{ "ownerDomain": "google.com", "ownerName": "Google", "rootUrl": "https://generativelanguage.googleapis.com/", "version_module": true, "mtlsRootUrl": "https://generativelanguage.mtls.googleapis.com/", "servicePath": "", "fullyEncodeReservedExpansion": true, "batchPath": "batch", "auth": { "oauth2": { "scopes": { "https://www.googleapis.com/auth/devstorage.read_only": { "description": "View your data in Google Cloud Storage" } } } }, "schemas": { "RetrievalConfig": { "description": "Retrieval config.", "properties": { "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": { "$ref": "LatLng", "description": "Optional. The location of the user." } }, "type": "object", "id": "RetrievalConfig" }, "FunctionCall": { "id": "FunctionCall", "type": "object", "description": "A predicted `FunctionCall` returned from the model that contains a string representing the `FunctionDeclaration.name` with the arguments and their values.", "properties": { "name": { "type": "string", "description": "Required. The name of the function to call. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 128." }, "args": { "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "description": "Optional. The function parameters and values in JSON object format." }, "id": { "description": "Optional. Unique identifier of the function call. If populated, the client to execute the `function_call` and return the response with the matching `id`.", "type": "string" } } }, "PromptFeedback": { "type": "object", "id": "PromptFeedback", "description": "A set of the feedback metadata the prompt specified in `GenerateContentRequest.content`.", "properties": { "blockReason": { "type": "string", "description": "Optional. If set, the prompt was blocked and no candidates are returned. Rephrase the prompt.", "enum": [ "BLOCK_REASON_UNSPECIFIED", "SAFETY", "OTHER", "BLOCKLIST", "PROHIBITED_CONTENT", "IMAGE_SAFETY" ], "enumDescriptions": [ "Default value. This value is unused.", "Prompt was blocked due to safety reasons. Inspect `safety_ratings` to understand which safety category blocked it.", "Prompt was blocked due to unknown reasons.", "Prompt was blocked due to the terms which are included from the terminology blocklist.", "Prompt was blocked due to prohibited content.", "Candidates blocked due to unsafe image generation content." ] }, "safetyRatings": { "description": "Ratings for safety of the prompt. There is at most one rating per category.", "type": "array", "items": { "$ref": "SafetyRating" } } } }, "GenerateContentResponse": { "properties": { "responseId": { "readOnly": true, "description": "Output only. response_id is used to identify each response.", "type": "string" }, "modelVersion": { "description": "Output only. The model version used to generate the response.", "readOnly": true, "type": "string" }, "promptFeedback": { "$ref": "PromptFeedback", "description": "Returns the prompt's feedback related to the content filters." }, "candidates": { "items": { "$ref": "Candidate" }, "description": "Candidate responses from the model.", "type": "array" }, "usageMetadata": { "$ref": "UsageMetadata", "description": "Output only. Metadata on the generation requests' token usage.", "readOnly": true }, "modelStatus": { "readOnly": true, "$ref": "ModelStatus", "description": "Output only. The current model status of this model." } }, "id": "GenerateContentResponse", "type": "object", "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`." }, "ModelStatus": { "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.", "enumDeprecated": [ false, true, false, false, false, false, true, false ], "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." ], "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" } }, "id": "ModelStatus" }, "CountTokensRequest": { "id": "CountTokensRequest", "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`.", "properties": { "generateContentRequest": { "$ref": "GenerateContentRequest", "description": "Optional. The overall input given to the `Model`. This includes the prompt as well as other model steering information like [system instructions](https://ai.google.dev/gemini-api/docs/system-instructions), and/or function declarations for [function calling](https://ai.google.dev/gemini-api/docs/function-calling). `Model`s/`Content`s and `generate_content_request`s are mutually exclusive. You can either send `Model` + `Content`s or a `generate_content_request`, but never both." }, "contents": { "items": { "$ref": "Content" }, "description": "Optional. The input given to the model as a prompt. This field is ignored when `generate_content_request` is set.", "type": "array" } }, "type": "object" }, "ListModelsResponse": { "type": "object", "properties": { "models": { "description": "The returned Models.", "items": { "$ref": "Model" }, "type": "array" }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no more pages.", "type": "string" } }, "description": "Response from `ListModel` containing a paginated list of Models.", "id": "ListModelsResponse" }, "DownloadParameters": { "type": "object", "id": "DownloadParameters", "properties": { "allowGzipCompression": { "type": "boolean", "description": "A boolean to be returned in the response to Scotty. Allows/disallows gzip encoding of the payload content when the server thinks it's advantageous (hence, does not guarantee compression) which allows Scotty to GZip the response to the client." }, "ignoreRange": { "description": "Determining whether or not Apiary should skip the inclusion of any Content-Range header on its response to Scotty.", "type": "boolean" } }, "description": "Parameters specific to media downloads." }, "EmbedContentBatch": { "description": "A resource representing a batch of `EmbedContent` requests.", "id": "EmbedContentBatch", "type": "object", "properties": { "model": { "type": "string", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`." }, "name": { "readOnly": true, "description": "Output only. Identifier. Resource name of the batch. Format: `batches/{batch_id}`.", "type": "string" }, "createTime": { "type": "string", "description": "Output only. The time at which the batch was created.", "format": "google-datetime", "readOnly": true }, "inputConfig": { "description": "Required. Input configuration of the instances on which batch processing are performed.", "$ref": "InputEmbedContentConfig" }, "priority": { "format": "int64", "description": "Optional. The priority of the batch. Batches with a higher priority value will be processed before batches with a lower priority value. Negative values are allowed. Default is 0.", "type": "string" }, "output": { "readOnly": true, "$ref": "EmbedContentBatchOutput", "description": "Output only. The output of the batch request." }, "updateTime": { "description": "Output only. The time at which the batch was last updated.", "format": "google-datetime", "readOnly": true, "type": "string" }, "endTime": { "readOnly": true, "type": "string", "format": "google-datetime", "description": "Output only. The time at which the batch processing completed." }, "displayName": { "description": "Required. The user-defined name of this batch.", "type": "string" }, "state": { "enumDescriptions": [ "The batch state is unspecified.", "The service is preparing to run the batch.", "The batch is in progress.", "The batch completed successfully.", "The batch failed.", "The batch has been cancelled.", "The batch has expired." ], "description": "Output only. The state of the batch.", "readOnly": true, "enum": [ "BATCH_STATE_UNSPECIFIED", "BATCH_STATE_PENDING", "BATCH_STATE_RUNNING", "BATCH_STATE_SUCCEEDED", "BATCH_STATE_FAILED", "BATCH_STATE_CANCELLED", "BATCH_STATE_EXPIRED" ], "type": "string" }, "batchStats": { "$ref": "EmbedContentBatchStats", "description": "Output only. Stats about the batch.", "readOnly": true } } }, "CustomMetadata": { "type": "object", "id": "CustomMetadata", "properties": { "stringListValue": { "$ref": "StringList", "description": "The StringList value of the metadata to store." }, "numericValue": { "type": "number", "description": "The numeric value of the metadata to store.", "format": "float" }, "stringValue": { "description": "The string value of the metadata to store.", "type": "string" }, "key": { "description": "Required. The key of the metadata to store.", "type": "string" } }, "description": "User provided metadata stored as key-value pairs." }, "ContentTypeInfo": { "description": "Detailed Content-Type information from Scotty. The Content-Type of the media will typically be filled in by the header or Scotty's best_guess, but this extended information provides the backend with more information so that it can make a better decision if needed. This is only used on media upload requests from Scotty.", "properties": { "fromFileName": { "description": "The content type of the file derived from the file extension of the original file name used by the client.", "type": "string" }, "fusionIdDetectionMetadata": { "type": "string", "format": "byte", "description": "Metadata information from Fusion ID detection. Serialized FusionIdDetectionMetadata proto. Only set if from_fusion_id is set." }, "fromFusionId": { "description": "The content type of the file detected by Fusion ID. go/fusionid", "type": "string" }, "fromUrlPath": { "type": "string", "description": "The content type of the file derived from the file extension of the URL path. The URL path is assumed to represent a file name (which is typically only true for agents that are providing a REST API)." }, "fromBytes": { "type": "string", "description": "The content type of the file derived by looking at specific bytes (i.e. \"magic bytes\") of the actual file." }, "fromHeader": { "description": "The content type of the file as specified in the request headers, multipart headers, or RUPIO start request.", "type": "string" }, "bestGuess": { "description": "Scotty's best guess of what the content type of the file is.", "type": "string" } }, "id": "ContentTypeInfo", "type": "object" }, "CreateFileRequest": { "description": "Request for `CreateFile`.", "type": "object", "id": "CreateFileRequest", "properties": { "file": { "description": "Optional. Metadata for the file to create.", "$ref": "File" } } }, "GenerateContentRequest": { "id": "GenerateContentRequest", "type": "object", "properties": { "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": { "$ref": "Tool" } }, "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "type": "string" }, "systemInstruction": { "description": "Optional. Developer set [system instruction(s)](https://ai.google.dev/gemini-api/docs/system-instructions). Currently, text only.", "$ref": "Content" }, "generationConfig": { "$ref": "GenerationConfig", "description": "Optional. Configuration options for model generation and outputs." }, "serviceTier": { "type": "string", "description": "Optional. The service tier of the request.", "enum": [ "unspecified", "standard", "flex", "priority" ], "enumDescriptions": [ "Default service tier, which is standard.", "Standard service tier.", "Flex service tier.", "Priority service tier." ] }, "store": { "description": "Optional. Configures the logging behavior for a given request. If set, it takes precedence over the project-level logging config.", "type": "boolean" }, "toolConfig": { "$ref": "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." }, "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, HARM_CATEGORY_JAILBREAK 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": { "$ref": "SafetySetting" } }, "contents": { "items": { "$ref": "Content" }, "type": "array", "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." }, "cachedContent": { "type": "string", "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}`" } }, "description": "Request to generate a completion from the model." }, "GenerateContentBatchOutput": { "description": "The output of a batch request. This is returned in the `BatchGenerateContentResponse` or the `GenerateContentBatch.output` field.", "type": "object", "properties": { "inlinedResponses": { "readOnly": true, "description": "Output only. The responses to the requests in the batch. Returned when the batch was built using inlined requests. The responses will be in the same order as the input requests.", "$ref": "InlinedResponses" }, "responsesFile": { "type": "string", "description": "Output only. The file ID of the file containing the responses. The file will be a JSONL file with a single response per line. The responses will be `GenerateContentResponse` messages formatted as JSON. The responses will be written in the same order as the input requests.", "readOnly": true } }, "id": "GenerateContentBatchOutput" }, "SafetySetting": { "type": "object", "id": "SafetySetting", "properties": { "category": { "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.", "**Gemini** - Prompts attempting to bypass or subvert the model's safety guidelines (jailbreak attempts)." ], "enumDeprecated": [ false, false, false, false, false, false, false, false, false, false, false, true, false ], "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", "HARM_CATEGORY_JAILBREAK" ], "description": "Required. The category for this setting.", "type": "string" }, "threshold": { "type": "string", "description": "Required. Controls the probability threshold at which harm is blocked.", "enum": [ "HARM_BLOCK_THRESHOLD_UNSPECIFIED", "BLOCK_LOW_AND_ABOVE", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_ONLY_HIGH", "BLOCK_NONE", "OFF" ], "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." ] } }, "description": "Safety setting, affecting the safety-blocking behavior. Passing a safety setting for a category changes the allowed probability that content is blocked." }, "GroundingSupport": { "properties": { "renderedParts": { "type": "array", "items": { "format": "int32", "type": "integer" }, "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 }, "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" } }, "segment": { "description": "Segment of the content this support belongs to.", "$ref": "Segment" }, "groundingChunkIndices": { "type": "array", "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).", "items": { "type": "integer", "format": "int32" } } }, "id": "GroundingSupport", "description": "Grounding support.", "type": "object" }, "ListCachedContentsResponse": { "type": "object", "id": "ListCachedContentsResponse", "description": "Response with CachedContents list.", "properties": { "cachedContents": { "description": "List of cached contents.", "items": { "$ref": "CachedContent" }, "type": "array" }, "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" } } }, "LatLng": { "properties": { "longitude": { "type": "number", "format": "double", "description": "The longitude in degrees. It must be in the range [-180.0, +180.0]." }, "latitude": { "format": "double", "type": "number", "description": "The latitude in degrees. It must be in the range [-90.0, +90.0]." } }, "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", "id": "LatLng" }, "ReviewSnippet": { "description": "Encapsulates a snippet of a user review that answers a question about the features of a specific place in Google Maps.", "id": "ReviewSnippet", "properties": { "title": { "description": "Title of the review.", "type": "string" }, "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" } }, "type": "object" }, "Blob": { "id": "Blob", "type": "object", "properties": { "data": { "format": "byte", "description": "Raw bytes for media formats.", "type": "string" }, "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" } }, "description": "Raw media bytes. Text should not be sent as raw bytes, use the 'text' field." }, "FileData": { "id": "FileData", "type": "object", "description": "URI based data.", "properties": { "mimeType": { "description": "Optional. The IANA standard MIME type of the source data.", "type": "string" }, "fileUri": { "description": "Required. URI.", "type": "string" } } }, "LogprobsResultCandidate": { "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.", "format": "int32", "type": "integer" }, "logProbability": { "format": "float", "description": "The candidate's log probability.", "type": "number" } }, "id": "LogprobsResultCandidate" }, "DynamicRetrievalConfig": { "description": "Describes the options to customize dynamic retrieval.", "type": "object", "id": "DynamicRetrievalConfig", "properties": { "mode": { "enum": [ "MODE_UNSPECIFIED", "MODE_DYNAMIC" ], "description": "The mode of the predictor to be used in dynamic retrieval.", "enumDescriptions": [ "Always trigger retrieval.", "Run retrieval only when system decides it is necessary." ], "type": "string" }, "dynamicThreshold": { "type": "number", "description": "The threshold to be used in dynamic retrieval. If not set, a system default value is used.", "format": "float" } } }, "SemanticRetrieverChunk": { "properties": { "chunk": { "readOnly": true, "description": "Output only. Name of the `Chunk` containing the attributed text. Example: `corpora/123/documents/abc/chunks/xyz`", "type": "string" }, "source": { "type": "string", "description": "Output only. Name of the source matching the request's `SemanticRetrieverConfig.source`. Example: `corpora/123` or `corpora/123/documents/abc`", "readOnly": true } }, "type": "object", "description": "Identifier for a `Chunk` retrieved via Semantic Retriever specified in the `GenerateAnswerRequest` using `SemanticRetrieverConfig`.", "id": "SemanticRetrieverChunk" }, "EmbeddingUsageMetadata": { "properties": { "promptTokenCount": { "readOnly": true, "description": "Output only. Number of tokens in the prompt.", "type": "integer", "format": "int32" }, "promptTokenDetails": { "type": "array", "items": { "$ref": "ModalityTokenCount" }, "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true } }, "description": "Metadata on the usage of the embedding request.", "type": "object", "id": "EmbeddingUsageMetadata" }, "EmbedContentRequest": { "type": "object", "id": "EmbedContentRequest", "description": "Request containing the `Content` for the model to embed.", "properties": { "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}`", "type": "string" }, "taskType": { "enum": [ "TASK_TYPE_UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ], "deprecated": true, "type": "string", "enumDescriptions": [ "Unset value, which will default to one of the other enum values.", "Specifies the given text is a query in a search/retrieval setting.", "Specifies the given text is a document from the corpus being searched.", "Specifies the given text will be used for STS.", "Specifies that the given text will be classified.", "Specifies that the embeddings will be used for clustering.", "Specifies that the given text will be used for question answering.", "Specifies that the given text will be used for fact verification.", "Specifies that the given text will be used for code retrieval." ], "description": "Optional. Deprecated: Please use EmbedContentConfig.task_type instead. Optional task type for which the embeddings will be used. Not supported on earlier models (`models/embedding-001`)." }, "outputDimensionality": { "deprecated": true, "type": "integer", "description": "Optional. Deprecated: Please use EmbedContentConfig.output_dimensionality instead. Optional reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end. Supported by newer models since 2024 only. You cannot set this value if using the earlier model (`models/embedding-001`).", "format": "int32" }, "content": { "description": "Required. The content to embed. Only the `parts.text` fields will be counted.", "$ref": "Content" }, "title": { "deprecated": true, "description": "Optional. Deprecated: Please use EmbedContentConfig.title instead. An optional title for the text. Only applicable when TaskType is `RETRIEVAL_DOCUMENT`. Note: Specifying a `title` for `RETRIEVAL_DOCUMENT` provides better quality embeddings for retrieval.", "type": "string" }, "embedContentConfig": { "description": "Optional. Configuration for the EmbedContent request.", "$ref": "EmbedContentConfig" } } }, "CountTokensResponse": { "properties": { "totalTokens": { "format": "int32", "description": "The number of tokens that the `Model` tokenizes the `prompt` into. Always non-negative.", "type": "integer" }, "promptTokensDetails": { "type": "array", "items": { "$ref": "ModalityTokenCount" }, "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true }, "cachedContentTokenCount": { "description": "Number of tokens in the cached part of the prompt (the cached content).", "format": "int32", "type": "integer" }, "cacheTokensDetails": { "type": "array", "description": "Output only. List of modalities that were processed in the cached content.", "items": { "$ref": "ModalityTokenCount" }, "readOnly": true } }, "id": "CountTokensResponse", "description": "A response from `CountTokens`. It returns the model's `token_count` for the `prompt`.", "type": "object" }, "Segment": { "description": "Segment of the content.", "id": "Segment", "properties": { "text": { "description": "The text corresponding to the segment from the response.", "type": "string" }, "startIndex": { "type": "integer", "format": "int32", "description": "Start index in the given Part, measured in bytes. Offset from the start of the Part, inclusive, starting at zero." }, "endIndex": { "description": "End index in the given Part, measured in bytes. Offset from the start of the Part, exclusive, starting at zero.", "format": "int32", "type": "integer" }, "partIndex": { "format": "int32", "description": "The index of a Part object within its parent Content object.", "type": "integer" } }, "type": "object" }, "CancelOperationRequest": { "description": "The request message for Operations.CancelOperation.", "id": "CancelOperationRequest", "type": "object", "properties": {} }, "RegisterFilesResponse": { "id": "RegisterFilesResponse", "type": "object", "properties": { "files": { "type": "array", "items": { "$ref": "File" }, "description": "The registered files to be used when calling GenerateContent." } }, "description": "Response for `RegisterFiles`." }, "Status": { "description": "The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors).", "properties": { "message": { "description": "A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.", "type": "string" }, "code": { "type": "integer", "description": "The status code, which should be an enum value of google.rpc.Code.", "format": "int32" }, "details": { "description": "A list of messages that carry the error details. There is a common set of message types for APIs to use.", "items": { "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "type": "object" }, "type": "array" } }, "id": "Status", "type": "object" }, "MediaResolution": { "id": "MediaResolution", "properties": { "level": { "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH", "MEDIA_RESOLUTION_ULTRA_HIGH" ], "enumDescriptions": [ "Media resolution has not been set.", "Media resolution set to low.", "Media resolution set to medium.", "Media resolution set to high.", "Media resolution set to ultra high." ], "type": "string", "description": "The tokenization quality used for given media. for Gemini API support ." } }, "type": "object", "description": "Media resolution for tokenization." }, "SearchEntryPoint": { "description": "Google search entry point.", "properties": { "sdkBlob": { "type": "string", "format": "byte", "description": "Optional. Base64 encoded JSON representing array of tuple." }, "renderedContent": { "type": "string", "description": "Optional. Web content snippet that can be embedded in a web page or an app webview." } }, "id": "SearchEntryPoint", "type": "object" }, "VideoMetadata": { "deprecated": true, "id": "VideoMetadata", "type": "object", "properties": { "fps": { "format": "double", "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" }, "endOffset": { "format": "google-duration", "type": "string", "description": "Optional. The end offset of the video." }, "startOffset": { "description": "Optional. The start offset of the video.", "type": "string", "format": "google-duration" } }, "description": "Deprecated: Use `GenerateContentRequest.processing_options` instead. Metadata describes the input video content." }, "Model": { "description": "Information about a Generative Language Model.", "properties": { "version": { "type": "string", "description": "Required. The version number of the model. This represents the major version (`1.0` or `1.5`)" }, "description": { "type": "string", "description": "A short description of the model." }, "topK": { "format": "int32", "type": "integer", "description": "For Top-k sampling. Top-k sampling considers the set of `top_k` most probable tokens. This value specifies default to be used by the backend while making the call to the model. If empty, indicates the model doesn't use top-k sampling, and `top_k` isn't allowed as a generation parameter." }, "thinking": { "description": "Whether the model supports thinking.", "type": "boolean" }, "supportedGenerationMethods": { "items": { "type": "string" }, "description": "The model's supported generation methods. The corresponding API method names are defined as Pascal case strings, such as `generateMessage` and `generateContent`.", "type": "array" }, "maxTemperature": { "description": "The maximum temperature this model can use.", "format": "float", "type": "number" }, "displayName": { "description": "The human-readable name of the model. E.g. \"Gemini 1.5 Flash\". The name can be up to 128 characters long and can consist of any UTF-8 characters.", "type": "string" }, "inputTokenLimit": { "type": "integer", "description": "Maximum number of input tokens allowed for this model.", "format": "int32" }, "name": { "type": "string", "description": "Required. The resource name of the `Model`. Refer to [Model variants](https://ai.google.dev/gemini-api/docs/models/gemini#model-variations) for all allowed values. Format: `models/{model}` with a `{model}` naming convention of: * \"{base_model_id}-{version}\" Examples: * `models/gemini-1.5-flash-001`" }, "baseModelId": { "type": "string", "description": "Required. The name of the base model, pass this to the generation request. Examples: * `gemini-1.5-flash`" }, "topP": { "type": "number", "description": "For [Nucleus sampling](https://ai.google.dev/gemini-api/docs/prompting-strategies#top-p). Nucleus sampling considers the smallest set of tokens whose probability sum is at least `top_p`. This value specifies default to be used by the backend while making the call to the model.", "format": "float" }, "outputTokenLimit": { "type": "integer", "format": "int32", "description": "Maximum number of output tokens available for this model." }, "temperature": { "type": "number", "description": "Controls the randomness of the output. Values can range over `[0.0,max_temperature]`, inclusive. A higher value will produce responses that are more varied, while a value closer to `0.0` will typically result in less surprising responses from the model. This value specifies default to be used by the backend while making the call to the model.", "format": "float" } }, "id": "Model", "type": "object" }, "InlinedEmbedContentResponses": { "properties": { "inlinedResponses": { "items": { "$ref": "InlinedEmbedContentResponse" }, "readOnly": true, "description": "Output only. The responses to the requests in the batch.", "type": "array" } }, "id": "InlinedEmbedContentResponses", "description": "The responses to the requests in the batch.", "type": "object" }, "CreateTunedModelMetadata": { "description": "Metadata about the state and progress of creating a tuned model returned from the long-running operation", "id": "CreateTunedModelMetadata", "type": "object", "properties": { "tunedModel": { "type": "string", "description": "Name of the tuned model associated with the tuning operation." }, "snapshots": { "description": "Metrics collected during tuning.", "type": "array", "items": { "$ref": "TuningSnapshot" } }, "completedSteps": { "format": "int32", "type": "integer", "description": "The number of steps completed." }, "completedPercent": { "format": "float", "description": "The completed percentage for the tuning operation.", "type": "number" }, "totalSteps": { "description": "The total number of tuning steps.", "type": "integer", "format": "int32" } } }, "FunctionResponse": { "type": "object", "id": "FunctionResponse", "description": "The result output from a `FunctionCall` that contains a string representing the `FunctionDeclaration.name` and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a`FunctionCall` made based on model prediction.", "properties": { "name": { "description": "Required. The name of the function to call. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 128.", "type": "string" }, "id": { "type": "string", "description": "Optional. The identifier of the function call this response is for. Populated by the client to match the corresponding function call `id`." }, "response": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object", "description": "Required. The function response in JSON object format. Callers can use any keys of their choice that fit the function's syntax to return the function output, e.g. \"output\", \"result\", etc. In particular, if the function call failed to execute, the response can have an \"error\" key to return error details to the model. Multimedia can be included by using a subobject containing a single \"$ref\" key whose value is the `inline_data.display_name` of a `FunctionResponsePart` holding the multimedia. See https://ai.google.dev/gemini-api/docs/function-calling#multimodal." } } }, "GoogleSearchRetrieval": { "id": "GoogleSearchRetrieval", "properties": { "dynamicRetrievalConfig": { "$ref": "DynamicRetrievalConfig", "description": "Specifies the dynamic retrieval configuration for the given source." } }, "type": "object", "description": "Tool to retrieve public web data for grounding, powered by Google." }, "Candidate": { "type": "object", "properties": { "logprobsResult": { "description": "Output only. Log-likelihood scores for the response tokens and top tokens", "readOnly": true, "$ref": "LogprobsResult" }, "citationMetadata": { "$ref": "CitationMetadata", "readOnly": true, "description": "Output only. Citation information for model-generated candidate. This field may be populated with recitation information for any text included in the `content`. These are passages that are \"recited\" from copyrighted material in the foundational LLM's training data." }, "groundingAttributions": { "items": { "$ref": "GroundingAttribution" }, "type": "array", "description": "Output only. Attribution information for sources that contributed to a grounded answer. This field is populated for `GenerateAnswer` calls.", "readOnly": true }, "urlContextMetadata": { "description": "Output only. Metadata related to url context retrieval tool.", "$ref": "UrlContextMetadata", "readOnly": true }, "safetyRatings": { "description": "List of ratings for the safety of a response candidate. There is at most one rating per category.", "items": { "$ref": "SafetyRating" }, "type": "array" }, "groundingMetadata": { "$ref": "GroundingMetadata", "readOnly": true, "description": "Output only. Grounding metadata for the candidate. This field is populated for `GenerateContent` calls." }, "tokenCount": { "description": "Output only. Token count for this candidate.", "type": "integer", "readOnly": true, "format": "int32" }, "index": { "type": "integer", "description": "Output only. Index of the candidate in the list of response candidates.", "readOnly": true, "format": "int32" }, "avgLogprobs": { "format": "double", "type": "number", "readOnly": true, "description": "Output only. Average log probability score of the candidate." }, "finishMessage": { "readOnly": true, "type": "string", "description": "Optional. Output only. Details the reason why the model stopped generating tokens. This is populated only when `finish_reason` is set." }, "content": { "description": "Output only. Generated content returned from the model.", "readOnly": true, "$ref": "Content" }, "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.", "Request was filtered by an escalation rule.", "Indicates that token generation stopped because the user account is limited or disabled due to Prohibited Use Policy (PUP) violations." ], "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", "ESCALATION", "PUP_LIMITED_DISABLED" ] } }, "description": "A response candidate generated from the model.", "id": "Candidate" }, "ListFileSearchStoresResponse": { "type": "object", "id": "ListFileSearchStoresResponse", "properties": { "fileSearchStores": { "description": "The returned rag_stores.", "type": "array", "items": { "$ref": "FileSearchStore" } }, "nextPageToken": { "type": "string", "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no more pages." } }, "description": "Response from `ListFileSearchStores` containing a paginated list of `FileSearchStores`. The results are sorted by ascending `file_search_store.create_time`." }, "BatchStats": { "properties": { "successfulRequestCount": { "format": "int64", "type": "string", "description": "Output only. The number of requests that were successfully processed.", "readOnly": true }, "pendingRequestCount": { "readOnly": true, "description": "Output only. The number of requests that are still pending processing.", "format": "int64", "type": "string" }, "requestCount": { "type": "string", "readOnly": true, "format": "int64", "description": "Output only. The number of requests in the batch." }, "failedRequestCount": { "type": "string", "format": "int64", "readOnly": true, "description": "Output only. The number of requests that failed to be processed." } }, "description": "Stats about the batch.", "type": "object", "id": "BatchStats" }, "InlinedRequest": { "type": "object", "description": "The request to be processed in the batch.", "properties": { "metadata": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The metadata to be associated with the request." }, "request": { "description": "Required. The request to be processed in the batch.", "$ref": "GenerateContentRequest" } }, "id": "InlinedRequest" }, "UrlMetadata": { "type": "object", "properties": { "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" ] }, "retrievedUrl": { "description": "Retrieved url by the tool.", "type": "string" } }, "description": "Context of the a single url retrieval.", "id": "UrlMetadata" }, "CodeExecution": { "id": "CodeExecution", "properties": {}, "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" }, "Blobstore2Info": { "description": "Information to read/write to blobstore2.", "properties": { "downloadExternalReadToken": { "type": "string", "format": "byte", "description": "A serialized External Read Token passed from Bigstore -\u003e Scotty for a GCS download. This field must never be consumed outside of Bigstore, and is not applicable to non-GCS media uploads." }, "blobId": { "description": "The blob id, e.g., /blobstore/prod/playground/scotty", "type": "string" }, "readToken": { "type": "string", "description": "The blob read token. Needed to read blobs that have not been replicated. Might not be available until the final call." }, "uploadFragmentListCreationInfo": { "type": "string", "description": "A serialized Object Fragment List Creation Info passed from Bigstore -\u003e Scotty for a GCS upload. This field must never be consumed outside of Bigstore, and is not applicable to non-GCS media uploads.", "format": "byte" }, "blobGeneration": { "type": "string", "description": "The blob generation id.", "format": "int64" }, "downloadReadHandle": { "format": "byte", "type": "string", "description": "Read handle passed from Bigstore -\u003e Scotty for a GCS download. This is a signed, serialized blobstore2.ReadHandle proto which must never be set outside of Bigstore, and is not applicable to non-GCS media downloads." }, "uploadMetadataContainer": { "format": "byte", "type": "string", "description": "Metadata passed from Blobstore -\u003e Scotty for a new GCS upload. This is a signed, serialized blobstore2.BlobMetadataContainer proto which must never be consumed outside of Bigstore, and is not applicable to non-GCS media uploads." } }, "type": "object", "id": "Blobstore2Info" }, "AsyncBatchEmbedContentRequest": { "id": "AsyncBatchEmbedContentRequest", "description": "Request for an `AsyncBatchEmbedContent` operation.", "type": "object", "properties": { "batch": { "description": "Required. The batch to create.", "$ref": "EmbedContentBatch" } } }, "FileSearchStore": { "id": "FileSearchStore", "description": "A `FileSearchStore` is a collection of `Document`s.", "type": "object", "properties": { "createTime": { "readOnly": true, "type": "string", "description": "Output only. The Timestamp of when the `FileSearchStore` was created.", "format": "google-datetime" }, "failedDocumentsCount": { "readOnly": true, "description": "Output only. The number of documents in the `FileSearchStore` that have failed processing.", "format": "int64", "type": "string" }, "embeddingModel": { "type": "string", "description": "Optional. The embedding model to use for the `FileSearchStore`. The model's resource name. This serves as an ID for the Model to use. Format: `models/{model}`. If not specified, the default embedding model will be used." }, "displayName": { "description": "Optional. The human-readable display name for the `FileSearchStore`. The display name must be no more than 512 characters in length, including spaces. Example: \"Docs on Semantic Retriever\"", "type": "string" }, "activeDocumentsCount": { "readOnly": true, "description": "Output only. The number of documents in the `FileSearchStore` that are active and ready for retrieval.", "format": "int64", "type": "string" }, "pendingDocumentsCount": { "format": "int64", "type": "string", "readOnly": true, "description": "Output only. The number of documents in the `FileSearchStore` that are being processed." }, "name": { "readOnly": true, "description": "Output only. Immutable. Identifier. The `FileSearchStore` resource name. It is an ID (name excluding the \"fileSearchStores/\" prefix) that can contain up to 40 characters that are lowercase alphanumeric or dashes (-). It is output only. The unique name will be derived from `display_name` along with a 12 character random suffix. Example: `fileSearchStores/my-awesome-file-search-store-123a456b789c` If `display_name` is not provided, the name will be randomly generated.", "type": "string" }, "sizeBytes": { "type": "string", "format": "int64", "description": "Output only. The size of raw bytes ingested into the `FileSearchStore`. This is the total size of all the documents in the `FileSearchStore`.", "readOnly": true }, "updateTime": { "readOnly": true, "description": "Output only. The Timestamp of when the `FileSearchStore` was last updated.", "type": "string", "format": "google-datetime" } } }, "DiffUploadResponse": { "type": "object", "description": "Backend response for a Diff upload request. For details on the Scotty Diff protocol, visit http://go/scotty-diff-protocol.", "id": "DiffUploadResponse", "properties": { "objectVersion": { "type": "string", "description": "The object version of the object at the server. Must be included in the end notification response. The version in the end notification response must correspond to the new version of the object that is now stored at the server, after the upload." }, "originalObject": { "description": "The location of the original file for a diff upload request. Must be filled in if responding to an upload start notification.", "$ref": "CompositeMedia" } } }, "Operation": { "type": "object", "properties": { "response": { "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", "type": "object", "additionalProperties": { "description": "Properties of the object. Contains field @type with type URL.", "type": "any" } }, "name": { "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.", "type": "string" }, "error": { "description": "The error result of the operation in case of failure or cancellation.", "$ref": "Status" }, "done": { "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.", "type": "boolean" }, "metadata": { "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "type": "object", "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any." } }, "description": "This resource represents a long-running operation that is the result of a network API call.", "id": "Operation" }, "TextResponseFormat": { "type": "object", "description": "Configuration for text output format.", "properties": { "schema": { "description": "Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.", "type": "any" }, "mimeType": { "enumDescriptions": [ "Default value. This value is unused.", "JSON output format.", "Plain text output format." ], "description": "Optional. The MIME type of the text output.", "enum": [ "MIME_TYPE_UNSPECIFIED", "APPLICATION_JSON", "TEXT_PLAIN" ], "type": "string" } }, "id": "TextResponseFormat" }, "WhiteSpaceConfig": { "description": "Configuration for a white space chunking algorithm [white space delimited].", "properties": { "maxTokensPerChunk": { "format": "int32", "description": "Maximum number of tokens per chunk. Tokens are defined as words for this chunking algorithm. Note: we are defining tokens as words split by whitespace as opposed to the output of a tokenizer. The context window of the latest gemini embedding model as of 2025-04-17 is currently 8192 tokens. We assume that the average word is 5 characters. Therefore, we set the upper limit to 2**9, which is 512 words, or 2560 tokens, assuming worst case a character per token. This is a conservative estimate meant to prevent context window overflow.", "type": "integer" }, "maxOverlapTokens": { "type": "integer", "format": "int32", "description": "Maximum number of overlapping tokens between two adjacent chunks." } }, "id": "WhiteSpaceConfig", "type": "object" }, "GroundingAttribution": { "type": "object", "description": "Attribution for a source that contributed to an answer.", "id": "GroundingAttribution", "properties": { "sourceId": { "readOnly": true, "$ref": "AttributionSourceId", "description": "Output only. Identifier for the source contributing to this attribution." }, "content": { "description": "Grounding source content that makes up this attribution.", "$ref": "Content" } } }, "WebSearch": { "properties": {}, "id": "WebSearch", "type": "object", "description": "Standard web search for grounding and related configurations." }, "CodeExecutionResult": { "id": "CodeExecutionResult", "description": "Result of executing the `ExecutableCode`. Generated only when the `CodeExecution` tool is used.", "type": "object", "properties": { "outcome": { "description": "Required. Outcome of the code execution.", "type": "string", "enumDescriptions": [ "Unspecified status. This value should not be used.", "Code execution completed successfully. `output` contains the stdout, if any.", "Code execution failed. `output` contains the stderr and stdout, if any.", "Code execution ran for too long, and was cancelled. There may or may not be a partial `output` present." ], "enum": [ "OUTCOME_UNSPECIFIED", "OUTCOME_OK", "OUTCOME_FAILED", "OUTCOME_DEADLINE_EXCEEDED" ] }, "output": { "type": "string", "description": "Optional. Contains stdout when code execution is successful, stderr or other description otherwise." }, "id": { "type": "string", "description": "Optional. The identifier of the `ExecutableCode` part this result is for. Only populated if the corresponding `ExecutableCode` has an id." } } }, "DownloadMediaResponse": { "description": "Response for DownloadMedia.", "type": "object", "properties": { "blob": { "$ref": "GdataMedia", "description": "Output only. The blob data.", "readOnly": true } }, "id": "DownloadMediaResponse" }, "ListFilesResponse": { "id": "ListFilesResponse", "description": "Response for `ListFiles`.", "properties": { "files": { "description": "The list of `File`s.", "items": { "$ref": "File" }, "type": "array" }, "nextPageToken": { "type": "string", "description": "A token that can be sent as a `page_token` into a subsequent `ListFiles` call." } }, "type": "object" }, "AudioResponseFormat": { "properties": { "delivery": { "enumDescriptions": [ "Default value. This value is unused.", "Audio data is returned inline in the response.", "Audio data is returned as a URI." ], "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "type": "string", "description": "Optional. The delivery mode for the audio output." }, "mimeType": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "MP3 audio format.", "OGG Opus audio format.", "Raw PCM (L16) audio format.", "WAV audio format.", "A-law audio format.", "Mu-law audio format." ], "enum": [ "MIME_TYPE_UNSPECIFIED", "AUDIO_MP3", "AUDIO_OGG_OPUS", "AUDIO_L16", "AUDIO_WAV", "AUDIO_ALAW", "AUDIO_MULAW" ], "description": "Optional. The MIME type of the audio output." }, "sampleRate": { "format": "int32", "description": "Optional. Sample rate in Hz.", "type": "integer" }, "bitRate": { "type": "integer", "description": "Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).", "format": "int32" } }, "description": "Configuration for audio output format.", "type": "object", "id": "AudioResponseFormat" }, "UrlContextMetadata": { "id": "UrlContextMetadata", "properties": { "urlMetadata": { "items": { "$ref": "UrlMetadata" }, "type": "array", "description": "List of url context." } }, "description": "Metadata related to url context retrieval tool.", "type": "object" }, "ImageConfig": { "id": "ImageConfig", "description": "Config for image generation features.", "type": "object", "properties": { "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" }, "aspectRatio": { "type": "string", "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." } } }, "Schema": { "properties": { "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" }, "minProperties": { "type": "string", "description": "Optional. Minimum number of the properties for Type.OBJECT.", "format": "int64" }, "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\"]}", "items": { "type": "string" }, "type": "array" }, "title": { "type": "string", "description": "Optional. The title of the schema." }, "maxLength": { "format": "int64", "type": "string", "description": "Optional. Maximum length of the Type.STRING" }, "maxItems": { "type": "string", "description": "Optional. Maximum number of the elements for Type.ARRAY.", "format": "int64" }, "properties": { "type": "object", "description": "Optional. Properties of Type.OBJECT.", "additionalProperties": { "$ref": "Schema" } }, "minimum": { "type": "number", "description": "Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER", "format": "double" }, "minItems": { "format": "int64", "type": "string", "description": "Optional. Minimum number of the elements for Type.ARRAY." }, "type": { "enumDescriptions": [ "Not specified, should not be used.", "String type.", "Number type.", "Integer type.", "Boolean type.", "Array type.", "Object type.", "Null type." ], "description": "Required. Data type.", "enum": [ "TYPE_UNSPECIFIED", "STRING", "NUMBER", "INTEGER", "BOOLEAN", "ARRAY", "OBJECT", "NULL" ], "type": "string" }, "nullable": { "description": "Optional. Indicates if the value may be null.", "type": "boolean" }, "maximum": { "type": "number", "format": "double", "description": "Optional. Maximum value of the Type.INTEGER and Type.NUMBER" }, "format": { "type": "string", "description": "Optional. The format of the data. Any value is allowed, but most do not trigger any special functionality." }, "propertyOrdering": { "description": "Optional. The order of the properties. Not a standard field in open api spec. Used to determine the order of the properties in the response.", "items": { "type": "string" }, "type": "array" }, "description": { "description": "Optional. A brief description of the parameter. This could contain examples of use. Parameter description may be formatted as Markdown.", "type": "string" }, "items": { "description": "Optional. Schema of the elements of Type.ARRAY.", "$ref": "Schema" }, "pattern": { "description": "Optional. Pattern of the Type.STRING to restrict a string to a regular expression.", "type": "string" }, "anyOf": { "type": "array", "items": { "$ref": "Schema" }, "description": "Optional. The value should be validated against any (one or more) of the subschemas in the list." }, "required": { "description": "Optional. Required properties of Type.OBJECT.", "type": "array", "items": { "type": "string" } }, "maxProperties": { "type": "string", "description": "Optional. Maximum number of the properties for Type.OBJECT.", "format": "int64" }, "minLength": { "description": "Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING", "format": "int64", "type": "string" }, "example": { "description": "Optional. Example of the object. Will only populated when the object is the root.", "type": "any" } }, "description": "The `Schema` object allows the definition of input and output data types. These types can be objects, but also primitives and arrays. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema).", "type": "object", "id": "Schema" }, "BatchEmbedContentsRequest": { "id": "BatchEmbedContentsRequest", "properties": { "requests": { "type": "array", "description": "Required. Embed requests for the batch. The model in each of these requests must match the model specified `BatchEmbedContentsRequest.model`.", "items": { "$ref": "EmbedContentRequest" } } }, "description": "Batch request to get embeddings from the model for a list of prompts.", "type": "object" }, "UsageMetadata": { "type": "object", "properties": { "cachedContentTokenCount": { "description": "Number of tokens in the cached part of the prompt (the cached content)", "type": "integer", "format": "int32" }, "promptTokenCount": { "type": "integer", "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.", "format": "int32" }, "cacheTokensDetails": { "items": { "$ref": "ModalityTokenCount" }, "type": "array", "description": "Output only. List of modalities of the cached content in the request input.", "readOnly": true }, "candidatesTokensDetails": { "description": "Output only. List of modalities that were returned in the response.", "readOnly": true, "items": { "$ref": "ModalityTokenCount" }, "type": "array" }, "candidatesTokenCount": { "description": "Total number of tokens across all the generated response candidates.", "format": "int32", "type": "integer" }, "thoughtsTokenCount": { "readOnly": true, "type": "integer", "description": "Output only. Number of tokens of thoughts for thinking models.", "format": "int32" }, "serviceTier": { "type": "string", "readOnly": true, "enumDescriptions": [ "Default service tier, which is standard.", "Standard service tier.", "Flex service tier.", "Priority service tier." ], "enum": [ "unspecified", "standard", "flex", "priority" ], "description": "Output only. Service tier of the request." }, "toolUsePromptTokensDetails": { "items": { "$ref": "ModalityTokenCount" }, "type": "array", "readOnly": true, "description": "Output only. List of modalities that were processed for tool-use request inputs." }, "totalTokenCount": { "description": "Total token count for the generation request (prompt + thoughts + response candidates).", "format": "int32", "type": "integer" }, "promptTokensDetails": { "description": "Output only. List of modalities that were processed in the request input.", "readOnly": true, "items": { "$ref": "ModalityTokenCount" }, "type": "array" }, "toolUsePromptTokenCount": { "type": "integer", "format": "int32", "description": "Output only. Number of tokens present in tool-use prompt(s).", "readOnly": true } }, "description": "Metadata on the generation request's token usage.", "id": "UsageMetadata" }, "BatchEmbedContentsResponse": { "id": "BatchEmbedContentsResponse", "properties": { "embeddings": { "items": { "$ref": "ContentEmbedding" }, "description": "Output only. The embeddings for each request, in the same order as provided in the batch request.", "type": "array", "readOnly": true }, "usageMetadata": { "description": "Output only. The usage metadata for the request.", "$ref": "EmbeddingUsageMetadata", "readOnly": true } }, "type": "object", "description": "The response to a `BatchEmbedContentsRequest`." }, "File": { "id": "File", "type": "object", "description": "A file uploaded to the API. Next ID: 15", "properties": { "displayName": { "type": "string", "description": "Optional. The human-readable display name for the `File`. The display name must be no more than 512 characters in length, including spaces. Example: \"Welcome Image\"" }, "updateTime": { "type": "string", "readOnly": true, "description": "Output only. The timestamp of when the `File` was last updated.", "format": "google-datetime" }, "expirationTime": { "description": "Output only. The timestamp of when the `File` will be deleted. Only set if the `File` is scheduled to expire.", "type": "string", "readOnly": true, "format": "google-datetime" }, "name": { "type": "string", "description": "Immutable. Identifier. The `File` resource name. The ID (name excluding the \"files/\" prefix) can contain up to 40 characters that are lowercase alphanumeric or dashes (-). The ID cannot start or end with a dash. If the name is empty on create, a unique name will be generated. Example: `files/123-456`" }, "createTime": { "description": "Output only. The timestamp of when the `File` was created.", "type": "string", "readOnly": true, "format": "google-datetime" }, "source": { "enum": [ "SOURCE_UNSPECIFIED", "UPLOADED", "GENERATED", "REGISTERED" ], "enumDescriptions": [ "Used if source is not specified.", "Indicates the file is uploaded by the user.", "Indicates the file is generated by Google.", "Indicates the file is a registered, i.e. a Google Cloud Storage file." ], "description": "Source of the File.", "type": "string" }, "sizeBytes": { "readOnly": true, "format": "int64", "description": "Output only. Size of the file in bytes.", "type": "string" }, "downloadUri": { "description": "Output only. The download uri of the `File`.", "type": "string", "readOnly": true }, "error": { "description": "Output only. Error status if File processing failed.", "readOnly": true, "$ref": "Status" }, "mimeType": { "description": "Output only. MIME type of the file.", "readOnly": true, "type": "string" }, "sha256Hash": { "description": "Output only. SHA-256 hash of the uploaded bytes.", "format": "byte", "readOnly": true, "type": "string" }, "state": { "readOnly": true, "type": "string", "description": "Output only. Processing state of the File.", "enum": [ "STATE_UNSPECIFIED", "PROCESSING", "ACTIVE", "FAILED" ], "enumDescriptions": [ "The default value. This value is used if the state is omitted.", "File is being processed and cannot be used for inference yet.", "File is processed and available for inference.", "File failed processing." ] }, "uri": { "readOnly": true, "description": "Output only. The uri of the `File`.", "type": "string" }, "videoMetadata": { "readOnly": true, "description": "Output only. Metadata for a video.", "$ref": "VideoFileMetadata" } } }, "TuningSnapshot": { "description": "Record for a single tuning step.", "properties": { "meanLoss": { "readOnly": true, "format": "float", "description": "Output only. The mean loss of the training examples for this step.", "type": "number" }, "step": { "readOnly": true, "format": "int32", "type": "integer", "description": "Output only. The tuning step." }, "epoch": { "format": "int32", "type": "integer", "description": "Output only. The epoch this step was part of.", "readOnly": true }, "computeTime": { "readOnly": true, "description": "Output only. The timestamp when this metric was computed.", "format": "google-datetime", "type": "string" } }, "id": "TuningSnapshot", "type": "object" }, "GroundingChunk": { "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.", "id": "GroundingChunk", "properties": { "image": { "$ref": "Image", "description": "Optional. Grounding chunk from image search." }, "maps": { "description": "Optional. Grounding chunk from Google Maps.", "$ref": "Maps" }, "web": { "$ref": "Web", "description": "Grounding chunk from the web." } }, "type": "object" }, "VideoFileMetadata": { "id": "VideoFileMetadata", "properties": { "videoDuration": { "format": "google-duration", "type": "string", "description": "Duration of the video." } }, "type": "object", "description": "Metadata for a video `File`." }, "Tool": { "id": "Tool", "properties": { "urlContext": { "description": "Optional. Tool to support URL context retrieval.", "$ref": "UrlContext" }, "googleMaps": { "description": "Optional. Tool that allows grounding the model's response with geospatial context related to the user's query.", "$ref": "GoogleMaps" }, "googleSearchRetrieval": { "$ref": "GoogleSearchRetrieval", "description": "Optional. Retrieval tool that is powered by Google search." }, "fileSearch": { "description": "Optional. FileSearch tool type. Tool to retrieve knowledge from Semantic Retrieval corpora.", "$ref": "FileSearch" }, "codeExecution": { "description": "Optional. Enables the model to execute code as part of generation.", "$ref": "CodeExecution" }, "functionDeclarations": { "items": { "$ref": "FunctionDeclaration" }, "description": "Optional. A list of `FunctionDeclarations` available to the model that can be used for function calling. The model or system does not execute the function. Instead the defined function may be returned as a FunctionCall with arguments to the client side for execution. The model may decide to call a subset of these functions by populating FunctionCall in the response. The next conversation turn may contain a FunctionResponse with the Content.role \"function\" generation context for the next model turn.", "type": "array" }, "googleSearch": { "description": "Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "$ref": "GoogleSearch" } }, "type": "object", "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: 17" }, "Maps": { "description": "A grounding chunk from Google Maps. A Maps chunk corresponds to a single place.", "type": "object", "id": "Maps", "properties": { "text": { "description": "Text description of the place answer.", "type": "string" }, "title": { "type": "string", "description": "Title of the place." }, "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": { "$ref": "PlaceAnswerSources", "description": "Sources that provide answers about the features of a given place in Google Maps." }, "uri": { "description": "URI reference of the place.", "type": "string" } } }, "ListDocumentsResponse": { "properties": { "documents": { "description": "The returned `Document`s.", "type": "array", "items": { "$ref": "Document" } }, "nextPageToken": { "description": "A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no more pages.", "type": "string" } }, "type": "object", "description": "Response from `ListDocuments` containing a paginated list of `Document`s. The `Document`s are sorted by ascending `document.create_time`.", "id": "ListDocumentsResponse" }, "PlaceAnswerSources": { "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": { "$ref": "ReviewSnippet" } } }, "description": "Collection of sources that provide answers about the features of a given place in Google Maps. Each PlaceAnswerSources message corresponds to a specific place in Google Maps. The Google Maps tool used these sources in order to answer questions about features of the place (e.g: \"does Bar Foo have Wifi\" or \"is Foo Bar wheelchair accessible?\"). Currently we only support review snippets as sources.", "id": "PlaceAnswerSources", "type": "object" }, "DiffDownloadResponse": { "type": "object", "description": "Backend response for a Diff download response. For details on the Scotty Diff protocol, visit http://go/scotty-diff-protocol.", "properties": { "objectLocation": { "$ref": "CompositeMedia", "description": "The original object location." } }, "id": "DiffDownloadResponse" }, "BatchGenerateContentRequest": { "type": "object", "id": "BatchGenerateContentRequest", "description": "Request for a `BatchGenerateContent` operation.", "properties": { "batch": { "description": "Required. The batch to create.", "$ref": "GenerateContentBatch" } } }, "Part": { "id": "Part", "description": "A datatype containing media that is part of a multi-part `Content` message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. A `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.", "properties": { "functionResponse": { "description": "The result output of a `FunctionCall` that contains a string representing the `FunctionDeclaration.name` and a structured JSON object containing any output from the function is used as context to the model.", "$ref": "FunctionResponse" }, "mediaProcessing": { "type": "string", "enum": [ "MEDIA_PROCESSING_UNSPECIFIED", "STATIC", "AGENTIC" ], "description": "Optional. How the model processes this part's media for understanding. Only meaningful for video parts (`inline_data` or `file_data` with video mime). Non-video parts ignore this field.", "enumDescriptions": [ "Defaults to model-specific processing.", "Fixed-rate frame extraction. All frames placed in context.", "Model-driven dynamic navigation. Recommended for most use cases." ] }, "toolCall": { "$ref": "ToolCall", "description": "Server-side tool call. This field is populated when the model predicts a tool invocation that should be executed on the server. The client is expected to echo this message back to the API." }, "thoughtSignature": { "format": "byte", "type": "string", "description": "Optional. An opaque signature for the thought so it can be reused in subsequent requests." }, "inlineData": { "description": "Inline media bytes.", "$ref": "Blob" }, "fileData": { "$ref": "FileData", "description": "URI based data." }, "functionCall": { "$ref": "FunctionCall", "description": "A predicted `FunctionCall` returned from the model that contains a string representing the `FunctionDeclaration.name` with the arguments and their values." }, "text": { "description": "Inline text.", "type": "string" }, "thought": { "description": "Optional. Indicates if the part is thought from the model.", "type": "boolean" }, "codeExecutionResult": { "$ref": "CodeExecutionResult", "description": "Result of executing the `ExecutableCode`." }, "videoMetadata": { "description": "Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.", "$ref": "VideoMetadata" }, "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`.", "$ref": "ToolResponse" }, "partMetadata": { "description": "Custom metadata associated with the Part. Agents using genai.Part as content representation may need to keep track of the additional information. For example it can be name of a file/source from which the Part originates or a way to multiplex multiple Part streams.", "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." } }, "mediaResolution": { "description": "Optional. Media resolution for the input media.", "$ref": "MediaResolution" }, "executableCode": { "description": "Code generated by the model that is meant to be executed.", "$ref": "ExecutableCode" } }, "type": "object" }, "CustomLongRunningOperation": { "properties": { "done": { "description": "If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.", "type": "boolean" }, "response": { "description": "The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.", "additionalProperties": { "type": "any", "description": "Properties of the object. Contains field @type with type URL." }, "type": "object" }, "name": { "description": "The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.", "type": "string" }, "error": { "description": "The error result of the operation in case of failure or cancellation.", "$ref": "Status" }, "metadata": { "description": "Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.", "type": "object", "additionalProperties": { "description": "Properties of the object. Contains field @type with type URL.", "type": "any" } } }, "type": "object", "id": "CustomLongRunningOperation" }, "GoogleSearch": { "properties": { "searchTypes": { "description": "Optional. The set of search types to enable. If not set, web search is enabled by default.", "$ref": "SearchTypes" }, "timeRangeFilter": { "description": "Optional. Filter search results to a specific time range. If customers set a start time, they must set an end time (and vice versa).", "$ref": "Interval" } }, "description": "GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.", "id": "GoogleSearch", "type": "object" }, "InlinedRequests": { "type": "object", "description": "The requests to be processed in the batch if provided as part of the batch creation request.", "properties": { "requests": { "description": "Required. The requests to be processed in the batch.", "type": "array", "items": { "$ref": "InlinedRequest" } } }, "id": "InlinedRequests" }, "EmbedContentConfig": { "properties": { "title": { "description": "Optional. The title for the text.", "type": "string" }, "outputDimensionality": { "type": "integer", "format": "int32", "description": "Optional. Reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end." }, "audioTrackExtraction": { "description": "Optional. Whether to extract audio from video content.", "type": "boolean" }, "documentOcr": { "type": "boolean", "description": "Optional. Whether to enable OCR for document content." }, "taskType": { "enumDescriptions": [ "Unset value, which will default to one of the other enum values.", "Specifies the given text is a query in a search/retrieval setting.", "Specifies the given text is a document from the corpus being searched.", "Specifies the given text will be used for STS.", "Specifies that the given text will be classified.", "Specifies that the embeddings will be used for clustering.", "Specifies that the given text will be used for question answering.", "Specifies that the given text will be used for fact verification.", "Specifies that the given text will be used for code retrieval." ], "description": "Optional. The task type of the embedding.", "type": "string", "enum": [ "TASK_TYPE_UNSPECIFIED", "RETRIEVAL_QUERY", "RETRIEVAL_DOCUMENT", "SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY" ] }, "autoTruncate": { "type": "boolean", "description": "Optional. Whether to silently truncate the input content if it's longer than the maximum sequence length." } }, "id": "EmbedContentConfig", "description": "Configurations for the EmbedContent request.", "type": "object" }, "EmbedContentResponse": { "id": "EmbedContentResponse", "properties": { "embedding": { "readOnly": true, "$ref": "ContentEmbedding", "description": "Output only. The embedding generated from the input content." }, "usageMetadata": { "readOnly": true, "$ref": "EmbeddingUsageMetadata", "description": "Output only. The usage metadata for the request." } }, "type": "object", "description": "The response to an `EmbedContentRequest`." }, "CitationSource": { "description": "A citation to a source for a portion of a specific response.", "properties": { "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" }, "endIndex": { "description": "Optional. End of the attributed segment, exclusive.", "type": "integer", "format": "int32" }, "startIndex": { "type": "integer", "format": "int32", "description": "Optional. Start of segment of the response that is attributed to this source. Index indicates the start of the segment, measured in bytes." }, "uri": { "type": "string", "description": "Optional. URI that is attributed as a source for a portion of the text." } }, "id": "CitationSource", "type": "object" }, "RetrievalMetadata": { "properties": { "googleSearchDynamicRetrievalScore": { "type": "number", "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.", "format": "float" } }, "type": "object", "id": "RetrievalMetadata", "description": "Metadata related to retrieval in the grounding flow." }, "Image": { "description": "Chunk from image search.", "type": "object", "id": "Image", "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": { "type": "string", "description": "The root domain of the web page that the image is from, e.g. \"example.com\"." } } }, "ThinkingConfig": { "properties": { "includeThoughts": { "description": "Indicates whether to include thoughts in the response. If true, thoughts are returned only when available.", "type": "boolean" }, "thinkingLevel": { "enum": [ "THINKING_LEVEL_UNSPECIFIED", "MINIMAL", "LOW", "MEDIUM", "HIGH" ], "type": "string", "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.", "enumDescriptions": [ "Default value.", "Little to no thinking.", "Low thinking level.", "Medium thinking level.", "High thinking level." ] }, "thinkingBudget": { "format": "int32", "description": "The number of thoughts tokens that the model should generate.", "type": "integer" } }, "description": "Config for thinking features.", "type": "object", "id": "ThinkingConfig" }, "CachedContentUsageMetadata": { "properties": { "totalTokenCount": { "description": "Total number of tokens that the cached content consumes.", "format": "int32", "type": "integer" } }, "id": "CachedContentUsageMetadata", "description": "Metadata on the usage of the cached content.", "type": "object" }, "InlinedResponses": { "id": "InlinedResponses", "type": "object", "properties": { "inlinedResponses": { "type": "array", "items": { "$ref": "InlinedResponse" }, "description": "Output only. The responses to the requests in the batch.", "readOnly": true } }, "description": "The responses to the requests in the batch." }, "TopCandidates": { "type": "object", "id": "TopCandidates", "properties": { "candidates": { "type": "array", "items": { "$ref": "LogprobsResultCandidate" }, "description": "Sorted by log probability in descending order." } }, "description": "Candidates with top log probabilities at each decoding step." }, "ToolResponse": { "type": "object", "id": "ToolResponse", "properties": { "toolType": { "enum": [ "TOOL_TYPE_UNSPECIFIED", "GOOGLE_SEARCH_WEB", "GOOGLE_SEARCH_IMAGE", "URL_CONTEXT", "GOOGLE_MAPS", "FILE_SEARCH" ], "description": "Required. The type of tool that was called, matching the `tool_type` in the corresponding `ToolCall`.", "enumDescriptions": [ "Unspecified tool type.", "Google search tool, maps to Tool.google_search.search_types.web_search.", "Image search tool, maps to Tool.google_search.search_types.image_search.", "URL context tool, maps to Tool.url_context.", "Google maps tool, maps to Tool.google_maps.", "File search tool, maps to Tool.file_search." ], "type": "string" }, "id": { "description": "Optional. The identifier of the tool call this response is for.", "type": "string" }, "response": { "description": "Optional. The tool response.", "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" } } }, "description": "The output from a server-side `ToolCall` execution. This message contains the results of a tool invocation that was initiated by a `ToolCall` from the model. The client should pass this `ToolResponse` back to the API in a subsequent turn within a `Content` message, along with the corresponding `ToolCall`." }, "InlinedEmbedContentRequests": { "properties": { "requests": { "description": "Required. The requests to be processed in the batch.", "items": { "$ref": "InlinedEmbedContentRequest" }, "type": "array" } }, "id": "InlinedEmbedContentRequests", "description": "The requests to be processed in the batch if provided as part of the batch creation request.", "type": "object" }, "ModalityTokenCount": { "type": "object", "description": "Represents token counting info for a single modality.", "properties": { "modality": { "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "VIDEO", "AUDIO", "DOCUMENT" ], "description": "The modality associated with this token count.", "enumDescriptions": [ "Unspecified modality.", "Plain text.", "Image.", "Video.", "Audio.", "Document, e.g. PDF." ], "type": "string" }, "tokenCount": { "format": "int32", "description": "Number of tokens.", "type": "integer" } }, "id": "ModalityTokenCount" }, "GdataMedia": { "description": "A reference to data stored on the filesystem, on GFS or in blobstore.", "type": "object", "properties": { "diffUploadResponse": { "$ref": "DiffUploadResponse", "description": "Set if reference_type is DIFF_UPLOAD_RESPONSE." }, "filename": { "type": "string", "description": "Original file name" }, "length": { "type": "string", "description": "Size of the data, in bytes", "format": "int64" }, "isPotentialRetry": { "description": "|is_potential_retry| is set false only when Scotty is certain that it has not sent the request before. When a client resumes an upload, this field must be set true in agent calls, because Scotty cannot be certain that it has never sent the request before due to potential failure in the session state persistence.", "type": "boolean" }, "diffVersionResponse": { "$ref": "DiffVersionResponse", "description": "Set if reference_type is DIFF_VERSION_RESPONSE." }, "blobRef": { "deprecated": true, "type": "string", "format": "byte", "description": "Blobstore v1 reference, set if reference_type is BLOBSTORE_REF This should be the byte representation of a blobstore.BlobRef. Since Blobstore is deprecating v1, use blobstore2_info instead. For now, any v2 blob will also be represented in this field as v1 BlobRef." }, "contentTypeInfo": { "description": "Extended content type information provided for Scotty uploads.", "$ref": "ContentTypeInfo" }, "timestamp": { "description": "Time at which the media data was last updated, in milliseconds since UNIX epoch", "format": "uint64", "type": "string" }, "compositeMedia": { "description": "A composite media composed of one or more media objects, set if reference_type is COMPOSITE_MEDIA. The media length field must be set to the sum of the lengths of all composite media objects. Note: All composite media must have length specified.", "type": "array", "items": { "$ref": "CompositeMedia" } }, "diffUploadRequest": { "description": "Set if reference_type is DIFF_UPLOAD_REQUEST.", "$ref": "DiffUploadRequest" }, "algorithm": { "description": "Deprecated, use one of explicit hash type fields instead. Algorithm used for calculating the hash. As of 2011/01/21, \"MD5\" is the only possible value for this field. New values may be added at any time.", "type": "string", "deprecated": true }, "blobstore2Info": { "$ref": "Blobstore2Info", "description": "Blobstore v2 info, set if reference_type is BLOBSTORE_REF and it refers to a v2 blob." }, "path": { "description": "Path to the data, set if reference_type is PATH", "type": "string" }, "hashVerified": { "description": "For Scotty uploads only. If a user sends a hash code and the backend has requested that Scotty verify the upload against the client hash, Scotty will perform the check on behalf of the backend and will reject it if the hashes don't match. This is set to true if Scotty performed this verification.", "type": "boolean" }, "token": { "description": "A unique fingerprint/version id for the media data", "type": "string" }, "downloadParameters": { "description": "Parameters for a media download.", "$ref": "DownloadParameters" }, "sha256Hash": { "type": "string", "format": "byte", "description": "Scotty-provided SHA256 hash for an upload." }, "contentType": { "description": "MIME type of the data", "type": "string" }, "bigstoreObjectRef": { "description": "Use object_id instead.", "format": "byte", "deprecated": true, "type": "string" }, "sha512Hash": { "description": "Scotty-provided SHA512 hash for an upload.", "type": "string", "format": "byte" }, "mediaId": { "description": "Media id to forward to the operation GetMedia. Can be set if reference_type is GET_MEDIA.", "format": "byte", "type": "string" }, "cosmoBinaryReference": { "format": "byte", "description": "A binary data reference for a media download. Serves as a technology-agnostic binary reference in some Google infrastructure. This value is a serialized storage_cosmo.BinaryReference proto. Storing it as bytes is a hack to get around the fact that the cosmo proto (as well as others it includes) doesn't support JavaScript. This prevents us from including the actual type of this field.", "type": "string" }, "diffChecksumsResponse": { "description": "Set if reference_type is DIFF_CHECKSUMS_RESPONSE.", "$ref": "DiffChecksumsResponse" }, "objectId": { "description": "Reference to a TI Blob, set if reference_type is BIGSTORE_REF.", "$ref": "ObjectId" }, "hash": { "type": "string", "deprecated": true, "description": "Deprecated, use one of explicit hash type fields instead. These two hash related fields will only be populated on Scotty based media uploads and will contain the content of the hash group in the NotificationRequest: http://cs/#google3/blobstore2/api/scotty/service/proto/upload_listener.proto&q=class:Hash Hex encoded hash value of the uploaded media." }, "sha1Hash": { "format": "byte", "type": "string", "description": "Scotty-provided SHA1 hash for an upload." }, "diffDownloadResponse": { "description": "Set if reference_type is DIFF_DOWNLOAD_RESPONSE.", "$ref": "DiffDownloadResponse" }, "inline": { "type": "string", "format": "byte", "description": "Media data, set if reference_type is INLINE" }, "md5Hash": { "type": "string", "format": "byte", "description": "Scotty-provided MD5 hash for an upload." }, "referenceType": { "type": "string", "enumDescriptions": [ "Reference contains a GFS path or a local path.", "Reference points to a blobstore object. This could be either a v1 blob_ref or a v2 blobstore2_info. Clients should check blobstore2_info first, since v1 is being deprecated.", "Data is included into this proto buffer", "Data should be accessed from the current service using the operation GetMedia.", "The content for this media object is stored across multiple partial media objects under the composite_media field.", "Reference points to a bigstore object", "Indicates the data is stored in diff_version_response.", "Indicates the data is stored in diff_checksums_response.", "Indicates the data is stored in diff_download_response.", "Indicates the data is stored in diff_upload_request.", "Indicates the data is stored in diff_upload_response.", "Indicates the data is stored in cosmo_binary_reference.", "Informs Scotty to generate a response payload with the size specified in the length field. The contents of the payload are generated by Scotty and are undefined. This is useful for testing download speeds between the user and Scotty without involving a real payload source. Note: range is not supported when using arbitrary_bytes." ], "enum": [ "PATH", "BLOB_REF", "INLINE", "GET_MEDIA", "COMPOSITE_MEDIA", "BIGSTORE_REF", "DIFF_VERSION_RESPONSE", "DIFF_CHECKSUMS_RESPONSE", "DIFF_DOWNLOAD_RESPONSE", "DIFF_UPLOAD_REQUEST", "DIFF_UPLOAD_RESPONSE", "COSMO_BINARY_REFERENCE", "ARBITRARY_BYTES" ], "description": "Describes what the field reference contains." }, "crc32cHash": { "description": "For Scotty Uploads: Scotty-provided hashes for uploads For Scotty Downloads: (WARNING: DO NOT USE WITHOUT PERMISSION FROM THE SCOTTY TEAM.) A Hash provided by the agent to be used to verify the data being downloaded. Currently only supported for inline payloads. Further, only crc32c_hash is currently supported.", "type": "integer", "format": "uint32" } }, "id": "GdataMedia" }, "CreateFileResponse": { "id": "CreateFileResponse", "type": "object", "properties": { "file": { "description": "Metadata for the created file.", "$ref": "File" } }, "description": "Response for `CreateFile`." }, "SafetyRating": { "type": "object", "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.", "properties": { "category": { "description": "Required. The category for this rating.", "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.", "**Gemini** - Prompts attempting to bypass or subvert the model's safety guidelines (jailbreak attempts)." ], "type": "string", "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", "HARM_CATEGORY_JAILBREAK" ], "enumDeprecated": [ false, false, false, false, false, false, false, false, false, false, false, true, false ] }, "probability": { "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" ], "description": "Required. The probability of harm for this content." }, "blocked": { "description": "Was this content blocked because of this rating?", "type": "boolean" } }, "id": "SafetyRating" }, "FunctionDeclaration": { "id": "FunctionDeclaration", "type": "object", "properties": { "description": { "type": "string", "description": "Required. A brief description of the function." }, "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": "Schema" }, "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" }, "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.", "$ref": "Schema" } }, "description": "Structured representation of a function declaration as defined by the [OpenAPI 3.03 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client." }, "DiffChecksumsResponse": { "type": "object", "id": "DiffChecksumsResponse", "description": "Backend response for a Diff get checksums response. For details on the Scotty Diff protocol, visit http://go/scotty-diff-protocol.", "properties": { "chunkSizeBytes": { "type": "string", "format": "int64", "description": "The chunk size of checksums. Must be a multiple of 256KB." }, "objectSizeBytes": { "format": "int64", "description": "The total size of the server object.", "type": "string" }, "objectLocation": { "description": "If set, calculate the checksums based on the contents and return them to the caller.", "$ref": "CompositeMedia" }, "objectVersion": { "type": "string", "description": "The object version of the object the checksums are being returned for." }, "checksumsLocation": { "description": "Exactly one of these fields must be populated. If checksums_location is filled, the server will return the corresponding contents to the user. If object_location is filled, the server will calculate the checksums based on the content there and return that to the user. For details on the format of the checksums, see http://go/scotty-diff-protocol.", "$ref": "CompositeMedia" } } }, "SearchTypes": { "properties": { "imageSearch": { "$ref": "ImageSearch", "description": "Optional. Enables image search. Image bytes are returned." }, "webSearch": { "$ref": "WebSearch", "description": "Optional. Enables web search. Only text results are returned." } }, "description": "Different types of search that can be enabled on the GoogleSearch tool.", "type": "object", "id": "SearchTypes" }, "GroundingPassageId": { "type": "object", "description": "Identifier for a part within a `GroundingPassage`.", "id": "GroundingPassageId", "properties": { "passageId": { "type": "string", "description": "Output only. ID of the passage matching the `GenerateAnswerRequest`'s `GroundingPassage.id`.", "readOnly": true }, "partIndex": { "format": "int32", "readOnly": true, "description": "Output only. Index of the part within the `GenerateAnswerRequest`'s `GroundingPassage.content`.", "type": "integer" } } }, "CompositeMedia": { "id": "CompositeMedia", "type": "object", "properties": { "crc32cHash": { "type": "integer", "format": "uint32", "description": "crc32.c hash for the payload." }, "length": { "format": "int64", "description": "Size of the data, in bytes", "type": "string" }, "md5Hash": { "format": "byte", "description": "MD5 hash for the payload.", "type": "string" }, "path": { "description": "Path to the data, set if reference_type is PATH", "type": "string" }, "cosmoBinaryReference": { "type": "string", "format": "byte", "description": "A binary data reference for a media download. Serves as a technology-agnostic binary reference in some Google infrastructure. This value is a serialized storage_cosmo.BinaryReference proto. Storing it as bytes is a hack to get around the fact that the cosmo proto (as well as others it includes) doesn't support JavaScript. This prevents us from including the actual type of this field." }, "referenceType": { "description": "Describes what the field reference contains.", "enum": [ "PATH", "BLOB_REF", "INLINE", "BIGSTORE_REF", "COSMO_BINARY_REFERENCE" ], "enumDescriptions": [ "Reference contains a GFS path or a local path.", "Reference points to a blobstore object. This could be either a v1 blob_ref or a v2 blobstore2_info. Clients should check blobstore2_info first, since v1 is being deprecated.", "Data is included into this proto buffer", "Reference points to a bigstore object", "Indicates the data is stored in cosmo_binary_reference." ], "type": "string" }, "sha1Hash": { "description": "SHA-1 hash for the payload.", "type": "string", "format": "byte" }, "blobRef": { "deprecated": true, "format": "byte", "description": "Blobstore v1 reference, set if reference_type is BLOBSTORE_REF This should be the byte representation of a blobstore.BlobRef. Since Blobstore is deprecating v1, use blobstore2_info instead. For now, any v2 blob will also be represented in this field as v1 BlobRef.", "type": "string" }, "inline": { "format": "byte", "description": "Media data, set if reference_type is INLINE", "type": "string" }, "objectId": { "description": "Reference to a TI Blob, set if reference_type is BIGSTORE_REF.", "$ref": "ObjectId" }, "blobstore2Info": { "$ref": "Blobstore2Info", "description": "Blobstore v2 info, set if reference_type is BLOBSTORE_REF and it refers to a v2 blob." } }, "description": "A sequence of media data references representing composite data. Introduced to support Bigstore composite objects. For details, visit http://go/bigstore-composites." }, "DiffVersionResponse": { "type": "object", "properties": { "objectSizeBytes": { "description": "The total size of the server object.", "type": "string", "format": "int64" }, "objectVersion": { "description": "The version of the object stored at the server.", "type": "string" } }, "description": "Backend response for a Diff get version response. For details on the Scotty Diff protocol, visit http://go/scotty-diff-protocol.", "id": "DiffVersionResponse" }, "GenerateContentBatch": { "properties": { "name": { "description": "Output only. Identifier. Resource name of the batch. Format: `batches/{batch_id}`.", "type": "string", "readOnly": true }, "createTime": { "description": "Output only. The time at which the batch was created.", "format": "google-datetime", "readOnly": true, "type": "string" }, "endTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. The time at which the batch processing completed.", "type": "string" }, "output": { "description": "Output only. The output of the batch request.", "readOnly": true, "$ref": "GenerateContentBatchOutput" }, "state": { "enum": [ "BATCH_STATE_UNSPECIFIED", "BATCH_STATE_PENDING", "BATCH_STATE_RUNNING", "BATCH_STATE_SUCCEEDED", "BATCH_STATE_FAILED", "BATCH_STATE_CANCELLED", "BATCH_STATE_EXPIRED" ], "description": "Output only. The state of the batch.", "readOnly": true, "type": "string", "enumDescriptions": [ "The batch state is unspecified.", "The service is preparing to run the batch.", "The batch is in progress.", "The batch completed successfully.", "The batch failed.", "The batch has been cancelled.", "The batch has expired." ] }, "displayName": { "type": "string", "description": "Required. The user-defined name of this batch." }, "batchStats": { "$ref": "BatchStats", "description": "Output only. Stats about the batch.", "readOnly": true }, "priority": { "type": "string", "format": "int64", "description": "Optional. The priority of the batch. Batches with a higher priority value will be processed before batches with a lower priority value. Negative values are allowed. Default is 0." }, "model": { "type": "string", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`." }, "inputConfig": { "$ref": "InputConfig", "description": "Required. Input configuration of the instances on which batch processing are performed." }, "updateTime": { "type": "string", "format": "google-datetime", "readOnly": true, "description": "Output only. The time at which the batch was last updated." } }, "description": "A resource representing a batch of `GenerateContent` requests.", "type": "object", "id": "GenerateContentBatch" }, "GoogleMaps": { "type": "object", "description": "The GoogleMaps Tool that provides geospatial context for the user's query.", "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" } }, "id": "GoogleMaps" }, "RegisterFilesRequest": { "type": "object", "properties": { "uris": { "type": "array", "description": "Required. The Google Cloud Storage URIs to register. Example: `gs://bucket/object`.", "items": { "type": "string" } } }, "description": "Request for `RegisterFiles`.", "id": "RegisterFilesRequest" }, "FileSearch": { "properties": { "metadataFilter": { "description": "Optional. Metadata filter to apply to the semantic retrieval documents and chunks.", "type": "string" }, "topK": { "type": "integer", "description": "Optional. The number of semantic retrieval chunks to retrieve.", "format": "int32" }, "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" } } }, "id": "FileSearch", "type": "object", "description": "The FileSearch tool that retrieves knowledge from Semantic Retrieval corpora. Files are imported to Semantic Retrieval corpora using the ImportFile API." }, "AttributionSourceId": { "properties": { "semanticRetrieverChunk": { "description": "Identifier for a `Chunk` fetched via Semantic Retriever.", "$ref": "SemanticRetrieverChunk" }, "groundingPassage": { "description": "Identifier for an inline passage.", "$ref": "GroundingPassageId" } }, "id": "AttributionSourceId", "type": "object", "description": "Identifier for the source contributing to this attribution." }, "GenerationConfig": { "description": "Configuration options for model generation and outputs. Not all parameters are configurable for every model.", "type": "object", "properties": { "responseFormat": { "description": "Optional. Configuration for the response output format. Allows specifying output configuration per modality (text, audio, image) in a flat structure.", "$ref": "ResponseFormatConfig" }, "presencePenalty": { "description": "Optional. Presence penalty applied to the next token's logprobs if the token has already been seen in the response. This penalty is binary on/off and not dependant on the number of times the token is used (after the first). Use frequency_penalty for a penalty that increases with each use. A positive penalty will discourage the use of tokens that have already been used in the response, increasing the vocabulary. A negative penalty will encourage the use of tokens that have already been used in the response, decreasing the vocabulary.", "type": "number", "format": "float" }, "responseJsonSchema": { "description": "Optional. An internal detail. Use `responseJsonSchema` rather than this field.", "type": "any" }, "responseSchema": { "description": "Optional. Output schema of the generated candidate text. Schemas must be a subset of the [OpenAPI schema](https://spec.openapis.org/oas/v3.0.3#schema) and can be objects, primitives or arrays. If set, a compatible `response_mime_type` must also be set. Compatible MIME types: `application/json`: Schema for JSON response. Refer to the [JSON text generation guide](https://ai.google.dev/gemini-api/docs/json-mode) for more details.", "$ref": "Schema", "deprecated": true }, "responseLogprobs": { "description": "Optional. If true, export the logprobs results in response.", "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": { "enum": [ "MODALITY_UNSPECIFIED", "TEXT", "IMAGE", "AUDIO" ], "enumDescriptions": [ "Default value.", "Indicates the model should return text.", "Indicates the model should return images.", "Indicates the model should return audio." ], "type": "string" } }, "seed": { "type": "integer", "description": "Optional. Seed used in decoding. If not set, the request uses a randomly generated seed.", "format": "int32" }, "logprobs": { "type": "integer", "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].", "format": "int32" }, "mediaResolution": { "enum": [ "MEDIA_RESOLUTION_UNSPECIFIED", "MEDIA_RESOLUTION_LOW", "MEDIA_RESOLUTION_MEDIUM", "MEDIA_RESOLUTION_HIGH" ], "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)." ] }, "temperature": { "format": "float", "type": "number", "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]." }, "topK": { "format": "int32", "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" }, "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" }, "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.", "$ref": "ImageConfig" }, "enableEnhancedCivicAnswers": { "type": "boolean", "description": "Optional. Enables enhanced civic answers. It may not be available for all models." }, "thinkingConfig": { "$ref": "ThinkingConfig", "description": "Optional. Config for thinking features. An error will be returned if this field is set for models that don't support thinking." }, "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" }, "responseMimeType": { "type": "string", "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." }, "candidateCount": { "format": "int32", "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" }, "frequencyPenalty": { "format": "float", "type": "number", "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." }, "_responseJsonSchema": { "type": "any", "deprecated": true, "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." }, "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" } } }, "id": "GenerationConfig" }, "Web": { "description": "Chunk from the web.", "type": "object", "properties": { "title": { "description": "Output only. Title of the chunk.", "type": "string", "readOnly": true }, "uri": { "description": "Output only. URI reference of the chunk.", "readOnly": true, "type": "string" } }, "id": "Web" }, "UploadToFileSearchStoreRequest": { "type": "object", "id": "UploadToFileSearchStoreRequest", "description": "Request for `UploadToFileSearchStore`.", "properties": { "chunkingConfig": { "description": "Optional. Config for telling the service how to chunk the data. If not provided, the service will use default parameters.", "$ref": "ChunkingConfig" }, "customMetadata": { "description": "Custom metadata to be associated with the data.", "items": { "$ref": "CustomMetadata" }, "type": "array" }, "displayName": { "description": "Optional. Display name of the created document.", "type": "string" }, "mimeType": { "type": "string", "description": "Optional. MIME type of the data. If not provided, it will be inferred from the uploaded content." } } }, "LogprobsResult": { "id": "LogprobsResult", "type": "object", "properties": { "topCandidates": { "type": "array", "items": { "$ref": "TopCandidates" }, "description": "Length = total number of decoding steps." }, "chosenCandidates": { "items": { "$ref": "LogprobsResultCandidate" }, "type": "array", "description": "Length = total number of decoding steps. The chosen candidates may or may not be in top_candidates." }, "logProbabilitySum": { "format": "float", "description": "Sum of log probabilities for all tokens.", "type": "number" } }, "description": "Logprobs Result" }, "ResponseFormatConfig": { "properties": { "text": { "$ref": "TextResponseFormat", "description": "Optional. Text output format configuration." }, "audio": { "description": "Optional. Audio output format configuration.", "$ref": "AudioResponseFormat" }, "image": { "description": "Optional. Image output format configuration.", "$ref": "ImageResponseFormat" } }, "description": "Configuration for the response output format. This is a flat object where each optional sub-field configures a specific output modality.", "id": "ResponseFormatConfig", "type": "object" }, "ImportFileRequest": { "id": "ImportFileRequest", "properties": { "chunkingConfig": { "description": "Optional. Config for telling the service how to chunk the file. If not provided, the service will use default parameters.", "$ref": "ChunkingConfig" }, "customMetadata": { "items": { "$ref": "CustomMetadata" }, "type": "array", "description": "Custom metadata to be associated with the file." }, "fileName": { "type": "string", "description": "Required. The name of the `File` to import. Example: `files/abc-123`" } }, "description": "Request for `ImportFile` to import a File API file with a `FileSearchStore`.", "type": "object" }, "EmbedContentBatchOutput": { "properties": { "inlinedResponses": { "description": "Output only. The responses to the requests in the batch. Returned when the batch was built using inlined requests. The responses will be in the same order as the input requests.", "$ref": "InlinedEmbedContentResponses", "readOnly": true }, "responsesFile": { "readOnly": true, "type": "string", "description": "Output only. The file ID of the file containing the responses. The file will be a JSONL file with a single response per line. The responses will be `EmbedContentResponse` messages formatted as JSON. The responses will be written in the same order as the input requests." } }, "description": "The output of a batch request. This is returned in the `AsyncBatchEmbedContentResponse` or the `EmbedContentBatch.output` field.", "type": "object", "id": "EmbedContentBatchOutput" }, "ImageSearch": { "properties": {}, "id": "ImageSearch", "description": "Image search for grounding and related configurations.", "type": "object" }, "ToolConfig": { "id": "ToolConfig", "properties": { "functionCallingConfig": { "$ref": "FunctionCallingConfig", "description": "Optional. Function calling config." }, "retrievalConfig": { "$ref": "RetrievalConfig", "description": "Optional. Retrieval config." }, "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" } }, "type": "object", "description": "The Tool configuration containing parameters for specifying `Tool` use in the request." }, "InputEmbedContentConfig": { "type": "object", "id": "InputEmbedContentConfig", "properties": { "fileName": { "type": "string", "description": "The name of the `File` containing the input requests." }, "requests": { "description": "The requests to be processed in the batch.", "$ref": "InlinedEmbedContentRequests" } }, "description": "Configures the input to the batch request." }, "EmbedContentBatchStats": { "type": "object", "id": "EmbedContentBatchStats", "description": "Stats about the batch.", "properties": { "failedRequestCount": { "readOnly": true, "description": "Output only. The number of requests that failed to be processed.", "format": "int64", "type": "string" }, "successfulRequestCount": { "readOnly": true, "format": "int64", "type": "string", "description": "Output only. The number of requests that were successfully processed." }, "requestCount": { "description": "Output only. The number of requests in the batch.", "type": "string", "format": "int64", "readOnly": true }, "pendingRequestCount": { "type": "string", "readOnly": true, "description": "Output only. The number of requests that are still pending processing.", "format": "int64" } } }, "DiffUploadRequest": { "id": "DiffUploadRequest", "description": "A Diff upload request. For details on the Scotty Diff protocol, visit http://go/scotty-diff-protocol.", "type": "object", "properties": { "objectVersion": { "description": "The object version of the object that is the base version the incoming diff script will be applied to. This field will always be filled in.", "type": "string" }, "objectInfo": { "description": "The location of the new object. Agents must clone the object located here, as the upload server will delete the contents once a response is received.", "$ref": "CompositeMedia" }, "checksumsInfo": { "description": "The location of the checksums for the new object. Agents must clone the object located here, as the upload server will delete the contents once a response is received. For details on the format of the checksums, see http://go/scotty-diff-protocol.", "$ref": "CompositeMedia" } } }, "ToolCall": { "id": "ToolCall", "type": "object", "properties": { "toolType": { "type": "string", "enumDescriptions": [ "Unspecified tool type.", "Google search tool, maps to Tool.google_search.search_types.web_search.", "Image search tool, maps to Tool.google_search.search_types.image_search.", "URL context tool, maps to Tool.url_context.", "Google maps tool, maps to Tool.google_maps.", "File search tool, maps to Tool.file_search." ], "enum": [ "TOOL_TYPE_UNSPECIFIED", "GOOGLE_SEARCH_WEB", "GOOGLE_SEARCH_IMAGE", "URL_CONTEXT", "GOOGLE_MAPS", "FILE_SEARCH" ], "description": "Required. The type of tool that was called." }, "id": { "type": "string", "description": "Optional. Unique identifier of the tool call. The server returns the tool response with the matching `id`." }, "toolName": { "description": "Optional. The name of the tool that was called.", "type": "string" }, "args": { "type": "object", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "description": "Optional. The tool call arguments. Example: {\"arg1\" : \"value1\", \"arg2\" : \"value2\" , ...}" } }, "description": "A predicted server-side `ToolCall` returned from the model. This message contains information about a tool that the model wants to invoke. The client is NOT expected to execute this `ToolCall`. Instead, the client should pass this `ToolCall` back to the API in a subsequent turn within a `Content` message, along with the corresponding `ToolResponse`." }, "CachedContent": { "type": "object", "id": "CachedContent", "properties": { "updateTime": { "format": "google-datetime", "description": "Output only. When the cache entry was last updated in UTC time.", "type": "string", "readOnly": true }, "contents": { "items": { "$ref": "Content" }, "type": "array", "description": "Optional. Input only. Immutable. The content to cache." }, "name": { "type": "string", "readOnly": true, "description": "Output only. Identifier. The resource name referring to the cached content. Format: `cachedContents/{id}`" }, "systemInstruction": { "$ref": "Content", "description": "Optional. Input only. Immutable. Developer set system instruction. Currently text only." }, "ttl": { "description": "Input only. New TTL for this resource, input only.", "format": "google-duration", "type": "string" }, "model": { "type": "string", "description": "Required. Immutable. The name of the `Model` to use for cached content Format: `models/{model}`" }, "toolConfig": { "$ref": "ToolConfig", "description": "Optional. Input only. Immutable. Tool config. This config is shared for all tools." }, "expireTime": { "format": "google-datetime", "type": "string", "description": "Timestamp in UTC of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input." }, "tools": { "type": "array", "items": { "$ref": "Tool" }, "description": "Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response" }, "createTime": { "readOnly": true, "format": "google-datetime", "description": "Output only. Creation time of the cache entry.", "type": "string" }, "displayName": { "description": "Optional. Immutable. The user-generated meaningful display name of the cached content. Maximum 128 Unicode characters.", "type": "string" }, "usageMetadata": { "$ref": "CachedContentUsageMetadata", "description": "Output only. Metadata on the usage of the cached content.", "readOnly": true } }, "description": "Content that has been preprocessed and can be used in subsequent request to GenerativeService. Cached content can be only used with model it was created for." }, "Document": { "description": "A `Document` is a collection of `Chunk`s.", "properties": { "state": { "description": "Output only. Current state of the `Document`.", "enumDescriptions": [ "The default value. This value is used if the state is omitted.", "Some `Chunks` of the `Document` are being processed (embedding and vector storage).", "All `Chunks` of the `Document` is processed and available for querying.", "Some `Chunks` of the `Document` failed processing." ], "type": "string", "readOnly": true, "enum": [ "STATE_UNSPECIFIED", "STATE_PENDING", "STATE_ACTIVE", "STATE_FAILED" ] }, "createTime": { "description": "Output only. The Timestamp of when the `Document` was created.", "readOnly": true, "type": "string", "format": "google-datetime" }, "customMetadata": { "type": "array", "description": "Optional. User provided custom metadata stored as key-value pairs used for querying. A `Document` can have a maximum of 20 `CustomMetadata`.", "items": { "$ref": "CustomMetadata" } }, "name": { "description": "Immutable. Identifier. The `Document` resource name. The ID (name excluding the \"fileSearchStores/*/documents/\" prefix) can contain up to 40 characters that are lowercase alphanumeric or dashes (-). The ID cannot start or end with a dash. If the name is empty on create, a unique name will be derived from `display_name` along with a 12 character random suffix. Example: `fileSearchStores/{file_search_store_id}/documents/my-awesome-doc-123a456b789c`", "type": "string" }, "updateTime": { "description": "Output only. The Timestamp of when the `Document` was last updated.", "type": "string", "format": "google-datetime", "readOnly": true }, "sizeBytes": { "type": "string", "format": "int64", "readOnly": true, "description": "Output only. The size of raw bytes ingested into the Document." }, "mimeType": { "readOnly": true, "description": "Output only. The mime type of the Document.", "type": "string" }, "displayName": { "description": "Optional. The human-readable display name for the `Document`. The display name must be no more than 512 characters in length, including spaces. Example: \"Semantic Retriever Documentation\"", "type": "string" } }, "id": "Document", "type": "object" }, "StringList": { "id": "StringList", "type": "object", "properties": { "values": { "type": "array", "items": { "type": "string" }, "description": "The string values of the metadata to store." } }, "description": "User provided string values assigned to a single metadata key." }, "Content": { "type": "object", "id": "Content", "properties": { "role": { "description": "Optional. The producer of the content. Must be either 'user' or 'model'. Useful to set for multi-turn conversations, otherwise can be left blank or unset.", "type": "string" }, "parts": { "items": { "$ref": "Part" }, "type": "array", "description": "Ordered `Parts` that constitute a single message. Parts may have different MIME types." } }, "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." }, "CitationMetadata": { "description": "A collection of source attributions for a piece of content.", "id": "CitationMetadata", "type": "object", "properties": { "citationSources": { "description": "Citations to sources for a specific response.", "items": { "$ref": "CitationSource" }, "type": "array" } } }, "GroundingMetadata": { "description": "Metadata returned to client when grounding is enabled.", "type": "object", "properties": { "retrievalMetadata": { "$ref": "RetrievalMetadata", "description": "Metadata related to retrieval in the grounding flow." }, "googleMapsWidgetContextToken": { "type": "string", "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." }, "groundingChunks": { "type": "array", "items": { "$ref": "GroundingChunk" }, "description": "List of supporting references retrieved from specified grounding source. When streaming, this only contains the grounding chunks that have not been included in the grounding metadata of previous responses." }, "searchEntryPoint": { "description": "Optional. Google search entry for the following-up web searches.", "$ref": "SearchEntryPoint" }, "groundingSupports": { "description": "List of grounding support.", "items": { "$ref": "GroundingSupport" }, "type": "array" }, "imageSearchQueries": { "type": "array", "description": "Image search queries used for grounding.", "items": { "type": "string" } }, "webSearchQueries": { "items": { "type": "string" }, "type": "array", "description": "Web search queries for the following-up web search." } }, "id": "GroundingMetadata" }, "InputConfig": { "id": "InputConfig", "type": "object", "properties": { "fileName": { "type": "string", "description": "The name of the `File` containing the input requests." }, "requests": { "description": "The requests to be processed in the batch.", "$ref": "InlinedRequests" } }, "description": "Configures the input to the batch request." }, "FunctionCallingConfig": { "description": "Configuration for specifying function calling behavior.", "type": "object", "id": "FunctionCallingConfig", "properties": { "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.", "items": { "type": "string" }, "type": "array" }, "mode": { "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\"." ], "type": "string", "description": "Optional. Specifies the mode in which function calling should execute. If unspecified, the default value will be set to AUTO.", "enum": [ "MODE_UNSPECIFIED", "AUTO", "ANY", "NONE", "VALIDATED" ] } } }, "ChunkingConfig": { "description": "Parameters for telling the service how to chunk the file. inspired by google3/cloud/ai/platform/extension/lib/retrieval/config/chunker_config.proto", "id": "ChunkingConfig", "properties": { "whiteSpaceConfig": { "$ref": "WhiteSpaceConfig", "description": "White space chunking configuration." } }, "type": "object" }, "ImageResponseFormat": { "type": "object", "id": "ImageResponseFormat", "description": "Configuration for image output format.", "properties": { "mimeType": { "enumDescriptions": [ "Default value. This value is unused.", "JPEG image format." ], "enum": [ "MIME_TYPE_UNSPECIFIED", "IMAGE_JPEG" ], "type": "string", "description": "Optional. The MIME type of the image output." }, "delivery": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "Image data is returned inline in the response.", "Image data is returned as a URI." ], "enum": [ "DELIVERY_UNSPECIFIED", "INLINE", "URI" ], "description": "Optional. The delivery mode for the image output." }, "aspectRatio": { "type": "string", "enumDescriptions": [ "Default value. This value is unused.", "1:1 aspect ratio.", "2:3 aspect ratio.", "3:2 aspect ratio.", "3:4 aspect ratio.", "4:3 aspect ratio.", "4:5 aspect ratio.", "5:4 aspect ratio.", "9:16 aspect ratio.", "16:9 aspect ratio.", "21:9 aspect ratio.", "1:8 aspect ratio.", "8:1 aspect ratio.", "1:4 aspect ratio.", "4:1 aspect ratio." ], "description": "Optional. The aspect ratio for the image output.", "enum": [ "ASPECT_RATIO_UNSPECIFIED", "ASPECT_RATIO_ONE_BY_ONE", "ASPECT_RATIO_TWO_BY_THREE", "ASPECT_RATIO_THREE_BY_TWO", "ASPECT_RATIO_THREE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_THREE", "ASPECT_RATIO_FOUR_BY_FIVE", "ASPECT_RATIO_FIVE_BY_FOUR", "ASPECT_RATIO_NINE_BY_SIXTEEN", "ASPECT_RATIO_SIXTEEN_BY_NINE", "ASPECT_RATIO_TWENTY_ONE_BY_NINE", "ASPECT_RATIO_ONE_BY_EIGHT", "ASPECT_RATIO_EIGHT_BY_ONE", "ASPECT_RATIO_ONE_BY_FOUR", "ASPECT_RATIO_FOUR_BY_ONE" ] }, "imageSize": { "enum": [ "IMAGE_SIZE_UNSPECIFIED", "IMAGE_SIZE_FIVE_TWELVE", "IMAGE_SIZE_ONE_K", "IMAGE_SIZE_TWO_K", "IMAGE_SIZE_FOUR_K" ], "description": "Optional. The size of the image output.", "enumDescriptions": [ "Default value. This value is unused.", "512px image size.", "1K image size.", "2K image size.", "4K image size." ], "type": "string" } } }, "Empty": { "type": "object", "properties": {}, "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); }" }, "InlinedResponse": { "description": "The response to a single request in the batch.", "id": "InlinedResponse", "properties": { "metadata": { "readOnly": true, "type": "object", "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "description": "Output only. The metadata associated with the request." }, "response": { "readOnly": true, "description": "Output only. The response to the request.", "$ref": "GenerateContentResponse" }, "error": { "description": "Output only. The error encountered while processing the request.", "readOnly": true, "$ref": "Status" } }, "type": "object" }, "InlinedEmbedContentResponse": { "description": "The response to a single request in the batch.", "properties": { "error": { "readOnly": true, "$ref": "Status", "description": "Output only. The error encountered while processing the request." }, "response": { "description": "Output only. The response to the request.", "readOnly": true, "$ref": "EmbedContentResponse" }, "metadata": { "type": "object", "description": "Output only. The metadata associated with the request.", "additionalProperties": { "type": "any", "description": "Properties of the object." }, "readOnly": true } }, "type": "object", "id": "InlinedEmbedContentResponse" }, "ContentEmbedding": { "id": "ContentEmbedding", "type": "object", "properties": { "shape": { "type": "array", "items": { "type": "integer", "format": "int32" }, "description": "This field stores the soft tokens tensor frame shape (e.g. [1, 1, 256, 2048])." }, "values": { "description": "The embedding values. This is for 3P users only and will not be populated for 1P calls.", "type": "array", "items": { "type": "number", "format": "float" } } }, "description": "A list of floats representing an embedding." }, "ExecutableCode": { "type": "object", "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.", "id": "ExecutableCode", "properties": { "language": { "enum": [ "LANGUAGE_UNSPECIFIED", "PYTHON" ], "enumDescriptions": [ "Unspecified language. This value should not be used.", "Python \u003e= 3.10, with numpy and simpy available. Python is the default language." ], "type": "string", "description": "Required. Programming language of the `code`." }, "id": { "description": "Optional. Unique identifier of the `ExecutableCode` part. The server returns the `CodeExecutionResult` with the matching `id`.", "type": "string" }, "code": { "type": "string", "description": "Required. The code to be executed." } } }, "UrlContext": { "type": "object", "properties": {}, "description": "Tool to support URL context retrieval.", "id": "UrlContext" }, "Interval": { "properties": { "startTime": { "format": "google-datetime", "type": "string", "description": "Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start." }, "endTime": { "type": "string", "format": "google-datetime", "description": "Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end." } }, "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" }, "ObjectId": { "id": "ObjectId", "properties": { "bucketName": { "description": "The name of the bucket to which this object belongs.", "type": "string" }, "generation": { "format": "int64", "type": "string", "description": "Generation of the object. Generations are monotonically increasing across writes, allowing them to be be compared to determine which generation is newer. If this is omitted in a request, then you are requesting the live object. See http://go/bigstore-versions" }, "objectName": { "type": "string", "description": "The name of the object." } }, "type": "object", "description": "This is a copy of the tech.blob.ObjectId proto, which could not be used directly here due to transitive closure issues with JavaScript support; see http://b/8801763." }, "InlinedEmbedContentRequest": { "id": "InlinedEmbedContentRequest", "type": "object", "description": "The request to be processed in the batch.", "properties": { "request": { "$ref": "EmbedContentRequest", "description": "Required. The request to be processed in the batch." }, "metadata": { "additionalProperties": { "description": "Properties of the object.", "type": "any" }, "type": "object", "description": "Optional. The metadata to be associated with the request." } } }, "ListOperationsResponse": { "properties": { "operations": { "description": "A list of operations that matches the specified filter in the request.", "type": "array", "items": { "$ref": "Operation" } }, "unreachable": { "description": "Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.", "type": "array", "items": { "type": "string" } }, "nextPageToken": { "description": "The standard List next-page token.", "type": "string" } }, "type": "object", "description": "The response message for Operations.ListOperations.", "id": "ListOperationsResponse" }, "DownloadFileResponse": { "id": "DownloadFileResponse", "description": "Response for `DownloadFile`.", "type": "object", "properties": {} } }, "baseUrl": "https://generativelanguage.googleapis.com/", "protocol": "rest", "icons": { "x32": "http://www.google.com/images/icons/product/search-32.gif", "x16": "http://www.google.com/images/icons/product/search-16.gif" }, "title": "Gemini API", "kind": "discovery#restDescription", "description": "The Gemini API allows developers to build generative AI applications using Gemini models. Gemini is our most capable model, built from the ground up to be multimodal. It can generalize and seamlessly understand, operate across, and combine different types of information including language, images, audio, video, and code. You can use the Gemini API for use cases like reasoning across text and images, content generation, dialogue agents, summarization and classification systems, and more.", "version": "v1", "resources": { "fileSearchStores": { "methods": { "list": { "flatPath": "v1/fileSearchStores", "description": "Lists all `FileSearchStores` owned by the user.", "response": { "$ref": "ListFileSearchStoresResponse" }, "path": "v1/fileSearchStores", "httpMethod": "GET", "parameters": { "pageSize": { "type": "integer", "location": "query", "format": "int32", "description": "Optional. The maximum number of `FileSearchStores` to return (per page). The service may return fewer `FileSearchStores`. If unspecified, at most 10 `FileSearchStores` will be returned. The maximum size limit is 20 `FileSearchStores` per page." }, "pageToken": { "type": "string", "description": "Optional. A page token, received from a previous `ListFileSearchStores` call. Provide the `next_page_token` returned in the response as an argument to the next request to retrieve the next page. When paginating, all other parameters provided to `ListFileSearchStores` must match the call that provided the page token.", "location": "query" } }, "id": "generativelanguage.fileSearchStores.list", "parameterOrder": [] }, "delete": { "response": { "$ref": "Empty" }, "httpMethod": "DELETE", "parameters": { "force": { "location": "query", "description": "Optional. If set to true, any `Document`s and objects related to this `FileSearchStore` will also be deleted. If false (the default), a `FAILED_PRECONDITION` error will be returned if `FileSearchStore` contains any `Document`s.", "type": "boolean" }, "name": { "location": "path", "type": "string", "description": "Required. The resource name of the `FileSearchStore`. Example: `fileSearchStores/my-file-search-store-123`", "pattern": "^fileSearchStores/[^/]+$", "required": true } }, "path": "v1/{+name}", "flatPath": "v1/fileSearchStores/{fileSearchStoresId}", "description": "Deletes a `FileSearchStore`.", "id": "generativelanguage.fileSearchStores.delete", "parameterOrder": [ "name" ] }, "importFile": { "parameterOrder": [ "fileSearchStoreName" ], "httpMethod": "POST", "request": { "$ref": "ImportFileRequest" }, "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "flatPath": "v1/fileSearchStores/{fileSearchStoresId}:importFile", "path": "v1/{+fileSearchStoreName}:importFile", "parameters": { "fileSearchStoreName": { "pattern": "^fileSearchStores/[^/]+$", "description": "Required. Immutable. The name of the `FileSearchStore` to import the file into. Example: `fileSearchStores/my-file-search-store-123`", "type": "string", "location": "path", "required": true } }, "response": { "$ref": "Operation" }, "description": "Imports a `File` from File Service to a `FileSearchStore`.", "id": "generativelanguage.fileSearchStores.importFile" }, "create": { "id": "generativelanguage.fileSearchStores.create", "httpMethod": "POST", "path": "v1/fileSearchStores", "response": { "$ref": "FileSearchStore" }, "parameterOrder": [], "request": { "$ref": "FileSearchStore" }, "parameters": {}, "flatPath": "v1/fileSearchStores", "description": "Creates an empty `FileSearchStore`." }, "get": { "parameterOrder": [ "name" ], "path": "v1/{+name}", "httpMethod": "GET", "parameters": { "name": { "pattern": "^fileSearchStores/[^/]+$", "required": true, "location": "path", "description": "Required. The name of the `FileSearchStore`. Example: `fileSearchStores/my-file-search-store-123`", "type": "string" } }, "response": { "$ref": "FileSearchStore" }, "description": "Gets information about a specific `FileSearchStore`.", "id": "generativelanguage.fileSearchStores.get", "flatPath": "v1/fileSearchStores/{fileSearchStoresId}" } }, "resources": { "operations": { "methods": { "get": { "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ], "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/operations/{operationsId}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "required": true, "pattern": "^fileSearchStores/[^/]+/operations/[^/]+$", "type": "string" } }, "path": "v1/{+name}", "response": { "$ref": "Operation" }, "id": "generativelanguage.fileSearchStores.operations.get" } } }, "documents": { "methods": { "get": { "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/documents/{documentsId}", "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The name of the `Document` to retrieve. Example: `fileSearchStores/my-file-search-store-123/documents/the-doc-abc`", "pattern": "^fileSearchStores/[^/]+/documents/[^/]+$", "required": true, "type": "string" } }, "path": "v1/{+name}", "description": "Gets information about a specific `Document`.", "parameterOrder": [ "name" ], "response": { "$ref": "Document" }, "id": "generativelanguage.fileSearchStores.documents.get" }, "list": { "response": { "$ref": "ListDocumentsResponse" }, "description": "Lists all `Document`s in a `Corpus`.", "parameterOrder": [ "parent" ], "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/documents", "id": "generativelanguage.fileSearchStores.documents.list", "path": "v1/{+parent}/documents", "httpMethod": "GET", "parameters": { "pageSize": { "location": "query", "description": "Optional. The maximum number of `Document`s to return (per page). The service may return fewer `Document`s. If unspecified, at most 10 `Document`s will be returned. The maximum size limit is 20 `Document`s per page.", "type": "integer", "format": "int32" }, "parent": { "description": "Required. The name of the `FileSearchStore` containing `Document`s. Example: `fileSearchStores/my-file-search-store-123`", "location": "path", "type": "string", "required": true, "pattern": "^fileSearchStores/[^/]+$" }, "pageToken": { "description": "Optional. A page token, received from a previous `ListDocuments` call. Provide the `next_page_token` returned in the response as an argument to the next request to retrieve the next page. When paginating, all other parameters provided to `ListDocuments` must match the call that provided the page token.", "location": "query", "type": "string" } } }, "delete": { "httpMethod": "DELETE", "parameters": { "name": { "required": true, "pattern": "^fileSearchStores/[^/]+/documents/[^/]+$", "type": "string", "description": "Required. The resource name of the `Document` to delete. Example: `fileSearchStores/my-file-search-store-123/documents/the-doc-abc`", "location": "path" }, "force": { "location": "query", "type": "boolean", "description": "Optional. If set to true, any `Chunk`s and objects related to this `Document` will also be deleted. If false (the default), a `FAILED_PRECONDITION` error will be returned if `Document` contains any `Chunk`s." } }, "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/documents/{documentsId}", "description": "Deletes a `Document`.", "parameterOrder": [ "name" ], "id": "generativelanguage.fileSearchStores.documents.delete", "path": "v1/{+name}", "response": { "$ref": "Empty" } } } }, "upload": { "resources": { "operations": { "methods": { "get": { "id": "generativelanguage.fileSearchStores.upload.operations.get", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "httpMethod": "GET", "parameters": { "name": { "description": "The name of the operation resource.", "pattern": "^fileSearchStores/[^/]+/upload/operations/[^/]+$", "required": true, "type": "string", "location": "path" } }, "response": { "$ref": "Operation" }, "path": "v1/{+name}", "parameterOrder": [ "name" ], "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/upload/operations/{operationsId}" } } } } } } }, "corpora": { "resources": { "operations": { "methods": { "get": { "path": "v1/{+name}", "parameterOrder": [ "name" ], "flatPath": "v1/corpora/{corporaId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "response": { "$ref": "Operation" }, "httpMethod": "GET", "parameters": { "name": { "required": true, "type": "string", "pattern": "^corpora/[^/]+/operations/[^/]+$", "location": "path", "description": "The name of the operation resource." } }, "id": "generativelanguage.corpora.operations.get" } } } } }, "dynamic": { "methods": { "streamGenerateContent": { "description": "Generates a [streamed response](https://ai.google.dev/gemini-api/docs/text-generation?lang=python#generate-a-text-stream) from the model given an input `GenerateContentRequest`.", "parameterOrder": [ "model" ], "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "location": "path", "required": true, "pattern": "^dynamic/[^/]+$", "type": "string" } }, "id": "generativelanguage.dynamic.streamGenerateContent", "response": { "$ref": "GenerateContentResponse" }, "request": { "$ref": "GenerateContentRequest" }, "httpMethod": "POST", "path": "v1/{+model}:streamGenerateContent", "flatPath": "v1/dynamic/{dynamicId}:streamGenerateContent" }, "generateContent": { "response": { "$ref": "GenerateContentResponse" }, "httpMethod": "POST", "parameterOrder": [ "model" ], "flatPath": "v1/dynamic/{dynamicId}:generateContent", "description": "Generates a model response given an input `GenerateContentRequest`. Refer to the [text generation guide](https://ai.google.dev/gemini-api/docs/text-generation) for detailed usage information. Input capabilities differ between models, including tuned models. Refer to the [model guide](https://ai.google.dev/gemini-api/docs/models/gemini) and [tuning guide](https://ai.google.dev/gemini-api/docs/model-tuning) for details.", "request": { "$ref": "GenerateContentRequest" }, "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "required": true, "pattern": "^dynamic/[^/]+$", "location": "path", "type": "string" } }, "path": "v1/{+model}:generateContent", "id": "generativelanguage.dynamic.generateContent" } } }, "models": { "methods": { "batchEmbedContents": { "parameterOrder": [ "model" ], "path": "v1/{+model}:batchEmbedContents", "httpMethod": "POST", "response": { "$ref": "BatchEmbedContentsResponse" }, "id": "generativelanguage.models.batchEmbedContents", "request": { "$ref": "BatchEmbedContentsRequest" }, "description": "Generates multiple embedding vectors from the input `Content` which consists of a batch of strings represented as `EmbedContentRequest` objects.", "flatPath": "v1/models/{modelsId}:batchEmbedContents", "parameters": { "model": { "pattern": "^models/[^/]+$", "required": true, "type": "string", "location": "path", "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}`" } } }, "streamGenerateContent": { "httpMethod": "POST", "response": { "$ref": "GenerateContentResponse" }, "description": "Generates a [streamed response](https://ai.google.dev/gemini-api/docs/text-generation?lang=python#generate-a-text-stream) from the model given an input `GenerateContentRequest`.", "id": "generativelanguage.models.streamGenerateContent", "parameterOrder": [ "model" ], "flatPath": "v1/models/{modelsId}:streamGenerateContent", "path": "v1/{+model}:streamGenerateContent", "parameters": { "model": { "required": true, "pattern": "^models/[^/]+$", "type": "string", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "location": "path" } }, "request": { "$ref": "GenerateContentRequest" } }, "generateContent": { "flatPath": "v1/models/{modelsId}:generateContent", "response": { "$ref": "GenerateContentResponse" }, "description": "Generates a model response given an input `GenerateContentRequest`. Refer to the [text generation guide](https://ai.google.dev/gemini-api/docs/text-generation) for detailed usage information. Input capabilities differ between models, including tuned models. Refer to the [model guide](https://ai.google.dev/gemini-api/docs/models/gemini) and [tuning guide](https://ai.google.dev/gemini-api/docs/model-tuning) for details.", "path": "v1/{+model}:generateContent", "httpMethod": "POST", "request": { "$ref": "GenerateContentRequest" }, "parameterOrder": [ "model" ], "id": "generativelanguage.models.generateContent", "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^models/[^/]+$", "location": "path", "required": true, "type": "string" } } }, "list": { "httpMethod": "GET", "parameters": { "pageToken": { "description": "A page token, received from a previous `ListModels` call. Provide the `page_token` returned by one request as an argument to the next request to retrieve the next page. When paginating, all other parameters provided to `ListModels` must match the call that provided the page token.", "type": "string", "location": "query" }, "pageSize": { "description": "The maximum number of `Models` to return (per page). If unspecified, 50 models will be returned per page. This method returns at most 1000 models per page, even if you pass a larger page_size.", "type": "integer", "location": "query", "format": "int32" } }, "flatPath": "v1/models", "path": "v1/models", "description": "Lists the [`Model`s](https://ai.google.dev/gemini-api/docs/models/gemini) available through the Gemini API.", "parameterOrder": [], "response": { "$ref": "ListModelsResponse" }, "id": "generativelanguage.models.list" }, "countTokens": { "httpMethod": "POST", "flatPath": "v1/models/{modelsId}:countTokens", "description": "Runs a model's tokenizer on input `Content` and returns the token count. Refer to the [tokens guide](https://ai.google.dev/gemini-api/docs/tokens) to learn more about tokens.", "id": "generativelanguage.models.countTokens", "response": { "$ref": "CountTokensResponse" }, "parameterOrder": [ "model" ], "parameters": { "model": { "type": "string", "location": "path", "required": true, "pattern": "^models/[^/]+$", "description": "Required. The model's resource name. This serves as an ID for the Model to use. This name should match a model name returned by the `ListModels` method. Format: `models/{model}`" } }, "request": { "$ref": "CountTokensRequest" }, "path": "v1/{+model}:countTokens" }, "batchGenerateContent": { "response": { "$ref": "Operation" }, "parameters": { "model": { "pattern": "^models/[^/]+$", "location": "path", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "type": "string", "required": true } }, "request": { "$ref": "BatchGenerateContentRequest" }, "path": "v1/{+model}:batchGenerateContent", "flatPath": "v1/models/{modelsId}:batchGenerateContent", "httpMethod": "POST", "id": "generativelanguage.models.batchGenerateContent", "description": "Enqueues a batch of `GenerateContent` requests for batch processing.", "parameterOrder": [ "model" ] }, "asyncBatchEmbedContent": { "parameters": { "model": { "required": true, "location": "path", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "type": "string", "pattern": "^models/[^/]+$" } }, "path": "v1/{+model}:asyncBatchEmbedContent", "request": { "$ref": "AsyncBatchEmbedContentRequest" }, "description": "Enqueues a batch of `EmbedContent` requests for batch processing. We have a `BatchEmbedContents` handler in `GenerativeService`, but it was synchronized. So we name this one to be `Async` to avoid confusion.", "httpMethod": "POST", "parameterOrder": [ "model" ], "response": { "$ref": "Operation" }, "id": "generativelanguage.models.asyncBatchEmbedContent", "flatPath": "v1/models/{modelsId}:asyncBatchEmbedContent" }, "get": { "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "Required. The resource name of the model. This name should match a model name returned by the `ListModels` method. Format: `models/{model}`", "type": "string", "pattern": "^models/[^/]+$", "required": true } }, "path": "v1/{+name}", "description": "Gets information about a specific `Model` such as its version number, token limits, [parameters](https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters) and other metadata. Refer to the [Gemini models guide](https://ai.google.dev/gemini-api/docs/models/gemini) for detailed model information.", "flatPath": "v1/models/{modelsId}", "response": { "$ref": "Model" }, "id": "generativelanguage.models.get", "parameterOrder": [ "name" ] }, "embedContent": { "path": "v1/{+model}:embedContent", "parameterOrder": [ "model" ], "request": { "$ref": "EmbedContentRequest" }, "httpMethod": "POST", "description": "Generates a text embedding vector from the input `Content` using the specified [Gemini Embedding model](https://ai.google.dev/gemini-api/docs/models/gemini#text-embedding).", "id": "generativelanguage.models.embedContent", "response": { "$ref": "EmbedContentResponse" }, "flatPath": "v1/models/{modelsId}:embedContent", "parameters": { "model": { "pattern": "^models/[^/]+$", "type": "string", "required": true, "description": "Required. The model's resource name. This serves as an ID for the Model to use. This name should match a model name returned by the `ListModels` method. Format: `models/{model}`", "location": "path" } } } }, "resources": { "operations": { "methods": { "get": { "response": { "$ref": "Operation" }, "id": "generativelanguage.models.operations.get", "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "location": "path", "description": "The name of the operation resource.", "type": "string", "required": true, "pattern": "^models/[^/]+/operations/[^/]+$" } }, "flatPath": "v1/models/{modelsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}" }, "list": { "parameterOrder": [ "name" ], "path": "v1/{+name}/operations", "flatPath": "v1/models/{modelsId}/operations", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "id": "generativelanguage.models.operations.list", "response": { "$ref": "ListOperationsResponse" }, "httpMethod": "GET", "parameters": { "name": { "required": true, "pattern": "^models/[^/]+$", "description": "The name of the operation's parent resource.", "type": "string", "location": "path" }, "filter": { "type": "string", "description": "The standard list filter.", "location": "query" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageToken": { "type": "string", "description": "The standard list page token.", "location": "query" }, "pageSize": { "location": "query", "description": "The standard list page size.", "type": "integer", "format": "int32" } } } } } } }, "generatedFiles": { "resources": { "operations": { "methods": { "get": { "response": { "$ref": "Operation" }, "httpMethod": "GET", "parameters": { "name": { "pattern": "^generatedFiles/[^/]+/operations/[^/]+$", "type": "string", "description": "The name of the operation resource.", "location": "path", "required": true } }, "flatPath": "v1/generatedFiles/{generatedFilesId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "path": "v1/{+name}", "id": "generativelanguage.generatedFiles.operations.get", "parameterOrder": [ "name" ] } } } } }, "cachedContents": { "methods": { "patch": { "id": "generativelanguage.cachedContents.patch", "flatPath": "v1/cachedContents/{cachedContentsId}", "request": { "$ref": "CachedContent" }, "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "httpMethod": "PATCH", "description": "Updates CachedContent resource (only expiration is updatable).", "parameterOrder": [ "name" ], "response": { "$ref": "CachedContent" }, "parameters": { "name": { "location": "path", "type": "string", "pattern": "^cachedContents/[^/]+$", "description": "Output only. Identifier. The resource name referring to the cached content. Format: `cachedContents/{id}`", "required": true }, "updateMask": { "type": "string", "location": "query", "format": "google-fieldmask", "description": "The list of fields to update." } }, "path": "v1/{+name}" }, "create": { "path": "v1/cachedContents", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "httpMethod": "POST", "request": { "$ref": "CachedContent" }, "response": { "$ref": "CachedContent" }, "id": "generativelanguage.cachedContents.create", "parameterOrder": [], "flatPath": "v1/cachedContents", "parameters": {}, "description": "Creates CachedContent resource." }, "list": { "flatPath": "v1/cachedContents", "parameterOrder": [], "response": { "$ref": "ListCachedContentsResponse" }, "parameters": { "pageSize": { "location": "query", "type": "integer", "format": "int32", "description": "Optional. The maximum number of cached contents to return. The service may return fewer than this value. If unspecified, some default (under maximum) number of items will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000." }, "pageToken": { "description": "Optional. A page token, received from a previous `ListCachedContents` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListCachedContents` must match the call that provided the page token.", "location": "query", "type": "string" } }, "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "description": "Lists CachedContents.", "path": "v1/cachedContents", "id": "generativelanguage.cachedContents.list", "httpMethod": "GET" }, "get": { "httpMethod": "GET", "path": "v1/{+name}", "parameters": { "name": { "pattern": "^cachedContents/[^/]+$", "type": "string", "location": "path", "required": true, "description": "Required. The resource name referring to the content cache entry. Format: `cachedContents/{id}`" } }, "response": { "$ref": "CachedContent" }, "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "description": "Reads CachedContent resource.", "parameterOrder": [ "name" ], "id": "generativelanguage.cachedContents.get", "flatPath": "v1/cachedContents/{cachedContentsId}" }, "delete": { "description": "Deletes CachedContent resource.", "id": "generativelanguage.cachedContents.delete", "httpMethod": "DELETE", "parameterOrder": [ "name" ], "path": "v1/{+name}", "response": { "$ref": "Empty" }, "parameters": { "name": { "type": "string", "location": "path", "required": true, "pattern": "^cachedContents/[^/]+$", "description": "Required. The resource name referring to the content cache entry Format: `cachedContents/{id}`" } }, "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "flatPath": "v1/cachedContents/{cachedContentsId}" } } }, "batches": { "methods": { "list": { "flatPath": "v1/batches", "httpMethod": "GET", "parameters": { "pageSize": { "format": "int32", "type": "integer", "description": "The standard list page size.", "location": "query" }, "filter": { "description": "The standard list filter.", "type": "string", "location": "query" }, "pageToken": { "location": "query", "description": "The standard list page token.", "type": "string" }, "name": { "pattern": "^batches$", "required": true, "description": "The name of the operation's parent resource.", "type": "string", "location": "path" }, "returnPartialSuccess": { "type": "boolean", "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query" } }, "parameterOrder": [ "name" ], "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "response": { "$ref": "ListOperationsResponse" }, "path": "v1/{+name}", "id": "generativelanguage.batches.list" }, "cancel": { "response": { "$ref": "Empty" }, "id": "generativelanguage.batches.cancel", "parameterOrder": [ "name" ], "httpMethod": "POST", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be cancelled.", "required": true, "pattern": "^batches/[^/]+$" } }, "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1/batches/{batchesId}:cancel", "path": "v1/{+name}:cancel" }, "get": { "httpMethod": "GET", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource.", "pattern": "^batches/[^/]+$", "required": true } }, "id": "generativelanguage.batches.get", "flatPath": "v1/batches/{batchesId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "parameterOrder": [ "name" ], "response": { "$ref": "Operation" }, "path": "v1/{+name}" }, "updateEmbedContentBatch": { "flatPath": "v1/batches/{batchesId}:updateEmbedContentBatch", "parameterOrder": [ "name" ], "path": "v1/{+name}:updateEmbedContentBatch", "httpMethod": "PATCH", "response": { "$ref": "EmbedContentBatch" }, "id": "generativelanguage.batches.updateEmbedContentBatch", "request": { "$ref": "EmbedContentBatch" }, "description": "Updates a batch of EmbedContent requests for batch processing.", "parameters": { "name": { "location": "path", "description": "Output only. Identifier. Resource name of the batch. Format: `batches/{batch_id}`.", "type": "string", "required": true, "pattern": "^batches/[^/]+$" }, "updateMask": { "format": "google-fieldmask", "description": "Optional. The list of fields to update.", "location": "query", "type": "string" } } }, "delete": { "response": { "$ref": "Empty" }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "id": "generativelanguage.batches.delete", "httpMethod": "DELETE", "parameters": { "name": { "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "required": true, "pattern": "^batches/[^/]+$" } }, "path": "v1/{+name}", "flatPath": "v1/batches/{batchesId}" }, "updateGenerateContentBatch": { "parameters": { "updateMask": { "format": "google-fieldmask", "description": "Optional. The list of fields to update.", "type": "string", "location": "query" }, "name": { "location": "path", "type": "string", "description": "Output only. Identifier. Resource name of the batch. Format: `batches/{batch_id}`.", "required": true, "pattern": "^batches/[^/]+$" } }, "request": { "$ref": "GenerateContentBatch" }, "description": "Updates a batch of GenerateContent requests for batch processing.", "id": "generativelanguage.batches.updateGenerateContentBatch", "httpMethod": "PATCH", "response": { "$ref": "GenerateContentBatch" }, "flatPath": "v1/batches/{batchesId}:updateGenerateContentBatch", "parameterOrder": [ "name" ], "path": "v1/{+name}:updateGenerateContentBatch" } } }, "files": { "methods": { "delete": { "response": { "$ref": "Empty" }, "parameters": { "name": { "type": "string", "pattern": "^files/[^/]+$", "required": true, "description": "Required. The name of the `File` to delete. Example: `files/abc-123`", "location": "path" } }, "flatPath": "v1/files/{filesId}", "id": "generativelanguage.files.delete", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "parameterOrder": [ "name" ], "httpMethod": "DELETE", "path": "v1/{+name}", "description": "Deletes the `File`." }, "list": { "flatPath": "v1/files", "id": "generativelanguage.files.list", "response": { "$ref": "ListFilesResponse" }, "parameters": { "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "Optional. Maximum number of `File`s to return per page. If unspecified, defaults to 10. Maximum `page_size` is 100." }, "pageToken": { "description": "Optional. A page token from a previous `ListFiles` call.", "type": "string", "location": "query" } }, "parameterOrder": [], "path": "v1/files", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "description": "Lists the metadata for `File`s owned by the requesting project.", "httpMethod": "GET" }, "get": { "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "parameters": { "name": { "location": "path", "description": "Required. The name of the `File` to get. Example: `files/abc-123`", "pattern": "^files/[^/]+$", "required": true, "type": "string" } }, "response": { "$ref": "File" }, "id": "generativelanguage.files.get", "parameterOrder": [ "name" ], "httpMethod": "GET", "flatPath": "v1/files/{filesId}", "description": "Gets the metadata for the given `File`.", "path": "v1/{+name}" }, "register": { "description": "Registers a Google Cloud Storage files with FileService. The user is expected to provide Google Cloud Storage URIs and will receive a File resource for each URI in return. Note that the files are not copied, just registered with File API. If one file fails to register, the whole request fails.", "parameters": {}, "parameterOrder": [], "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "response": { "$ref": "RegisterFilesResponse" }, "id": "generativelanguage.files.register", "path": "v1/files:register", "request": { "$ref": "RegisterFilesRequest" }, "flatPath": "v1/files:register", "httpMethod": "POST" } } }, "media": { "methods": { "upload": { "description": "Creates a `File`.", "parameters": {}, "response": { "$ref": "CreateFileResponse" }, "mediaUpload": { "accept": [ "*/*" ], "protocols": { "resumable": { "multipart": true, "path": "/resumable/upload/v1/files" }, "simple": { "multipart": true, "path": "/upload/v1/files" } }, "maxSize": "2147483648" }, "request": { "$ref": "CreateFileRequest" }, "parameterOrder": [], "flatPath": "v1/files", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "path": "v1/files", "httpMethod": "POST", "id": "generativelanguage.media.upload", "supportsMediaUpload": true }, "download": { "path": "v1/{+name}", "parameters": { "name": { "required": true, "pattern": "^fileSearchStores/[^/]+/media/.*$", "type": "string", "location": "path", "description": "Required. The resource name of the media to download. Example: `fileSearchStores/abc-123/media/blob123`" } }, "useMediaDownloadService": true, "id": "generativelanguage.media.download", "description": "Downloads media from a `FileSearchStore`.", "response": { "$ref": "DownloadMediaResponse" }, "httpMethod": "GET", "supportsMediaDownload": true, "flatPath": "v1/fileSearchStores/{fileSearchStoresId}/media/{mediaId}", "parameterOrder": [ "name" ] }, "uploadToFileSearchStore": { "request": { "$ref": "UploadToFileSearchStoreRequest" }, "httpMethod": "POST", "id": "generativelanguage.media.uploadToFileSearchStore", "flatPath": "v1/fileSearchStores/{fileSearchStoresId}:uploadToFileSearchStore", "path": "v1/{+fileSearchStoreName}:uploadToFileSearchStore", "scopes": [ "https://www.googleapis.com/auth/devstorage.read_only" ], "response": { "$ref": "CustomLongRunningOperation" }, "supportsMediaUpload": true, "mediaUpload": { "maxSize": "104857600", "accept": [ "*/*" ], "protocols": { "simple": { "multipart": true, "path": "/upload/v1/{+fileSearchStoreName}:uploadToFileSearchStore" }, "resumable": { "path": "/resumable/upload/v1/{+fileSearchStoreName}:uploadToFileSearchStore", "multipart": true } } }, "parameterOrder": [ "fileSearchStoreName" ], "parameters": { "fileSearchStoreName": { "location": "path", "description": "Required. Immutable. The name of the `FileSearchStore` to upload the file into. Example: `fileSearchStores/my-file-search-store-123`", "type": "string", "required": true, "pattern": "^fileSearchStores/[^/]+$" } }, "description": "Uploads data to a FileSearchStore, preprocesses and chunks before storing it in a FileSearchStore Document." } } }, "tunedModels": { "methods": { "generateContent": { "request": { "$ref": "GenerateContentRequest" }, "httpMethod": "POST", "flatPath": "v1/tunedModels/{tunedModelsId}:generateContent", "id": "generativelanguage.tunedModels.generateContent", "description": "Generates a model response given an input `GenerateContentRequest`. Refer to the [text generation guide](https://ai.google.dev/gemini-api/docs/text-generation) for detailed usage information. Input capabilities differ between models, including tuned models. Refer to the [model guide](https://ai.google.dev/gemini-api/docs/models/gemini) and [tuning guide](https://ai.google.dev/gemini-api/docs/model-tuning) for details.", "parameterOrder": [ "model" ], "parameters": { "model": { "type": "string", "location": "path", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^tunedModels/[^/]+$", "required": true } }, "response": { "$ref": "GenerateContentResponse" }, "path": "v1/{+model}:generateContent" }, "streamGenerateContent": { "id": "generativelanguage.tunedModels.streamGenerateContent", "httpMethod": "POST", "parameterOrder": [ "model" ], "response": { "$ref": "GenerateContentResponse" }, "request": { "$ref": "GenerateContentRequest" }, "path": "v1/{+model}:streamGenerateContent", "description": "Generates a [streamed response](https://ai.google.dev/gemini-api/docs/text-generation?lang=python#generate-a-text-stream) from the model given an input `GenerateContentRequest`.", "flatPath": "v1/tunedModels/{tunedModelsId}:streamGenerateContent", "parameters": { "model": { "location": "path", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^tunedModels/[^/]+$", "type": "string", "required": true } } }, "batchGenerateContent": { "parameterOrder": [ "model" ], "parameters": { "model": { "type": "string", "location": "path", "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "pattern": "^tunedModels/[^/]+$", "required": true } }, "id": "generativelanguage.tunedModels.batchGenerateContent", "path": "v1/{+model}:batchGenerateContent", "httpMethod": "POST", "flatPath": "v1/tunedModels/{tunedModelsId}:batchGenerateContent", "description": "Enqueues a batch of `GenerateContent` requests for batch processing.", "response": { "$ref": "Operation" }, "request": { "$ref": "BatchGenerateContentRequest" } }, "asyncBatchEmbedContent": { "flatPath": "v1/tunedModels/{tunedModelsId}:asyncBatchEmbedContent", "id": "generativelanguage.tunedModels.asyncBatchEmbedContent", "parameterOrder": [ "model" ], "description": "Enqueues a batch of `EmbedContent` requests for batch processing. We have a `BatchEmbedContents` handler in `GenerativeService`, but it was synchronized. So we name this one to be `Async` to avoid confusion.", "request": { "$ref": "AsyncBatchEmbedContentRequest" }, "parameters": { "model": { "description": "Required. The name of the `Model` to use for generating the completion. Format: `models/{model}`.", "required": true, "location": "path", "pattern": "^tunedModels/[^/]+$", "type": "string" } }, "response": { "$ref": "Operation" }, "httpMethod": "POST", "path": "v1/{+model}:asyncBatchEmbedContent" } }, "resources": { "operations": { "methods": { "cancel": { "path": "v1/{+name}:cancel", "response": { "$ref": "Empty" }, "httpMethod": "POST", "parameterOrder": [ "name" ], "description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.", "flatPath": "v1/tunedModels/{tunedModelsId}/operations/{operationsId}:cancel", "request": { "$ref": "CancelOperationRequest" }, "id": "generativelanguage.tunedModels.operations.cancel", "parameters": { "name": { "description": "The name of the operation resource to be cancelled.", "type": "string", "pattern": "^tunedModels/[^/]+/operations/[^/]+$", "location": "path", "required": true } } }, "list": { "id": "generativelanguage.tunedModels.operations.list", "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "flatPath": "v1/tunedModels/{tunedModelsId}/operations", "httpMethod": "GET", "parameters": { "pageToken": { "location": "query", "type": "string", "description": "The standard list page token." }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "type": "boolean", "location": "query" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "name": { "required": true, "type": "string", "description": "The name of the operation's parent resource.", "pattern": "^tunedModels/[^/]+$", "location": "path" }, "pageSize": { "description": "The standard list page size.", "type": "integer", "location": "query", "format": "int32" } }, "path": "v1/{+name}/operations", "parameterOrder": [ "name" ], "response": { "$ref": "ListOperationsResponse" } }, "get": { "response": { "$ref": "Operation" }, "parameterOrder": [ "name" ], "httpMethod": "GET", "parameters": { "name": { "description": "The name of the operation resource.", "location": "path", "required": true, "pattern": "^tunedModels/[^/]+/operations/[^/]+$", "type": "string" } }, "path": "v1/{+name}", "flatPath": "v1/tunedModels/{tunedModelsId}/operations/{operationsId}", "description": "Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.", "id": "generativelanguage.tunedModels.operations.get" } } } } }, "operations": { "methods": { "list": { "path": "v1/{+name}", "response": { "$ref": "ListOperationsResponse" }, "id": "generativelanguage.operations.list", "httpMethod": "GET", "parameters": { "pageToken": { "type": "string", "location": "query", "description": "The standard list page token." }, "name": { "pattern": "^operations$", "location": "path", "description": "The name of the operation's parent resource.", "required": true, "type": "string" }, "filter": { "description": "The standard list filter.", "location": "query", "type": "string" }, "returnPartialSuccess": { "description": "When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `\"projects/example/locations/-\"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.", "location": "query", "type": "boolean" }, "pageSize": { "format": "int32", "type": "integer", "location": "query", "description": "The standard list page size." } }, "description": "Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.", "parameterOrder": [ "name" ], "flatPath": "v1/operations" }, "delete": { "path": "v1/{+name}", "id": "generativelanguage.operations.delete", "response": { "$ref": "Empty" }, "flatPath": "v1/operations/{operationsId}", "httpMethod": "DELETE", "parameters": { "name": { "required": true, "location": "path", "type": "string", "description": "The name of the operation resource to be deleted.", "pattern": "^operations/.*$" } }, "description": "Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.", "parameterOrder": [ "name" ] } } } }, "documentationLink": "https://developers.generativeai.google/api", "discoveryVersion": "v1", "canonicalName": "Generative Language", "name": "generativelanguage", "id": "generativelanguage:v1", "basePath": "", "parameters": { "callback": { "type": "string", "location": "query", "description": "JSONP" }, "alt": { "type": "string", "enum": [ "json", "media", "proto" ], "description": "Data format for response.", "enumDescriptions": [ "Responses with Content-Type of application/json", "Media download with context-dependent Content-Type", "Responses with Content-Type of application/x-protobuf" ], "default": "json", "location": "query" }, "key": { "description": "API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token.", "type": "string", "location": "query" }, "access_token": { "type": "string", "location": "query", "description": "OAuth access token." }, "upload_protocol": { "type": "string", "location": "query", "description": "Upload protocol for media (e.g. \"raw\", \"multipart\")." }, "quotaUser": { "location": "query", "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." }, "prettyPrint": { "type": "boolean", "default": "true", "location": "query", "description": "Returns response with indentations and line breaks." }, "fields": { "description": "Selector specifying which fields to include in a partial response.", "type": "string", "location": "query" }, "uploadType": { "location": "query", "type": "string", "description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\")." }, "$.xgafv": { "enum": [ "1", "2" ], "description": "V1 error format.", "enumDescriptions": [ "v1 error format", "v2 error format" ], "type": "string", "location": "query" }, "oauth_token": { "description": "OAuth 2.0 token for the current user.", "location": "query", "type": "string" } }, "revision": "20260904" }