feat(aiplatform): update the api

#### aiplatform:v1

The following keys were deleted:
- schemas.GoogleCloudAiplatformV1VertexRagStore.properties.ragCorpora (Total Keys: 3)

The following keys were added:
- resources.media.methods.upload (Total Keys: 16)
- resources.projects.resources.locations.methods.augmentPrompt (Total Keys: 12)
- resources.projects.resources.locations.methods.corroborateContent (Total Keys: 12)
- resources.projects.resources.locations.methods.retrieveContexts (Total Keys: 12)
- resources.projects.resources.locations.resources.cachedContents.methods.create (Total Keys: 12)
- resources.projects.resources.locations.resources.cachedContents.methods.delete (Total Keys: 11)
- resources.projects.resources.locations.resources.cachedContents.methods.get (Total Keys: 11)
- resources.projects.resources.locations.resources.cachedContents.methods.list (Total Keys: 16)
- resources.projects.resources.locations.resources.cachedContents.methods.patch (Total Keys: 15)
- resources.projects.resources.locations.resources.ragCorpora.methods.create (Total Keys: 12)
- resources.projects.resources.locations.resources.ragCorpora.methods.delete (Total Keys: 13)
- resources.projects.resources.locations.resources.ragCorpora.methods.get (Total Keys: 11)
- resources.projects.resources.locations.resources.ragCorpora.methods.list (Total Keys: 16)
- resources.projects.resources.locations.resources.ragCorpora.methods.patch (Total Keys: 12)
- resources.projects.resources.locations.resources.ragCorpora.resources.ragFiles.methods.delete (Total Keys: 11)
- resources.projects.resources.locations.resources.ragCorpora.resources.ragFiles.methods.get (Total Keys: 11)
- resources.projects.resources.locations.resources.ragCorpora.resources.ragFiles.methods.import (Total Keys: 12)
- resources.projects.resources.locations.resources.ragCorpora.resources.ragFiles.methods.list (Total Keys: 16)
- resources.projects.resources.locations.resources.reasoningEngines.methods.query (Total Keys: 12)
- schemas.GoogleCloudAiplatformV1ApiAuth (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1AugmentPromptRequest (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1AugmentPromptResponse (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1CachedContent (Total Keys: 35)
- schemas.GoogleCloudAiplatformV1Claim (Total Keys: 11)
- schemas.GoogleCloudAiplatformV1CorpusStatus (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1CorroborateContentRequest (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1CorroborateContentResponse (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1DedicatedResources.properties.requiredReplicaCount (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1DeployedModel.properties.status (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1DeployedModelStatus (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1DirectUploadSource (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1Fact (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1FileStatus (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1GenerateContentRequest.properties.cachedContent.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1GenerateContentResponseUsageMetadata.properties.cachedContentTokenCount (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1GoogleDriveSource (Total Keys: 8)
- schemas.GoogleCloudAiplatformV1ImportRagFilesConfig (Total Keys: 13)
- schemas.GoogleCloudAiplatformV1ImportRagFilesRequest (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1JiraSource (Total Keys: 13)
- schemas.GoogleCloudAiplatformV1ListCachedContentsResponse (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1ListRagCorporaResponse (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1ListRagFilesResponse (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1QueryReasoningEngineRequest (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1QueryReasoningEngineResponse (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1RagContexts (Total Keys: 11)
- schemas.GoogleCloudAiplatformV1RagCorpus (Total Keys: 14)
- schemas.GoogleCloudAiplatformV1RagEmbeddingModelConfig (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1RagFile (Total Keys: 33)
- schemas.GoogleCloudAiplatformV1RagQuery (Total Keys: 4)
- schemas.GoogleCloudAiplatformV1RagRetrievalConfig (Total Keys: 12)
- schemas.GoogleCloudAiplatformV1RagVectorDbConfig (Total Keys: 13)
- schemas.GoogleCloudAiplatformV1RetrieveContextsRequest (Total Keys: 16)
- schemas.GoogleCloudAiplatformV1RetrieveContextsResponse (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1SlackSource (Total Keys: 16)
- schemas.GoogleCloudAiplatformV1TuningJob.properties.serviceAccount.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1UploadRagFileConfig (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1UploadRagFileRequest (Total Keys: 4)
- schemas.GoogleCloudAiplatformV1UploadRagFileResponse (Total Keys: 4)
- schemas.GoogleCloudAiplatformV1VertexRagStore.properties.ragRetrievalConfig.$ref (Total Keys: 1)

#### aiplatform:v1beta1

The following keys were added:
- schemas.GoogleCloudAiplatformV1beta1DedicatedResources.properties.requiredReplicaCount (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1DeployedModel.properties.status (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1DeployedModelStatus (Total Keys: 10)
- schemas.GoogleCloudAiplatformV1beta1Extension.properties.satisfiesPzi (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1Extension.properties.satisfiesPzs (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1Fact.properties.score (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1ImportRagFilesConfig.properties.ragFileTransformationConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagContextsContext.properties.score (Total Keys: 2)
- schemas.GoogleCloudAiplatformV1beta1RagContextsContext.properties.sourceDisplayName.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagCorpus.properties.vectorDbConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagCorpus.properties.vertexAiSearchConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagFileChunkingConfig.properties.fixedLengthChunking.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking (Total Keys: 6)
- schemas.GoogleCloudAiplatformV1beta1RagFileParsingConfig.properties.advancedParser.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagFileParsingConfig.properties.layoutParser.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1beta1RagFileTransformationConfig (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1beta1RagQuery.properties.ragRetrievalConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1RagRetrievalConfig (Total Keys: 28)
- schemas.GoogleCloudAiplatformV1beta1RagVectorDbConfig.properties.ragEmbeddingModelConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1TuningJob.properties.serviceAccount.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1UploadRagFileConfig.properties.ragFileTransformationConfig.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1VertexAiSearchConfig (Total Keys: 3)
- schemas.GoogleCloudAiplatformV1beta1VertexRagStore.properties.ragRetrievalConfig.$ref (Total Keys: 1)

Author: yoshi-automation

docs/dyn/aiplatform_v1.endpoints.html

@@ -395,9 +395,6 @@ <h3>Method Details</h3>
           &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
-          &quot;ragCorpora&quot;: [ # Optional. Deprecated. Please use rag_resources instead.
-            &quot;A String&quot;,
-          ],
           &quot;ragResources&quot;: [ # 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.
               &quot;ragCorpus&quot;: &quot;A String&quot;, # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
@@ -406,6 +403,14 @@ <h3>Method Details</h3>
               ],
             },
           ],
+          &quot;ragRetrievalConfig&quot;: { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+            &quot;filter&quot;: { # Config for filters. # Optional. Config for filters.
+              &quot;metadataFilter&quot;: &quot;A String&quot;, # Optional. String for metadata filtering.
+              &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+              &quot;vectorSimilarityThreshold&quot;: 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+            },
+            &quot;topK&quot;: 42, # Optional. The number of contexts to retrieve.
+          },
           &quot;similarityTopK&quot;: 42, # Optional. Number of top k results to return from the selected corpora.
           &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only return results with vector distance smaller than the threshold.
         },
@@ -438,6 +443,7 @@ <h3>Method Details</h3>
     The object takes the form of:
 
 { # Request message for [PredictionService.GenerateContent].
+  &quot;cachedContent&quot;: &quot;A String&quot;, # Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`
   &quot;contents&quot;: [ # Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.
     { # 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.
       &quot;parts&quot;: [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
@@ -669,9 +675,6 @@ <h3>Method Details</h3>
           &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
-          &quot;ragCorpora&quot;: [ # Optional. Deprecated. Please use rag_resources instead.
-            &quot;A String&quot;,
-          ],
           &quot;ragResources&quot;: [ # 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.
               &quot;ragCorpus&quot;: &quot;A String&quot;, # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
@@ -680,6 +683,14 @@ <h3>Method Details</h3>
               ],
             },
           ],
+          &quot;ragRetrievalConfig&quot;: { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+            &quot;filter&quot;: { # Config for filters. # Optional. Config for filters.
+              &quot;metadataFilter&quot;: &quot;A String&quot;, # Optional. String for metadata filtering.
+              &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+              &quot;vectorSimilarityThreshold&quot;: 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+            },
+            &quot;topK&quot;: 42, # Optional. The number of contexts to retrieve.
+          },
           &quot;similarityTopK&quot;: 42, # Optional. Number of top k results to return from the selected corpora.
           &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only return results with vector distance smaller than the threshold.
         },
@@ -840,6 +851,7 @@ <h3>Method Details</h3>
     ],
   },
   &quot;usageMetadata&quot;: { # Usage metadata about response(s). # Usage metadata about the response(s).
+    &quot;cachedContentTokenCount&quot;: 42, # Output only. Number of tokens in the cached part in the input (the cached content).
     &quot;candidatesTokenCount&quot;: 42, # Number of tokens in the response(s).
     &quot;promptTokenCount&quot;: 42, # Number of tokens in the request. When `cached_content` is set, this is still the total effective prompt size meaning this includes the number of tokens in the cached content.
     &quot;totalTokenCount&quot;: 42, # Total token count for prompt and response candidates.
@@ -857,6 +869,7 @@ <h3>Method Details</h3>
     The object takes the form of:
 
 { # Request message for [PredictionService.GenerateContent].
+  &quot;cachedContent&quot;: &quot;A String&quot;, # Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}`
   &quot;contents&quot;: [ # Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.
     { # 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.
       &quot;parts&quot;: [ # Required. Ordered `Parts` that constitute a single message. Parts may have different IANA MIME types.
@@ -1088,9 +1101,6 @@ <h3>Method Details</h3>
           &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
         },
         &quot;vertexRagStore&quot;: { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
-          &quot;ragCorpora&quot;: [ # Optional. Deprecated. Please use rag_resources instead.
-            &quot;A String&quot;,
-          ],
           &quot;ragResources&quot;: [ # 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.
               &quot;ragCorpus&quot;: &quot;A String&quot;, # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
@@ -1099,6 +1109,14 @@ <h3>Method Details</h3>
               ],
             },
           ],
+          &quot;ragRetrievalConfig&quot;: { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+            &quot;filter&quot;: { # Config for filters. # Optional. Config for filters.
+              &quot;metadataFilter&quot;: &quot;A String&quot;, # Optional. String for metadata filtering.
+              &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+              &quot;vectorSimilarityThreshold&quot;: 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+            },
+            &quot;topK&quot;: 42, # Optional. The number of contexts to retrieve.
+          },
           &quot;similarityTopK&quot;: 42, # Optional. Number of top k results to return from the selected corpora.
           &quot;vectorDistanceThreshold&quot;: 3.14, # Optional. Only return results with vector distance smaller than the threshold.
         },
@@ -1259,6 +1277,7 @@ <h3>Method Details</h3>
     ],
   },
   &quot;usageMetadata&quot;: { # Usage metadata about response(s). # Usage metadata about the response(s).
+    &quot;cachedContentTokenCount&quot;: 42, # Output only. Number of tokens in the cached part in the input (the cached content).
     &quot;candidatesTokenCount&quot;: 42, # Number of tokens in the response(s).
     &quot;promptTokenCount&quot;: 42, # Number of tokens in the request. When `cached_content` is set, this is still the total effective prompt size meaning this includes the number of tokens in the cached content.
     &quot;totalTokenCount&quot;: 42, # Total token count for prompt and response candidates.

docs/dyn/aiplatform_v1.html

@@ -84,6 +84,11 @@ <h2>Instance Methods</h2>
 </p>
 <p class="firstline">Returns the endpoints Resource.</p>
 
+<p class="toc_element">
+  <code><a href="aiplatform_v1.media.html">media()</a></code>
+</p>
+<p class="firstline">Returns the media Resource.</p>
+
 <p class="toc_element">
   <code><a href="aiplatform_v1.projects.html">projects()</a></code>
 </p>