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@@ -74,6 +74,16 @@
 
 <h1><a href="aiplatform_v1.html">Vertex AI API</a></h1>
 <h2>Instance Methods</h2>
+<p class="toc_element">
+  <code><a href="aiplatform_v1.datasets.html">datasets()</a></code>
+</p>
+<p class="firstline">Returns the datasets Resource.</p>
+
+<p class="toc_element">
+  <code><a href="aiplatform_v1.endpoints.html">endpoints()</a></code>
+</p>
+<p class="firstline">Returns the endpoints Resource.</p>
+
 <p class="toc_element">
   <code><a href="aiplatform_v1.projects.html">projects()</a></code>
 </p>
 
@@ -174,6 +174,7 @@ <h3>Method Details</h3>
     ],
     &quot;scheduling&quot;: { # All parameters related to queuing and scheduling of custom jobs. # Scheduling options for a CustomJob.
       &quot;disableRetries&quot;: True or False, # Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
+      &quot;maxWaitDuration&quot;: &quot;A String&quot;, # Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours.
       &quot;restartJobOnWorkerRestart&quot;: True or False, # Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
       &quot;strategy&quot;: &quot;A String&quot;, # Optional. This determines which type of scheduling strategy to use.
       &quot;timeout&quot;: &quot;A String&quot;, # The maximum job running time. The default is 7 days.
@@ -298,6 +299,7 @@ <h3>Method Details</h3>
     ],
     &quot;scheduling&quot;: { # All parameters related to queuing and scheduling of custom jobs. # Scheduling options for a CustomJob.
       &quot;disableRetries&quot;: True or False, # Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
+      &quot;maxWaitDuration&quot;: &quot;A String&quot;, # Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours.
       &quot;restartJobOnWorkerRestart&quot;: True or False, # Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
       &quot;strategy&quot;: &quot;A String&quot;, # Optional. This determines which type of scheduling strategy to use.
       &quot;timeout&quot;: &quot;A String&quot;, # The maximum job running time. The default is 7 days.
@@ -464,6 +466,7 @@ <h3>Method Details</h3>
     ],
     &quot;scheduling&quot;: { # All parameters related to queuing and scheduling of custom jobs. # Scheduling options for a CustomJob.
       &quot;disableRetries&quot;: True or False, # Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
+      &quot;maxWaitDuration&quot;: &quot;A String&quot;, # Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours.
       &quot;restartJobOnWorkerRestart&quot;: True or False, # Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
       &quot;strategy&quot;: &quot;A String&quot;, # Optional. This determines which type of scheduling strategy to use.
       &quot;timeout&quot;: &quot;A String&quot;, # The maximum job running time. The default is 7 days.
@@ -601,6 +604,7 @@ <h3>Method Details</h3>
         ],
         &quot;scheduling&quot;: { # All parameters related to queuing and scheduling of custom jobs. # Scheduling options for a CustomJob.
           &quot;disableRetries&quot;: True or False, # Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false.
+          &quot;maxWaitDuration&quot;: &quot;A String&quot;, # Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours.
           &quot;restartJobOnWorkerRestart&quot;: True or False, # Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job.
           &quot;strategy&quot;: &quot;A String&quot;, # Optional. This determines which type of scheduling strategy to use.
           &quot;timeout&quot;: &quot;A String&quot;, # The maximum job running time. The default is 7 days.
 
@@ -341,8 +341,23 @@ <h3>Method Details</h3>
       },
       &quot;retrieval&quot;: { # 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.
         &quot;disableAttribution&quot;: True or False, # Optional. Deprecated. This option is no longer supported.
-        &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation # Set to use data source powered by Vertex AI Search.
-          &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search&#x27;s datastore resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+        &quot;vertexAiSearch&quot;: { # 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.
+          &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}`
+              &quot;ragFileIds&quot;: [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+                &quot;A String&quot;,
+              ],
+            },
+          ],
+          &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.
         },
       },
     },
@@ -1195,7 +1210,7 @@ <h3>Method Details</h3>
   <pre>Generate content with multimodal inputs.
 
 Args:
-  model: string, Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*` (required)
+  model: string, Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` (required)
   body: object, The request body.
     The object takes the form of:
 
@@ -1268,12 +1283,12 @@ <h3>Method Details</h3>
       &quot;title&quot;: &quot;A String&quot;, # Optional. The title of the Schema.
       &quot;type&quot;: &quot;A String&quot;, # Optional. The type of the data.
     },
-    &quot;routingConfig&quot;: { # Routing config. # Optional. Routing configuration.
+    &quot;routingConfig&quot;: { # The configuration for routing the request to a specific model. # Optional. Routing configuration.
       &quot;autoMode&quot;: { # When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # Automated routing.
         &quot;modelRoutingPreference&quot;: &quot;A String&quot;, # The model routing preference.
       },
       &quot;manualMode&quot;: { # When manual routing is set, the specified model will be used directly. # Manual routing.
-        &quot;modelName&quot;: &quot;A String&quot;, # The model name to use. Only the public LLM models are accepted. e.g. gemini-1.5-pro-001.
+        &quot;modelName&quot;: &quot;A String&quot;, # The model name to use. Only the public LLM models are accepted. e.g. &#x27;gemini-1.5-pro-001&#x27;.
       },
     },
     &quot;seed&quot;: 42, # Optional. Seed.
@@ -1371,8 +1386,23 @@ <h3>Method Details</h3>
       },
       &quot;retrieval&quot;: { # 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.
         &quot;disableAttribution&quot;: True or False, # Optional. Deprecated. This option is no longer supported.
-        &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation # Set to use data source powered by Vertex AI Search.
-          &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search&#x27;s datastore resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+        &quot;vertexAiSearch&quot;: { # 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.
+          &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}`
+              &quot;ragFileIds&quot;: [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+                &quot;A String&quot;,
+              ],
+            },
+          ],
+          &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.
         },
       },
     },
@@ -2831,7 +2861,7 @@ <h3>Method Details</h3>
   <pre>Generate content with multimodal inputs with streaming support.
 
 Args:
-  model: string, Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*` (required)
+  model: string, Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` (required)
   body: object, The request body.
     The object takes the form of:
 
@@ -2904,12 +2934,12 @@ <h3>Method Details</h3>
       &quot;title&quot;: &quot;A String&quot;, # Optional. The title of the Schema.
       &quot;type&quot;: &quot;A String&quot;, # Optional. The type of the data.
     },
-    &quot;routingConfig&quot;: { # Routing config. # Optional. Routing configuration.
+    &quot;routingConfig&quot;: { # The configuration for routing the request to a specific model. # Optional. Routing configuration.
       &quot;autoMode&quot;: { # When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # Automated routing.
         &quot;modelRoutingPreference&quot;: &quot;A String&quot;, # The model routing preference.
       },
       &quot;manualMode&quot;: { # When manual routing is set, the specified model will be used directly. # Manual routing.
-        &quot;modelName&quot;: &quot;A String&quot;, # The model name to use. Only the public LLM models are accepted. e.g. gemini-1.5-pro-001.
+        &quot;modelName&quot;: &quot;A String&quot;, # The model name to use. Only the public LLM models are accepted. e.g. &#x27;gemini-1.5-pro-001&#x27;.
       },
     },
     &quot;seed&quot;: 42, # Optional. Seed.
@@ -3007,8 +3037,23 @@ <h3>Method Details</h3>
       },
       &quot;retrieval&quot;: { # 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.
         &quot;disableAttribution&quot;: True or False, # Optional. Deprecated. This option is no longer supported.
-        &quot;vertexAiSearch&quot;: { # Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation # Set to use data source powered by Vertex AI Search.
-          &quot;datastore&quot;: &quot;A String&quot;, # Required. Fully-qualified Vertex AI Search&#x27;s datastore resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+        &quot;vertexAiSearch&quot;: { # 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.
+          &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}`
+              &quot;ragFileIds&quot;: [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+                &quot;A String&quot;,
+              ],
+            },
+          ],
+          &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.
         },
       },
     },