string" } }, "default": { "description": "Optional. Default value of the field. Per JSON Schema, this field is intended for documentation generators and doesn't affect validation. Thus it's included here and ignored so that developers who send schemas with a `default` field don't get unknown-field errors.", "type": "any" } } }, "GoogleAiGenerativelanguageV1betaGoogleSearchRetrieval": { "id": "GoogleAiGenerativelanguageV1betaGoogleSearchRetrieval", "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.", "$ref": "GoogleAiGenerativelanguageV1betaDynamicRetrievalConfig" } } }, "GoogleAiGenerativelanguageV1betaDynamicRetrievalConfig": { "id": "GoogleAiGenerativelanguageV1betaDynamicRetrievalConfig", "description": "Describes the options to customize dynamic retrieval.", "type": "object", "properties": { "mode": { "description": "The mode of the predictor to be used in dynamic retrieval.", "type": "string", "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ], "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ] }, "dynamicThreshold": { "description": "The threshold to be used in dynamic retrieval. If not set, a system default value is used.", "type": "number", "format": "float" } } }, "GoogleAiGenerativelanguageV1betaCodeExecution": { "id": "GoogleAiGenerativelanguageV1betaCodeExecution", "description": "Tool that executes code generated by the model, and automatically returns the result to the model. See also `ExecutableCode` and `CodeExecutionResult` which are only generated when using this tool.", "type": "object", "properties": {} }, "GoogleAiGenerativelanguageV1betaToolGoogleSearch": { "id": "GoogleAiGenerativelanguageV1betaToolGoogleSearch", "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "type": "object", "properties": { "timeRangeFilter": { "description": "Optional. Filter search results to a specific time range. If customers set a start time, they must set an end time (and vice versa).", "$ref": "Interval" }, "searchTypes": { "description": "Optional. The set of search types to enable. If not set, web search is enabled by default.", "$ref": "GoogleAiGenerativelanguageV1betaToolGoogleSearchSearchTypes" } } }, "Interval": { "id": "Interval", "description": "Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time.", "type": "object", "properties": { "startTime": { "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start.", "type": "string", "format": "google-datetime" }, "endTime": { "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.", "type": "string", "format": "google-datetime" } } }, "GoogleAiGenerativelanguageV1betaToolGoogleSearchSearchTypes": { "id": "GoogleAiGenerativelanguageV1betaToolGoogleSearchSearchTypes", "description": "Different types of search that can be enabled on the GoogleSearch tool.", "type": "object", "properties": { "webSearch": { "description": "Optional. Enables web search. Only text results are returned.", "$ref": "GoogleAiGenerativelanguageV1betaToolGoogleSearchWebSearch" }, "imageSearch": { "description": "Optional. Enables image search. Image bytes are returned.", "$ref": "GoogleAiGenerativelanguageV1betaToolGoogleSearchImageSearch" } } }, "GoogleAiGenerativelanguageV1betaToolGoogleSearchWebSearch": { "id": "GoogleAiGenerativelanguageV1betaToolGoogleSearchWebSearch", "description": "Standard web search for grounding and related configurations.", "type": "object", "properties": {} }, "GoogleAiGenerativelanguageV1betaToolGoogleSearchImageSearch": { "id": "GoogleAiGenerativelanguageV1betaToolGoogleSearchImageSearch", "description": "Image search for grounding and related configurations.", "type": "object", "properties": {} }, "GoogleAiGenerativelanguageV1betaToolComputerUse": { "id": "GoogleAiGenerativelanguageV1betaToolComputerUse", "description": "Computer Use tool type.", "type": "object", "properties": { "environment": { "description": "Required. The environment being operated.", "type": "string", "enumDescriptions": [ "Defaults to browser.", "Operates in a web browser." ], "enum": [ "ENVIRONMENT_UNSPECIFIED", "ENVIRONMENT_BROWSER" ] }, "excludedPredefinedFunctions": { "description": "Optional. By default, predefined functions 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.", "type": "array", "items": { "type": "string" } } } }, "GoogleAiGenerativelanguageV1betaUrlContext": { "id": "GoogleAiGenerativelanguageV1betaUrlContext", "description": "Tool to support URL context retrieval.", "type": "object", "properties": {} }, "GoogleAiGenerativelanguageV1betaFileSearch": { "id": "GoogleAiGenerativelanguageV1betaFileSearch", "description": "The FileSearch tool that retrieves knowledge from Semantic Retrieval corpora. Files are imported to Semantic Retrieval corpora using the ImportFile API.", "type": "object", "properties": { "fileSearchStoreNames": { "description": "Required. The names of the file_search_stores to retrieve from. Example: `fileSearchStores/my-file-search-store-123`", "type": "array", "items": { "type": "string" } }, "topK": { "description": "Optional. The number of semantic retrieval chunks to retrieve.", "type": "integer", "format": "int32" }, "metadataFilter": { "description": "Optional. Metadata filter to apply to the semantic retrieval documents and chunks.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaToolMcpServer": { "id": "GoogleAiGenerativelanguageV1betaToolMcpServer", "description": "A MCPServer is a server that can be called by the model to perform actions. It is a server that implements the MCP protocol. Next ID: 6", "type": "object", "properties": { "streamableHttpTransport": { "description": "A transport that can stream HTTP requests and responses.", "$ref": "GoogleAiGenerativelanguageV1betaToolMcpServerStreamableHttpTransport" }, "name": { "description": "The name of the MCPServer.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaToolMcpServerStreamableHttpTransport": { "id": "GoogleAiGenerativelanguageV1betaToolMcpServerStreamableHttpTransport", "description": "A transport that can stream HTTP requests and responses. Next ID: 6", "type": "object", "properties": { "url": { "description": "The full URL for the MCPServer endpoint. Example: \"https://api.example.com/mcp\"", "type": "string" }, "headers": { "description": "Optional: Fields for authentication headers, timeouts, etc., if needed.", "type": "object", "additionalProperties": { "type": "string" } }, "timeout": { "description": "HTTP timeout for regular operations.", "type": "string", "format": "google-duration" }, "sseReadTimeout": { "description": "Timeout for SSE read operations.", "type": "string", "format": "google-duration" }, "terminateOnClose": { "description": "Whether to close the client session when the transport closes.", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaGoogleMaps": { "id": "GoogleAiGenerativelanguageV1betaGoogleMaps", "description": "The GoogleMaps Tool that provides geospatial context for the user's query.", "type": "object", "properties": { "enableWidget": { "description": "Optional. Whether to return a widget context token in the GroundingMetadata of the response. Developers can use the widget context token to render a Google Maps widget with geospatial context related to the places that the model references in the response.", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaToolConfig": { "id": "GoogleAiGenerativelanguageV1betaToolConfig", "description": "The Tool configuration containing parameters for specifying `Tool` use in the request.", "type": "object", "properties": { "functionCallingConfig": { "description": "Optional. Function calling config.", "$ref": "GoogleAiGenerativelanguageV1betaFunctionCallingConfig" }, "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "GoogleAiGenerativelanguageV1betaRetrievalConfig" }, "includeServerSideToolInvocations": { "description": "Optional. If true, the API response will include the server-side tool calls and responses within the `Content` message. This allows clients to observe the server's tool interactions.", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaFunctionCallingConfig": { "id": "GoogleAiGenerativelanguageV1betaFunctionCallingConfig", "description": "Configuration for specifying function calling behavior.", "type": "object", "properties": { "mode": { "description": "Optional. Specifies the mode in which function calling should execute. If unspecified, the default value will be set to AUTO.", "type": "string", "enumDescriptions": [ "Unspecified function calling mode. This value should not be used.", "Default model behavior, model decides to predict either a function call or a natural language response.", "Model is constrained to always predicting a function call only. If \"allowed_function_names\" are set, the predicted function call will be limited to any one of \"allowed_function_names\", else the predicted function call will be any one of the provided \"function_declarations\".", "Model will not predict any function call. Model behavior is same as when not passing any function declarations.", "Model decides to predict either a function call or a natural language response, but will validate function calls with constrained decoding. If \"allowed_function_names\" are set, the predicted function call will be limited to any one of \"allowed_function_names\", else the predicted function call will be any one of the provided \"function_declarations\"." ], "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ] }, "allowedFunctionNames": { "description": "Optional. A set of function names that, when provided, limits the functions the model will call. This should only be set when the Mode is ANY or VALIDATED. Function names should match [FunctionDeclaration.name]. When set, model will predict a function call from only allowed function names.", "type": "array", "items": { "type": "string" } } } }, "GoogleAiGenerativelanguageV1betaRetrievalConfig": { "id": "GoogleAiGenerativelanguageV1betaRetrievalConfig", "description": "Retrieval config.", "type": "object", "properties": { "latLng": { "description": "Optional. The location of the user.", "$ref": "LatLng" }, "languageCode": { "description": "Optional. The language code of the user. Language code for content. Use language tags defined by [BCP47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt).", "type": "string" } } }, "LatLng": { "id": "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": { "latitude": { "description": "The latitude in degrees. It must be in the range [-90.0, +90.0].", "type": "number", "format": "double" }, "longitude": { "description": "The longitude in degrees. It must be in the range [-180.0, +180.0].", "type": "number", "format": "double" } } }, "GoogleAiGenerativelanguageV1betaSafetySetting": { "id": "GoogleAiGenerativelanguageV1betaSafetySetting", "description": "Safety setting, affecting the safety-blocking behavior. Passing a safety setting for a category changes the allowed probability that content is blocked.", "type": "object", "properties": { "category": { "description": "Required. The category for this setting.", "type": "string", "enumDescriptions": [ "Category is unspecified.", "**PaLM** - Negative or harmful comments targeting identity and/or protected attribute.", "**PaLM** - Content that is rude, disrespectful, or profane.", "**PaLM** - Describes scenarios depicting violence against an individual or group, or general descriptions of gore.", "**PaLM** - Contains references to sexual acts or other lewd content.", "**PaLM** - Promotes unchecked medical advice.", "**PaLM** - Dangerous content that promotes, facilitates, or encourages harmful acts.", "**Gemini** - Harassment content.", "**Gemini** - Hate speech and content.", "**Gemini** - Sexually explicit content.", "**Gemini** - Dangerous content.", "**Gemini** - Content that may be used to harm civic integrity. DEPRECATED: use enable_enhanced_civic_answers instead." ], "enumDeprecated": [ false, false, false, false, false, false, false, false, false, false, false, true ], "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_DEROGATORY", "HARM_CATEGORY_TOXICITY", "HARM_CATEGORY_VIOLENCE", "HARM_CATEGORY_SEXUAL", "HARM_CATEGORY_MEDICAL", "HARM_CATEGORY_DANGEROUS", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_CIVIC_INTEGRITY" ] }, "threshold": { "description": "Required. Controls the probability threshold at which harm is blocked.", "type": "string", "enumDescriptions": [ "Threshold is unspecified.", "Content with NEGLIGIBLE will be allowed.", "Content with NEGLIGIBLE and LOW will be allowed.", "Content with NEGLIGIBLE, LOW, and MEDIUM will be allowed.", "All content will be allowed.", "Turn off the safety filter." ], "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ] } } }, "GoogleAiGenerativelanguageV1betaGenerationConfig": { "id": "GoogleAiGenerativelanguageV1betaGenerationConfig", "description": "Configuration options for model generation and outputs. Not all parameters are configurable for every model.", "type": "object", "properties": { "candidateCount": { "description": "Optional. Number of generated responses to return. If unset, this will default to 1. Please note that this doesn't work for previous generation models (Gemini 1.0 family)", "type": "integer", "format": "int32" }, "stopSequences": { "description": "Optional. The set of character sequences (up to 5) that will stop output generation. If specified, the API will stop at the first appearance of a `stop_sequence`. The stop sequence will not be included as part of the response.", "type": "array", "items": { "type": "string" } }, "maxOutputTokens": { "description": "Optional. The maximum number of tokens to include in a response candidate. Note: The default value varies by model, see the `Model.output_token_limit` attribute of the `Model` returned from the `getModel` function.", "type": "integer", "format": "int32" }, "temperature": { "description": "Optional. Controls the randomness of the output. Note: The default value varies by model, see the `Model.temperature` attribute of the `Model` returned from the `getModel` function. Values can range from [0.0, 2.0].", "type": "number", "format": "float" }, "topP": { "description": "Optional. The maximum cumulative probability of tokens to consider when sampling. The model uses combined Top-k and Top-p (nucleus) sampling. Tokens are sorted based on their assigned probabilities so that only the most likely tokens are considered. Top-k sampling directly limits the maximum number of tokens to consider, while Nucleus sampling limits the number of tokens based on the cumulative probability. Note: The default value varies by `Model` and is specified by the`Model.top_p` attribute returned from the `getModel` function. An empty `top_k` attribute indicates that the model doesn't apply top-k sampling and doesn't allow setting `top_k` on requests.", "type": "number", "format": "float" }, "topK": { "description": "Optional. The maximum number of tokens to consider when sampling. Gemini models use Top-p (nucleus) sampling or a combination of Top-k and nucleus sampling. Top-k sampling considers the set of `top_k` most probable tokens. Models running with nucleus sampling don't allow top_k setting. Note: The default value varies by `Model` and is specified by the`Model.top_p` attribute returned from the `getModel` function. An empty `top_k` attribute indicates that the model doesn't apply top-k sampling and doesn't allow setting `top_k` on requests.", "type": "integer", "format": "int32" }, "seed": { "description": "Optional. Seed used in decoding. If not set, the request uses a randomly generated seed.", "type": "integer", "format": "int32" }, "responseMimeType": { "description": "Optional. MIME type of the generated candidate text. Supported MIME types are: `text/plain`: (default) Text output. `application/json`: JSON response in the response candidates. `text/x.enum`: ENUM as a string response in the response candidates. Refer to the [docs](https://ai.google.dev/gemini-api/docs/prompting_with_media#plain_text_formats) for a list of all supported text MIME types.", "type": "string" }, "responseSchema": { "description": "Optional. Output schema of the generated candidate text. Schemas must be a subset of the [OpenAPI schema](https://spec.openapis.org/oas/v3.0.3#schema) and can be objects, primitives or arrays. If set, a compatible `response_mime_type` must also be set. Compatible MIME types: `application/json`: Schema for JSON response. Refer to the [JSON text generation guide](https://ai.google.dev/gemini-api/docs/json-mode) for more details.", "$ref": "GoogleAiGenerativelanguageV1betaSchema" }, "_responseJsonSchema": { "description": "Optional. Output schema of the generated response. This is an alternative to `response_schema` that accepts [JSON Schema](https://json-schema.org/). If set, `response_schema` must be omitted, but `response_mime_type` is required. While the full JSON Schema may be sent, not all features are supported. Specifically, only the following properties are supported: - `$id` - `$defs` - `$ref` - `$anchor` - `type` - `format` - `title` - `description` - `enum` (for strings and numbers) - `items` - `prefixItems` - `minItems` - `maxItems` - `minimum` - `maximum` - `anyOf` - `oneOf` (interpreted the same as `anyOf`) - `properties` - `additionalProperties` - `required` The non-standard `propertyOrdering` property may also be set. Cyclic references are unrolled to a limited degree and, as such, may only be used within non-required properties. (Nullable properties are not sufficient.) If `$ref` is set on a sub-schema, no other properties, except for than those starting as a `$`, may be set.", "type": "any" }, "responseJsonSchema": { "description": "Optional. An internal detail. Use `responseJsonSchema` rather than this field.", "type": "any" }, "presencePenalty": { "description": "Optional. Presence penalty applied to the next token's logprobs if the token has already been seen in the response. This penalty is binary on/off and not dependant on the number of times the token is used (after the first). Use frequency_penalty for a penalty that increases with each use. A positive penalty will discourage the use of tokens that have already been used in the response, increasing the vocabulary. A negative penalty will encourage the use of tokens that have already been used in the response, decreasing the vocabulary.", "type": "number", "format": "float" }, "frequencyPenalty": { "description": "Optional. Frequency penalty applied to the next token's logprobs, multiplied by the number of times each token has been seen in the respponse so far. A positive penalty will discourage the use of tokens that have already been used, proportional to the number of times the token has been used: The more a token is used, the more difficult it is for the model to use that token again increasing the vocabulary of responses. Caution: A _negative_ penalty will encourage the model to reuse tokens proportional to the number of times the token has been used. Small negative values will reduce the vocabulary of a response. Larger negative values will cause the model to start repeating a common token until it hits the max_output_tokens limit.", "type": "number", "format": "float" }, "responseLogprobs": { "description": "Optional. If true, export the logprobs results in response.", "type": "boolean" }, "logprobs": { "description": "Optional. Only valid if response_logprobs=True. This sets the number of top logprobs, including the chosen candidate, to return at each decoding step in the Candidate.logprobs_result. The number must be in the range of [0, 20].", "type": "integer", "format": "int32" }, "enableEnhancedCivicAnswers": { "description": "Optional. Enables enhanced civic answers. It may not be available for all models.", "type": "boolean" }, "responseModalities": { "description": "Optional. The requested modalities of the response. Represents the set of modalities that the model can return, and should be expected in the response. This is an exact match to the modalities of the response. A model may have multiple combinations of supported modalities. If the requested modalities do not match any of the supported combinations, an error will be returned. An empty list is equivalent to requesting only text.", "type": "array", "items": { "type": "string", "enumDescriptions": [ "Default value.", "Indicates the model should return text.", "Indicates the model should return images.", "Indicates the model should return audio." ], "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO" ] } }, "speechConfig": { "description": "Optional. The speech generation config.", "$ref": "GoogleAiGenerativelanguageV1betaSpeechConfig" }, "thinkingConfig": { "description": "Optional. Config for thinking features. An error will be returned if this field is set for models that don't support thinking.", "$ref": "GoogleAiGenerativelanguageV1betaThinkingConfig" }, "imageConfig": { "description": "Optional. Config for image generation. An error will be returned if this field is set for models that don't support these config options.", "$ref": "GoogleAiGenerativelanguageV1betaImageConfig" }, "mediaResolution": { "description": "Optional. If specified, the media resolution specified will be used.", "type": "string", "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low (64 tokens).", "Media resolution set to medium (256 tokens).", "Media resolution set to high (zoomed reframing with 256 tokens)." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ] } } }, "GoogleAiGenerativelanguageV1betaSpeechConfig": { "id": "GoogleAiGenerativelanguageV1betaSpeechConfig", "description": "Config for speech generation and transcription.", "type": "object", "properties": { "voiceConfig": { "description": "The configuration in case of single-voice output.", "$ref": "GoogleAiGenerativelanguageV1betaVoiceConfig" }, "multiSpeakerVoiceConfig": { "description": "Optional. The configuration for the multi-speaker setup. It is mutually exclusive with the voice_config field.", "$ref": "GoogleAiGenerativelanguageV1betaMultiSpeakerVoiceConfig" }, "languageCode": { "description": "Optional. The IETF [BCP-47](https://www.rfc-editor.org/rfc/bcp/bcp47.txt) language code that the user configured the app to use. Used for speech recognition and synthesis. Valid values are: `de-DE`, `en-AU`, `en-GB`, `en-IN`, `en-US`, `es-US`, `fr-FR`, `hi-IN`, `pt-BR`, `ar-XA`, `es-ES`, `fr-CA`, `id-ID`, `it-IT`, `ja-JP`, `tr-TR`, `vi-VN`, `bn-IN`, `gu-IN`, `kn-IN`, `ml-IN`, `mr-IN`, `ta-IN`, `te-IN`, `nl-NL`, `ko-KR`, `cmn-CN`, `pl-PL`, `ru-RU`, and `th-TH`.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaVoiceConfig": { "id": "GoogleAiGenerativelanguageV1betaVoiceConfig", "description": "The configuration for the voice to use.", "type": "object", "properties": { "prebuiltVoiceConfig": { "description": "The configuration for the prebuilt voice to use.", "$ref": "GoogleAiGenerativelanguageV1betaPrebuiltVoiceConfig" } } }, "GoogleAiGenerativelanguageV1betaPrebuiltVoiceConfig": { "id": "GoogleAiGenerativelanguageV1betaPrebuiltVoiceConfig", "description": "The configuration for the prebuilt speaker to use.", "type": "object", "properties": { "voiceName": { "description": "The name of the preset voice to use.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaMultiSpeakerVoiceConfig": { "id": "GoogleAiGenerativelanguageV1betaMultiSpeakerVoiceConfig", "description": "The configuration for the multi-speaker setup.", "type": "object", "properties": { "speakerVoiceConfigs": { "description": "Required. All the enabled speaker voices.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaSpeakerVoiceConfig" } } } }, "GoogleAiGenerativelanguageV1betaSpeakerVoiceConfig": { "id": "GoogleAiGenerativelanguageV1betaSpeakerVoiceConfig", "description": "The configuration for a single speaker in a multi speaker setup.", "type": "object", "properties": { "speaker": { "description": "Required. The name of the speaker to use. Should be the same as in the prompt.", "type": "string" }, "voiceConfig": { "description": "Required. The configuration for the voice to use.", "$ref": "GoogleAiGenerativelanguageV1betaVoiceConfig" } } }, "GoogleAiGenerativelanguageV1betaThinkingConfig": { "id": "GoogleAiGenerativelanguageV1betaThinkingConfig", "description": "Config for thinking features.", "type": "object", "properties": { "includeThoughts": { "description": "Indicates whether to include thoughts in the response. If true, thoughts are returned only when available.", "type": "boolean" }, "thinkingBudget": { "description": "The number of thoughts tokens that the model should generate.", "type": "integer", "format": "int32" }, "thinkingLevel": { "description": "Optional. Controls the maximum depth of the model's internal reasoning process before it produces a response. The default value is model-dependent. Refer to the [Thinking levels guide](https://ai.google.dev/gemini-api/docs/thinking#thinking-levels) for more details. Recommended for Gemini 3 or later models. Use with earlier models results in an error.", "type": "string", "enumDescriptions": [ "Default value.", "Little to no thinking.", "Low thinking level.", "Medium thinking level.", "High thinking level." ], "enum": [ "THINKING_LEVEL_UNSPECIFIED", "MINIMAL", "LOW", "MEDIUM", "HIGH" ] } } }, "GoogleAiGenerativelanguageV1betaImageConfig": { "id": "GoogleAiGenerativelanguageV1betaImageConfig", "description": "Config for image generation features.", "type": "object", "properties": { "aspectRatio": { "description": "Optional. The aspect ratio of the image to generate. Supported aspect ratios: `1:1`, `1:4`, `4:1`, `1:8`, `8:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, or `21:9`. If not specified, the model will choose a default aspect ratio based on any reference images provided.", "type": "string" }, "imageSize": { "description": "Optional. Specifies the size of generated images. Supported values are `512`, `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaCountTokensResponse": { "id": "GoogleAiGenerativelanguageV1betaCountTokensResponse", "description": "A response from `CountTokens`. It returns the model's `token_count` for the `prompt`.", "type": "object", "properties": { "totalTokens": { "description": "The number of tokens that the `Model` tokenizes the `prompt` into. Always non-negative.", "type": "integer", "format": "int32" }, "cachedContentTokenCount": { "description": "Number of tokens in the cached part of the prompt (the cached content).", "type": "integer", "format": "int32" }, "promptTokensDetails": { "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } }, "cacheTokensDetails": { "description": "Output only. List of modalities that were processed in the cached content.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } } } }, "GoogleAiGenerativelanguageV1betaModalityTokenCount": { "id": "GoogleAiGenerativelanguageV1betaModalityTokenCount", "description": "Represents token counting info for a single modality.", "type": "object", "properties": { "modality": { "description": "The modality associated with this token count.", "type": "string", "enumDescriptions": [ "Unspecified modality.", "Plain text.", "Image.", "Video.", "Audio.", "Document, e.g. PDF." ], "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ] }, "tokenCount": { "description": "Number of tokens.", "type": "integer", "format": "int32" } } }, "GoogleAiGenerativelanguageV1betaGenerateContentResponse": { "id": "GoogleAiGenerativelanguageV1betaGenerateContentResponse", "description": "Response from the model supporting multiple candidate responses. Safety ratings and content filtering are reported for both prompt in `GenerateContentResponse.prompt_feedback` and for each candidate in `finish_reason` and in `safety_ratings`. The API: - Returns either all requested candidates or none of them - Returns no candidates at all only if there was something wrong with the prompt (check `prompt_feedback`) - Reports feedback on each candidate in `finish_reason` and `safety_ratings`.", "type": "object", "properties": { "candidates": { "description": "Candidate responses from the model.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaCandidate" } }, "promptFeedback": { "description": "Returns the prompt's feedback related to the content filters.", "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponsePromptFeedback" }, "usageMetadata": { "description": "Output only. Metadata on the generation requests' token usage.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaGenerateContentResponseUsageMetadata" }, "modelVersion": { "description": "Output only. The model version used to generate the response.", "readOnly": true, "type": "string" }, "responseId": { "description": "Output only. response_id is used to identify each response.", "readOnly": true, "type": "string" }, "modelStatus": { "description": "Output only. The current model status of this model.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaModelStatus" } } }, "GoogleAiGenerativelanguageV1betaCandidate": { "id": "GoogleAiGenerativelanguageV1betaCandidate", "description": "A response candidate generated from the model.", "type": "object", "properties": { "index": { "description": "Output only. Index of the candidate in the list of response candidates.", "readOnly": true, "type": "integer", "format": "int32" }, "content": { "description": "Output only. Generated content returned from the model.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaContent" }, "finishReason": { "description": "Optional. Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating tokens.", "readOnly": true, "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Natural stop point of the model or provided stop sequence.", "The maximum number of tokens as specified in the request was reached.", "The response candidate content was flagged for safety reasons.", "The response candidate content was flagged for recitation reasons.", "The response candidate content was flagged for using an unsupported language.", "Unknown reason.", "Token generation stopped because the content contains forbidden terms.", "Token generation stopped for potentially containing prohibited content.", "Token generation stopped because the content potentially contains Sensitive Personally Identifiable Information (SPII).", "The function call generated by the model is invalid.", "Token generation stopped because generated images contain safety violations.", "Image generation stopped because generated images has other prohibited content.", "Image generation stopped because of other miscellaneous issue.", "The model was expected to generate an image, but none was generated.", "Image generation stopped due to recitation.", "Model generated a tool call but no tools were enabled in the request.", "Model called too many tools consecutively, thus the system exited execution.", "Request has at least one thought signature missing.", "Finished due to malformed response." ], "enum": [ "FINISH_REASON_UNSPECIFIED", "STOP", "MAX_TOKENS", "SAFETY", "RECITATION", "LANGUAGE", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "SPII", "MALFORMED_FUNCTION_CALL", "IMAGE_SAFETY", "IMAGE_PROHIBITED_CONTENT", "IMAGE_OTHER", "NO_IMAGE", "IMAGE_RECITATION", "UNEXPECTED_TOOL_CALL", "TOO_MANY_TOOL_CALLS", "MISSING_THOUGHT_SIGNATURE", "MALFORMED_RESPONSE" ] }, "finishMessage": { "description": "Optional. Output only. Details the reason why the model stopped generating tokens. This is populated only when `finish_reason` is set.", "readOnly": true, "type": "string" }, "safetyRatings": { "description": "List of ratings for the safety of a response candidate. There is at most one rating per category.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaSafetyRating" } }, "citationMetadata": { "description": "Output only. Citation information for model-generated candidate. This field may be populated with recitation information for any text included in the `content`. These are passages that are \"recited\" from copyrighted material in the foundational LLM's training data.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaCitationMetadata" }, "tokenCount": { "description": "Output only. Token count for this candidate.", "readOnly": true, "type": "integer", "format": "int32" }, "groundingAttributions": { "description": "Output only. Attribution information for sources that contributed to a grounded answer. This field is populated for `GenerateAnswer` calls.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaGroundingAttribution" } }, "groundingMetadata": { "description": "Output only. Grounding metadata for the candidate. This field is populated for `GenerateContent` calls.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaGroundingMetadata" }, "avgLogprobs": { "description": "Output only. Average log probability score of the candidate.", "readOnly": true, "type": "number", "format": "double" }, "logprobsResult": { "description": "Output only. Log-likelihood scores for the response tokens and top tokens", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaLogprobsResult" }, "urlContextMetadata": { "description": "Output only. Metadata related to url context retrieval tool.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaUrlContextMetadata" } } }, "GoogleAiGenerativelanguageV1betaSafetyRating": { "id": "GoogleAiGenerativelanguageV1betaSafetyRating", "description": "Safety rating for a piece of content. The safety rating contains the category of harm and the harm probability level in that category for a piece of content. Content is classified for safety across a number of harm categories and the probability of the harm classification is included here.", "type": "object", "properties": { "category": { "description": "Required. The category for this rating.", "type": "string", "enumDescriptions": [ "Category is unspecified.", "**PaLM** - Negative or harmful comments targeting identity and/or protected attribute.", "**PaLM** - Content that is rude, disrespectful, or profane.", "**PaLM** - Describes scenarios depicting violence against an individual or group, or general descriptions of gore.", "**PaLM** - Contains references to sexual acts or other lewd content.", "**PaLM** - Promotes unchecked medical advice.", "**PaLM** - Dangerous content that promotes, facilitates, or encourages harmful acts.", "**Gemini** - Harassment content.", "**Gemini** - Hate speech and content.", "**Gemini** - Sexually explicit content.", "**Gemini** - Dangerous content.", "**Gemini** - Content that may be used to harm civic integrity. DEPRECATED: use enable_enhanced_civic_answers instead." ], "enumDeprecated": [ false, false, false, false, false, false, false, false, false, false, false, true ], "enum": [ "HARM_CATEGORY_UNSPECIFIED", "HARM_CATEGORY_DEROGATORY", "HARM_CATEGORY_TOXICITY", "HARM_CATEGORY_VIOLENCE", "HARM_CATEGORY_SEXUAL", "HARM_CATEGORY_MEDICAL", "HARM_CATEGORY_DANGEROUS", "HARM_CATEGORY_HARASSMENT", "HARM_CATEGORY_HATE_SPEECH", "HARM_CATEGORY_SEXUALLY_EXPLICIT", "HARM_CATEGORY_DANGEROUS_CONTENT", "HARM_CATEGORY_CIVIC_INTEGRITY" ] }, "probability": { "description": "Required. The probability of harm for this content.", "type": "string", "enumDescriptions": [ "Probability is unspecified.", "Content has a negligible chance of being unsafe.", "Content has a low chance of being unsafe.", "Content has a medium chance of being unsafe.", "Content has a high chance of being unsafe." ], "enum": [ "HARM_PROBABILITY_UNSPECIFIED", "NEGLIGIBLE", "LOW", "MEDIUM", "HIGH" ] }, "blocked": { "description": "Was this content blocked because of this rating?", "type": "boolean" } } }, "GoogleAiGenerativelanguageV1betaCitationMetadata": { "id": "GoogleAiGenerativelanguageV1betaCitationMetadata", "description": "A collection of source attributions for a piece of content.", "type": "object", "properties": { "citationSources": { "description": "Citations to sources for a specific response.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaCitationSource" } } } }, "GoogleAiGenerativelanguageV1betaCitationSource": { "id": "GoogleAiGenerativelanguageV1betaCitationSource", "description": "A citation to a source for a portion of a specific response.", "type": "object", "properties": { "startIndex": { "description": "Optional. Start of segment of the response that is attributed to this source. Index indicates the start of the segment, measured in bytes.", "type": "integer", "format": "int32" }, "endIndex": { "description": "Optional. End of the attributed segment, exclusive.", "type": "integer", "format": "int32" }, "uri": { "description": "Optional. URI that is attributed as a source for a portion of the text.", "type": "string" }, "license": { "description": "Optional. License for the GitHub project that is attributed as a source for segment. License info is required for code citations.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingAttribution": { "id": "GoogleAiGenerativelanguageV1betaGroundingAttribution", "description": "Attribution for a source that contributed to an answer.", "type": "object", "properties": { "sourceId": { "description": "Output only. Identifier for the source contributing to this attribution.", "readOnly": true, "$ref": "GoogleAiGenerativelanguageV1betaAttributionSourceId" }, "content": { "description": "Grounding source content that makes up this attribution.", "$ref": "GoogleAiGenerativelanguageV1betaContent" } } }, "GoogleAiGenerativelanguageV1betaAttributionSourceId": { "id": "GoogleAiGenerativelanguageV1betaAttributionSourceId", "description": "Identifier for the source contributing to this attribution.", "type": "object", "properties": { "groundingPassage": { "description": "Identifier for an inline passage.", "$ref": "GoogleAiGenerativelanguageV1betaAttributionSourceIdGroundingPassageId" }, "semanticRetrieverChunk": { "description": "Identifier for a `Chunk` fetched via Semantic Retriever.", "$ref": "GoogleAiGenerativelanguageV1betaAttributionSourceIdSemanticRetrieverChunk" } } }, "GoogleAiGenerativelanguageV1betaAttributionSourceIdGroundingPassageId": { "id": "GoogleAiGenerativelanguageV1betaAttributionSourceIdGroundingPassageId", "description": "Identifier for a part within a `GroundingPassage`.", "type": "object", "properties": { "passageId": { "description": "Output only. ID of the passage matching the `GenerateAnswerRequest`'s `GroundingPassage.id`.", "readOnly": true, "type": "string" }, "partIndex": { "description": "Output only. Index of the part within the `GenerateAnswerRequest`'s `GroundingPassage.content`.", "readOnly": true, "type": "integer", "format": "int32" } } }, "GoogleAiGenerativelanguageV1betaAttributionSourceIdSemanticRetrieverChunk": { "id": "GoogleAiGenerativelanguageV1betaAttributionSourceIdSemanticRetrieverChunk", "description": "Identifier for a `Chunk` retrieved via Semantic Retriever specified in the `GenerateAnswerRequest` using `SemanticRetrieverConfig`.", "type": "object", "properties": { "source": { "description": "Output only. Name of the source matching the request's `SemanticRetrieverConfig.source`. Example: `corpora/123` or `corpora/123/documents/abc`", "readOnly": true, "type": "string" }, "chunk": { "description": "Output only. Name of the `Chunk` containing the attributed text. Example: `corpora/123/documents/abc/chunks/xyz`", "readOnly": true, "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingMetadata": { "id": "GoogleAiGenerativelanguageV1betaGroundingMetadata", "description": "Metadata returned to client when grounding is enabled.", "type": "object", "properties": { "searchEntryPoint": { "description": "Optional. Google search entry for the following-up web searches.", "$ref": "GoogleAiGenerativelanguageV1betaSearchEntryPoint" }, "groundingChunks": { "description": "List of supporting references retrieved from specified grounding source. When streaming, this only contains the grounding chunks that have not been included in the grounding metadata of previous responses.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunk" } }, "groundingSupports": { "description": "List of grounding support.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaGroundingSupport" } }, "retrievalMetadata": { "description": "Metadata related to retrieval in the grounding flow.", "$ref": "GoogleAiGenerativelanguageV1betaRetrievalMetadata" }, "webSearchQueries": { "description": "Web search queries for the following-up web search.", "type": "array", "items": { "type": "string" } }, "imageSearchQueries": { "description": "Image search queries used for grounding.", "type": "array", "items": { "type": "string" } }, "googleMapsWidgetContextToken": { "description": "Optional. Resource name of the Google Maps widget context token that can be used with the PlacesContextElement widget in order to render contextual data. Only populated in the case that grounding with Google Maps is enabled.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaSearchEntryPoint": { "id": "GoogleAiGenerativelanguageV1betaSearchEntryPoint", "description": "Google search entry point.", "type": "object", "properties": { "renderedContent": { "description": "Optional. Web content snippet that can be embedded in a web page or an app webview.", "type": "string" }, "sdkBlob": { "description": "Optional. Base64 encoded JSON representing array of tuple.", "type": "string", "format": "byte" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunk": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunk", "description": "A `GroundingChunk` represents a segment of supporting evidence that grounds the model's response. It can be a chunk from the web, a retrieved context from a file, or information from Google Maps.", "type": "object", "properties": { "web": { "description": "Grounding chunk from the web.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkWeb" }, "image": { "description": "Optional. Grounding chunk from image search.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkImage" }, "retrievedContext": { "description": "Optional. Grounding chunk from context retrieved by the file search tool.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkRetrievedContext" }, "maps": { "description": "Optional. Grounding chunk from Google Maps.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkMaps" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkWeb": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkWeb", "description": "Chunk from the web.", "type": "object", "properties": { "uri": { "description": "Output only. URI reference of the chunk.", "readOnly": true, "type": "string" }, "title": { "description": "Output only. Title of the chunk.", "readOnly": true, "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkImage": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkImage", "description": "Chunk from image search.", "type": "object", "properties": { "sourceUri": { "description": "The web page URI for attribution.", "type": "string" }, "imageUri": { "description": "The image asset URL.", "type": "string" }, "title": { "description": "The title of the web page that the image is from.", "type": "string" }, "domain": { "description": "The root domain of the web page that the image is from, e.g. \"example.com\".", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkRetrievedContext": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkRetrievedContext", "description": "Chunk from context retrieved by the file search tool.", "type": "object", "properties": { "uri": { "description": "Optional. URI reference of the semantic retrieval document.", "type": "string" }, "title": { "description": "Optional. Title of the document.", "type": "string" }, "text": { "description": "Optional. Text of the chunk.", "type": "string" }, "fileSearchStore": { "description": "Optional. Name of the `FileSearchStore` containing the document. Example: `fileSearchStores/123`", "type": "string" }, "customMetadata": { "description": "Optional. User-provided metadata about the retrieved context.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkCustomMetadata" } }, "pageNumber": { "description": "Optional. Page number of the retrieved context, if applicable.", "type": "integer", "format": "int32" }, "mediaId": { "description": "Optional. The media blob resource name for multimodal file search results. Format: fileSearchStores/{file_search_store_id}/media/{blob_id}", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkCustomMetadata": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkCustomMetadata", "description": "User provided metadata about the GroundingFact.", "type": "object", "properties": { "stringValue": { "description": "Optional. The string value of the metadata.", "type": "string" }, "stringListValue": { "description": "Optional. A list of string values for the metadata.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkStringList" }, "numericValue": { "description": "Optional. The numeric value of the metadata. The expected range for this value depends on the specific `key` used.", "type": "number", "format": "float" }, "key": { "description": "The key of the metadata.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkStringList": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkStringList", "description": "A list of string values.", "type": "object", "properties": { "values": { "description": "The string values of the list.", "type": "array", "items": { "type": "string" } } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkMaps": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkMaps", "description": "A grounding chunk from Google Maps. A Maps chunk corresponds to a single place.", "type": "object", "properties": { "uri": { "description": "URI reference of the place.", "type": "string" }, "title": { "description": "Title of the place.", "type": "string" }, "text": { "description": "Text description of the place answer.", "type": "string" }, "placeId": { "description": "The ID of the place, in `places/{place_id}` format. A user can use this ID to look up that place.", "type": "string" }, "placeAnswerSources": { "description": "Sources that provide answers about the features of a given place in Google Maps.", "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSources" } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSources": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSources", "description": "Collection of sources that provide answers about the features of a given place in Google Maps. Each PlaceAnswerSources message corresponds to a specific place in Google Maps. The Google Maps tool used these sources in order to answer questions about features of the place (e.g: \"does Bar Foo have Wifi\" or \"is Foo Bar wheelchair accessible?\"). Currently we only support review snippets as sources.", "type": "object", "properties": { "reviewSnippets": { "description": "Snippets of reviews that are used to generate answers about the features of a given place in Google Maps.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSourcesReviewSnippet" } } } }, "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSourcesReviewSnippet": { "id": "GoogleAiGenerativelanguageV1betaGroundingChunkMapsPlaceAnswerSourcesReviewSnippet", "description": "Encapsulates a snippet of a user review that answers a question about the features of a specific place in Google Maps.", "type": "object", "properties": { "reviewId": { "description": "The ID of the review snippet.", "type": "string" }, "googleMapsUri": { "description": "A link that corresponds to the user review on Google Maps.", "type": "string" }, "title": { "description": "Title of the review.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaGroundingSupport": { "id": "GoogleAiGenerativelanguageV1betaGroundingSupport", "description": "Grounding support.", "type": "object", "properties": { "segment": { "description": "Segment of the content this support belongs to.", "$ref": "GoogleAiGenerativelanguageV1betaSegment" }, "groundingChunkIndices": { "description": "Optional. A list of indices (into 'grounding_chunk' in `response.candidate.grounding_metadata`) specifying the citations associated with the claim. For instance [1,3,4] means that grounding_chunk[1], grounding_chunk[3], grounding_chunk[4] are the retrieved content attributed to the claim. If the response is streaming, the grounding_chunk_indices refer to the indices across all responses. It is the client's responsibility to accumulate the grounding chunks from all responses (while maintaining the same order).", "type": "array", "items": { "type": "integer", "format": "int32" } }, "confidenceScores": { "description": "Optional. Confidence score of the support references. Ranges from 0 to 1. 1 is the most confident. This list must have the same size as the grounding_chunk_indices.", "type": "array", "items": { "type": "number", "format": "float" } }, "renderedParts": { "description": "Output only. Indices into the `parts` field of the candidate's content. These indices specify which rendered parts are associated with this support source.", "readOnly": true, "type": "array", "items": { "type": "integer", "format": "int32" } } } }, "GoogleAiGenerativelanguageV1betaSegment": { "id": "GoogleAiGenerativelanguageV1betaSegment", "description": "Segment of the content.", "type": "object", "properties": { "partIndex": { "description": "The index of a Part object within its parent Content object.", "type": "integer", "format": "int32" }, "startIndex": { "description": "Start index in the given Part, measured in bytes. Offset from the start of the Part, inclusive, starting at zero.", "type": "integer", "format": "int32" }, "endIndex": { "description": "End index in the given Part, measured in bytes. Offset from the start of the Part, exclusive, starting at zero.", "type": "integer", "format": "int32" }, "text": { "description": "The text corresponding to the segment from the response.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaRetrievalMetadata": { "id": "GoogleAiGenerativelanguageV1betaRetrievalMetadata", "description": "Metadata related to retrieval in the grounding flow.", "type": "object", "properties": { "googleSearchDynamicRetrievalScore": { "description": "Optional. Score indicating how likely information from google search could help answer the prompt. The score is in the range [0, 1], where 0 is the least likely and 1 is the most likely. This score is only populated when google search grounding and dynamic retrieval is enabled. It will be compared to the threshold to determine whether to trigger google search.", "type": "number", "format": "float" } } }, "GoogleAiGenerativelanguageV1betaLogprobsResult": { "id": "GoogleAiGenerativelanguageV1betaLogprobsResult", "description": "Logprobs Result", "type": "object", "properties": { "logProbabilitySum": { "description": "Sum of log probabilities for all tokens.", "type": "number", "format": "float" }, "topCandidates": { "description": "Length = total number of decoding steps.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaLogprobsResultTopCandidates" } }, "chosenCandidates": { "description": "Length = total number of decoding steps. The chosen candidates may or may not be in top_candidates.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaLogprobsResultCandidate" } } } }, "GoogleAiGenerativelanguageV1betaLogprobsResultTopCandidates": { "id": "GoogleAiGenerativelanguageV1betaLogprobsResultTopCandidates", "description": "Candidates with top log probabilities at each decoding step.", "type": "object", "properties": { "candidates": { "description": "Sorted by log probability in descending order.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaLogprobsResultCandidate" } } } }, "GoogleAiGenerativelanguageV1betaLogprobsResultCandidate": { "id": "GoogleAiGenerativelanguageV1betaLogprobsResultCandidate", "description": "Candidate for the logprobs token and score.", "type": "object", "properties": { "token": { "description": "The candidate’s token string value.", "type": "string" }, "tokenId": { "description": "The candidate’s token id value.", "type": "integer", "format": "int32" }, "logProbability": { "description": "The candidate's log probability.", "type": "number", "format": "float" } } }, "GoogleAiGenerativelanguageV1betaUrlContextMetadata": { "id": "GoogleAiGenerativelanguageV1betaUrlContextMetadata", "description": "Metadata related to url context retrieval tool.", "type": "object", "properties": { "urlMetadata": { "description": "List of url context.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaUrlMetadata" } } } }, "GoogleAiGenerativelanguageV1betaUrlMetadata": { "id": "GoogleAiGenerativelanguageV1betaUrlMetadata", "description": "Context of the a single url retrieval.", "type": "object", "properties": { "retrievedUrl": { "description": "Retrieved url by the tool.", "type": "string" }, "urlRetrievalStatus": { "description": "Status of the url retrieval.", "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Url retrieval is successful.", "Url retrieval is failed due to error.", "Url retrieval is failed because the content is behind paywall.", "Url retrieval is failed because the content is unsafe." ], "enum": [ "URL_RETRIEVAL_STATUS_UNSPECIFIED", "URL_RETRIEVAL_STATUS_SUCCESS", "URL_RETRIEVAL_STATUS_ERROR", "URL_RETRIEVAL_STATUS_PAYWALL", "URL_RETRIEVAL_STATUS_UNSAFE" ] } } }, "GoogleAiGenerativelanguageV1betaGenerateContentResponsePromptFeedback": { "id": "GoogleAiGenerativelanguageV1betaGenerateContentResponsePromptFeedback", "description": "A set of the feedback metadata the prompt specified in `GenerateContentRequest.content`.", "type": "object", "properties": { "blockReason": { "description": "Optional. If set, the prompt was blocked and no candidates are returned. Rephrase the prompt.", "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Prompt was blocked due to safety reasons. Inspect `safety_ratings` to understand which safety category blocked it.", "Prompt was blocked due to unknown reasons.", "Prompt was blocked due to the terms which are included from the terminology blocklist.", "Prompt was blocked due to prohibited content.", "Candidates blocked due to unsafe image generation content." ], "enum": [ "BLOCK_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "IMAGE_SAFETY" ] }, "safetyRatings": { "description": "Ratings for safety of the prompt. There is at most one rating per category.", "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaSafetyRating" } } } }, "GoogleAiGenerativelanguageV1betaGenerateContentResponseUsageMetadata": { "id": "GoogleAiGenerativelanguageV1betaGenerateContentResponseUsageMetadata", "description": "Metadata on the generation request's token usage.", "type": "object", "properties": { "promptTokenCount": { "description": "Number of tokens in the prompt. When `cached_content` is set, this is still the total effective prompt size meaning this includes the number of tokens in the cached content.", "type": "integer", "format": "int32" }, "cachedContentTokenCount": { "description": "Number of tokens in the cached part of the prompt (the cached content)", "type": "integer", "format": "int32" }, "candidatesTokenCount": { "description": "Total number of tokens across all the generated response candidates.", "type": "integer", "format": "int32" }, "toolUsePromptTokenCount": { "description": "Output only. Number of tokens present in tool-use prompt(s).", "readOnly": true, "type": "integer", "format": "int32" }, "thoughtsTokenCount": { "description": "Output only. Number of tokens of thoughts for thinking models.", "readOnly": true, "type": "integer", "format": "int32" }, "totalTokenCount": { "description": "Total token count for the generation request (prompt + thoughts + response candidates).", "type": "integer", "format": "int32" }, "promptTokensDetails": { "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } }, "cacheTokensDetails": { "description": "Output only. List of modalities of the cached content in the request input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } }, "candidatesTokensDetails": { "description": "Output only. List of modalities that were returned in the response.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } }, "toolUsePromptTokensDetails": { "description": "Output only. List of modalities that were processed for tool-use request inputs.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleAiGenerativelanguageV1betaModalityTokenCount" } }, "serviceTier": { "description": "Output only. Service tier of the request.", "readOnly": true, "type": "string", "enumDescriptions": [ "Default service tier, which is standard.", "Standard service tier.", "Flex service tier.", "Priority service tier." ], "enum": [ "unspecified", "standard", "flex", "priority" ] } } }, "GoogleAiGenerativelanguageV1betaModelStatus": { "id": "GoogleAiGenerativelanguageV1betaModelStatus", "description": "The status of the underlying model. This is used to indicate the stage of the underlying model and the retirement time if applicable.", "type": "object", "properties": { "modelStage": { "description": "The stage of the underlying model.", "type": "string", "enumDescriptions": [ "Unspecified model stage.", "The underlying model is subject to lots of tunings.", "Models in this stage are for experimental purposes only.", "Models in this stage are more mature than experimental models.", "Models in this stage are considered stable and ready for production use.", "If the model is on this stage, it means that this model is on the path to deprecation in near future. Only existing customers can use this model.", "Models in this stage are deprecated. These models cannot be used.", "Models in this stage are retired. These models cannot be used." ], "enumDeprecated": [ false, true, false, false, false, false, true, false ], "enum": [ "MODEL_STAGE_UNSPECIFIED", "UNSTABLE_EXPERIMENTAL", "EXPERIMENTAL", "PREVIEW", "STABLE", "LEGACY", "DEPRECATED", "RETIRED" ] }, "retirementTime": { "description": "The time at which the model will be retired.", "type": "string", "format": "google-datetime" }, "message": { "description": "A message explaining the model status.", "type": "string" } } }, "TemplateGenerateContentRequest": { "id": "TemplateGenerateContentRequest", "description": "Request for performing a GenerateContent operation.", "type": "object", "properties": { "inputs": { "description": "Optional. Client provided data that can be used when rendering the template. When calling via JSON/http surfaces this should be wire compatible with an arbitrary JSON object.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "history": { "description": "Optional. Conversation history for multi-turn prompts and function calling.", "type": "array", "items": { "$ref": "HistoryContent" } }, "tools": { "description": "Optional. A list of tools that the model may use to generate the response.", "type": "array", "items": { "$ref": "Tool" } }, "toolConfig": { "description": "Optional. Tool configuration for any tool specified in the request.", "$ref": "ToolConfig" } } }, "HistoryContent": { "id": "HistoryContent", "description": "A single content block from the conversation history list.", "type": "object", "properties": { "role": { "description": "Optional. Indicates who generated these messages in the history. Generally this will be either 'user' or 'model'.", "type": "string" }, "parts": { "description": "List of consecutive messages from a given party.", "type": "array", "items": { "$ref": "HistoryPart" } } } }, "HistoryPart": { "id": "HistoryPart", "description": "A single message from the conversation history list. This can represent a plain text message, a request to invoke a client-side function or the output from invoking a client-side function.", "type": "object", "properties": { "text": { "description": "Optional. A plain text message from one party in the conversation.", "type": "string" }, "functionCall": { "description": "Optional. A request to invoke a client-side function", "$ref": "FunctionCall" }, "functionResponse": { "description": "Optional. The output from a client-side function invocation", "$ref": "FunctionResponse" }, "inlineData": { "description": "Optional. Inline media bytes.", "$ref": "Blob" }, "fileData": { "description": "Optional. URI based data.", "$ref": "FileData" }, "executableCode": { "description": "Optional. Code generated by the model that is meant to be executed.", "$ref": "ExecutableCode" }, "codeExecutionResult": { "description": "Optional. Result of executing the `ExecutableCode`.", "$ref": "CodeExecutionResult" }, "thought": { "description": "Optional. Indicates if the part is thought from the model.", "type": "boolean" }, "thoughtSignature": { "description": "Optional. Represents an opaque signature for the thought so it can be reused in subsequent requests.", "type": "string", "format": "byte" } } }, "FunctionCall": { "id": "FunctionCall", "description": "An element in the history the represents the model asking the client to invoke a client-side function.", "type": "object", "properties": { "id": { "description": "Required. ID of the individual function invocation assigned by the model when it requests the function invocation.", "type": "string" }, "name": { "description": "Required. The name of the function to be invoked.", "type": "string" }, "args": { "description": "Optional. Inputs to the function passed by the model", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "FunctionResponse": { "id": "FunctionResponse", "description": "An element in the history that represents the results of a function invocation.", "type": "object", "properties": { "id": { "description": "Required. ID of the individual function invocation assigned by the model when it requests the function invocation.", "type": "string" }, "name": { "description": "Required. The name of the function.", "type": "string" }, "response": { "description": "Optional. The results of the function invocation.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "Blob": { "id": "Blob", "description": "An element in the history the represents raw binary data.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data. Examples: - image/png - image/jpeg", "type": "string" }, "data": { "description": "Required. Raw bytes for media formats.", "type": "string", "format": "byte" } } }, "FileData": { "id": "FileData", "description": "An element in the history the represents an external data file.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data. Examples: - image/png - image/jpeg", "type": "string" }, "fileUri": { "description": "Required. URI.", "type": "string" } } }, "ExecutableCode": { "id": "ExecutableCode", "description": "An element in the history that represents code generated by the model that is meant to be executed, and the result returned to the model.", "type": "object", "properties": { "language": { "description": "Required. Programming language of the `code`. String representation of a Gemini ExecutableCode.Language enum http://google3/google/ai/generativelanguage/v1main/content.proto?q=symbol:%5CbLanguage%5Cb", "type": "string" }, "code": { "description": "Required. The code to be executed.", "type": "string" } } }, "CodeExecutionResult": { "id": "CodeExecutionResult", "description": "An element in the history that represents the result of executing the `ExecutableCode` and always follows a `part` containing the `ExecutableCode`.", "type": "object", "properties": { "outcome": { "description": "Required. Outcome of the code execution. String representation of a Gemini CodeExecutionResult.Outcome enum http://google3/google/ai/generativelanguage/v1main/content.proto?q=symbol:%5CbOutcome%5Cb", "type": "string" }, "output": { "description": "Optional. Contains stdout when code execution is successful; stderr or other description otherwise.", "type": "string" } } }, "Tool": { "id": "Tool", "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.", "type": "object", "properties": { "templateFunctions": { "description": "Optional. A list of user-provided functions for function calling. For functions whose names are listed in the template frontmatter, the 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.", "type": "array", "items": { "$ref": "TemplateFunction" } }, "googleMaps": { "description": "Optional. Tool to retrieve public maps data for grounding, powered by Google.", "$ref": "GoogleMaps" } } }, "TemplateFunction": { "id": "TemplateFunction", "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). This is a representation of a block of code that can be used as a `Tool` by the model and executed by the client. The name of the function must be listed in the template frontmatter for the model to be able to call it.", "type": "object", "properties": { "name": { "description": "Required. The name of the function to call.", "type": "string" }, "inputSchema": { "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\"] } ```", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "outputSchema": { "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.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleMaps": { "id": "GoogleMaps", "description": "Tool to retrieve public maps data for grounding, powered by Google.", "type": "object", "properties": { "enableWidget": { "description": "Optional. If true, include the widget context token in the response.", "type": "boolean" } } }, "ToolConfig": { "id": "ToolConfig", "description": "Tool config. This config is shared for all tools provided in the request.", "type": "object", "properties": { "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "RetrievalConfig" } } }, "RetrievalConfig": { "id": "RetrievalConfig", "description": "Retrieval config.", "type": "object", "properties": { "latLng": { "description": "Optional. The location of the user.", "$ref": "LatLng" }, "languageCode": { "description": "Optional. The language code of the user.", "type": "string" } } }, "GoogleAiGenerativelanguageV1betaPredictRequest": { "id": "GoogleAiGenerativelanguageV1betaPredictRequest", "description": "Request message for PredictionService.Predict.", "type": "object", "properties": { "instances": { "description": "Required. The instances that are the input to the prediction call.", "type": "array", "items": { "type": "any" } }, "parameters": { "description": "Optional. The parameters that govern the prediction call.", "type": "any" } } }, "GoogleAiGenerativelanguageV1betaPredictResponse": { "id": "GoogleAiGenerativelanguageV1betaPredictResponse", "description": "Response message for [PredictionService.Predict].", "type": "object", "properties": { "predictions": { "description": "The outputs of the prediction call.", "type": "array", "items": { "type": "any" } } } }, "GoogleCloudAiplatformV1beta1PredictRequest": { "id": "GoogleCloudAiplatformV1beta1PredictRequest", "description": "Request message for PredictionService.Predict.", "type": "object", "properties": { "instances": { "description": "Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.", "type": "array", "items": { "type": "any" } }, "parameters": { "description": "The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.", "type": "any" }, "labels": { "description": "Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored.", "type": "object", "additionalProperties": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1PredictResponse": { "id": "GoogleCloudAiplatformV1beta1PredictResponse", "description": "Response message for PredictionService.Predict.", "type": "object", "properties": { "predictions": { "description": "The predictions that are the output of the predictions call. The schema of any single prediction may be specified via Endpoint's DeployedModels' Model's PredictSchemata's prediction_schema_uri.", "type": "array", "items": { "type": "any" } }, "deployedModelId": { "description": "ID of the Endpoint's DeployedModel that served this prediction.", "type": "string" }, "model": { "description": "Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits.", "readOnly": true, "type": "string" }, "modelVersionId": { "description": "Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits.", "readOnly": true, "type": "string" }, "modelDisplayName": { "description": "Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits.", "readOnly": true, "type": "string" }, "metadata": { "description": "Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation.", "readOnly": true, "type": "any" } } }, "GoogleCloudAiplatformV1beta1CountTokensRequest": { "id": "GoogleCloudAiplatformV1beta1CountTokensRequest", "description": "Request message for PredictionService.CountTokens.", "type": "object", "properties": { "model": { "description": "Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`", "type": "string" }, "instances": { "description": "Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.", "type": "array", "items": { "type": "any" } }, "contents": { "description": "Optional. Input content.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "systemInstruction": { "description": "Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "tools": { "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "generationConfig": { "description": "Optional. Generation config that the model will use to generate the response.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" } } }, "GoogleCloudAiplatformV1beta1Content": { "id": "GoogleCloudAiplatformV1beta1Content", "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.", "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": { "$ref": "GoogleCloudAiplatformV1beta1Part" } } } }, "GoogleCloudAiplatformV1beta1Part": { "id": "GoogleCloudAiplatformV1beta1Part", "description": "A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.", "type": "object", "properties": { "text": { "description": "Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.", "type": "string" }, "inlineData": { "description": "Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.", "$ref": "GoogleCloudAiplatformV1beta1Blob" }, "fileData": { "description": "Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.", "$ref": "GoogleCloudAiplatformV1beta1FileData" }, "functionCall": { "description": "Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.", "$ref": "GoogleCloudAiplatformV1beta1FunctionCall" }, "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.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponse" }, "executableCode": { "description": "Optional. Code generated by the model that is intended to be executed.", "$ref": "GoogleCloudAiplatformV1beta1ExecutableCode" }, "codeExecutionResult": { "description": "Optional. The result of executing the ExecutableCode.", "$ref": "GoogleCloudAiplatformV1beta1CodeExecutionResult" }, "videoMetadata": { "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", "$ref": "GoogleCloudAiplatformV1beta1VideoMetadata" }, "thought": { "description": "Optional. Indicates whether the `part` represents the model's thought process or reasoning.", "type": "boolean" }, "thoughtSignature": { "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests.", "type": "string", "format": "byte" }, "mediaResolution": { "description": "per part media resolution. Media resolution for the input media.", "$ref": "GoogleCloudAiplatformV1beta1PartMediaResolution" } } }, "GoogleCloudAiplatformV1beta1Blob": { "id": "GoogleCloudAiplatformV1beta1Blob", "description": "A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "description": "Required. The raw bytes of the data.", "type": "string", "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" } } }, "GoogleCloudAiplatformV1beta1FileData": { "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.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1beta1FunctionCall": { "id": "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": { "description": "Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "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" } } }, "GoogleCloudAiplatformV1beta1PartialArg": { "id": "GoogleCloudAiplatformV1beta1PartialArg", "description": "Partial argument value of the function call.", "type": "object", "properties": { "nullValue": { "description": "Optional. Represents a null value.", "type": "string", "enumDescriptions": [ "Null value." ], "enum": [ "NULL_VALUE" ] }, "numberValue": { "description": "Optional. Represents a double value.", "type": "number", "format": "double" }, "stringValue": { "description": "Optional. Represents a string value.", "type": "string" }, "boolValue": { "description": "Optional. Represents a boolean value.", "type": "boolean" }, "jsonPath": { "description": "Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. \"$.foo.bar[0].data\".", "type": "string" }, "willContinue": { "description": "Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1FunctionResponse": { "id": "GoogleCloudAiplatformV1beta1FunctionResponse", "description": "The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction.", "type": "object", "properties": { "id": { "description": "Optional. The id of the function call this response is for. Populated by the client to match the corresponding function call `id`.", "type": "string" }, "name": { "description": "Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.", "type": "string" }, "response": { "description": "Required. The function response in JSON object format. Use \"output\" key to specify function output and \"error\" key to specify error details (if any). If \"output\" and \"error\" keys are not specified, then whole \"response\" is treated as function output.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "parts": { "description": "Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1FunctionResponsePart" } }, "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", "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." ], "enum": [ "SCHEDULING_UNSPECIFIED", "SILENT", "WHEN_IDLE", "INTERRUPT" ] } } }, "GoogleCloudAiplatformV1beta1FunctionResponsePart": { "id": "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.", "type": "object", "properties": { "inlineData": { "description": "Inline media bytes.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseBlob" }, "fileData": { "description": "URI based data.", "$ref": "GoogleCloudAiplatformV1beta1FunctionResponseFileData" } } }, "GoogleCloudAiplatformV1beta1FunctionResponseBlob": { "id": "GoogleCloudAiplatformV1beta1FunctionResponseBlob", "description": "Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "data": { "description": "Required. Raw bytes.", "type": "string", "format": "byte" }, "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" } } }, "GoogleCloudAiplatformV1beta1FunctionResponseFileData": { "id": "GoogleCloudAiplatformV1beta1FunctionResponseFileData", "description": "URI based data for function response.", "type": "object", "properties": { "mimeType": { "description": "Required. The IANA standard MIME type of the source data.", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1beta1ExecutableCode": { "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.", "type": "object", "properties": { "language": { "description": "Required. Programming language of the `code`.", "type": "string", "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available." ], "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ] }, "code": { "description": "Required. The code to be executed.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1CodeExecutionResult": { "id": "GoogleCloudAiplatformV1beta1CodeExecutionResult", "description": "Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used.", "type": "object", "properties": { "outcome": { "description": "Required. Outcome of the code execution.", "type": "string", "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." ], "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" } } }, "GoogleCloudAiplatformV1beta1VideoMetadata": { "id": "GoogleCloudAiplatformV1beta1VideoMetadata", "description": "Provides metadata for a video, including the start and end offsets for clipping and the frame rate.", "type": "object", "properties": { "startOffset": { "description": "Optional. The start offset of the video.", "type": "string", "format": "google-duration" }, "endOffset": { "description": "Optional. The end offset of the video.", "type": "string", "format": "google-duration" }, "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].", "type": "number", "format": "double" } } }, "GoogleCloudAiplatformV1beta1PartMediaResolution": { "id": "GoogleCloudAiplatformV1beta1PartMediaResolution", "description": "per part media resolution. Media resolution for the input media.", "type": "object", "properties": { "level": { "description": "The tokenization quality used for given media.", "type": "string", "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." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH", "MEDIA_RESOLUTION_ULTRA_HIGH" ] } } }, "GoogleCloudAiplatformV1beta1Tool": { "id": "GoogleCloudAiplatformV1beta1Tool", "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).", "type": "object", "properties": { "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": { "$ref": "GoogleCloudAiplatformV1beta1FunctionDeclaration" } }, "retrieval": { "description": "Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.", "$ref": "GoogleCloudAiplatformV1beta1Retrieval" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearch" }, "googleSearchRetrieval": { "description": "Optional. Specialized retrieval tool that is powered by Google Search.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval" }, "googleMaps": { "description": "Optional. GoogleMaps tool type. Tool to support Google Maps in Model.", "$ref": "GoogleCloudAiplatformV1beta1GoogleMaps" }, "enterpriseWebSearch": { "description": "Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.", "$ref": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch" }, "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", "$ref": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch" }, "codeExecution": { "description": "Optional. CodeExecution tool type. Enables the model to execute code as part of generation.", "$ref": "GoogleCloudAiplatformV1beta1ToolCodeExecution" }, "urlContext": { "description": "Optional. Tool to support URL context retrieval.", "$ref": "GoogleCloudAiplatformV1beta1UrlContext" }, "computerUse": { "description": "Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.", "$ref": "GoogleCloudAiplatformV1beta1ToolComputerUse" } } }, "GoogleCloudAiplatformV1beta1FunctionDeclaration": { "id": "GoogleCloudAiplatformV1beta1FunctionDeclaration", "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.", "type": "object", "properties": { "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" }, "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", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "parametersJsonSchema": { "description": "Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { \"type\": \"object\", \"properties\": { \"name\": { \"type\": \"string\" }, \"age\": { \"type\": \"integer\" } }, \"additionalProperties\": false, \"required\": [\"name\", \"age\"], \"propertyOrdering\": [\"name\", \"age\"] } ``` This field is mutually exclusive with `parameters`.", "type": "any" }, "response": { "description": "Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "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" }, "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.", "type": "string", "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." ], "enum": [ "UNSPECIFIED", "BLOCKING", "NON_BLOCKING" ] } } }, "GoogleCloudAiplatformV1beta1Schema": { "id": "GoogleCloudAiplatformV1beta1Schema", "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).", "type": "object", "properties": { "type": { "description": "Optional. Data type of the schema field.", "type": "string", "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" ], "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ] }, "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" }, "title": { "description": "Optional. Title for the schema.", "type": "string" }, "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" }, "nullable": { "description": "Optional. Indicates if the value of this field can be null.", "type": "boolean" }, "default": { "description": "Optional. Default value to use if the field is not specified.", "type": "any" }, "items": { "description": "Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "minItems": { "description": "Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.", "type": "string", "format": "int64" }, "maxItems": { "description": "Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.", "type": "string", "format": "int64" }, "enum": { "description": "Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:[\"EAST\", \"NORTH\", \"SOUTH\", \"WEST\"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:[\"101\", \"201\", \"301\"]}`", "type": "array", "items": { "type": "string" } }, "properties": { "description": "Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" } }, "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.", "type": "array", "items": { "type": "string" } }, "required": { "description": "Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.", "type": "array", "items": { "type": "string" } }, "minProperties": { "description": "Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.", "type": "string", "format": "int64" }, "maxProperties": { "description": "Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.", "type": "string", "format": "int64" }, "minimum": { "description": "Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.", "type": "number", "format": "double" }, "maximum": { "description": "Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.", "type": "number", "format": "double" }, "minLength": { "description": "Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.", "type": "string", "format": "int64" }, "maxLength": { "description": "Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.", "type": "string", "format": "int64" }, "pattern": { "description": "Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.", "type": "string" }, "example": { "description": "Optional. Example of an instance of this schema.", "type": "any" }, "anyOf": { "description": "Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Schema" } }, "additionalProperties": { "description": "Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.", "type": "any" }, "ref": { "description": "Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named \"Pet\": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the \"pet\" property is a reference to the schema node named \"Pet\". See details in https://json-schema.org/understanding-json-schema/structuring", "type": "string" }, "defs": { "description": "Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.", "type": "object", "additionalProperties": { "$ref": "GoogleCloudAiplatformV1beta1Schema" } } } }, "GoogleCloudAiplatformV1beta1Retrieval": { "id": "GoogleCloudAiplatformV1beta1Retrieval", "description": "Defines a retrieval tool that model can call to access external knowledge.", "type": "object", "properties": { "vertexAiSearch": { "description": "Set to use data source powered by Vertex AI Search.", "$ref": "GoogleCloudAiplatformV1beta1VertexAISearch" }, "vertexRagStore": { "description": "Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.", "$ref": "GoogleCloudAiplatformV1beta1VertexRagStore" }, "externalApi": { "description": "Use data source powered by external API for grounding.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApi" }, "disableAttribution": { "description": "Optional. Deprecated. This option is no longer supported.", "deprecated": true, "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1VertexAISearch": { "id": "GoogleCloudAiplatformV1beta1VertexAISearch", "description": "Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder", "type": "object", "properties": { "datastore": { "description": "Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" }, "engine": { "description": "Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`", "type": "string" }, "maxResults": { "description": "Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.", "type": "integer", "format": "int32" }, "filter": { "description": "Optional. Filter strings to be passed to the search API.", "type": "string" }, "dataStoreSpecs": { "description": "Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec" } } } }, "GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec": { "id": "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": { "dataStore": { "description": "Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1beta1VertexRagStore": { "id": "GoogleCloudAiplatformV1beta1VertexRagStore", "description": "Retrieve from Vertex RAG Store for grounding.", "type": "object", "properties": { "ragCorpora": { "description": "Optional. Deprecated. Please use rag_resources instead.", "deprecated": true, "type": "array", "items": { "type": "string" } }, "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource" } }, "similarityTopK": { "description": "Optional. Number of top k results to return from the selected corpora.", "deprecated": true, "type": "integer", "format": "int32" }, "vectorDistanceThreshold": { "description": "Optional. Only return results with vector distance smaller than the threshold.", "deprecated": true, "type": "number", "format": "double" }, "ragRetrievalConfig": { "description": "Optional. The retrieval config for the Rag query.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfig" }, "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" } } }, "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource": { "id": "GoogleCloudAiplatformV1beta1VertexRagStoreRagResource", "description": "The definition of the Rag resource.", "type": "object", "properties": { "ragCorpus": { "description": "Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`", "type": "string" }, "ragFileIds": { "description": "Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfig", "description": "Specifies the context retrieval config.", "type": "object", "properties": { "topK": { "description": "Optional. The number of contexts to retrieve.", "type": "integer", "format": "int32" }, "hybridSearch": { "description": "Optional. Config for Hybrid Search.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch" }, "filter": { "description": "Optional. Config for filters.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter" }, "ranking": { "description": "Optional. Config for ranking and reranking.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch", "description": "Config for Hybrid Search.", "type": "object", "properties": { "alpha": { "description": "Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.", "type": "number", "format": "float" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter", "description": "Config for filters.", "type": "object", "properties": { "vectorDistanceThreshold": { "description": "Optional. Only returns contexts with vector distance smaller than the threshold.", "type": "number", "format": "double" }, "vectorSimilarityThreshold": { "description": "Optional. Only returns contexts with vector similarity larger than the threshold.", "type": "number", "format": "double" }, "metadataFilter": { "description": "Optional. String for metadata filtering.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking", "description": "Config for ranking and reranking.", "type": "object", "properties": { "rankService": { "description": "Optional. Config for Rank Service.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService" }, "llmRanker": { "description": "Optional. Config for LlmRanker.", "$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService", "description": "Config for Rank Service.", "type": "object", "properties": { "modelName": { "description": "Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker": { "id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker", "description": "Config for LlmRanker.", "type": "object", "properties": { "modelName": { "description": "Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ExternalApi": { "id": "GoogleCloudAiplatformV1beta1ExternalApi", "description": "Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec.", "type": "object", "properties": { "simpleSearchParams": { "description": "Parameters for the simple search API.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams" }, "elasticSearchParams": { "description": "Parameters for the elastic search API.", "$ref": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams" }, "apiSpec": { "description": "The API spec that the external API implements.", "type": "string", "enumDescriptions": [ "Unspecified API spec. This value should not be used.", "Simple search API spec.", "Elastic search API spec." ], "enum": [ "API_SPEC_UNSPECIFIED", "SIMPLE_SEARCH", "ELASTIC_SEARCH" ] }, "endpoint": { "description": "The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search", "type": "string" }, "apiAuth": { "description": "The authentication config to access the API. Deprecated. Please use auth_config instead.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1ApiAuth" }, "authConfig": { "description": "The authentication config to access the API.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfig" } } }, "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams": { "id": "GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams", "description": "The search parameters to use for SIMPLE_SEARCH spec.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams": { "id": "GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams", "description": "The search parameters to use for the ELASTIC_SEARCH spec.", "type": "object", "properties": { "index": { "description": "The ElasticSearch index to use.", "type": "string" }, "searchTemplate": { "description": "The ElasticSearch search template to use.", "type": "string" }, "numHits": { "description": "Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1ApiAuth": { "id": "GoogleCloudAiplatformV1beta1ApiAuth", "description": "The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead.", "type": "object", "properties": { "apiKeyConfig": { "description": "The API secret.", "$ref": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig" } } }, "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig": { "id": "GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig", "description": "The API secret.", "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" } } }, "GoogleCloudAiplatformV1beta1AuthConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfig", "description": "Auth configuration to run the extension.", "type": "object", "properties": { "apiKeyConfig": { "description": "Config for API key auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig" }, "httpBasicAuthConfig": { "description": "Config for HTTP Basic auth.", "$ref": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig" }, "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" }, "authType": { "description": "Type of auth scheme.", "type": "string", "enumDescriptions": [ "", "No Auth.", "API Key Auth.", "HTTP Basic Auth.", "Google Service Account Auth.", "OAuth auth.", "OpenID Connect (OIDC) Auth." ], "enum": [ "AUTH_TYPE_UNSPECIFIED", "NO_AUTH", "API_KEY_AUTH", "HTTP_BASIC_AUTH", "GOOGLE_SERVICE_ACCOUNT_AUTH", "OAUTH", "OIDC_AUTH" ] } } }, "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig", "description": "Config for authentication with API key.", "type": "object", "properties": { "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" }, "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.", "type": "string", "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." ], "enum": [ "HTTP_IN_UNSPECIFIED", "HTTP_IN_QUERY", "HTTP_IN_HEADER", "HTTP_IN_PATH", "HTTP_IN_BODY", "HTTP_IN_COOKIE" ] } } }, "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig", "description": "Config for HTTP Basic Authentication.", "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" } } }, "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig", "description": "Config for Google Service Account Authentication.", "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" } } }, "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigOauthConfig", "description": "Config for user oauth.", "type": "object", "properties": { "accessToken": { "description": "Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig": { "id": "GoogleCloudAiplatformV1beta1AuthConfigOidcConfig", "description": "Config for user OIDC auth.", "type": "object", "properties": { "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" }, "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" } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearch", "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "type": "object", "properties": { "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: [\"amazon.com\", \"facebook.com\"].", "type": "array", "items": { "type": "string" } }, "blockingConfidence": { "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "type": "string", "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." ], "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" ] }, "searchTypes": { "description": "Optional. The set of search types to enable. If not set, web search is enabled by default.", "$ref": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes" } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchSearchTypes", "description": "Different types of search that can be enabled on the GoogleSearch tool.", "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" } } }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchWebSearch", "description": "Standard web search for grounding and related configurations. Only text results are returned.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch": { "id": "GoogleCloudAiplatformV1beta1ToolGoogleSearchImageSearch", "description": "Image search for grounding and related configurations.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1GoogleSearchRetrieval": { "id": "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" } } }, "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1DynamicRetrievalConfig", "description": "Describes the options to customize dynamic retrieval.", "type": "object", "properties": { "mode": { "description": "The mode of the predictor to be used in dynamic retrieval.", "type": "string", "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ], "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ] }, "dynamicThreshold": { "description": "Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.", "type": "number", "format": "float" } } }, "GoogleCloudAiplatformV1beta1GoogleMaps": { "id": "GoogleCloudAiplatformV1beta1GoogleMaps", "description": "Tool to retrieve public maps data for grounding, powered by Google.", "type": "object", "properties": { "enableWidget": { "description": "Optional. If true, include the widget context token in the response.", "type": "boolean" } } }, "GoogleCloudAiplatformV1beta1EnterpriseWebSearch": { "id": "GoogleCloudAiplatformV1beta1EnterpriseWebSearch", "description": "Tool to search public web data, powered by Vertex AI Search and Sec4 compliance.", "type": "object", "properties": { "excludeDomains": { "description": "Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.", "type": "array", "items": { "type": "string" } }, "blockingConfidence": { "description": "Optional. Sites with confidence level chosen & above this value will be blocked from the search results.", "type": "string", "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." ], "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" ] } } }, "GoogleCloudAiplatformV1beta1ToolParallelAiSearch": { "id": "GoogleCloudAiplatformV1beta1ToolParallelAiSearch", "description": "ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding.", "type": "object", "properties": { "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" }, "customConfigs": { "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 } }", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } } } }, "GoogleCloudAiplatformV1beta1ToolCodeExecution": { "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.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1UrlContext": { "id": "GoogleCloudAiplatformV1beta1UrlContext", "description": "Tool to support URL context.", "type": "object", "properties": {} }, "GoogleCloudAiplatformV1beta1ToolComputerUse": { "id": "GoogleCloudAiplatformV1beta1ToolComputerUse", "description": "Tool to support computer use.", "type": "object", "properties": { "environment": { "description": "Required. The environment being operated.", "type": "string", "enumDescriptions": [ "Defaults to browser.", "Operates in a web browser." ], "enum": [ "ENVIRONMENT_UNSPECIFIED", "ENVIRONMENT_BROWSER" ] }, "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.", "type": "array", "items": { "type": "string" } } } }, "GoogleCloudAiplatformV1beta1GenerationConfig": { "id": "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].", "type": "number", "format": "float" }, "topP": { "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.", "type": "number", "format": "float" }, "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.", "type": "number", "format": "float" }, "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.", "type": "integer", "format": "int32" }, "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.", "type": "integer", "format": "int32" }, "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" } }, "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" }, "logprobs": { "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.", "type": "integer", "format": "int32" }, "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].", "type": "number", "format": "float" }, "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].", "type": "number", "format": "float" }, "seed": { "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.", "type": "integer", "format": "int32" }, "responseMimeType": { "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.", "type": "string" }, "responseSchema": { "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`.", "$ref": "GoogleCloudAiplatformV1beta1Schema" }, "responseJsonSchema": { "description": "Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`.", "type": "any" }, "routingConfig": { "description": "Optional. Routing configuration.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig" }, "audioTimestamp": { "description": "Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.", "type": "boolean" }, "responseModalities": { "description": "Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.", "type": "array", "items": { "type": "string", "enumDescriptions": [ "Unspecified modality. Will be processed as text.", "Text modality.", "Image modality.", "Audio modality.", "Video modality." ], "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO", "VIDEO" ] } }, "mediaResolution": { "description": "Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.", "type": "string", "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low (64 tokens).", "Media resolution set to medium (256 tokens).", "Media resolution set to high (zoomed reframing with 256 tokens)." ], "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ] }, "speechConfig": { "description": "Optional. The speech generation config.", "$ref": "GoogleCloudAiplatformV1beta1SpeechConfig" }, "thinkingConfig": { "description": "Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig" }, "modelConfig": { "description": "Optional. Config for model selection.", "deprecated": true, "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig" }, "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" }, "imageConfig": { "description": "Optional. Config for image generation features.", "$ref": "GoogleCloudAiplatformV1beta1ImageConfig" } } }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig", "description": "The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name.", "type": "object", "properties": { "autoMode": { "description": "In this mode, the model is selected automatically based on the content of the request.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode" }, "manualMode": { "description": "In this mode, the model is specified manually.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode" } } }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode", "description": "The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference.", "type": "object", "properties": { "modelRoutingPreference": { "description": "The model routing preference.", "type": "string", "enumDescriptions": [ "Unspecified model routing preference.", "The model will be selected to prioritize the quality of the response.", "The model will be selected to balance quality and cost.", "The model will be selected to prioritize the cost of the request." ], "enum": [ "UNKNOWN", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ] } } }, "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode", "description": "The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided.", "type": "object", "properties": { "modelName": { "description": "The name of the model to use. Only public LLM models are accepted.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SpeechConfig": { "id": "GoogleCloudAiplatformV1beta1SpeechConfig", "description": "Configuration for speech generation.", "type": "object", "properties": { "voiceConfig": { "description": "The configuration for the voice to use.", "$ref": "GoogleCloudAiplatformV1beta1VoiceConfig" }, "languageCode": { "description": "Optional. The language code (ISO 639-1) for the speech synthesis.", "type": "string" }, "multiSpeakerVoiceConfig": { "description": "The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.", "$ref": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig" } } }, "GoogleCloudAiplatformV1beta1VoiceConfig": { "id": "GoogleCloudAiplatformV1beta1VoiceConfig", "description": "Configuration for a voice.", "type": "object", "properties": { "prebuiltVoiceConfig": { "description": "The configuration for a prebuilt voice.", "$ref": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig" }, "replicatedVoiceConfig": { "description": "Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.", "$ref": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig" } } }, "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig", "description": "Configuration for a prebuilt voice.", "type": "object", "properties": { "voiceName": { "description": "The name of the prebuilt voice to use.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1ReplicatedVoiceConfig", "description": "The configuration for the replicated voice to use.", "type": "object", "properties": { "mimeType": { "description": "Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.", "type": "string" }, "voiceSampleAudio": { "description": "Optional. The sample of the custom voice.", "type": "string", "format": "byte" } } }, "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig", "description": "Configuration for a multi-speaker text-to-speech request.", "type": "object", "properties": { "speakerVoiceConfigs": { "description": "Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig" } } } }, "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig": { "id": "GoogleCloudAiplatformV1beta1SpeakerVoiceConfig", "description": "Configuration for a single speaker in a multi-speaker setup.", "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" } } }, "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig", "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.", "type": "object", "properties": { "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" }, "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.", "type": "integer", "format": "int32" }, "thinkingLevel": { "description": "Optional. The number of thoughts tokens that the model should generate.", "type": "string", "enumDescriptions": [ "Unspecified thinking level.", "Low thinking level.", "Medium thinking level.", "High thinking level.", "MINIMAL thinking level." ], "enum": [ "THINKING_LEVEL_UNSPECIFIED", "LOW", "MEDIUM", "HIGH", "MINIMAL" ] } } }, "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig": { "id": "GoogleCloudAiplatformV1beta1GenerationConfigModelConfig", "description": "Config for model selection.", "type": "object", "properties": { "featureSelectionPreference": { "description": "Required. Feature selection preference.", "type": "string", "enumDescriptions": [ "Unspecified feature selection preference.", "Prefer higher quality over lower cost.", "Balanced feature selection preference.", "Prefer lower cost over higher quality." ], "enum": [ "FEATURE_SELECTION_PREFERENCE_UNSPECIFIED", "PRIORITIZE_QUALITY", "BALANCED", "PRIORITIZE_COST" ] } } }, "GoogleCloudAiplatformV1beta1ImageConfig": { "id": "GoogleCloudAiplatformV1beta1ImageConfig", "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.", "type": "object", "properties": { "imageOutputOptions": { "description": "Optional. The image output format for generated images.", "$ref": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions" }, "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" }, "personGeneration": { "description": "Optional. Controls whether the model can generate people.", "type": "string", "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." ], "enum": [ "PERSON_GENERATION_UNSPECIFIED", "ALLOW_ALL", "ALLOW_ADULT", "ALLOW_NONE" ] }, "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": { "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.", "type": "string", "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." ], "enum": [ "PROMINENT_PEOPLE_UNSPECIFIED", "ALLOW_PROMINENT_PEOPLE", "BLOCK_PROMINENT_PEOPLE" ] } } }, "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions": { "id": "GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions", "description": "The image output format for generated images.", "type": "object", "properties": { "mimeType": { "description": "Optional. The image format that the output should be saved as.", "type": "string" }, "compressionQuality": { "description": "Optional. The compression quality of the output image.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1CountTokensResponse": { "id": "GoogleCloudAiplatformV1beta1CountTokensResponse", "description": "Response message for PredictionService.CountTokens.", "type": "object", "properties": { "totalTokens": { "description": "The total number of tokens counted across all instances from the request.", "type": "integer", "format": "int32" }, "totalBillableCharacters": { "description": "The total number of billable characters counted across all instances from the request.", "type": "integer", "format": "int32" }, "promptTokensDetails": { "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } } } }, "GoogleCloudAiplatformV1beta1ModalityTokenCount": { "id": "GoogleCloudAiplatformV1beta1ModalityTokenCount", "description": "Represents a breakdown of token usage by modality. This message is used in CountTokensResponse and GenerateContentResponse.UsageMetadata to provide a detailed view of how many tokens are used by each modality (e.g., text, image, video) in a request. This is particularly useful for multimodal models, allowing you to track and manage token consumption for billing and quota purposes.", "type": "object", "properties": { "modality": { "description": "The modality that this token count applies to.", "type": "string", "enumDescriptions": [ "When a modality is not specified, it is treated as `TEXT`.", "The `Part` contains plain text.", "The `Part` contains an image.", "The `Part` contains a video.", "The `Part` contains audio.", "The `Part` contains a document, such as a PDF." ], "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ] }, "tokenCount": { "description": "The number of tokens counted for this modality.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1GenerateContentRequest": { "id": "GoogleCloudAiplatformV1beta1GenerateContentRequest", "description": "Request message for [PredictionService.GenerateContent].", "type": "object", "properties": { "contents": { "description": "Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Content" } }, "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.", "$ref": "GoogleCloudAiplatformV1beta1Content" }, "cachedContent": { "description": "Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`", "type": "string" }, "tools": { "description": "Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Tool" } }, "toolConfig": { "description": "Optional. Tool config. This config is shared for all tools provided in the request.", "$ref": "GoogleCloudAiplatformV1beta1ToolConfig" }, "labels": { "description": "Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter.", "type": "object", "additionalProperties": { "type": "string" } }, "safetySettings": { "description": "Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetySetting" } }, "modelArmorConfig": { "description": "Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied.", "$ref": "GoogleCloudAiplatformV1beta1ModelArmorConfig" }, "generationConfig": { "description": "Optional. Generation config.", "$ref": "GoogleCloudAiplatformV1beta1GenerationConfig" } } }, "GoogleCloudAiplatformV1beta1ToolConfig": { "id": "GoogleCloudAiplatformV1beta1ToolConfig", "description": "Tool config. This config is shared for all tools provided in the request.", "type": "object", "properties": { "functionCallingConfig": { "description": "Optional. Function calling config.", "$ref": "GoogleCloudAiplatformV1beta1FunctionCallingConfig" }, "retrievalConfig": { "description": "Optional. Retrieval config.", "$ref": "GoogleCloudAiplatformV1beta1RetrievalConfig" } } }, "GoogleCloudAiplatformV1beta1FunctionCallingConfig": { "id": "GoogleCloudAiplatformV1beta1FunctionCallingConfig", "description": "Function calling config.", "type": "object", "properties": { "mode": { "description": "Optional. Function calling mode.", "type": "string", "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\"." ], "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ] }, "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.", "type": "array", "items": { "type": "string" } }, "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" } } }, "GoogleCloudAiplatformV1beta1RetrievalConfig": { "id": "GoogleCloudAiplatformV1beta1RetrievalConfig", "description": "Retrieval config.", "type": "object", "properties": { "latLng": { "description": "The location of the user.", "$ref": "LatLng" }, "languageCode": { "description": "The language code of the user.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1SafetySetting": { "id": "GoogleCloudAiplatformV1beta1SafetySetting", "description": "A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category.", "type": "object", "properties": { "category": { "description": "Required. The harm category to be blocked.", "type": "string", "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." ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "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.", "type": "string", "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." ], "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", "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." ], "enum": [ "HARM_BLOCK_METHOD_UNSPECIFIED", "SEVERITY", "PROBABILITY" ] } } }, "GoogleCloudAiplatformV1beta1ModelArmorConfig": { "id": "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" } } }, "GoogleCloudAiplatformV1beta1GenerateContentResponse": { "id": "GoogleCloudAiplatformV1beta1GenerateContentResponse", "description": "Response message for [PredictionService.GenerateContent].", "type": "object", "properties": { "candidates": { "description": "Output only. Generated candidates.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Candidate" } }, "modelVersion": { "description": "Output only. The model version used to generate the response.", "readOnly": true, "type": "string" }, "createTime": { "description": "Output only. Timestamp when the request is made to the server.", "readOnly": true, "type": "string", "format": "google-datetime" }, "responseId": { "description": "Output only. response_id is used to identify each response. It is the encoding of the event_id.", "readOnly": true, "type": "string" }, "promptFeedback": { "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, "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback" }, "usageMetadata": { "description": "Usage metadata about the response(s).", "$ref": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata" } } }, "GoogleCloudAiplatformV1beta1Candidate": { "id": "GoogleCloudAiplatformV1beta1Candidate", "description": "A response candidate generated from the model.", "type": "object", "properties": { "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.", "readOnly": true, "type": "integer", "format": "int32" }, "content": { "description": "Output only. The content of the candidate.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1Content" }, "avgLogprobs": { "description": "Output only. The average log probability of the tokens in this candidate. This is a length-normalized score that can be used to compare the quality of candidates of different lengths. A higher average log probability suggests a more confident and coherent response.", "readOnly": true, "type": "number", "format": "double" }, "logprobsResult": { "description": "Output only. The detailed log probability information for the tokens in this candidate. This is useful for debugging, understanding model uncertainty, and identifying potential \"hallucinations\".", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1LogprobsResult" }, "finishReason": { "description": "Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating.", "readOnly": true, "type": "string", "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." ], "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": { "description": "Output only. A list of ratings for the safety of a response candidate. There is at most one rating per category.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" } }, "finishMessage": { "description": "Output only. Describes the reason the model stopped generating tokens in more detail. This field is returned only when `finish_reason` is set.", "readOnly": true, "type": "string" }, "citationMetadata": { "description": "Output only. A collection of citations that apply to the generated content.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1CitationMetadata" }, "groundingMetadata": { "description": "Output only. Metadata returned when grounding is enabled. It contains the sources used to ground the generated content.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadata" }, "urlContextMetadata": { "description": "Output only. Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1UrlContextMetadata" } } }, "GoogleCloudAiplatformV1beta1LogprobsResult": { "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.", "type": "object", "properties": { "topCandidates": { "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates" } }, "chosenCandidates": { "description": "A list of the chosen candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps. Note that the chosen candidate might not be in `top_candidates`.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" } } } }, "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates": { "id": "GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates", "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.", "type": "object", "properties": { "candidates": { "description": "The list of candidate tokens, sorted by log probability in descending order.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate" } } } }, "GoogleCloudAiplatformV1beta1LogprobsResultCandidate": { "id": "GoogleCloudAiplatformV1beta1LogprobsResultCandidate", "description": "A single token and its associated log probability.", "type": "object", "properties": { "token": { "description": "The token's string representation.", "type": "string" }, "tokenId": { "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.", "type": "integer", "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.", "type": "number", "format": "float" } } }, "GoogleCloudAiplatformV1beta1SafetyRating": { "id": "GoogleCloudAiplatformV1beta1SafetyRating", "description": "A safety rating for a piece of content. The safety rating contains the harm category and the harm probability level.", "type": "object", "properties": { "category": { "description": "Output only. The harm category of this rating.", "readOnly": true, "type": "string", "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." ], "enumDeprecated": [ false, false, false, false, false, true, false, false, false, false, false ], "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" ] }, "probability": { "description": "Output only. The probability of harm for this category.", "readOnly": true, "type": "string", "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." ], "enum": [ "HARM_PROBABILITY_UNSPECIFIED", "NEGLIGIBLE", "LOW", "MEDIUM", "HIGH" ] }, "probabilityScore": { "description": "Output only. The probability score of harm for this category.", "readOnly": true, "type": "number", "format": "float" }, "severity": { "description": "Output only. The severity of harm for this category.", "readOnly": true, "type": "string", "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." ], "enum": [ "HARM_SEVERITY_UNSPECIFIED", "HARM_SEVERITY_NEGLIGIBLE", "HARM_SEVERITY_LOW", "HARM_SEVERITY_MEDIUM", "HARM_SEVERITY_HIGH" ] }, "severityScore": { "description": "Output only. The severity score of harm for this category.", "readOnly": true, "type": "number", "format": "float" }, "blocked": { "description": "Output only. Indicates whether the content was blocked because of this rating.", "readOnly": true, "type": "boolean" }, "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.", "readOnly": true, "type": "string", "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." ], "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ] } } }, "GoogleCloudAiplatformV1beta1CitationMetadata": { "id": "GoogleCloudAiplatformV1beta1CitationMetadata", "description": "A collection of citations that apply to a piece of generated content.", "type": "object", "properties": { "citations": { "description": "Output only. A list of citations for the content.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1Citation" } } } }, "GoogleCloudAiplatformV1beta1Citation": { "id": "GoogleCloudAiplatformV1beta1Citation", "description": "A citation for a piece of generatedcontent.", "type": "object", "properties": { "startIndex": { "description": "Output only. The start index of the citation in the content.", "readOnly": true, "type": "integer", "format": "int32" }, "endIndex": { "description": "Output only. The end index of the citation in the content.", "readOnly": true, "type": "integer", "format": "int32" }, "uri": { "description": "Output only. The URI of the source of the citation.", "readOnly": true, "type": "string" }, "title": { "description": "Output only. The title of the source of the citation.", "readOnly": true, "type": "string" }, "license": { "description": "Output only. The license of the source of the citation.", "readOnly": true, "type": "string" }, "publicationDate": { "description": "Output only. The publication date of the source of the citation.", "readOnly": true, "$ref": "Date" } } }, "Date": { "id": "Date", "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", "type": "object", "properties": { "year": { "description": "Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year.", "type": "integer", "format": "int32" }, "month": { "description": "Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day.", "type": "integer", "format": "int32" }, "day": { "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.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1GroundingMetadata": { "id": "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.", "type": "object", "properties": { "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" } }, "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" } }, "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" }, "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.", "type": "array", "items": { "type": "string" } }, "groundingChunks": { "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunk" } }, "groundingSupports": { "description": "Optional. A list of grounding supports that connect the generated content to the grounding chunks. This field is populated when the grounding source is Google Search or Vertex AI Search.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingSupport" } }, "retrievalMetadata": { "description": "Optional. Output only. Metadata related to the retrieval grounding source.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1RetrievalMetadata" }, "googleMapsWidgetContextToken": { "description": "Optional. Output only. A token that can be used to render a Google Maps widget with the contextual data. This field is populated only when the grounding source is Google Maps.", "readOnly": true, "type": "string" }, "sourceFlaggingUris": { "description": "Optional. Output only. A list of URIs that can be used to flag a place or review for inappropriate content. This field is populated only when the grounding source is Google Maps.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri" } } } }, "GoogleCloudAiplatformV1beta1SearchEntryPoint": { "id": "GoogleCloudAiplatformV1beta1SearchEntryPoint", "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.", "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": { "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.", "type": "string", "format": "byte" } } }, "GoogleCloudAiplatformV1beta1GroundingChunk": { "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.", "type": "object", "properties": { "web": { "description": "A grounding chunk from a web page, typically from Google Search. See the `Web` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkWeb" }, "image": { "description": "A grounding chunk from an image search result. See the `Image` message for details.", "$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", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext" }, "maps": { "description": "A grounding chunk from Google Maps. See the `Maps` message for details.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMaps" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkWeb": { "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.", "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" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkImage": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkImage", "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.", "type": "object", "properties": { "sourceUri": { "description": "The URI of the image search result page.", "type": "string" }, "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" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext": { "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.", "type": "object", "properties": { "ragChunk": { "description": "Additional context for a Retrieval-Augmented Generation (RAG) retrieval result. This is populated only when the RAG retrieval tool is used.", "$ref": "GoogleCloudAiplatformV1beta1RagChunk" }, "uri": { "description": "The URI of the retrieved data source.", "type": "string" }, "title": { "description": "The title of the retrieved data source.", "type": "string" }, "text": { "description": "The content of the retrieved data source.", "type": "string" }, "documentName": { "description": "Output only. The full resource name of the referenced Vertex AI Search document. This is used to identify the specific document that was retrieved. The format is `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/branches/{branch}/documents/{document}`.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagChunk": { "id": "GoogleCloudAiplatformV1beta1RagChunk", "description": "A RagChunk includes the content of a chunk of a RagFile, and associated metadata.", "type": "object", "properties": { "text": { "description": "The content of the chunk.", "type": "string" }, "pageSpan": { "description": "If populated, represents where the chunk starts and ends in the document.", "$ref": "GoogleCloudAiplatformV1beta1RagChunkPageSpan" }, "fileId": { "description": "The ID of the file that the chunk belongs to.", "type": "string" }, "chunkId": { "description": "The ID of the chunk.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1RagChunkPageSpan": { "id": "GoogleCloudAiplatformV1beta1RagChunkPageSpan", "description": "Represents where the chunk starts and ends in the document.", "type": "object", "properties": { "firstPage": { "description": "Page where chunk starts in the document. Inclusive. 1-indexed.", "type": "integer", "format": "int32" }, "lastPage": { "description": "Page where chunk ends in the document. Inclusive. 1-indexed.", "type": "integer", "format": "int32" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMaps": { "id": "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": { "uri": { "description": "The URI of the place.", "type": "string" }, "title": { "description": "The title of the place.", "type": "string" }, "text": { "description": "The text of the place answer.", "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" }, "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.", "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources" }, "route": { "description": "Output only. Route information.", "readOnly": true, "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources": { "id": "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.", "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet" } } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet", "description": "A review snippet that is used to generate the answer.", "type": "object", "properties": { "reviewId": { "description": "The ID of the review that is being referenced.", "type": "string" }, "googleMapsUri": { "description": "A link to show the review on Google Maps.", "type": "string" }, "title": { "description": "The title of the review.", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute": { "id": "GoogleCloudAiplatformV1beta1GroundingChunkMapsRoute", "description": "Route information from Google Maps.", "type": "object", "properties": { "distanceMeters": { "description": "The total distance of the route, in meters.", "type": "integer", "format": "int32" }, "duration": { "description": "The total duration of the route.", "type": "string", "format": "google-duration" }, "encodedPolyline": { "description": "An encoded polyline of the route. See https://developers.google.com/maps/documentation/utilities/polylinealgorithm", "type": "string" } } }, "GoogleCloudAiplatformV1beta1GroundingSupport": { "id": "GoogleCloudAiplatformV1beta1GroundingSupport", "description": "A collection of supporting references for a segment or part of the model's response.", "type": "object", "properties": { "segment": { "description": "The content segment that this support message applies to.", "$ref": "GoogleCloudAiplatformV1beta1Segment" }, "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.", "type": "array", "items": { "type": "integer", "format": "int32" } }, "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" } }, "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" } } } }, "GoogleCloudAiplatformV1beta1Segment": { "id": "GoogleCloudAiplatformV1beta1Segment", "description": "A segment of the content.", "type": "object", "properties": { "partIndex": { "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.", "readOnly": true, "type": "integer", "format": "int32" }, "startIndex": { "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.", "readOnly": true, "type": "integer", "format": "int32" }, "endIndex": { "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.", "readOnly": true, "type": "integer", "format": "int32" }, "text": { "description": "Output only. The text of the segment.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1RetrievalMetadata": { "id": "GoogleCloudAiplatformV1beta1RetrievalMetadata", "description": "Metadata related to the retrieval grounding source. This is part of the `GroundingMetadata` returned when grounding is enabled.", "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.", "type": "number", "format": "float" } } }, "GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri": { "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.", "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" } } }, "GoogleCloudAiplatformV1beta1UrlContextMetadata": { "id": "GoogleCloudAiplatformV1beta1UrlContextMetadata", "description": "Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL.", "type": "object", "properties": { "urlMetadata": { "description": "Output only. A list of URL metadata, with one entry for each URL retrieved by the tool.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1UrlMetadata" } } } }, "GoogleCloudAiplatformV1beta1UrlMetadata": { "id": "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", "enumDescriptions": [ "Default value. This value is unused.", "The URL was retrieved successfully.", "The URL retrieval failed." ], "enum": [ "URL_RETRIEVAL_STATUS_UNSPECIFIED", "URL_RETRIEVAL_STATUS_SUCCESS", "URL_RETRIEVAL_STATUS_ERROR" ] } } }, "GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback": { "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.", "type": "object", "properties": { "blockReason": { "description": "Output only. The reason why the prompt was blocked.", "readOnly": true, "type": "string", "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." ], "enum": [ "BLOCKED_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "MODEL_ARMOR", "IMAGE_SAFETY", "JAILBREAK" ] }, "safetyRatings": { "description": "Output only. A list of safety ratings for the prompt. There is one rating per category.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1SafetyRating" } }, "blockReasonMessage": { "description": "Output only. A readable message that explains the reason why the prompt was blocked.", "readOnly": true, "type": "string" } } }, "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata": { "id": "GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata", "description": "Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics.", "type": "object", "properties": { "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.", "type": "integer", "format": "int32" }, "candidatesTokenCount": { "description": "The total number of tokens in the generated candidates.", "type": "integer", "format": "int32" }, "totalTokenCount": { "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`.", "type": "integer", "format": "int32" }, "toolUsePromptTokenCount": { "description": "Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable.", "readOnly": true, "type": "integer", "format": "int32" }, "thoughtsTokenCount": { "description": "Output only. The number of tokens that were part of the model's generated \"thoughts\" output, if applicable.", "readOnly": true, "type": "integer", "format": "int32" }, "cachedContentTokenCount": { "description": "Output only. The number of tokens in the cached content that was used for this request.", "readOnly": true, "type": "integer", "format": "int32" }, "promptTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the prompt.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "cacheTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the cached content.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "candidatesTokensDetails": { "description": "Output only. A detailed breakdown of the token count for each modality in the generated candidates.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "toolUsePromptTokensDetails": { "description": "Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input.", "readOnly": true, "type": "array", "items": { "$ref": "GoogleCloudAiplatformV1beta1ModalityTokenCount" } }, "trafficType": { "description": "Output only. The traffic type for this request.", "readOnly": true, "type": "string", "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 Provisioned Throughput traffic." ], "enum": [ "TRAFFIC_TYPE_UNSPECIFIED", "ON_DEMAND", "ON_DEMAND_PRIORITY", "ON_DEMAND_FLEX", "PROVISIONED_THROUGHPUT" ] } } }, "PromptTemplate": { "id": "PromptTemplate", "description": "Represents a Prompt Template resource.", "type": "object", "properties": { "name": { "description": "Identifier. The resource name of the PromptTemplate. Format: projects/{project}/locations/{location}/templates/{prompt_template}", "type": "string" }, "templateId": { "description": "Output only. Immutable. The unique ID of the PromptTemplate, which is the final component of the PromptTemplate's resource name.", "readOnly": true, "type": "string" }, "displayName": { "description": "Optional. The display name of the PromptTemplate.", "type": "string" }, "templateString": { "description": "Required. The DotPrompt raw template string.", "type": "string" }, "model": { "description": "Output only. The model name parsed from the template_string.", "readOnly": true, "type": "string" }, "createTime": { "description": "Output only. Timestamp when the PromptTemplate was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "updateTime": { "description": "Output only. Timestamp when the PromptTemplate was last updated.", "readOnly": true, "type": "string", "format": "google-datetime" }, "stateChangeTime": { "description": "Output only. Timestamp when the PromptTemplate state was last changed.", "readOnly": true, "type": "string", "format": "google-datetime" }, "etag": { "description": "Optional. The etag of the PromptTemplate. If this is provided with an update request, it must match the server's etag for the operation to succeed.", "type": "string" }, "locked": { "description": "Output only. Indicates if the PromptTemplate has been locked for mutations. It is strongly recommended that PromptTemplates used in production Apps be locked to avoid accidental distruption to live apps. To modify a PromptTemplate that has been locked, a call to ModifyLock with lock=false is required first.", "readOnly": true, "type": "boolean" } } }, "ListPromptTemplatesResponse": { "id": "ListPromptTemplatesResponse", "description": "Response message for TemplateService.ListPromptTemplates.", "type": "object", "properties": { "templates": { "description": "The PromptTemplates from the specified parent.", "type": "array", "items": { "$ref": "PromptTemplate" } }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.", "type": "string" } } }, "Empty": { "id": "Empty", "description": "A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }", "type": "object", "properties": {} }, "ModifyLockRequest": { "id": "ModifyLockRequest", "description": "Request message for TemplateService.ModifyLock.", "type": "object", "properties": { "locked": { "description": "Required. Updates the lock on a PromptTemplate to match this value. If True, mutations to the PromptTemplate will be blocked.", "type": "boolean" }, "regionalPropagationDisabled": { "description": "Optional. For global endpoints only. If true, the PromptTemplate's lock state will be modified in global only. Otherwise, the lock state will _also_ be modified in all regions where applicable.", "type": "boolean" } } }, "ModifyLockResponse": { "id": "ModifyLockResponse", "description": "Response message for TemplateService.ModifyLock.", "type": "object", "properties": {} } }, "protocol": "rest", "version_module": true, "title": "Firebase AI Logic API", "fullyEncodeReservedExpansion": true, "ownerDomain": "google.com", "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." } } } }, "description": "The Firebase AI Logic API provides programmatic access for creating, testing, and managing server prompt templates.", "parameters": { "access_token": { "type": "string", "description": "OAuth access token.", "location": "query" }, "alt": { "type": "string", "description": "Data format for response.", "default": "json", "enum": [ "json", "media", "proto" ], "enumDescriptions": [ "Responses with Content-Type of application/json", "Media download with context-dependent Content-Type", "Responses with Content-Type of application/x-protobuf" ], "location": "query" }, "callback": { "type": "string", "description": "JSONP", "location": "query" }, "fields": { "type": "string", "description": "Selector specifying which fields to include in a partial response.", "location": "query" }, "key": { "type": "string", "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.", "location": "query" }, "oauth_token": { "type": "string", "description": "OAuth 2.0 token for the current user.", "location": "query" }, "prettyPrint": { "type": "boolean", "description": "Returns response with indentations and line breaks.", "default": "true", "location": "query" }, "quotaUser": { "type": "string", "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" }, "upload_protocol": { "type": "string", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\").", "location": "query" }, "uploadType": { "type": "string", "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").", "location": "query" }, "$.xgafv": { "type": "string", "description": "V1 error format.", "enum": [ "1", "2" ], "enumDescriptions": [ "v1 error format", "v2 error format" ], "location": "query" } }, "id": "firebasevertexai:v1beta", "servicePath": "", "mtlsRootUrl": "https://firebasevertexai.mtls.googleapis.com/" }