Vertex AI API . projects . locations . cachedContents

close()

Close httplib2 connections.

create(parent, body=None, x__xgafv=None)

Creates cached content, this call will initialize the cached content in the data storage, and users need to pay for the cache data storage.

Args:
  parent: string, Required. The parent resource where the cached content will be created (required)
  body: object, The request body.
    The object takes the form of:

{ # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
  "contents": [ # Optional. Input only. Immutable. The content to cache
    { # 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.
      "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
        { # 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 `inline_data` or `file_data` field is filled with raw bytes.
          "fileData": { # URI based data. # Optional. URI based data.
            "fileUri": "A String", # Required. URI.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
            "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
              "a_key": "", # Properties of the object.
            },
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
          },
          "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
            "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
              "a_key": "", # Properties of the object.
            },
          },
          "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
            "data": "A String", # Required. Raw bytes.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "text": "A String", # Optional. Text part (can be code).
          "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
            "endOffset": "A String", # Optional. The end offset of the video.
            "startOffset": "A String", # Optional. The start offset of the video.
          },
        },
      ],
      "role": "A String", # 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.
    },
  ],
  "createTime": "A String", # Output only. Creatation time of the cache entry.
  "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
  "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
  "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
  "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
  "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
    "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
      { # 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 `inline_data` or `file_data` field is filled with raw bytes.
        "fileData": { # URI based data. # Optional. URI based data.
          "fileUri": "A String", # Required. URI.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
          "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
            "a_key": "", # Properties of the object.
          },
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
        },
        "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
          "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
            "a_key": "", # Properties of the object.
          },
        },
        "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
          "data": "A String", # Required. Raw bytes.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "text": "A String", # Optional. Text part (can be code).
        "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
          "endOffset": "A String", # Optional. The end offset of the video.
          "startOffset": "A String", # Optional. The start offset of the video.
        },
      },
    ],
    "role": "A String", # 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.
  },
  "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
    "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
      "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
        "A String",
      ],
      "mode": "A String", # Optional. Function calling mode.
    },
  },
  "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
    { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
      "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
        { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
          "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
          "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
          "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
          "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
        },
      ],
      "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
      },
      "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
        "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
          "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
          "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
        },
      },
      "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
        "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
        "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
          "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
        },
        "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
          "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
            { # The definition of the Rag resource.
              "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
              "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                "A String",
              ],
            },
          ],
          "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
            "filter": { # Config for filters. # Optional. Config for filters.
              "metadataFilter": "A String", # Optional. String for metadata filtering.
              "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
              "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
            },
            "topK": 42, # Optional. The number of contexts to retrieve.
          },
          "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
          "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
        },
      },
    },
  ],
  "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
  "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
  "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
    "audioDurationSeconds": 42, # Duration of audio in seconds.
    "imageCount": 42, # Number of images.
    "textCount": 42, # Number of text characters.
    "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
    "videoDurationSeconds": 42, # Duration of video in seconds.
  },
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
  "contents": [ # Optional. Input only. Immutable. The content to cache
    { # 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.
      "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
        { # 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 `inline_data` or `file_data` field is filled with raw bytes.
          "fileData": { # URI based data. # Optional. URI based data.
            "fileUri": "A String", # Required. URI.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
            "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
              "a_key": "", # Properties of the object.
            },
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
          },
          "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
            "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
              "a_key": "", # Properties of the object.
            },
          },
          "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
            "data": "A String", # Required. Raw bytes.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "text": "A String", # Optional. Text part (can be code).
          "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
            "endOffset": "A String", # Optional. The end offset of the video.
            "startOffset": "A String", # Optional. The start offset of the video.
          },
        },
      ],
      "role": "A String", # 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.
    },
  ],
  "createTime": "A String", # Output only. Creatation time of the cache entry.
  "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
  "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
  "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
  "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
  "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
    "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
      { # 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 `inline_data` or `file_data` field is filled with raw bytes.
        "fileData": { # URI based data. # Optional. URI based data.
          "fileUri": "A String", # Required. URI.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
          "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
            "a_key": "", # Properties of the object.
          },
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
        },
        "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
          "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
            "a_key": "", # Properties of the object.
          },
        },
        "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
          "data": "A String", # Required. Raw bytes.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "text": "A String", # Optional. Text part (can be code).
        "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
          "endOffset": "A String", # Optional. The end offset of the video.
          "startOffset": "A String", # Optional. The start offset of the video.
        },
      },
    ],
    "role": "A String", # 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.
  },
  "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
    "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
      "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
        "A String",
      ],
      "mode": "A String", # Optional. Function calling mode.
    },
  },
  "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
    { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
      "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
        { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
          "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
          "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
          "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
          "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
        },
      ],
      "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
      },
      "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
        "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
          "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
          "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
        },
      },
      "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
        "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
        "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
          "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
        },
        "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
          "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
            { # The definition of the Rag resource.
              "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
              "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                "A String",
              ],
            },
          ],
          "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
            "filter": { # Config for filters. # Optional. Config for filters.
              "metadataFilter": "A String", # Optional. String for metadata filtering.
              "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
              "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
            },
            "topK": 42, # Optional. The number of contexts to retrieve.
          },
          "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
          "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
        },
      },
    },
  ],
  "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
  "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
  "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
    "audioDurationSeconds": 42, # Duration of audio in seconds.
    "imageCount": 42, # Number of images.
    "textCount": 42, # Number of text characters.
    "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
    "videoDurationSeconds": 42, # Duration of video in seconds.
  },
}

delete(name, x__xgafv=None)

Deletes cached content

Args:
  name: string, Required. The resource name referring to the cached content (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # 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); }
}

get(name, x__xgafv=None)

Gets cached content configurations

Args:
  name: string, Required. The resource name referring to the cached content (required)
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
  "contents": [ # Optional. Input only. Immutable. The content to cache
    { # 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.
      "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
        { # 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 `inline_data` or `file_data` field is filled with raw bytes.
          "fileData": { # URI based data. # Optional. URI based data.
            "fileUri": "A String", # Required. URI.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
            "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
              "a_key": "", # Properties of the object.
            },
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
          },
          "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
            "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
              "a_key": "", # Properties of the object.
            },
          },
          "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
            "data": "A String", # Required. Raw bytes.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "text": "A String", # Optional. Text part (can be code).
          "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
            "endOffset": "A String", # Optional. The end offset of the video.
            "startOffset": "A String", # Optional. The start offset of the video.
          },
        },
      ],
      "role": "A String", # 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.
    },
  ],
  "createTime": "A String", # Output only. Creatation time of the cache entry.
  "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
  "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
  "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
  "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
  "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
    "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
      { # 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 `inline_data` or `file_data` field is filled with raw bytes.
        "fileData": { # URI based data. # Optional. URI based data.
          "fileUri": "A String", # Required. URI.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
          "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
            "a_key": "", # Properties of the object.
          },
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
        },
        "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
          "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
            "a_key": "", # Properties of the object.
          },
        },
        "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
          "data": "A String", # Required. Raw bytes.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "text": "A String", # Optional. Text part (can be code).
        "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
          "endOffset": "A String", # Optional. The end offset of the video.
          "startOffset": "A String", # Optional. The start offset of the video.
        },
      },
    ],
    "role": "A String", # 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.
  },
  "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
    "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
      "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
        "A String",
      ],
      "mode": "A String", # Optional. Function calling mode.
    },
  },
  "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
    { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
      "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
        { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
          "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
          "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
          "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
          "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
        },
      ],
      "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
      },
      "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
        "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
          "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
          "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
        },
      },
      "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
        "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
        "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
          "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
        },
        "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
          "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
            { # The definition of the Rag resource.
              "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
              "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                "A String",
              ],
            },
          ],
          "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
            "filter": { # Config for filters. # Optional. Config for filters.
              "metadataFilter": "A String", # Optional. String for metadata filtering.
              "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
              "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
            },
            "topK": 42, # Optional. The number of contexts to retrieve.
          },
          "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
          "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
        },
      },
    },
  ],
  "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
  "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
  "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
    "audioDurationSeconds": 42, # Duration of audio in seconds.
    "imageCount": 42, # Number of images.
    "textCount": 42, # Number of text characters.
    "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
    "videoDurationSeconds": 42, # Duration of video in seconds.
  },
}

list(parent, pageSize=None, pageToken=None, x__xgafv=None)

Lists cached contents in a project

Args:
  parent: string, Required. The parent, which owns this collection of cached contents. (required)
  pageSize: integer, 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: string, 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.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response with a list of CachedContents.
  "cachedContents": [ # List of cached contents.
    { # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
      "contents": [ # Optional. Input only. Immutable. The content to cache
        { # 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.
          "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
            { # 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 `inline_data` or `file_data` field is filled with raw bytes.
              "fileData": { # URI based data. # Optional. URI based data.
                "fileUri": "A String", # Required. URI.
                "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
              },
              "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
                "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
                  "a_key": "", # Properties of the object.
                },
                "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
              },
              "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
                "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
                "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
                  "a_key": "", # Properties of the object.
                },
              },
              "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
                "data": "A String", # Required. Raw bytes.
                "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
              },
              "text": "A String", # Optional. Text part (can be code).
              "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
                "endOffset": "A String", # Optional. The end offset of the video.
                "startOffset": "A String", # Optional. The start offset of the video.
              },
            },
          ],
          "role": "A String", # 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.
        },
      ],
      "createTime": "A String", # Output only. Creatation time of the cache entry.
      "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
      "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
      "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
      "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
      "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
        "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
          { # 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 `inline_data` or `file_data` field is filled with raw bytes.
            "fileData": { # URI based data. # Optional. URI based data.
              "fileUri": "A String", # Required. URI.
              "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
            },
            "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
              "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
                "a_key": "", # Properties of the object.
              },
              "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
            },
            "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
              "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
              "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
                "a_key": "", # Properties of the object.
              },
            },
            "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
              "data": "A String", # Required. Raw bytes.
              "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
            },
            "text": "A String", # Optional. Text part (can be code).
            "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
              "endOffset": "A String", # Optional. The end offset of the video.
              "startOffset": "A String", # Optional. The start offset of the video.
            },
          },
        ],
        "role": "A String", # 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.
      },
      "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
        "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
          "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
            "A String",
          ],
          "mode": "A String", # Optional. Function calling mode.
        },
      },
      "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
              "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
                  # Object with schema name: GoogleCloudAiplatformV1Schema
                ],
                "default": "", # Optional. Default value of the data.
                "description": "A String", # Optional. The description of the data.
                "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
                  "A String",
                ],
                "example": "", # Optional. Example of the object. Will only populated when the object is the root.
                "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
                "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
                "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
                "maxLength": "A String", # Optional. Maximum length of the Type.STRING
                "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
                "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
                "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
                "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
                "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
                "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
                "nullable": True or False, # Optional. Indicates if the value may be null.
                "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
                "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
                },
                "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
                  "A String",
                ],
                "required": [ # Optional. Required properties of Type.OBJECT.
                  "A String",
                ],
                "title": "A String", # Optional. The title of the Schema.
                "type": "A String", # Optional. The type of the data.
              },
              "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
                "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
                  # Object with schema name: GoogleCloudAiplatformV1Schema
                ],
                "default": "", # Optional. Default value of the data.
                "description": "A String", # Optional. The description of the data.
                "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
                  "A String",
                ],
                "example": "", # Optional. Example of the object. Will only populated when the object is the root.
                "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
                "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
                "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
                "maxLength": "A String", # Optional. Maximum length of the Type.STRING
                "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
                "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
                "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
                "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
                "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
                "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
                "nullable": True or False, # Optional. Indicates if the value may be null.
                "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
                "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
                },
                "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
                  "A String",
                ],
                "required": [ # Optional. Required properties of Type.OBJECT.
                  "A String",
                ],
                "title": "A String", # Optional. The title of the Schema.
                "type": "A String", # Optional. The type of the data.
              },
            },
          ],
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
        },
      ],
      "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
      "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
      "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
        "audioDurationSeconds": 42, # Duration of audio in seconds.
        "imageCount": 42, # Number of images.
        "textCount": 42, # Number of text characters.
        "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
        "videoDurationSeconds": 42, # Duration of video in seconds.
      },
    },
  ],
  "nextPageToken": "A String", # A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages.
}

list_next()

Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.
        

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates cached content configurations

Args:
  name: string, Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content} (required)
  body: object, The request body.
    The object takes the form of:

{ # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
  "contents": [ # Optional. Input only. Immutable. The content to cache
    { # 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.
      "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
        { # 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 `inline_data` or `file_data` field is filled with raw bytes.
          "fileData": { # URI based data. # Optional. URI based data.
            "fileUri": "A String", # Required. URI.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
            "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
              "a_key": "", # Properties of the object.
            },
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
          },
          "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
            "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
              "a_key": "", # Properties of the object.
            },
          },
          "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
            "data": "A String", # Required. Raw bytes.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "text": "A String", # Optional. Text part (can be code).
          "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
            "endOffset": "A String", # Optional. The end offset of the video.
            "startOffset": "A String", # Optional. The start offset of the video.
          },
        },
      ],
      "role": "A String", # 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.
    },
  ],
  "createTime": "A String", # Output only. Creatation time of the cache entry.
  "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
  "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
  "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
  "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
  "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
    "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
      { # 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 `inline_data` or `file_data` field is filled with raw bytes.
        "fileData": { # URI based data. # Optional. URI based data.
          "fileUri": "A String", # Required. URI.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
          "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
            "a_key": "", # Properties of the object.
          },
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
        },
        "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
          "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
            "a_key": "", # Properties of the object.
          },
        },
        "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
          "data": "A String", # Required. Raw bytes.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "text": "A String", # Optional. Text part (can be code).
        "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
          "endOffset": "A String", # Optional. The end offset of the video.
          "startOffset": "A String", # Optional. The start offset of the video.
        },
      },
    ],
    "role": "A String", # 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.
  },
  "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
    "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
      "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
        "A String",
      ],
      "mode": "A String", # Optional. Function calling mode.
    },
  },
  "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
    { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
      "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
        { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
          "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
          "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
          "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
          "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
        },
      ],
      "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
      },
      "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
        "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
          "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
          "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
        },
      },
      "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
        "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
        "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
          "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
        },
        "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
          "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
            { # The definition of the Rag resource.
              "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
              "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                "A String",
              ],
            },
          ],
          "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
            "filter": { # Config for filters. # Optional. Config for filters.
              "metadataFilter": "A String", # Optional. String for metadata filtering.
              "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
              "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
            },
            "topK": 42, # Optional. The number of contexts to retrieve.
          },
          "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
          "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
        },
      },
    },
  ],
  "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
  "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
  "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
    "audioDurationSeconds": 42, # Duration of audio in seconds.
    "imageCount": 42, # Number of images.
    "textCount": 42, # Number of text characters.
    "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
    "videoDurationSeconds": 42, # Duration of video in seconds.
  },
}

  updateMask: string, Required. The list of fields to update.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # A resource used in LLM queries for users to explicitly specify what to cache and how to cache.
  "contents": [ # Optional. Input only. Immutable. The content to cache
    { # 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.
      "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
        { # 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 `inline_data` or `file_data` field is filled with raw bytes.
          "fileData": { # URI based data. # Optional. URI based data.
            "fileUri": "A String", # Required. URI.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
            "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
              "a_key": "", # Properties of the object.
            },
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
          },
          "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
            "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
            "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
              "a_key": "", # Properties of the object.
            },
          },
          "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
            "data": "A String", # Required. Raw bytes.
            "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
          },
          "text": "A String", # Optional. Text part (can be code).
          "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
            "endOffset": "A String", # Optional. The end offset of the video.
            "startOffset": "A String", # Optional. The start offset of the video.
          },
        },
      ],
      "role": "A String", # 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.
    },
  ],
  "createTime": "A String", # Output only. Creatation time of the cache entry.
  "displayName": "A String", # Optional. Immutable. The user-generated meaningful display name of the cached content.
  "expireTime": "A String", # Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
  "model": "A String", # Immutable. The name of the publisher model to use for cached content. Format: projects/{project}/locations/{location}/publishers/{publisher}/models/{model}
  "name": "A String", # Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
  "systemInstruction": { # 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. # Optional. Input only. Immutable. Developer set system instruction. Currently, text only
    "parts": [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
      { # 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 `inline_data` or `file_data` field is filled with raw bytes.
        "fileData": { # URI based data. # Optional. URI based data.
          "fileUri": "A String", # Required. URI.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] with the parameters and their values.
          "args": { # Optional. Required. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
            "a_key": "", # Properties of the object.
          },
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name].
        },
        "functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result output of a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function call. It is used as context to the model.
          "name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
          "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
            "a_key": "", # Properties of the object.
          },
        },
        "inlineData": { # Content blob. It's preferred to send as text directly rather than raw bytes. # Optional. Inlined bytes data.
          "data": "A String", # Required. Raw bytes.
          "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
        },
        "text": "A String", # Optional. Text part (can be code).
        "videoMetadata": { # Metadata describes the input video content. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
          "endOffset": "A String", # Optional. The end offset of the video.
          "startOffset": "A String", # Optional. The start offset of the video.
        },
      },
    ],
    "role": "A String", # 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.
  },
  "toolConfig": { # Tool config. This config is shared for all tools provided in the request. # Optional. Input only. Immutable. Tool config. This config is shared for all tools
    "functionCallingConfig": { # Function calling config. # Optional. Function calling config.
      "allowedFunctionNames": [ # Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided.
        "A String",
      ],
      "mode": "A String", # Optional. Function calling mode.
    },
  },
  "tools": [ # Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response
    { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
      "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 128 function declarations can be provided.
        { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
          "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
          "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64.
          "parameters": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
          "response": { # Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. # 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.
            "anyOf": [ # Optional. The value should be validated against any (one or more) of the subschemas in the list.
              # Object with schema name: GoogleCloudAiplatformV1Schema
            ],
            "default": "", # Optional. Default value of the data.
            "description": "A String", # Optional. The description of the data.
            "enum": [ # Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]}
              "A String",
            ],
            "example": "", # Optional. Example of the object. Will only populated when the object is the root.
            "format": "A String", # Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc
            "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY.
            "maxItems": "A String", # Optional. Maximum number of the elements for Type.ARRAY.
            "maxLength": "A String", # Optional. Maximum length of the Type.STRING
            "maxProperties": "A String", # Optional. Maximum number of the properties for Type.OBJECT.
            "maximum": 3.14, # Optional. Maximum value of the Type.INTEGER and Type.NUMBER
            "minItems": "A String", # Optional. Minimum number of the elements for Type.ARRAY.
            "minLength": "A String", # Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING
            "minProperties": "A String", # Optional. Minimum number of the properties for Type.OBJECT.
            "minimum": 3.14, # Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER
            "nullable": True or False, # Optional. Indicates if the value may be null.
            "pattern": "A String", # Optional. Pattern of the Type.STRING to restrict a string to a regular expression.
            "properties": { # Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT.
              "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
            },
            "propertyOrdering": [ # Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties.
              "A String",
            ],
            "required": [ # Optional. Required properties of Type.OBJECT.
              "A String",
            ],
            "title": "A String", # Optional. The title of the Schema.
            "type": "A String", # Optional. The type of the data.
          },
        },
      ],
      "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
      },
      "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. GoogleSearchRetrieval tool type. Specialized retrieval tool that is powered by Google search.
        "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
          "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
          "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
        },
      },
      "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
        "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
        "vertexAiSearch": { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
          "datastore": "A String", # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
        },
        "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
          "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
            { # The definition of the Rag resource.
              "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
              "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                "A String",
              ],
            },
          ],
          "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
            "filter": { # Config for filters. # Optional. Config for filters.
              "metadataFilter": "A String", # Optional. String for metadata filtering.
              "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
              "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
            },
            "topK": 42, # Optional. The number of contexts to retrieve.
          },
          "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
          "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
        },
      },
    },
  ],
  "ttl": "A String", # Input only. The TTL for this resource. The expiration time is computed: now + TTL.
  "updateTime": "A String", # Output only. When the cache entry was last updated in UTC time.
  "usageMetadata": { # Metadata on the usage of the cached content. # Output only. Metadata on the usage of the cached content.
    "audioDurationSeconds": 42, # Duration of audio in seconds.
    "imageCount": 42, # Number of images.
    "textCount": 42, # Number of text characters.
    "totalTokenCount": 42, # Total number of tokens that the cached content consumes.
    "videoDurationSeconds": 42, # Duration of video in seconds.
  },
}