feat(firebaseml): update the api

#### firebaseml:v2beta The following keys were added: - schemas.GoogleCloudAiplatformV1beta1RagRetrievalConfig (Total Keys: 28) - schemas.GoogleCloudAiplatformV1beta1VertexRagStore.properties.ragRetrievalConfig.$ref (Total Keys: 1)
googleapis · Nov 26, 2024 · 1c0258e · 1c0258e
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diff --git a/docs/dyn/firebaseml_v1.operations.html b/docs/dyn/firebaseml_v1.operations.html
@@ -76,7 +76,7 @@ <h1><a href="firebaseml_v1.html">Firebase ML API</a> . <a href="firebaseml_v1.op
 <h2>Instance Methods</h2>
 <p class="toc_element">
   <code><a href="#cancel">cancel(name, body=None, x__xgafv=None)</a></code></p>
-<p class="firstline">Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.</p>
+<p class="firstline">Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.</p>
 <p class="toc_element">
   <code><a href="#close">close()</a></code></p>
 <p class="firstline">Close httplib2 connections.</p>
@@ -92,7 +92,7 @@ <h2>Instance Methods</h2>
 <h3>Method Details</h3>
 <div class="method">
     <code class="details" id="cancel">cancel(name, body=None, x__xgafv=None)</code>
-  <pre>Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn&#x27;t support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.
+  <pre>Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn&#x27;t support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
 
 Args:
   name: string, The name of the operation resource to be cancelled. (required)

diff --git a/docs/dyn/firebaseml_v2beta.projects.locations.publishers.models.html b/docs/dyn/firebaseml_v2beta.projects.locations.publishers.models.html
@@ -348,6 +348,25 @@ <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;hybridSearch&quot;: { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
+              &quot;alpha&quot;: 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
+            },
+            &quot;ranking&quot;: { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+              &quot;llmRanker&quot;: { # Config for LlmRanker. # Optional. Config for LlmRanker.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name used for ranking. Format: `gemini-1.5-pro`
+              },
+              &quot;rankService&quot;: { # Config for Rank Service. # Optional. Config for Rank Service.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+              },
+            },
+            &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.
         },
@@ -641,6 +660,25 @@ <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;hybridSearch&quot;: { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
+              &quot;alpha&quot;: 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
+            },
+            &quot;ranking&quot;: { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+              &quot;llmRanker&quot;: { # Config for LlmRanker. # Optional. Config for LlmRanker.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name used for ranking. Format: `gemini-1.5-pro`
+              },
+              &quot;rankService&quot;: { # Config for Rank Service. # Optional. Config for Rank Service.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+              },
+            },
+            &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.
         },
@@ -1091,6 +1129,25 @@ <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;hybridSearch&quot;: { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
+              &quot;alpha&quot;: 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
+            },
+            &quot;ranking&quot;: { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+              &quot;llmRanker&quot;: { # Config for LlmRanker. # Optional. Config for LlmRanker.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name used for ranking. Format: `gemini-1.5-pro`
+              },
+              &quot;rankService&quot;: { # Config for Rank Service. # Optional. Config for Rank Service.
+                &quot;modelName&quot;: &quot;A String&quot;, # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+              },
+            },
+            &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.
         },

diff --git a/googleapiclient/discovery_cache/documents/firebaseml.v1.json b/googleapiclient/discovery_cache/documents/firebaseml.v1.json
@@ -108,7 +108,7 @@
 "operations": {
 "methods": {
 "cancel": {
-"description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of 1, corresponding to `Code.CANCELLED`.",
+"description": "Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.",
 "flatPath": "v1/operations/{operationsId}:cancel",
 "httpMethod": "POST",
 "id": "firebaseml.operations.cancel",
@@ -204,7 +204,7 @@
 }
 }
 },
-"revision": "20240705",
+"revision": "20241117",
 "rootUrl": "https://firebaseml.googleapis.com/",
 "schemas": {
 "CancelOperationRequest": {

diff --git a/googleapiclient/discovery_cache/documents/firebaseml.v2beta.json b/googleapiclient/discovery_cache/documents/firebaseml.v2beta.json
@@ -206,7 +206,7 @@
 }
 }
 },
-"revision": "20241101",
+"revision": "20241117",
 "rootUrl": "https://firebaseml.googleapis.com/",
 "schemas": {
 "Date": {
@@ -1138,6 +1138,100 @@
 },
 "type": "object"
 },
+"GoogleCloudAiplatformV1beta1RagRetrievalConfig": {
+"description": "Specifies the context retrieval config.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfig",
+"properties": {
+"filter": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter",
+"description": "Optional. Config for filters."
+},
+"hybridSearch": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch",
+"description": "Optional. Config for Hybrid Search."
+},
+"ranking": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking",
+"description": "Optional. Config for ranking and reranking."
+},
+"topK": {
+"description": "Optional. The number of contexts to retrieve.",
+"format": "int32",
+"type": "integer"
+}
+},
+"type": "object"
+},
+"GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter": {
+"description": "Config for filters.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter",
+"properties": {
+"metadataFilter": {
+"description": "Optional. String for metadata filtering.",
+"type": "string"
+},
+"vectorDistanceThreshold": {
+"description": "Optional. Only returns contexts with vector distance smaller than the threshold.",
+"format": "double",
+"type": "number"
+},
+"vectorSimilarityThreshold": {
+"description": "Optional. Only returns contexts with vector similarity larger than the threshold.",
+"format": "double",
+"type": "number"
+}
+},
+"type": "object"
+},
+"GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch": {
+"description": "Config for Hybrid Search.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch",
+"properties": {
+"alpha": {
+"description": "Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.",
+"format": "float",
+"type": "number"
+}
+},
+"type": "object"
+},
+"GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking": {
+"description": "Config for ranking and reranking.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking",
+"properties": {
+"llmRanker": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker",
+"description": "Optional. Config for LlmRanker."
+},
+"rankService": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService",
+"description": "Optional. Config for Rank Service."
+}
+},
+"type": "object"
+},
+"GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker": {
+"description": "Config for LlmRanker.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker",
+"properties": {
+"modelName": {
+"description": "Optional. The model name used for ranking. Format: `gemini-1.5-pro`",
+"type": "string"
+}
+},
+"type": "object"
+},
+"GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService": {
+"description": "Config for Rank Service.",
+"id": "GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService",
+"properties": {
+"modelName": {
+"description": "Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`",
+"type": "string"
+}
+},
+"type": "object"
+},
 "GoogleCloudAiplatformV1beta1Retrieval": {
 "description": "Defines a retrieval tool that model can call to access external knowledge.",
 "id": "GoogleCloudAiplatformV1beta1Retrieval",
@@ -1569,6 +1663,10 @@
 },
 "type": "array"
 },
+"ragRetrievalConfig": {
+"$ref": "GoogleCloudAiplatformV1beta1RagRetrievalConfig",
+"description": "Optional. The retrieval config for the Rag query."
+},
 "similarityTopK": {
 "deprecated": true,
 "description": "Optional. Number of top k results to return from the selected corpora.",