Español – América Latina Português – Brasil The Gemini API supports content generation with images, audio, code, tools, and more. For details on each of these features, read on and check out the task-focused sample code, or read the comprehensive guides. Text generation Function calling System instructions Method: models.generateContent Path parameters Request body JSON representation JSON representation Authorization scopes Example request Text Image Audio Video PDF Chat Cache Tuned Model JSON Mode Code execution Function Calling Generation config Safety Settings System Instruction Function Calling Generation config Safety Settings System Instruction Generates a model response given an input GenerateContentRequest . Refer to the text generation guide for detailed usage information. Input capabilities differ between models, including tuned models. Refer to the model guide and tuning guide for details. Path parameters Required. The name of the Model to use for generating the completion. Format: models/{model} . It takes the form models/{model} . The request body contains data with the following structure: 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 , this is a repeated field that contains the conversation history and the latest request. 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 codeExecution . Refer to the Function calling and the Code execution guides to learn more. Optional. Tool configuration for any Tool specified in the request. Refer to the Function calling guide for a usage example. 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 safetySettings. 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, HARM_CATEGORY_JAILBREAK are supported. Refer to the guide for detailed information on available safety settings. Also refer to the Safety guidance to learn how to incorporate safety considerations in your AI applications. Optional. Developer set system instruction(s) . Currently, text only. Optional. Configuration options for model generation and outputs. Optional. The name of the content cached to use as context to serve the prediction. Format: cachedContents/{cachedContent} Optional. The service tier of the request. Optional. Configures the logging behavior for a given request. If set, it takes precedence over the project-level logging config. Example request Function Calling Generation config Safety Settings System Instruction If successful, the response body contains an instance of GenerateContentResponse . Method: models.streamGenerateContent Path parameters Request body JSON representation JSON representation Authorization scopes Example request Text Image Audio Video PDF Chat Generates a streamed response from the model given an input GenerateContentRequest . Path parameters Required. The name of the Model to use for generating the completion. Format: models/{model} . It takes the form models/{model} . The request body contains data with the following structure: 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 , this is a repeated field that contains the conversation history and the latest request. 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 codeExecution . Refer to the Function calling and the Code execution guides to learn more. Optional. Tool configuration for any Tool specified in the request. Refer to the Function calling guide for a usage example. 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 safetySettings. 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, HARM_CATEGORY_JAILBREAK are supported. Refer to the guide for detailed information on available safety settings. Also refer to the Safety guidance to learn how to incorporate safety considerations in your AI applications. Optional. Developer set system instruction(s) . Currently, text only. Optional. Configuration options for model generation and outputs. Optional. The name of the content cached to use as context to serve the prediction. Format: cachedContents/{cachedContent} Optional. The service tier of the request. Optional. Configures the logging behavior for a given request. If set, it takes precedence over the project-level logging config. Example request If successful, the response body contains a stream of GenerateContentResponse instances. GenerateContentResponse JSON representation PromptFeedback JSON representation JSON representation UsageMetadata JSON representation JSON representation ModelStatus JSON representation JSON representation 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 finishReason and in safetyRatings . 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 promptFeedback ) - Reports feedback on each candidate in finishReason and safetyRatings . Candidate responses from the model. Returns the prompt's feedback related to the content filters. Output only. Metadata on the generation requests' token usage. Output only. The model version used to generate the response. Output only. responseId is used to identify each response. Output only. The current model status of this model. A set of the feedback metadata the prompt specified in GenerateContentRequest.content . Optional. If set, the prompt was blocked and no candidates are returned. Rephrase the prompt. Ratings for safety of the prompt. There is at most one rating per category. Specifies the reason why the prompt was blocked. Metadata on the generation request's token usage. Number of tokens in the prompt. When cachedContent is set, this is still the total effective prompt size meaning this includes the number of tokens in the cached content. Number of tokens in the cached part of the prompt (the cached content) Total number of tokens across all the generated response candidates. Output only. Number of tokens present in tool-use prompt(s). Output only. Number of tokens of thoughts for thinking models. Total token count for the generation request (prompt + thoughts + response candidates). Output only. List of modalities that were processed in the request input. Output only. List of modalities of the cached content in the request input. Output only. List of modalities that were returned in the response. Output only. List of modalities that were processed for tool-use request inputs. Output only. Service tier of the request. The status of the underlying model. This is used to indicate the stage of the underlying model and the retirement time if applicable. The stage of the underlying model. The time at which the model will be retired. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . A message explaining the model status. Defines the stage of the underlying model. The underlying model is subject to lots of tunings. Models in this stage are deprecated. These models cannot be used. JSON representation GroundingAttribution JSON representation JSON representation AttributionSourceId JSON representation JSON representation GroundingPassageId JSON representation JSON representation SemanticRetrieverChunk JSON representation JSON representation GroundingMetadata JSON representation JSON representation SearchEntryPoint JSON representation JSON representation GroundingChunk JSON representation JSON representation Web JSON representation JSON representation Image JSON representation JSON representation RetrievedContext JSON representation JSON representation CustomMetadata JSON representation JSON representation StringList JSON representation JSON representation Maps JSON representation JSON representation PlaceAnswerSources JSON representation JSON representation ReviewSnippet JSON representation JSON representation GroundingSupport JSON representation JSON representation Segment JSON representation JSON representation RetrievalMetadata JSON representation JSON representation LogprobsResult JSON representation JSON representation TopCandidates JSON representation JSON representation Candidate JSON representation JSON representation UrlContextMetadata JSON representation JSON representation UrlMetadata JSON representation JSON representation UrlRetrievalStatus A response candidate generated from the model. Output only. Generated content returned from the model. Optional. Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating tokens. List of ratings for the safety of a response candidate. There is at most one rating per category. 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. Output only. Token count for this candidate. Output only. Attribution information for sources that contributed to a grounded answer. This field is populated for GenerateAnswer calls. Output only. Grounding metadata for the candidate. This field is populated for GenerateContent calls. Output only. Average log probability score of the candidate. Output only. Log-likelihood scores for the response tokens and top tokens Output only. Metadata related to url context retrieval tool. Output only. Index of the candidate in the list of response candidates. Optional. Output only. Details the reason why the model stopped generating tokens. This is populated only when finishReason is set. Defines the reason why the model stopped generating tokens. GroundingAttribution Attribution for a source that contributed to an answer. Output only. Identifier for the source contributing to this attribution. Grounding source content that makes up this attribution. AttributionSourceId Identifier for the source contributing to this attribution. Identifier for an inline passage. Identifier for a Chunk fetched via Semantic Retriever. GroundingPassageId Identifier for a part within a GroundingPassage . Output only. ID of the passage matching the GenerateAnswerRequest 's GroundingPassage.id . Output only. Index of the part within the GenerateAnswerRequest 's GroundingPassage.content . SemanticRetrieverChunk Identifier for a Chunk retrieved via Semantic Retriever specified in the GenerateAnswerRequest using SemanticRetrieverConfig . Output only. Name of the source matching the request's SemanticRetrieverConfig.source . Example: corpora/123 or corpora/123/documents/abc Output only. Name of the Chunk containing the attributed text. Example: corpora/123/documents/abc/chunks/xyz GroundingMetadata Metadata returned to client when grounding is enabled. 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. List of grounding support. Web search queries for the following-up web search. Image search queries used for grounding. Optional. Google search entry for the following-up web searches. Metadata related to retrieval in the grounding flow. 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. SearchEntryPoint Google search entry point. Optional. Web content snippet that can be embedded in a web page or an app webview. Optional. Base64 encoded JSON representing array of <search term, search url> tuple. A base64-encoded string. 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. Grounding chunk from the web. Optional. Grounding chunk from image search. Optional. Grounding chunk from context retrieved by the file search tool. Optional. Grounding chunk from Google Maps. Chunk from the web. Output only. URI reference of the chunk. Output only. Title of the chunk. Chunk from image search. The web page URI for attribution. The image asset URL. The title of the web page that the image is from. The root domain of the web page that the image is from, e.g. "example.com". RetrievedContext Chunk from context retrieved by the file search tool. Optional. User-provided metadata about the retrieved context. Optional. URI reference of the semantic retrieval document. Optional. Title of the document. Optional. Text of the chunk. Optional. Name of the FileSearchStore containing the document. Example: fileSearchStores/123 Optional. Page number of the retrieved context, if applicable. Optional. The media blob resource name for multimodal file search results. Format: fileSearchStores/{file_search_store_id}/media/{blobId} User provided metadata about the GroundingFact. The key of the metadata. Optional. The string value of the metadata. Optional. A list of string values for the metadata. Optional. The numeric value of the metadata. The expected range for this value depends on the specific key used. A list of string values. The string values of the list. A grounding chunk from Google Maps. A Maps chunk corresponds to a single place. URI reference of the place. Title of the place. Text description of the place answer. The ID of the place, in places/{placeId} format. A user can use this ID to look up that place. Sources that provide answers about the features of a given place in Google Maps. PlaceAnswerSources 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. Snippets of reviews that are used to generate answers about the features of a given place in Google Maps. Encapsulates a snippet of a user review that answers a question about the features of a specific place in Google Maps. The ID of the review snippet. A link that corresponds to the user review on Google Maps. Title of the review. GroundingSupport Grounding support. 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 groundingChunkIndices 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). 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 groundingChunkIndices. Output only. Indices into the parts field of the candidate's content. These indices specify which rendered parts are associated with this support source. Segment of the content this support belongs to. Segment of the content. The index of a Part object within its parent Content object. Start index in the given Part, measured in bytes. Offset from the start of the Part, inclusive, starting at zero. End index in the given Part, measured in bytes. Offset from the start of the Part, exclusive, starting at zero. The text corresponding to the segment from the response. RetrievalMetadata Metadata related to retrieval in the grounding flow. 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. Logprobs Result Length = total number of decoding steps. Length = total number of decoding steps. The chosen candidates may or may not be in topCandidates. Sum of log probabilities for all tokens. Candidates with top log probabilities at each decoding step. Sorted by log probability in descending order. Candidate for the logprobs token and score. The candidate’s token string value. The candidate’s token id value. The candidate's log probability. UrlContextMetadata Metadata related to url context retrieval tool. List of url context. Context of the a single url retrieval. Retrieved url by the tool. Status of the url retrieval. UrlRetrievalStatus Status of the url retrieval. CitationMetadata JSON representation CitationSource JSON representation JSON representation A collection of source attributions for a piece of content. Citations to sources for a specific response. A citation to a source for a portion of a specific response. Optional. Start of segment of the response that is attributed to this source. Index indicates the start of the segment, measured in bytes. Optional. End of the attributed segment, exclusive. Optional. URI that is attributed as a source for a portion of the text. Optional. License for the GitHub project that is attributed as a source for segment. License info is required for code citations. The category of a rating. These categories cover various kinds of harms that developers may wish to adjust. Gemini - Content that may be used to harm civic integrity. DEPRECATED: use enableEnhancedCivicAnswers instead. ModalityTokenCount JSON representation Represents token counting info for a single modality. The modality associated with this token count. Number of tokens. Content Part modality JSON representation HarmProbability 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. Required. The category for this rating. Required. The probability of harm for this content. Was this content blocked because of this rating? HarmProbability The probability that a piece of content is harmful. The classification system gives the probability of the content being unsafe. This does not indicate the severity of harm for a piece of content. JSON representation HarmBlockThreshold Safety setting, affecting the safety-blocking behavior. Passing a safety setting for a category changes the allowed probability that content is blocked. Required. The category for this setting. Required. Controls the probability threshold at which harm is blocked. HarmBlockThreshold Block at and beyond a specified harm probability. Service tier of the request. JSON representation Part JSON representation JSON representation Blob JSON representation JSON representation FunctionCall JSON representation JSON representation FunctionResponse JSON representation JSON representation FunctionResponsePart JSON representation JSON representation FunctionResponseBlob JSON representation JSON representation FileData JSON representation JSON representation ExecutableCode JSON representation JSON representation CodeExecutionResult JSON representation JSON representation ToolCall JSON representation JSON representation ToolResponse JSON representation JSON representation VideoMetadata JSON representation JSON representation MediaResolution JSON representation JSON representation MediaProcessing 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. Ordered Parts that constitute a single message. Parts may have different MIME types. 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. 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 inlineData field is filled with raw bytes. Optional. Indicates if the part is thought from the model. Optional. An opaque signature for the thought so it can be reused in subsequent requests. A base64-encoded string. 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. Optional. Media resolution for the input media. Optional. How the model processes this part's media for understanding. Only meaningful for video parts ( inlineData or fileData with video mime). Non-video parts ignore this field. Inline media bytes. A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name with the arguments and their values. 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. URI based data. Code generated by the model that is meant to be executed. Result of executing the ExecutableCode . 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. The output from a server-side ToolCall execution. This field is populated by the client with the results of executing the corresponding ToolCall . Optional. Video metadata. The metadata should only be specified while the video data is presented in inlineData or fileData. Raw media bytes. Text should not be sent as raw bytes, use the 'text' field. 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 . // Raw bytes for media formats. A base64-encoded string. A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name with the arguments and their values. Optional. Unique identifier of the function call. If populated, the client to execute the functionCall and return the response with the matching id . 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. Optional. The function parameters and values in JSON object format. FunctionResponse 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. Optional. The identifier of the function call this response is for. Populated by the client to match the corresponding function call id . 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. 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. Multimedia can be included by using a subobject containing a single "$ref" key whose value is the inlineData.display_name of a FunctionResponsePart holding the multimedia. See https://ai.google.dev/gemini-api/docs/function-calling#multimodal . Optional. Ordered Parts that constitute a function response. Parts may have different IANA MIME types. 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 willContinue=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 . 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. FunctionResponsePart 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 inlineData field is filled with raw bytes. Inline media bytes. FunctionResponseBlob Raw media bytes for function response. Text should not be sent as raw bytes, use the 'FunctionResponse.response' field. 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 . Raw bytes for media formats. A base64-encoded string. Specifies how the response should be scheduled in the conversation. URI based data. Optional. The IANA standard MIME type of the source data. 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. Optional. Unique identifier of the ExecutableCode part. The server returns the CodeExecutionResult with the matching id . Required. Programming language of the code . Required. The code to be executed. Supported programming languages for the generated code. CodeExecutionResult Result of executing the ExecutableCode . Generated only when the CodeExecution tool is used. Optional. The identifier of the ExecutableCode part this result is for. Only populated if the corresponding ExecutableCode has an id. Required. Outcome of the code execution. Optional. Contains stdout when code execution is successful, stderr or other description otherwise. Enumeration of possible outcomes of the code execution. 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 . Optional. Unique identifier of the tool call. The server returns the tool response with the matching id . Optional. The name of the tool that was called. Required. The type of tool that was called. Optional. The tool call arguments. Example: {"arg1" : "value1", "arg2" : "value2" , ...} The type of tool in the function call. 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 . Optional. The identifier of the tool call this response is for. Required. The type of tool that was called, matching the toolType in the corresponding ToolCall . Optional. The tool response.

Deprecated: Use GenerateContentRequest.processing_options instead. Metadata describes the input video content. Optional. The start offset of the video. A duration in seconds with up to nine fractional digits, ending with ' s '. Example: "3.5s" . Optional. The end offset of the video. A duration in seconds with up to nine fractional digits, ending with ' s '. Example: "3.5s" . 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]. MediaResolution Media resolution for tokenization. The tokenization quality used for given media. for Gemini API support . The media resolution level. MediaProcessing How the model processes input media for understanding. JSON representation An execution environment for an agent. Required. Output only. The ID of the environment. Sources to be mounted into the environment. Output only. The time at which the environment was created in ISO 8601 format (YYYY-MM-DDThh:mm:ssZ). Output only. The time at which the environment was last updated in ISO 8601 format (YYYY-MM-DDThh:mm:ssZ). Output only. The time at which the environment was last accessed in ISO 8601 format (YYYY-MM-DDThh:mm:ssZ). Output only. The status of the environment container. Output only. The number of files in the environment, output only. Output only. The total size of the environment files in bytes, output only. Allow only specific domains. Network egress mode. Status of the environment. Network egress mode for non-allowlist configurations. JSON representation 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 . Required. Data type. Optional. The format of the data. Any value is allowed, but most do not trigger any special functionality. Optional. The title of the schema. Optional. A brief description of the parameter. This could contain examples of use. Parameter description may be formatted as Markdown. Optional. Indicates if the value may be null. 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"]} Optional. Maximum number of the elements for Type.ARRAY. Optional. Minimum number of the elements for Type.ARRAY. Optional. Properties of Type.OBJECT. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" } . Optional. Required properties of Type.OBJECT. Optional. Minimum number of the properties for Type.OBJECT. Optional. Maximum number of the properties for Type.OBJECT. Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING Optional. Maximum length of the Type.STRING Optional. Pattern of the Type.STRING to restrict a string to a regular expression. Optional. Example of the object. Will only populated when the object is the root. Optional. The value should be validated against any (one or more) of the subschemas in the list. 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. 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. Optional. Schema of the elements of Type.ARRAY. Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER Optional. Maximum value of the Type.INTEGER and Type.NUMBER Type contains the list of OpenAPI data types as defined by https://spec.openapis.org/oas/v3.0.3#data-types JSON representation FunctionDeclaration JSON representation JSON representation GoogleSearchRetrieval JSON representation JSON representation DynamicRetrievalConfig JSON representation JSON representation GoogleSearch JSON representation JSON representation Interval JSON representation JSON representation SearchTypes JSON representation JSON representation ComputerUse JSON representation JSON representation FileSearch JSON representation JSON representation McpServer JSON representation JSON representation StreamableHttpTransport JSON representation JSON representation GoogleMaps JSON representation JSON representation 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. 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. Optional. Retrieval tool that is powered by Google search. Optional. Enables the model to execute code as part of generation. Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations. Optional. Tool to support URL context retrieval. Optional. FileSearch tool type. Tool to retrieve knowledge from Semantic Retrieval corpora. Optional. MCP Servers to connect to. Optional. Tool that allows grounding the model's response with geospatial context related to the user's query. FunctionDeclaration Structured representation of a function declaration as defined by the OpenAPI 3.03 specification . 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. 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. Required. A brief description of the function. Optional. Specifies the function Behavior. Currently only supported by the BidiGenerateContent method. 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. 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: This field is mutually exclusive with parameters . 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. 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 . Defines the function behavior. Defaults to BLOCKING . GoogleSearchRetrieval Tool to retrieve public web data for grounding, powered by Google. Specifies the dynamic retrieval configuration for the given source. DynamicRetrievalConfig Describes the options to customize dynamic retrieval. The mode of the predictor to be used in dynamic retrieval. The threshold to be used in dynamic retrieval. If not set, a system default value is used. The mode of the predictor to be used in dynamic retrieval. This type has no fields. 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. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. Optional. Filter search results to a specific time range. If customers set a start time, they must set an end time (and vice versa). Optional. The set of search types to enable. If not set, web search is enabled by default. 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. Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Different types of search that can be enabled on the GoogleSearch tool. Optional. Enables web search. Only text results are returned. Optional. Enables image search. Image bytes are returned. This type has no fields. Standard web search for grounding and related configurations. This type has no fields. Image search for grounding and related configurations. Computer Use tool type. Required. The environment being operated. 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. Optional. Whether enable the prompt injection detection check on computer-use request. Optional. Disabled safety policies for computer use. Represents the environment being operated, such as a web browser. Predefined safety policies for computer use. This type has no fields. Tool to support URL context retrieval. The FileSearch tool that retrieves knowledge from Semantic Retrieval corpora. Files are imported to Semantic Retrieval corpora using the ImportFile API. Required. The names of the fileSearchStores to retrieve from. Example: fileSearchStores/my-file-search-store-123 Optional. Metadata filter to apply to the semantic retrieval documents and chunks. Optional. The number of semantic retrieval chunks to retrieve. 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 The name of the MCPServer. A transport that can stream HTTP requests and responses. StreamableHttpTransport A transport that can stream HTTP requests and responses. Next ID: 6 The full URL for the MCPServer endpoint. Example: "https://api.example.com/mcp" Optional: Fields for authentication headers, timeouts, etc., if needed. An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" } . HTTP timeout for regular operations. A duration in seconds with up to nine fractional digits, ending with ' s '. Example: "3.5s" . Timeout for SSE read operations. A duration in seconds with up to nine fractional digits, ending with ' s '. Example: "3.5s" . Whether to close the client session when the transport closes. The GoogleMaps Tool that provides geospatial context for the user's query. 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. REST Resource: auth_tokens Resource: AuthToken JSON representation JSON representation BidiGenerateContentSetup JSON representation JSON representation GenerationConfig JSON representation JSON representation SpeechConfig JSON representation JSON representation VoiceConfig JSON representation JSON representation PrebuiltVoiceConfig JSON representation JSON representation MultiSpeakerVoiceConfig JSON representation JSON representation SpeakerVoiceConfig JSON representation JSON representation ThinkingConfig JSON representation JSON representation ImageConfig JSON representation JSON representation MediaResolution ResponseFormatConfig JSON representation JSON representation TextResponseFormat JSON representation JSON representation AudioResponseFormat JSON representation JSON representation ImageResponseFormat JSON representation JSON representation TranslationConfig JSON representation JSON representation AudioTranscriptionConfig JSON representation JSON representation LanguageHints JSON representation JSON representation RealtimeInputConfig JSON representation JSON representation AutomaticActivityDetection JSON representation JSON representation StartSensitivity ActivityHandling SessionResumptionConfig JSON representation JSON representation ContextWindowCompressionConfig JSON representation JSON representation SlidingWindow JSON representation JSON representation HistoryConfig JSON representation JSON representation Resource: AuthToken A request to create an ephemeral authentication token. Output only. Identifier. The token itself. Optional. Input only. Immutable. An optional time after which, when using the resulting token, messages in BidiGenerateContent sessions will be rejected. (Gemini may preemptively close the session after this time.) If not set then this defaults to 30 minutes in the future. If set, this value must be less than 20 hours in the future. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Optional. Input only. Immutable. The time after which new Live API sessions using the token resulting from this request will be rejected. If not set this defaults to 60 seconds in the future. If set, this value must be less than 20 hours in the future. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Optional. Input only. Immutable. If fieldMask is empty, and bidiGenerateContentSetup is not present, then the effective BidiGenerateContentSetup message is taken from the Live API connection. If fieldMask is empty, and bidiGenerateContentSetup is present, then the effective BidiGenerateContentSetup message is taken entirely from bidiGenerateContentSetup in this request. The setup message from the Live API connection is ignored. If fieldMask is not empty, then the corresponding fields from bidiGenerateContentSetup will overwrite the fields from the setup message in the Live API connection. This is a comma-separated list of fully qualified names of fields. Example: "user.displayName,photo" . Optional. Input only. Immutable. Configuration specific to BidiGenerateContent . Optional. Input only. Immutable. The number of times the token can be used. If this value is zero then no limit is applied. Resuming a Live API session does not count as a use. If unspecified, the default is 1. BidiGenerateContentSetup Message to be sent in the first (and only in the first) BidiGenerateContentClientMessage . Contains configuration that will apply for the duration of the streaming RPC. Clients should wait for a BidiGenerateContentSetupComplete message before sending any additional messages. Required. The model's resource name. This serves as an ID for the Model to use. Format: models/{model} Optional. Generation config. The following fields are not supported: responseLogprobs responseMimeType responseJsonSchema skipResponseCache audio_timestamp 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. 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. Optional. Configures the handling of realtime input. Optional. Configures session resumption mechanism. If included, the server will send SessionResumptionUpdate messages. Optional. Configures a context window compression mechanism. If included, the server will automatically reduce the size of the context when it exceeds the configured length. Optional. If set, enables transcription of voice input. The transcription aligns with the input audio language, if configured. Optional. If set, enables transcription of the model's audio output. The transcription aligns with the language code specified for the output audio, if configured. Optional. Configures the exchange of history between the client and the server. GenerationConfig Configuration options for model generation and outputs. Not all parameters are configurable for every model. 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. 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 for a list of all supported text MIME types. Optional. Output schema of the generated candidate text. Schemas must be a subset of the OpenAPI schema and can be objects, primitives or arrays. If set, a compatible responseMimeType must also be set. Compatible MIME types: application/json : Schema for JSON response. Refer to the JSON text generation guide for more details. Optional. Output schema of the generated response. This is an alternative to responseSchema that accepts JSON Schema . If set, responseSchema must be omitted, but responseMimeType is required. While the full JSON Schema may be sent, not all features are supported. Specifically, only the following properties are supported: enum (for strings and numbers) oneOf (interpreted the same as anyOf ) additionalProperties 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. Optional. An internal detail. Use responseJsonSchema rather than this field. 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. 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) 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. 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]. 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 topK attribute indicates that the model doesn't apply top-k sampling and doesn't allow setting topK on requests. 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 topK most probable tokens. Models running with nucleus sampling don't allow topK setting. Note: The default value varies by Model and is specified by the Model.top_p attribute returned from the getModel function. An empty topK attribute indicates that the model doesn't apply top-k sampling and doesn't allow setting topK on requests. Optional. Seed used in decoding. If not set, the request uses a randomly generated seed. 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 frequencyPenalty 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. 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 maxOutputTokens limit. Optional. If true, export the logprobs results in response. Optional. Only valid if responseLogprobs=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]. Optional. Enables enhanced civic answers. It may not be available for all models. Optional. The speech generation config. Optional. Config for thinking features. An error will be returned if this field is set for models that don't support thinking. Optional. Config for image generation. An error will be returned if this field is set for models that don't support these config options. Optional. If specified, the media resolution specified will be used. Optional. If enabled, the model will detect emotions and adapt its responses accordingly. Optional. Configuration for the response output format. Allows specifying output configuration per modality (text, audio, image) in a flat structure. Optional. Config for translation. Optional. Config for audio transcription (speech recognition). Supported modalities of the response. Config for speech generation and transcription. The configuration in case of single-voice output. Optional. The configuration for the multi-speaker setup. It is mutually exclusive with the voiceConfig field. Optional. The IETF BCP-47 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 . The configuration for the voice to use. The configuration for the prebuilt voice to use. PrebuiltVoiceConfig The configuration for the prebuilt speaker to use. The name of the preset voice to use. MultiSpeakerVoiceConfig The configuration for the multi-speaker setup. Required. All the enabled speaker voices. SpeakerVoiceConfig The configuration for a single speaker in a multi speaker setup. Required. The name of the speaker to use. Should be the same as in the prompt. Required. The configuration for the voice to use. Config for thinking features. Indicates whether to include thoughts in the response. If true, thoughts are returned only when available. The number of thoughts tokens that the model should generate. 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 for more details. Recommended for Gemini 3 or later models. Use with earlier models results in an error. Allow user to specify how much to think using enum instead of integer budget. Config for image generation features. 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. Optional. Specifies the size of generated images. Supported values are 512 , 1K , 2K , 4K . If not specified, the model will use default value 1K . MediaResolution Media resolution for the input media. ResponseFormatConfig Configuration for the response output format. This is a flat object where each optional sub-field configures a specific output modality. Optional. Text output format configuration. Optional. Audio output format configuration. Optional. Image output format configuration. TextResponseFormat Configuration for text output format. Optional. The MIME type of the text output. Optional. The JSON schema that the output should conform to. Only applicable when mimeType is APPLICATION_JSON. Supported MIME types for text output. AudioResponseFormat Configuration for audio output format. Optional. The MIME type of the audio output. Optional. The delivery mode for the audio output. Optional. Sample rate in Hz. Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus). Supported MIME types for audio output. Delivery mode for audio output. ImageResponseFormat Configuration for image output format. Optional. The MIME type of the image output. Optional. The delivery mode for the image output. Optional. The aspect ratio for the image output. Optional. The size of the image output. Supported MIME types for image output. Delivery mode for image output. Supported aspect ratios for image output. Supported image sizes for image output. TranslationConfig Config for translation features. Required. The target language for translation. Supported values are BCP-47 language codes (e.g. "en", "es", "fr"). Optional. If true, the model will generate audio when the target language is spoken, essentially it will parrot the input. If false, we will not produce audio for the target language. AudioTranscriptionConfig The audio transcription configuration. Optional. BCP-47 language codes providing hints about the languages present in the audio. If omitted or empty, defaults to automatic language detection. Optional. A list of phrases used for speech adaptation, which biases the ASR model to improve recognition of these specific terms. Optional. A list of custom vocabulary phrases to bias the speech recognition model toward recognizing specific terms (product names, proper nouns, jargon). Optional. Configures word-level timestamp generation. Optional. Configures speaker diarization. Optional. The model will detect the language automatically. Optional. Specifies one or more languages in the audio. This type has no fields. Indicates the language of the audio should be automatically detected. Provides hints to the model about possible languages present in the audio. Required. BCP-47 language codes. RealtimeInputConfig Configures the realtime input behavior in BidiGenerateContent . Optional. If not set, automatic activity detection is enabled by default. If automatic voice detection is disabled, the client must send activity signals. Optional. Defines what effect activity has. Optional. Defines which input is included in the user's turn. AutomaticActivityDetection Configures automatic detection of activity. Optional. If enabled (the default), detected voice and text input count as activity. If disabled, the client must send activity signals. Optional. Determines how likely speech is to be detected. Optional. The required duration of detected speech before start-of-speech is committed. The lower this value, the more sensitive the start-of-speech detection is and shorter speech can be recognized. However, this also increases the probability of false positives. Optional. Determines how likely detected speech is ended. Optional. The required duration of detected non-speech (e.g. silence) before end-of-speech is committed. The larger this value, the longer speech gaps can be without interrupting the user's activity but this will increase the model's latency. StartSensitivity Determines how start of speech is detected. Determines how end of speech is detected. ActivityHandling The different ways of handling user activity. Options about which input is included in the user's turn. SessionResumptionConfig Session resumption configuration. This message is included in the session configuration as BidiGenerateContentSetup.session_resumption . If configured, the server will send SessionResumptionUpdate messages. The handle of a previous session. If not present then a new session is created. Session handles come from SessionResumptionUpdate.token values in previous connections. ContextWindowCompressionConfig Enables context window compression — a mechanism for managing the model's context window so that it does not exceed a given length. A sliding-window mechanism. The number of tokens (before running a turn) required to trigger a context window compression. This can be used to balance quality against latency as shorter context windows may result in faster model responses. However, any compression operation will cause a temporary latency increase, so they should not be triggered frequently. If not set, the default is 80% of the model's context window limit. This leaves 20% for the next user request/model response. The SlidingWindow method operates by discarding content at the beginning of the context window. The resulting context will always begin at the start of a USER role turn. System instructions and any BidiGenerateContentSetup.prefix_turns will always remain at the beginning of the result. The target number of tokens to keep. The default value is triggerTokens/2. Discarding parts of the context window causes a temporary latency increase so this value should be calibrated to avoid frequent compression operations. History configuration. This message is included in the session configuration as BidiGenerateContentSetup.history_config . Configures the exchange of history messages. Optional. If true, after sending setupComplete , the server will wait and at first process clientContent messages until turnComplete is true . This initial history will not trigger a model call and may end with role MODEL . After turnComplete is true , the client can start the realtime conversation via realtimeInput . Method: auth_tokens.create Authorization scopes Creates a token that can be used to constrain the behavior of a BidiGenerateContent session. The request body contains an instance of AuthToken . Optional. Input only. Immutable. An optional time after which, when using the resulting token, messages in BidiGenerateContent sessions will be rejected. (Gemini may preemptively close the session after this time.) If not set then this defaults to 30 minutes in the future. If set, this value must be less than 20 hours in the future. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Optional. Input only. Immutable. The time after which new Live API sessions using the token resulting from this request will be rejected. If not set this defaults to 60 seconds in the future. If set, this value must be less than 20 hours in the future. Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z" , "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30" . Optional. Input only. Immutable. If fieldMask is empty, and bidiGenerateContentSetup is not present, then the effective BidiGenerateContentSetup message is taken from the Live API connection. If fieldMask is empty, and bidiGenerateContentSetup is present, then the effective BidiGenerateContentSetup message is taken entirely from bidiGenerateContentSetup in this request. The setup message from the Live API connection is ignored. If fieldMask is not empty, then the corresponding fields from bidiGenerateContentSetup will overwrite the fields from the setup message in the Live API connection. This is a comma-separated list of fully qualified names of fields. Example: "user.displayName,photo" . Optional. Input only. Immutable. Configuration specific to BidiGenerateContent . Optional. Input only. Immutable. The number of times the token can be used. If this value is zero then no limit is applied. Resuming a Live API session does not count as a use. If unspecified, the default is 1. If successful, the response body contains a newly created instance of AuthToken . Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Last updated 2026-08-17 UTC.