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.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/__init__.py

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+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from google.ai.generativelanguage_v1alpha import gapic_version as package_version
+
+__version__ = package_version.__version__
+
+
+from .services.cache_service import CacheServiceAsyncClient, CacheServiceClient
+from .services.discuss_service import DiscussServiceAsyncClient, DiscussServiceClient
+from .services.file_service import FileServiceAsyncClient, FileServiceClient
+from .services.generative_service import (
+    GenerativeServiceAsyncClient,
+    GenerativeServiceClient,
+)
+from .services.model_service import ModelServiceAsyncClient, ModelServiceClient
+from .services.permission_service import (
+    PermissionServiceAsyncClient,
+    PermissionServiceClient,
+)
+from .services.prediction_service import (
+    PredictionServiceAsyncClient,
+    PredictionServiceClient,
+)
+from .services.retriever_service import (
+    RetrieverServiceAsyncClient,
+    RetrieverServiceClient,
+)
+from .services.text_service import TextServiceAsyncClient, TextServiceClient
+from .types.cache_service import (
+    CreateCachedContentRequest,
+    DeleteCachedContentRequest,
+    GetCachedContentRequest,
+    ListCachedContentsRequest,
+    ListCachedContentsResponse,
+    UpdateCachedContentRequest,
+)
+from .types.cached_content import CachedContent
+from .types.citation import CitationMetadata, CitationSource
+from .types.content import (
+    Blob,
+    CodeExecution,
+    CodeExecutionResult,
+    Content,
+    DynamicRetrievalConfig,
+    ExecutableCode,
+    FileData,
+    FunctionCall,
+    FunctionCallingConfig,
+    FunctionDeclaration,
+    FunctionResponse,
+    GoogleSearchRetrieval,
+    GroundingPassage,
+    GroundingPassages,
+    Part,
+    Schema,
+    Tool,
+    ToolConfig,
+    Type,
+)
+from .types.discuss_service import (
+    CountMessageTokensRequest,
+    CountMessageTokensResponse,
+    Example,
+    GenerateMessageRequest,
+    GenerateMessageResponse,
+    Message,
+    MessagePrompt,
+)
+from .types.file import File, VideoMetadata
+from .types.file_service import (
+    CreateFileRequest,
+    CreateFileResponse,
+    DeleteFileRequest,
+    GetFileRequest,
+    ListFilesRequest,
+    ListFilesResponse,
+)
+from .types.generative_service import (
+    AttributionSourceId,
+    BatchEmbedContentsRequest,
+    BatchEmbedContentsResponse,
+    BidiGenerateContentClientContent,
+    BidiGenerateContentClientMessage,
+    BidiGenerateContentRealtimeInput,
+    BidiGenerateContentServerContent,
+    BidiGenerateContentServerMessage,
+    BidiGenerateContentSetup,
+    BidiGenerateContentSetupComplete,
+    BidiGenerateContentToolCall,
+    BidiGenerateContentToolCallCancellation,
+    BidiGenerateContentToolResponse,
+    Candidate,
+    ContentEmbedding,
+    CountTokensRequest,
+    CountTokensResponse,
+    EmbedContentRequest,
+    EmbedContentResponse,
+    GenerateAnswerRequest,
+    GenerateAnswerResponse,
+    GenerateContentRequest,
+    GenerateContentResponse,
+    GenerationConfig,
+    GroundingAttribution,
+    GroundingChunk,
+    GroundingMetadata,
+    GroundingSupport,
+    LogprobsResult,
+    PrebuiltVoiceConfig,
+    RetrievalMetadata,
+    SearchEntryPoint,
+    Segment,
+    SemanticRetrieverConfig,
+    SpeechConfig,
+    TaskType,
+    VoiceConfig,
+)
+from .types.model import Model
+from .types.model_service import (
+    CreateTunedModelMetadata,
+    CreateTunedModelRequest,
+    DeleteTunedModelRequest,
+    GetModelRequest,
+    GetTunedModelRequest,
+    ListModelsRequest,
+    ListModelsResponse,
+    ListTunedModelsRequest,
+    ListTunedModelsResponse,
+    UpdateTunedModelRequest,
+)
+from .types.permission import Permission
+from .types.permission_service import (
+    CreatePermissionRequest,
+    DeletePermissionRequest,
+    GetPermissionRequest,
+    ListPermissionsRequest,
+    ListPermissionsResponse,
+    TransferOwnershipRequest,
+    TransferOwnershipResponse,
+    UpdatePermissionRequest,
+)
+from .types.prediction_service import PredictRequest, PredictResponse
+from .types.retriever import (
+    Chunk,
+    ChunkData,
+    Condition,
+    Corpus,
+    CustomMetadata,
+    Document,
+    MetadataFilter,
+    StringList,
+)
+from .types.retriever_service import (
+    BatchCreateChunksRequest,
+    BatchCreateChunksResponse,
+    BatchDeleteChunksRequest,
+    BatchUpdateChunksRequest,
+    BatchUpdateChunksResponse,
+    CreateChunkRequest,
+    CreateCorpusRequest,
+    CreateDocumentRequest,
+    DeleteChunkRequest,
+    DeleteCorpusRequest,
+    DeleteDocumentRequest,
+    GetChunkRequest,
+    GetCorpusRequest,
+    GetDocumentRequest,
+    ListChunksRequest,
+    ListChunksResponse,
+    ListCorporaRequest,
+    ListCorporaResponse,
+    ListDocumentsRequest,
+    ListDocumentsResponse,
+    QueryCorpusRequest,
+    QueryCorpusResponse,
+    QueryDocumentRequest,
+    QueryDocumentResponse,
+    RelevantChunk,
+    UpdateChunkRequest,
+    UpdateCorpusRequest,
+    UpdateDocumentRequest,
+)
+from .types.safety import (
+    ContentFilter,
+    HarmCategory,
+    SafetyFeedback,
+    SafetyRating,
+    SafetySetting,
+)
+from .types.text_service import (
+    BatchEmbedTextRequest,
+    BatchEmbedTextResponse,
+    CountTextTokensRequest,
+    CountTextTokensResponse,
+    Embedding,
+    EmbedTextRequest,
+    EmbedTextResponse,
+    GenerateTextRequest,
+    GenerateTextResponse,
+    TextCompletion,
+    TextPrompt,
+)
+from .types.tuned_model import (
+    Dataset,
+    Hyperparameters,
+    TunedModel,
+    TunedModelSource,
+    TuningContent,
+    TuningExample,
+    TuningExamples,
+    TuningMultiturnExample,
+    TuningPart,
+    TuningSnapshot,
+    TuningTask,
+)
+
+__all__ = (
+    "CacheServiceAsyncClient",
+    "DiscussServiceAsyncClient",
+    "FileServiceAsyncClient",
+    "GenerativeServiceAsyncClient",
+    "ModelServiceAsyncClient",
+    "PermissionServiceAsyncClient",
+    "PredictionServiceAsyncClient",
+    "RetrieverServiceAsyncClient",
+    "TextServiceAsyncClient",
+    "AttributionSourceId",
+    "BatchCreateChunksRequest",
+    "BatchCreateChunksResponse",
+    "BatchDeleteChunksRequest",
+    "BatchEmbedContentsRequest",
+    "BatchEmbedContentsResponse",
+    "BatchEmbedTextRequest",
+    "BatchEmbedTextResponse",
+    "BatchUpdateChunksRequest",
+    "BatchUpdateChunksResponse",
+    "BidiGenerateContentClientContent",
+    "BidiGenerateContentClientMessage",
+    "BidiGenerateContentRealtimeInput",
+    "BidiGenerateContentServerContent",
+    "BidiGenerateContentServerMessage",
+    "BidiGenerateContentSetup",
+    "BidiGenerateContentSetupComplete",
+    "BidiGenerateContentToolCall",
+    "BidiGenerateContentToolCallCancellation",
+    "BidiGenerateContentToolResponse",
+    "Blob",
+    "CacheServiceClient",
+    "CachedContent",
+    "Candidate",
+    "Chunk",
+    "ChunkData",
+    "CitationMetadata",
+    "CitationSource",
+    "CodeExecution",
+    "CodeExecutionResult",
+    "Condition",
+    "Content",
+    "ContentEmbedding",
+    "ContentFilter",
+    "Corpus",
+    "CountMessageTokensRequest",
+    "CountMessageTokensResponse",
+    "CountTextTokensRequest",
+    "CountTextTokensResponse",
+    "CountTokensRequest",
+    "CountTokensResponse",
+    "CreateCachedContentRequest",
+    "CreateChunkRequest",
+    "CreateCorpusRequest",
+    "CreateDocumentRequest",
+    "CreateFileRequest",
+    "CreateFileResponse",
+    "CreatePermissionRequest",
+    "CreateTunedModelMetadata",
+    "CreateTunedModelRequest",
+    "CustomMetadata",
+    "Dataset",
+    "DeleteCachedContentRequest",
+    "DeleteChunkRequest",
+    "DeleteCorpusRequest",
+    "DeleteDocumentRequest",
+    "DeleteFileRequest",
+    "DeletePermissionRequest",
+    "DeleteTunedModelRequest",
+    "DiscussServiceClient",
+    "Document",
+    "DynamicRetrievalConfig",
+    "EmbedContentRequest",
+    "EmbedContentResponse",
+    "EmbedTextRequest",
+    "EmbedTextResponse",
+    "Embedding",
+    "Example",
+    "ExecutableCode",
+    "File",
+    "FileData",
+    "FileServiceClient",
+    "FunctionCall",
+    "FunctionCallingConfig",
+    "FunctionDeclaration",
+    "FunctionResponse",
+    "GenerateAnswerRequest",
+    "GenerateAnswerResponse",
+    "GenerateContentRequest",
+    "GenerateContentResponse",
+    "GenerateMessageRequest",
+    "GenerateMessageResponse",
+    "GenerateTextRequest",
+    "GenerateTextResponse",
+    "GenerationConfig",
+    "GenerativeServiceClient",
+    "GetCachedContentRequest",
+    "GetChunkRequest",
+    "GetCorpusRequest",
+    "GetDocumentRequest",
+    "GetFileRequest",
+    "GetModelRequest",
+    "GetPermissionRequest",
+    "GetTunedModelRequest",
+    "GoogleSearchRetrieval",
+    "GroundingAttribution",
+    "GroundingChunk",
+    "GroundingMetadata",
+    "GroundingPassage",
+    "GroundingPassages",
+    "GroundingSupport",
+    "HarmCategory",
+    "Hyperparameters",
+    "ListCachedContentsRequest",
+    "ListCachedContentsResponse",
+    "ListChunksRequest",
+    "ListChunksResponse",
+    "ListCorporaRequest",
+    "ListCorporaResponse",
+    "ListDocumentsRequest",
+    "ListDocumentsResponse",
+    "ListFilesRequest",
+    "ListFilesResponse",
+    "ListModelsRequest",
+    "ListModelsResponse",
+    "ListPermissionsRequest",
+    "ListPermissionsResponse",
+    "ListTunedModelsRequest",
+    "ListTunedModelsResponse",
+    "LogprobsResult",
+    "Message",
+    "MessagePrompt",
+    "MetadataFilter",
+    "Model",
+    "ModelServiceClient",
+    "Part",
+    "Permission",
+    "PermissionServiceClient",
+    "PrebuiltVoiceConfig",
+    "PredictRequest",
+    "PredictResponse",
+    "PredictionServiceClient",
+    "QueryCorpusRequest",
+    "QueryCorpusResponse",
+    "QueryDocumentRequest",
+    "QueryDocumentResponse",
+    "RelevantChunk",
+    "RetrievalMetadata",
+    "RetrieverServiceClient",
+    "SafetyFeedback",
+    "SafetyRating",
+    "SafetySetting",
+    "Schema",
+    "SearchEntryPoint",
+    "Segment",
+    "SemanticRetrieverConfig",
+    "SpeechConfig",
+    "StringList",
+    "TaskType",
+    "TextCompletion",
+    "TextPrompt",
+    "TextServiceClient",
+    "Tool",
+    "ToolConfig",
+    "TransferOwnershipRequest",
+    "TransferOwnershipResponse",
+    "TunedModel",
+    "TunedModelSource",
+    "TuningContent",
+    "TuningExample",
+    "TuningExamples",
+    "TuningMultiturnExample",
+    "TuningPart",
+    "TuningSnapshot",
+    "TuningTask",
+    "Type",
+    "UpdateCachedContentRequest",
+    "UpdateChunkRequest",
+    "UpdateCorpusRequest",
+    "UpdateDocumentRequest",
+    "UpdatePermissionRequest",
+    "UpdateTunedModelRequest",
+    "VideoMetadata",
+    "VoiceConfig",
+)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/gapic_metadata.json

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+ {
+  "comment": "This file maps proto services/RPCs to the corresponding library clients/methods",
+  "language": "python",
+  "libraryPackage": "google.ai.generativelanguage_v1alpha",
+  "protoPackage": "google.ai.generativelanguage.v1alpha",
+  "schema": "1.0",
+  "services": {
+    "CacheService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "CacheServiceClient",
+          "rpcs": {
+            "CreateCachedContent": {
+              "methods": [
+                "create_cached_content"
+              ]
+            },
+            "DeleteCachedContent": {
+              "methods": [
+                "delete_cached_content"
+              ]
+            },
+            "GetCachedContent": {
+              "methods": [
+                "get_cached_content"
+              ]
+            },
+            "ListCachedContents": {
+              "methods": [
+                "list_cached_contents"
+              ]
+            },
+            "UpdateCachedContent": {
+              "methods": [
+                "update_cached_content"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "CacheServiceAsyncClient",
+          "rpcs": {
+            "CreateCachedContent": {
+              "methods": [
+                "create_cached_content"
+              ]
+            },
+            "DeleteCachedContent": {
+              "methods": [
+                "delete_cached_content"
+              ]
+            },
+            "GetCachedContent": {
+              "methods": [
+                "get_cached_content"
+              ]
+            },
+            "ListCachedContents": {
+              "methods": [
+                "list_cached_contents"
+              ]
+            },
+            "UpdateCachedContent": {
+              "methods": [
+                "update_cached_content"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "CacheServiceClient",
+          "rpcs": {
+            "CreateCachedContent": {
+              "methods": [
+                "create_cached_content"
+              ]
+            },
+            "DeleteCachedContent": {
+              "methods": [
+                "delete_cached_content"
+              ]
+            },
+            "GetCachedContent": {
+              "methods": [
+                "get_cached_content"
+              ]
+            },
+            "ListCachedContents": {
+              "methods": [
+                "list_cached_contents"
+              ]
+            },
+            "UpdateCachedContent": {
+              "methods": [
+                "update_cached_content"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "DiscussService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "DiscussServiceClient",
+          "rpcs": {
+            "CountMessageTokens": {
+              "methods": [
+                "count_message_tokens"
+              ]
+            },
+            "GenerateMessage": {
+              "methods": [
+                "generate_message"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "DiscussServiceAsyncClient",
+          "rpcs": {
+            "CountMessageTokens": {
+              "methods": [
+                "count_message_tokens"
+              ]
+            },
+            "GenerateMessage": {
+              "methods": [
+                "generate_message"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "DiscussServiceClient",
+          "rpcs": {
+            "CountMessageTokens": {
+              "methods": [
+                "count_message_tokens"
+              ]
+            },
+            "GenerateMessage": {
+              "methods": [
+                "generate_message"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "FileService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "FileServiceClient",
+          "rpcs": {
+            "CreateFile": {
+              "methods": [
+                "create_file"
+              ]
+            },
+            "DeleteFile": {
+              "methods": [
+                "delete_file"
+              ]
+            },
+            "GetFile": {
+              "methods": [
+                "get_file"
+              ]
+            },
+            "ListFiles": {
+              "methods": [
+                "list_files"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "FileServiceAsyncClient",
+          "rpcs": {
+            "CreateFile": {
+              "methods": [
+                "create_file"
+              ]
+            },
+            "DeleteFile": {
+              "methods": [
+                "delete_file"
+              ]
+            },
+            "GetFile": {
+              "methods": [
+                "get_file"
+              ]
+            },
+            "ListFiles": {
+              "methods": [
+                "list_files"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "FileServiceClient",
+          "rpcs": {
+            "CreateFile": {
+              "methods": [
+                "create_file"
+              ]
+            },
+            "DeleteFile": {
+              "methods": [
+                "delete_file"
+              ]
+            },
+            "GetFile": {
+              "methods": [
+                "get_file"
+              ]
+            },
+            "ListFiles": {
+              "methods": [
+                "list_files"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "GenerativeService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "GenerativeServiceClient",
+          "rpcs": {
+            "BatchEmbedContents": {
+              "methods": [
+                "batch_embed_contents"
+              ]
+            },
+            "BidiGenerateContent": {
+              "methods": [
+                "bidi_generate_content"
+              ]
+            },
+            "CountTokens": {
+              "methods": [
+                "count_tokens"
+              ]
+            },
+            "EmbedContent": {
+              "methods": [
+                "embed_content"
+              ]
+            },
+            "GenerateAnswer": {
+              "methods": [
+                "generate_answer"
+              ]
+            },
+            "GenerateContent": {
+              "methods": [
+                "generate_content"
+              ]
+            },
+            "StreamGenerateContent": {
+              "methods": [
+                "stream_generate_content"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "GenerativeServiceAsyncClient",
+          "rpcs": {
+            "BatchEmbedContents": {
+              "methods": [
+                "batch_embed_contents"
+              ]
+            },
+            "BidiGenerateContent": {
+              "methods": [
+                "bidi_generate_content"
+              ]
+            },
+            "CountTokens": {
+              "methods": [
+                "count_tokens"
+              ]
+            },
+            "EmbedContent": {
+              "methods": [
+                "embed_content"
+              ]
+            },
+            "GenerateAnswer": {
+              "methods": [
+                "generate_answer"
+              ]
+            },
+            "GenerateContent": {
+              "methods": [
+                "generate_content"
+              ]
+            },
+            "StreamGenerateContent": {
+              "methods": [
+                "stream_generate_content"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "GenerativeServiceClient",
+          "rpcs": {
+            "BatchEmbedContents": {
+              "methods": [
+                "batch_embed_contents"
+              ]
+            },
+            "BidiGenerateContent": {
+              "methods": [
+                "bidi_generate_content"
+              ]
+            },
+            "CountTokens": {
+              "methods": [
+                "count_tokens"
+              ]
+            },
+            "EmbedContent": {
+              "methods": [
+                "embed_content"
+              ]
+            },
+            "GenerateAnswer": {
+              "methods": [
+                "generate_answer"
+              ]
+            },
+            "GenerateContent": {
+              "methods": [
+                "generate_content"
+              ]
+            },
+            "StreamGenerateContent": {
+              "methods": [
+                "stream_generate_content"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "ModelService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "ModelServiceClient",
+          "rpcs": {
+            "CreateTunedModel": {
+              "methods": [
+                "create_tuned_model"
+              ]
+            },
+            "DeleteTunedModel": {
+              "methods": [
+                "delete_tuned_model"
+              ]
+            },
+            "GetModel": {
+              "methods": [
+                "get_model"
+              ]
+            },
+            "GetTunedModel": {
+              "methods": [
+                "get_tuned_model"
+              ]
+            },
+            "ListModels": {
+              "methods": [
+                "list_models"
+              ]
+            },
+            "ListTunedModels": {
+              "methods": [
+                "list_tuned_models"
+              ]
+            },
+            "UpdateTunedModel": {
+              "methods": [
+                "update_tuned_model"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "ModelServiceAsyncClient",
+          "rpcs": {
+            "CreateTunedModel": {
+              "methods": [
+                "create_tuned_model"
+              ]
+            },
+            "DeleteTunedModel": {
+              "methods": [
+                "delete_tuned_model"
+              ]
+            },
+            "GetModel": {
+              "methods": [
+                "get_model"
+              ]
+            },
+            "GetTunedModel": {
+              "methods": [
+                "get_tuned_model"
+              ]
+            },
+            "ListModels": {
+              "methods": [
+                "list_models"
+              ]
+            },
+            "ListTunedModels": {
+              "methods": [
+                "list_tuned_models"
+              ]
+            },
+            "UpdateTunedModel": {
+              "methods": [
+                "update_tuned_model"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "ModelServiceClient",
+          "rpcs": {
+            "CreateTunedModel": {
+              "methods": [
+                "create_tuned_model"
+              ]
+            },
+            "DeleteTunedModel": {
+              "methods": [
+                "delete_tuned_model"
+              ]
+            },
+            "GetModel": {
+              "methods": [
+                "get_model"
+              ]
+            },
+            "GetTunedModel": {
+              "methods": [
+                "get_tuned_model"
+              ]
+            },
+            "ListModels": {
+              "methods": [
+                "list_models"
+              ]
+            },
+            "ListTunedModels": {
+              "methods": [
+                "list_tuned_models"
+              ]
+            },
+            "UpdateTunedModel": {
+              "methods": [
+                "update_tuned_model"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "PermissionService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "PermissionServiceClient",
+          "rpcs": {
+            "CreatePermission": {
+              "methods": [
+                "create_permission"
+              ]
+            },
+            "DeletePermission": {
+              "methods": [
+                "delete_permission"
+              ]
+            },
+            "GetPermission": {
+              "methods": [
+                "get_permission"
+              ]
+            },
+            "ListPermissions": {
+              "methods": [
+                "list_permissions"
+              ]
+            },
+            "TransferOwnership": {
+              "methods": [
+                "transfer_ownership"
+              ]
+            },
+            "UpdatePermission": {
+              "methods": [
+                "update_permission"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "PermissionServiceAsyncClient",
+          "rpcs": {
+            "CreatePermission": {
+              "methods": [
+                "create_permission"
+              ]
+            },
+            "DeletePermission": {
+              "methods": [
+                "delete_permission"
+              ]
+            },
+            "GetPermission": {
+              "methods": [
+                "get_permission"
+              ]
+            },
+            "ListPermissions": {
+              "methods": [
+                "list_permissions"
+              ]
+            },
+            "TransferOwnership": {
+              "methods": [
+                "transfer_ownership"
+              ]
+            },
+            "UpdatePermission": {
+              "methods": [
+                "update_permission"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "PermissionServiceClient",
+          "rpcs": {
+            "CreatePermission": {
+              "methods": [
+                "create_permission"
+              ]
+            },
+            "DeletePermission": {
+              "methods": [
+                "delete_permission"
+              ]
+            },
+            "GetPermission": {
+              "methods": [
+                "get_permission"
+              ]
+            },
+            "ListPermissions": {
+              "methods": [
+                "list_permissions"
+              ]
+            },
+            "TransferOwnership": {
+              "methods": [
+                "transfer_ownership"
+              ]
+            },
+            "UpdatePermission": {
+              "methods": [
+                "update_permission"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "PredictionService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "PredictionServiceClient",
+          "rpcs": {
+            "Predict": {
+              "methods": [
+                "predict"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "PredictionServiceAsyncClient",
+          "rpcs": {
+            "Predict": {
+              "methods": [
+                "predict"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "PredictionServiceClient",
+          "rpcs": {
+            "Predict": {
+              "methods": [
+                "predict"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "RetrieverService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "RetrieverServiceClient",
+          "rpcs": {
+            "BatchCreateChunks": {
+              "methods": [
+                "batch_create_chunks"
+              ]
+            },
+            "BatchDeleteChunks": {
+              "methods": [
+                "batch_delete_chunks"
+              ]
+            },
+            "BatchUpdateChunks": {
+              "methods": [
+                "batch_update_chunks"
+              ]
+            },
+            "CreateChunk": {
+              "methods": [
+                "create_chunk"
+              ]
+            },
+            "CreateCorpus": {
+              "methods": [
+                "create_corpus"
+              ]
+            },
+            "CreateDocument": {
+              "methods": [
+                "create_document"
+              ]
+            },
+            "DeleteChunk": {
+              "methods": [
+                "delete_chunk"
+              ]
+            },
+            "DeleteCorpus": {
+              "methods": [
+                "delete_corpus"
+              ]
+            },
+            "DeleteDocument": {
+              "methods": [
+                "delete_document"
+              ]
+            },
+            "GetChunk": {
+              "methods": [
+                "get_chunk"
+              ]
+            },
+            "GetCorpus": {
+              "methods": [
+                "get_corpus"
+              ]
+            },
+            "GetDocument": {
+              "methods": [
+                "get_document"
+              ]
+            },
+            "ListChunks": {
+              "methods": [
+                "list_chunks"
+              ]
+            },
+            "ListCorpora": {
+              "methods": [
+                "list_corpora"
+              ]
+            },
+            "ListDocuments": {
+              "methods": [
+                "list_documents"
+              ]
+            },
+            "QueryCorpus": {
+              "methods": [
+                "query_corpus"
+              ]
+            },
+            "QueryDocument": {
+              "methods": [
+                "query_document"
+              ]
+            },
+            "UpdateChunk": {
+              "methods": [
+                "update_chunk"
+              ]
+            },
+            "UpdateCorpus": {
+              "methods": [
+                "update_corpus"
+              ]
+            },
+            "UpdateDocument": {
+              "methods": [
+                "update_document"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "RetrieverServiceAsyncClient",
+          "rpcs": {
+            "BatchCreateChunks": {
+              "methods": [
+                "batch_create_chunks"
+              ]
+            },
+            "BatchDeleteChunks": {
+              "methods": [
+                "batch_delete_chunks"
+              ]
+            },
+            "BatchUpdateChunks": {
+              "methods": [
+                "batch_update_chunks"
+              ]
+            },
+            "CreateChunk": {
+              "methods": [
+                "create_chunk"
+              ]
+            },
+            "CreateCorpus": {
+              "methods": [
+                "create_corpus"
+              ]
+            },
+            "CreateDocument": {
+              "methods": [
+                "create_document"
+              ]
+            },
+            "DeleteChunk": {
+              "methods": [
+                "delete_chunk"
+              ]
+            },
+            "DeleteCorpus": {
+              "methods": [
+                "delete_corpus"
+              ]
+            },
+            "DeleteDocument": {
+              "methods": [
+                "delete_document"
+              ]
+            },
+            "GetChunk": {
+              "methods": [
+                "get_chunk"
+              ]
+            },
+            "GetCorpus": {
+              "methods": [
+                "get_corpus"
+              ]
+            },
+            "GetDocument": {
+              "methods": [
+                "get_document"
+              ]
+            },
+            "ListChunks": {
+              "methods": [
+                "list_chunks"
+              ]
+            },
+            "ListCorpora": {
+              "methods": [
+                "list_corpora"
+              ]
+            },
+            "ListDocuments": {
+              "methods": [
+                "list_documents"
+              ]
+            },
+            "QueryCorpus": {
+              "methods": [
+                "query_corpus"
+              ]
+            },
+            "QueryDocument": {
+              "methods": [
+                "query_document"
+              ]
+            },
+            "UpdateChunk": {
+              "methods": [
+                "update_chunk"
+              ]
+            },
+            "UpdateCorpus": {
+              "methods": [
+                "update_corpus"
+              ]
+            },
+            "UpdateDocument": {
+              "methods": [
+                "update_document"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "RetrieverServiceClient",
+          "rpcs": {
+            "BatchCreateChunks": {
+              "methods": [
+                "batch_create_chunks"
+              ]
+            },
+            "BatchDeleteChunks": {
+              "methods": [
+                "batch_delete_chunks"
+              ]
+            },
+            "BatchUpdateChunks": {
+              "methods": [
+                "batch_update_chunks"
+              ]
+            },
+            "CreateChunk": {
+              "methods": [
+                "create_chunk"
+              ]
+            },
+            "CreateCorpus": {
+              "methods": [
+                "create_corpus"
+              ]
+            },
+            "CreateDocument": {
+              "methods": [
+                "create_document"
+              ]
+            },
+            "DeleteChunk": {
+              "methods": [
+                "delete_chunk"
+              ]
+            },
+            "DeleteCorpus": {
+              "methods": [
+                "delete_corpus"
+              ]
+            },
+            "DeleteDocument": {
+              "methods": [
+                "delete_document"
+              ]
+            },
+            "GetChunk": {
+              "methods": [
+                "get_chunk"
+              ]
+            },
+            "GetCorpus": {
+              "methods": [
+                "get_corpus"
+              ]
+            },
+            "GetDocument": {
+              "methods": [
+                "get_document"
+              ]
+            },
+            "ListChunks": {
+              "methods": [
+                "list_chunks"
+              ]
+            },
+            "ListCorpora": {
+              "methods": [
+                "list_corpora"
+              ]
+            },
+            "ListDocuments": {
+              "methods": [
+                "list_documents"
+              ]
+            },
+            "QueryCorpus": {
+              "methods": [
+                "query_corpus"
+              ]
+            },
+            "QueryDocument": {
+              "methods": [
+                "query_document"
+              ]
+            },
+            "UpdateChunk": {
+              "methods": [
+                "update_chunk"
+              ]
+            },
+            "UpdateCorpus": {
+              "methods": [
+                "update_corpus"
+              ]
+            },
+            "UpdateDocument": {
+              "methods": [
+                "update_document"
+              ]
+            }
+          }
+        }
+      }
+    },
+    "TextService": {
+      "clients": {
+        "grpc": {
+          "libraryClient": "TextServiceClient",
+          "rpcs": {
+            "BatchEmbedText": {
+              "methods": [
+                "batch_embed_text"
+              ]
+            },
+            "CountTextTokens": {
+              "methods": [
+                "count_text_tokens"
+              ]
+            },
+            "EmbedText": {
+              "methods": [
+                "embed_text"
+              ]
+            },
+            "GenerateText": {
+              "methods": [
+                "generate_text"
+              ]
+            }
+          }
+        },
+        "grpc-async": {
+          "libraryClient": "TextServiceAsyncClient",
+          "rpcs": {
+            "BatchEmbedText": {
+              "methods": [
+                "batch_embed_text"
+              ]
+            },
+            "CountTextTokens": {
+              "methods": [
+                "count_text_tokens"
+              ]
+            },
+            "EmbedText": {
+              "methods": [
+                "embed_text"
+              ]
+            },
+            "GenerateText": {
+              "methods": [
+                "generate_text"
+              ]
+            }
+          }
+        },
+        "rest": {
+          "libraryClient": "TextServiceClient",
+          "rpcs": {
+            "BatchEmbedText": {
+              "methods": [
+                "batch_embed_text"
+              ]
+            },
+            "CountTextTokens": {
+              "methods": [
+                "count_text_tokens"
+              ]
+            },
+            "EmbedText": {
+              "methods": [
+                "embed_text"
+              ]
+            },
+            "GenerateText": {
+              "methods": [
+                "generate_text"
+              ]
+            }
+          }
+        }
+      }
+    }
+  }
+}

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/py.typed

@@ -0,0 +1,2 @@
+# Marker file for PEP 561.
+# The google-ai-generativelanguage package uses inline types.

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/__init__.py

@@ -0,0 +1,369 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from .cache_service import (
+    CreateCachedContentRequest,
+    DeleteCachedContentRequest,
+    GetCachedContentRequest,
+    ListCachedContentsRequest,
+    ListCachedContentsResponse,
+    UpdateCachedContentRequest,
+)
+from .cached_content import CachedContent
+from .citation import CitationMetadata, CitationSource
+from .content import (
+    Blob,
+    CodeExecution,
+    CodeExecutionResult,
+    Content,
+    DynamicRetrievalConfig,
+    ExecutableCode,
+    FileData,
+    FunctionCall,
+    FunctionCallingConfig,
+    FunctionDeclaration,
+    FunctionResponse,
+    GoogleSearchRetrieval,
+    GroundingPassage,
+    GroundingPassages,
+    Part,
+    Schema,
+    Tool,
+    ToolConfig,
+    Type,
+)
+from .discuss_service import (
+    CountMessageTokensRequest,
+    CountMessageTokensResponse,
+    Example,
+    GenerateMessageRequest,
+    GenerateMessageResponse,
+    Message,
+    MessagePrompt,
+)
+from .file import File, VideoMetadata
+from .file_service import (
+    CreateFileRequest,
+    CreateFileResponse,
+    DeleteFileRequest,
+    GetFileRequest,
+    ListFilesRequest,
+    ListFilesResponse,
+)
+from .generative_service import (
+    AttributionSourceId,
+    BatchEmbedContentsRequest,
+    BatchEmbedContentsResponse,
+    BidiGenerateContentClientContent,
+    BidiGenerateContentClientMessage,
+    BidiGenerateContentRealtimeInput,
+    BidiGenerateContentServerContent,
+    BidiGenerateContentServerMessage,
+    BidiGenerateContentSetup,
+    BidiGenerateContentSetupComplete,
+    BidiGenerateContentToolCall,
+    BidiGenerateContentToolCallCancellation,
+    BidiGenerateContentToolResponse,
+    Candidate,
+    ContentEmbedding,
+    CountTokensRequest,
+    CountTokensResponse,
+    EmbedContentRequest,
+    EmbedContentResponse,
+    GenerateAnswerRequest,
+    GenerateAnswerResponse,
+    GenerateContentRequest,
+    GenerateContentResponse,
+    GenerationConfig,
+    GroundingAttribution,
+    GroundingChunk,
+    GroundingMetadata,
+    GroundingSupport,
+    LogprobsResult,
+    PrebuiltVoiceConfig,
+    RetrievalMetadata,
+    SearchEntryPoint,
+    Segment,
+    SemanticRetrieverConfig,
+    SpeechConfig,
+    TaskType,
+    VoiceConfig,
+)
+from .model import Model
+from .model_service import (
+    CreateTunedModelMetadata,
+    CreateTunedModelRequest,
+    DeleteTunedModelRequest,
+    GetModelRequest,
+    GetTunedModelRequest,
+    ListModelsRequest,
+    ListModelsResponse,
+    ListTunedModelsRequest,
+    ListTunedModelsResponse,
+    UpdateTunedModelRequest,
+)
+from .permission import Permission
+from .permission_service import (
+    CreatePermissionRequest,
+    DeletePermissionRequest,
+    GetPermissionRequest,
+    ListPermissionsRequest,
+    ListPermissionsResponse,
+    TransferOwnershipRequest,
+    TransferOwnershipResponse,
+    UpdatePermissionRequest,
+)
+from .prediction_service import PredictRequest, PredictResponse
+from .retriever import (
+    Chunk,
+    ChunkData,
+    Condition,
+    Corpus,
+    CustomMetadata,
+    Document,
+    MetadataFilter,
+    StringList,
+)
+from .retriever_service import (
+    BatchCreateChunksRequest,
+    BatchCreateChunksResponse,
+    BatchDeleteChunksRequest,
+    BatchUpdateChunksRequest,
+    BatchUpdateChunksResponse,
+    CreateChunkRequest,
+    CreateCorpusRequest,
+    CreateDocumentRequest,
+    DeleteChunkRequest,
+    DeleteCorpusRequest,
+    DeleteDocumentRequest,
+    GetChunkRequest,
+    GetCorpusRequest,
+    GetDocumentRequest,
+    ListChunksRequest,
+    ListChunksResponse,
+    ListCorporaRequest,
+    ListCorporaResponse,
+    ListDocumentsRequest,
+    ListDocumentsResponse,
+    QueryCorpusRequest,
+    QueryCorpusResponse,
+    QueryDocumentRequest,
+    QueryDocumentResponse,
+    RelevantChunk,
+    UpdateChunkRequest,
+    UpdateCorpusRequest,
+    UpdateDocumentRequest,
+)
+from .safety import (
+    ContentFilter,
+    HarmCategory,
+    SafetyFeedback,
+    SafetyRating,
+    SafetySetting,
+)
+from .text_service import (
+    BatchEmbedTextRequest,
+    BatchEmbedTextResponse,
+    CountTextTokensRequest,
+    CountTextTokensResponse,
+    Embedding,
+    EmbedTextRequest,
+    EmbedTextResponse,
+    GenerateTextRequest,
+    GenerateTextResponse,
+    TextCompletion,
+    TextPrompt,
+)
+from .tuned_model import (
+    Dataset,
+    Hyperparameters,
+    TunedModel,
+    TunedModelSource,
+    TuningContent,
+    TuningExample,
+    TuningExamples,
+    TuningMultiturnExample,
+    TuningPart,
+    TuningSnapshot,
+    TuningTask,
+)
+
+__all__ = (
+    "CreateCachedContentRequest",
+    "DeleteCachedContentRequest",
+    "GetCachedContentRequest",
+    "ListCachedContentsRequest",
+    "ListCachedContentsResponse",
+    "UpdateCachedContentRequest",
+    "CachedContent",
+    "CitationMetadata",
+    "CitationSource",
+    "Blob",
+    "CodeExecution",
+    "CodeExecutionResult",
+    "Content",
+    "DynamicRetrievalConfig",
+    "ExecutableCode",
+    "FileData",
+    "FunctionCall",
+    "FunctionCallingConfig",
+    "FunctionDeclaration",
+    "FunctionResponse",
+    "GoogleSearchRetrieval",
+    "GroundingPassage",
+    "GroundingPassages",
+    "Part",
+    "Schema",
+    "Tool",
+    "ToolConfig",
+    "Type",
+    "CountMessageTokensRequest",
+    "CountMessageTokensResponse",
+    "Example",
+    "GenerateMessageRequest",
+    "GenerateMessageResponse",
+    "Message",
+    "MessagePrompt",
+    "File",
+    "VideoMetadata",
+    "CreateFileRequest",
+    "CreateFileResponse",
+    "DeleteFileRequest",
+    "GetFileRequest",
+    "ListFilesRequest",
+    "ListFilesResponse",
+    "AttributionSourceId",
+    "BatchEmbedContentsRequest",
+    "BatchEmbedContentsResponse",
+    "BidiGenerateContentClientContent",
+    "BidiGenerateContentClientMessage",
+    "BidiGenerateContentRealtimeInput",
+    "BidiGenerateContentServerContent",
+    "BidiGenerateContentServerMessage",
+    "BidiGenerateContentSetup",
+    "BidiGenerateContentSetupComplete",
+    "BidiGenerateContentToolCall",
+    "BidiGenerateContentToolCallCancellation",
+    "BidiGenerateContentToolResponse",
+    "Candidate",
+    "ContentEmbedding",
+    "CountTokensRequest",
+    "CountTokensResponse",
+    "EmbedContentRequest",
+    "EmbedContentResponse",
+    "GenerateAnswerRequest",
+    "GenerateAnswerResponse",
+    "GenerateContentRequest",
+    "GenerateContentResponse",
+    "GenerationConfig",
+    "GroundingAttribution",
+    "GroundingChunk",
+    "GroundingMetadata",
+    "GroundingSupport",
+    "LogprobsResult",
+    "PrebuiltVoiceConfig",
+    "RetrievalMetadata",
+    "SearchEntryPoint",
+    "Segment",
+    "SemanticRetrieverConfig",
+    "SpeechConfig",
+    "VoiceConfig",
+    "TaskType",
+    "Model",
+    "CreateTunedModelMetadata",
+    "CreateTunedModelRequest",
+    "DeleteTunedModelRequest",
+    "GetModelRequest",
+    "GetTunedModelRequest",
+    "ListModelsRequest",
+    "ListModelsResponse",
+    "ListTunedModelsRequest",
+    "ListTunedModelsResponse",
+    "UpdateTunedModelRequest",
+    "Permission",
+    "CreatePermissionRequest",
+    "DeletePermissionRequest",
+    "GetPermissionRequest",
+    "ListPermissionsRequest",
+    "ListPermissionsResponse",
+    "TransferOwnershipRequest",
+    "TransferOwnershipResponse",
+    "UpdatePermissionRequest",
+    "PredictRequest",
+    "PredictResponse",
+    "Chunk",
+    "ChunkData",
+    "Condition",
+    "Corpus",
+    "CustomMetadata",
+    "Document",
+    "MetadataFilter",
+    "StringList",
+    "BatchCreateChunksRequest",
+    "BatchCreateChunksResponse",
+    "BatchDeleteChunksRequest",
+    "BatchUpdateChunksRequest",
+    "BatchUpdateChunksResponse",
+    "CreateChunkRequest",
+    "CreateCorpusRequest",
+    "CreateDocumentRequest",
+    "DeleteChunkRequest",
+    "DeleteCorpusRequest",
+    "DeleteDocumentRequest",
+    "GetChunkRequest",
+    "GetCorpusRequest",
+    "GetDocumentRequest",
+    "ListChunksRequest",
+    "ListChunksResponse",
+    "ListCorporaRequest",
+    "ListCorporaResponse",
+    "ListDocumentsRequest",
+    "ListDocumentsResponse",
+    "QueryCorpusRequest",
+    "QueryCorpusResponse",
+    "QueryDocumentRequest",
+    "QueryDocumentResponse",
+    "RelevantChunk",
+    "UpdateChunkRequest",
+    "UpdateCorpusRequest",
+    "UpdateDocumentRequest",
+    "ContentFilter",
+    "SafetyFeedback",
+    "SafetyRating",
+    "SafetySetting",
+    "HarmCategory",
+    "BatchEmbedTextRequest",
+    "BatchEmbedTextResponse",
+    "CountTextTokensRequest",
+    "CountTextTokensResponse",
+    "Embedding",
+    "EmbedTextRequest",
+    "EmbedTextResponse",
+    "GenerateTextRequest",
+    "GenerateTextResponse",
+    "TextCompletion",
+    "TextPrompt",
+    "Dataset",
+    "Hyperparameters",
+    "TunedModel",
+    "TunedModelSource",
+    "TuningContent",
+    "TuningExample",
+    "TuningExamples",
+    "TuningMultiturnExample",
+    "TuningPart",
+    "TuningSnapshot",
+    "TuningTask",
+)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/cache_service.py

@@ -0,0 +1,167 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import field_mask_pb2  # type: ignore
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1alpha.types import (
+    cached_content as gag_cached_content,
+)
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "ListCachedContentsRequest",
+        "ListCachedContentsResponse",
+        "CreateCachedContentRequest",
+        "GetCachedContentRequest",
+        "UpdateCachedContentRequest",
+        "DeleteCachedContentRequest",
+    },
+)
+
+
+class ListCachedContentsRequest(proto.Message):
+    r"""Request to list CachedContents.
+
+    Attributes:
+        page_size (int):
+            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.
+        page_token (str):
+            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.
+    """
+
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class ListCachedContentsResponse(proto.Message):
+    r"""Response with CachedContents list.
+
+    Attributes:
+        cached_contents (MutableSequence[google.ai.generativelanguage_v1alpha.types.CachedContent]):
+            List of cached contents.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page. If this field is omitted, there are no subsequent
+            pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    cached_contents: MutableSequence[
+        gag_cached_content.CachedContent
+    ] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=gag_cached_content.CachedContent,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class CreateCachedContentRequest(proto.Message):
+    r"""Request to create CachedContent.
+
+    Attributes:
+        cached_content (google.ai.generativelanguage_v1alpha.types.CachedContent):
+            Required. The cached content to create.
+    """
+
+    cached_content: gag_cached_content.CachedContent = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=gag_cached_content.CachedContent,
+    )
+
+
+class GetCachedContentRequest(proto.Message):
+    r"""Request to read CachedContent.
+
+    Attributes:
+        name (str):
+            Required. The resource name referring to the content cache
+            entry. Format: ``cachedContents/{id}``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class UpdateCachedContentRequest(proto.Message):
+    r"""Request to update CachedContent.
+
+    Attributes:
+        cached_content (google.ai.generativelanguage_v1alpha.types.CachedContent):
+            Required. The content cache entry to update
+        update_mask (google.protobuf.field_mask_pb2.FieldMask):
+            The list of fields to update.
+    """
+
+    cached_content: gag_cached_content.CachedContent = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=gag_cached_content.CachedContent,
+    )
+    update_mask: field_mask_pb2.FieldMask = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=field_mask_pb2.FieldMask,
+    )
+
+
+class DeleteCachedContentRequest(proto.Message):
+    r"""Request to delete CachedContent.
+
+    Attributes:
+        name (str):
+            Required. The resource name referring to the content cache
+            entry Format: ``cachedContents/{id}``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/content.py

@@ -0,0 +1,819 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import struct_pb2  # type: ignore
+import proto  # type: ignore
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "Type",
+        "Content",
+        "Part",
+        "Blob",
+        "FileData",
+        "ExecutableCode",
+        "CodeExecutionResult",
+        "Tool",
+        "GoogleSearchRetrieval",
+        "DynamicRetrievalConfig",
+        "CodeExecution",
+        "ToolConfig",
+        "FunctionCallingConfig",
+        "FunctionDeclaration",
+        "FunctionCall",
+        "FunctionResponse",
+        "Schema",
+        "GroundingPassage",
+        "GroundingPassages",
+    },
+)
+
+
+class Type(proto.Enum):
+    r"""Type contains the list of OpenAPI data types as defined by
+    https://spec.openapis.org/oas/v3.0.3#data-types
+
+    Values:
+        TYPE_UNSPECIFIED (0):
+            Not specified, should not be used.
+        STRING (1):
+            String type.
+        NUMBER (2):
+            Number type.
+        INTEGER (3):
+            Integer type.
+        BOOLEAN (4):
+            Boolean type.
+        ARRAY (5):
+            Array type.
+        OBJECT (6):
+            Object type.
+    """
+    TYPE_UNSPECIFIED = 0
+    STRING = 1
+    NUMBER = 2
+    INTEGER = 3
+    BOOLEAN = 4
+    ARRAY = 5
+    OBJECT = 6
+
+
+class Content(proto.Message):
+    r"""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.
+
+    Attributes:
+        parts (MutableSequence[google.ai.generativelanguage_v1alpha.types.Part]):
+            Ordered ``Parts`` that constitute a single message. Parts
+            may have different MIME types.
+        role (str):
+            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.
+    """
+
+    parts: MutableSequence["Part"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="Part",
+    )
+    role: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class Part(proto.Message):
+    r"""A datatype containing media that is part of a multi-part ``Content``
+    message.
+
+    A ``Part`` consists of data which has an associated datatype. A
+    ``Part`` can only contain one of the accepted types in
+    ``Part.data``.
+
+    A ``Part`` must have a fixed IANA MIME type identifying the type and
+    subtype of the media if the ``inline_data`` field is filled with raw
+    bytes.
+
+    This message has `oneof`_ fields (mutually exclusive fields).
+    For each oneof, at most one member field can be set at the same time.
+    Setting any member of the oneof automatically clears all other
+    members.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        text (str):
+            Inline text.
+
+            This field is a member of `oneof`_ ``data``.
+        inline_data (google.ai.generativelanguage_v1alpha.types.Blob):
+            Inline media bytes.
+
+            This field is a member of `oneof`_ ``data``.
+        function_call (google.ai.generativelanguage_v1alpha.types.FunctionCall):
+            A predicted ``FunctionCall`` returned from the model that
+            contains a string representing the
+            ``FunctionDeclaration.name`` with the arguments and their
+            values.
+
+            This field is a member of `oneof`_ ``data``.
+        function_response (google.ai.generativelanguage_v1alpha.types.FunctionResponse):
+            The result output of a ``FunctionCall`` that contains a
+            string representing the ``FunctionDeclaration.name`` and a
+            structured JSON object containing any output from the
+            function is used as context to the model.
+
+            This field is a member of `oneof`_ ``data``.
+        file_data (google.ai.generativelanguage_v1alpha.types.FileData):
+            URI based data.
+
+            This field is a member of `oneof`_ ``data``.
+        executable_code (google.ai.generativelanguage_v1alpha.types.ExecutableCode):
+            Code generated by the model that is meant to
+            be executed.
+
+            This field is a member of `oneof`_ ``data``.
+        code_execution_result (google.ai.generativelanguage_v1alpha.types.CodeExecutionResult):
+            Result of executing the ``ExecutableCode``.
+
+            This field is a member of `oneof`_ ``data``.
+    """
+
+    text: str = proto.Field(
+        proto.STRING,
+        number=2,
+        oneof="data",
+    )
+    inline_data: "Blob" = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        oneof="data",
+        message="Blob",
+    )
+    function_call: "FunctionCall" = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        oneof="data",
+        message="FunctionCall",
+    )
+    function_response: "FunctionResponse" = proto.Field(
+        proto.MESSAGE,
+        number=5,
+        oneof="data",
+        message="FunctionResponse",
+    )
+    file_data: "FileData" = proto.Field(
+        proto.MESSAGE,
+        number=6,
+        oneof="data",
+        message="FileData",
+    )
+    executable_code: "ExecutableCode" = proto.Field(
+        proto.MESSAGE,
+        number=9,
+        oneof="data",
+        message="ExecutableCode",
+    )
+    code_execution_result: "CodeExecutionResult" = proto.Field(
+        proto.MESSAGE,
+        number=10,
+        oneof="data",
+        message="CodeExecutionResult",
+    )
+
+
+class Blob(proto.Message):
+    r"""Raw media bytes.
+
+    Text should not be sent as raw bytes, use the 'text' field.
+
+    Attributes:
+        mime_type (str):
+            The IANA standard MIME type of the source data. Examples:
+
+            -  image/png
+            -  image/jpeg If an unsupported MIME type is provided, an
+               error will be returned. For a complete list of supported
+               types, see `Supported file
+               formats <https://ai.google.dev/gemini-api/docs/prompting_with_media#supported_file_formats>`__.
+        data (bytes):
+            Raw bytes for media formats.
+    """
+
+    mime_type: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    data: bytes = proto.Field(
+        proto.BYTES,
+        number=2,
+    )
+
+
+class FileData(proto.Message):
+    r"""URI based data.
+
+    Attributes:
+        mime_type (str):
+            Optional. The IANA standard MIME type of the
+            source data.
+        file_uri (str):
+            Required. URI.
+    """
+
+    mime_type: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    file_uri: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class ExecutableCode(proto.Message):
+    r"""Code generated by the model that is meant to be executed, and the
+    result returned to the model.
+
+    Only generated when using the ``CodeExecution`` tool, in which the
+    code will be automatically executed, and a corresponding
+    ``CodeExecutionResult`` will also be generated.
+
+    Attributes:
+        language (google.ai.generativelanguage_v1alpha.types.ExecutableCode.Language):
+            Required. Programming language of the ``code``.
+        code (str):
+            Required. The code to be executed.
+    """
+
+    class Language(proto.Enum):
+        r"""Supported programming languages for the generated code.
+
+        Values:
+            LANGUAGE_UNSPECIFIED (0):
+                Unspecified language. This value should not
+                be used.
+            PYTHON (1):
+                Python >= 3.10, with numpy and simpy
+                available.
+        """
+        LANGUAGE_UNSPECIFIED = 0
+        PYTHON = 1
+
+    language: Language = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum=Language,
+    )
+    code: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class CodeExecutionResult(proto.Message):
+    r"""Result of executing the ``ExecutableCode``.
+
+    Only generated when using the ``CodeExecution``, and always follows
+    a ``part`` containing the ``ExecutableCode``.
+
+    Attributes:
+        outcome (google.ai.generativelanguage_v1alpha.types.CodeExecutionResult.Outcome):
+            Required. Outcome of the code execution.
+        output (str):
+            Optional. Contains stdout when code execution
+            is successful, stderr or other description
+            otherwise.
+    """
+
+    class Outcome(proto.Enum):
+        r"""Enumeration of possible outcomes of the code execution.
+
+        Values:
+            OUTCOME_UNSPECIFIED (0):
+                Unspecified status. This value should not be
+                used.
+            OUTCOME_OK (1):
+                Code execution completed successfully.
+            OUTCOME_FAILED (2):
+                Code execution finished but with a failure. ``stderr``
+                should contain the reason.
+            OUTCOME_DEADLINE_EXCEEDED (3):
+                Code execution ran for too long, and was
+                cancelled. There may or may not be a partial
+                output present.
+        """
+        OUTCOME_UNSPECIFIED = 0
+        OUTCOME_OK = 1
+        OUTCOME_FAILED = 2
+        OUTCOME_DEADLINE_EXCEEDED = 3
+
+    outcome: Outcome = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum=Outcome,
+    )
+    output: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class Tool(proto.Message):
+    r"""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.
+
+    Attributes:
+        function_declarations (MutableSequence[google.ai.generativelanguage_v1alpha.types.FunctionDeclaration]):
+            Optional. A list of ``FunctionDeclarations`` available to
+            the model that can be used for function calling.
+
+            The model or system does not execute the function. Instead
+            the defined function may be returned as a
+            [FunctionCall][google.ai.generativelanguage.v1alpha.Part.function_call]
+            with arguments to the client side for execution. The model
+            may decide to call a subset of these functions by populating
+            [FunctionCall][google.ai.generativelanguage.v1alpha.Part.function_call]
+            in the response. The next conversation turn may contain a
+            [FunctionResponse][google.ai.generativelanguage.v1alpha.Part.function_response]
+            with the
+            [Content.role][google.ai.generativelanguage.v1alpha.Content.role]
+            "function" generation context for the next model turn.
+        google_search_retrieval (google.ai.generativelanguage_v1alpha.types.GoogleSearchRetrieval):
+            Optional. Retrieval tool that is powered by
+            Google search.
+        code_execution (google.ai.generativelanguage_v1alpha.types.CodeExecution):
+            Optional. Enables the model to execute code
+            as part of generation.
+        google_search (google.ai.generativelanguage_v1alpha.types.Tool.GoogleSearch):
+            Optional. GoogleSearch tool type.
+            Tool to support Google Search in Model. Powered
+            by Google.
+    """
+
+    class GoogleSearch(proto.Message):
+        r"""GoogleSearch tool type.
+        Tool to support Google Search in Model. Powered by Google.
+
+        """
+
+    function_declarations: MutableSequence["FunctionDeclaration"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="FunctionDeclaration",
+    )
+    google_search_retrieval: "GoogleSearchRetrieval" = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message="GoogleSearchRetrieval",
+    )
+    code_execution: "CodeExecution" = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        message="CodeExecution",
+    )
+    google_search: GoogleSearch = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message=GoogleSearch,
+    )
+
+
+class GoogleSearchRetrieval(proto.Message):
+    r"""Tool to retrieve public web data for grounding, powered by
+    Google.
+
+    Attributes:
+        dynamic_retrieval_config (google.ai.generativelanguage_v1alpha.types.DynamicRetrievalConfig):
+            Specifies the dynamic retrieval configuration
+            for the given source.
+    """
+
+    dynamic_retrieval_config: "DynamicRetrievalConfig" = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message="DynamicRetrievalConfig",
+    )
+
+
+class DynamicRetrievalConfig(proto.Message):
+    r"""Describes the options to customize dynamic retrieval.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        mode (google.ai.generativelanguage_v1alpha.types.DynamicRetrievalConfig.Mode):
+            The mode of the predictor to be used in
+            dynamic retrieval.
+        dynamic_threshold (float):
+            The threshold to be used in dynamic
+            retrieval. If not set, a system default value is
+            used.
+
+            This field is a member of `oneof`_ ``_dynamic_threshold``.
+    """
+
+    class Mode(proto.Enum):
+        r"""The mode of the predictor to be used in dynamic retrieval.
+
+        Values:
+            MODE_UNSPECIFIED (0):
+                Always trigger retrieval.
+            MODE_DYNAMIC (1):
+                Run retrieval only when system decides it is
+                necessary.
+        """
+        MODE_UNSPECIFIED = 0
+        MODE_DYNAMIC = 1
+
+    mode: Mode = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum=Mode,
+    )
+    dynamic_threshold: float = proto.Field(
+        proto.FLOAT,
+        number=2,
+        optional=True,
+    )
+
+
+class CodeExecution(proto.Message):
+    r"""Tool that executes code generated by the model, and automatically
+    returns the result to the model.
+
+    See also ``ExecutableCode`` and ``CodeExecutionResult`` which are
+    only generated when using this tool.
+
+    """
+
+
+class ToolConfig(proto.Message):
+    r"""The Tool configuration containing parameters for specifying ``Tool``
+    use in the request.
+
+    Attributes:
+        function_calling_config (google.ai.generativelanguage_v1alpha.types.FunctionCallingConfig):
+            Optional. Function calling config.
+    """
+
+    function_calling_config: "FunctionCallingConfig" = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message="FunctionCallingConfig",
+    )
+
+
+class FunctionCallingConfig(proto.Message):
+    r"""Configuration for specifying function calling behavior.
+
+    Attributes:
+        mode (google.ai.generativelanguage_v1alpha.types.FunctionCallingConfig.Mode):
+            Optional. Specifies the mode in which
+            function calling should execute. If unspecified,
+            the default value will be set to AUTO.
+        allowed_function_names (MutableSequence[str]):
+            Optional. A set of function names that, when provided,
+            limits the functions the model will call.
+
+            This should only be set when the Mode is ANY. Function names
+            should match [FunctionDeclaration.name]. With mode set to
+            ANY, model will predict a function call from the set of
+            function names provided.
+    """
+
+    class Mode(proto.Enum):
+        r"""Defines the execution behavior for function calling by
+        defining the execution mode.
+
+        Values:
+            MODE_UNSPECIFIED (0):
+                Unspecified function calling mode. This value
+                should not be used.
+            AUTO (1):
+                Default model behavior, model decides to
+                predict either a function call or a natural
+                language response.
+            ANY (2):
+                Model is constrained to always predicting a function call
+                only. If "allowed_function_names" are set, the predicted
+                function call will be limited to any one of
+                "allowed_function_names", else the predicted function call
+                will be any one of the provided "function_declarations".
+            NONE (3):
+                Model will not predict any function call.
+                Model behavior is same as when not passing any
+                function declarations.
+        """
+        MODE_UNSPECIFIED = 0
+        AUTO = 1
+        ANY = 2
+        NONE = 3
+
+    mode: Mode = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum=Mode,
+    )
+    allowed_function_names: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=2,
+    )
+
+
+class FunctionDeclaration(proto.Message):
+    r"""Structured representation of a function declaration as defined by
+    the `OpenAPI 3.03
+    specification <https://spec.openapis.org/oas/v3.0.3>`__. Included in
+    this declaration are the function name and parameters. This
+    FunctionDeclaration is a representation of a block of code that can
+    be used as a ``Tool`` by the model and executed by the client.
+
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        name (str):
+            Required. The name of the function.
+            Must be a-z, A-Z, 0-9, or contain underscores
+            and dashes, with a maximum length of 63.
+        description (str):
+            Required. A brief description of the
+            function.
+        parameters (google.ai.generativelanguage_v1alpha.types.Schema):
+            Optional. Describes the parameters to this
+            function. Reflects the Open API 3.03 Parameter
+            Object string Key: the name of the parameter.
+            Parameter names are case sensitive. Schema
+            Value: the Schema defining the type used for the
+            parameter.
+
+            This field is a member of `oneof`_ ``_parameters``.
+        response (google.ai.generativelanguage_v1alpha.types.Schema):
+            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.
+
+            This field is a member of `oneof`_ ``_response``.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    description: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    parameters: "Schema" = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        optional=True,
+        message="Schema",
+    )
+    response: "Schema" = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        optional=True,
+        message="Schema",
+    )
+
+
+class FunctionCall(proto.Message):
+    r"""A predicted ``FunctionCall`` returned from the model that contains a
+    string representing the ``FunctionDeclaration.name`` with the
+    arguments and their values.
+
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        id (str):
+            Optional. The unique id of the function call. If populated,
+            the client to execute the ``function_call`` and return the
+            response with the matching ``id``.
+        name (str):
+            Required. The name of the function to call.
+            Must be a-z, A-Z, 0-9, or contain underscores
+            and dashes, with a maximum length of 63.
+        args (google.protobuf.struct_pb2.Struct):
+            Optional. The function parameters and values
+            in JSON object format.
+
+            This field is a member of `oneof`_ ``_args``.
+    """
+
+    id: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    args: struct_pb2.Struct = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        optional=True,
+        message=struct_pb2.Struct,
+    )
+
+
+class FunctionResponse(proto.Message):
+    r"""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.
+
+    Attributes:
+        id (str):
+            Optional. The id of the function call this response is for.
+            Populated by the client to match the corresponding function
+            call ``id``.
+        name (str):
+            Required. The name of the function to call.
+            Must be a-z, A-Z, 0-9, or contain underscores
+            and dashes, with a maximum length of 63.
+        response (google.protobuf.struct_pb2.Struct):
+            Required. The function response in JSON
+            object format.
+    """
+
+    id: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    response: struct_pb2.Struct = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=struct_pb2.Struct,
+    )
+
+
+class Schema(proto.Message):
+    r"""The ``Schema`` object allows the definition of input and output data
+    types. These types can be objects, but also primitives and arrays.
+    Represents a select subset of an `OpenAPI 3.0 schema
+    object <https://spec.openapis.org/oas/v3.0.3#schema>`__.
+
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        type_ (google.ai.generativelanguage_v1alpha.types.Type):
+            Required. Data type.
+        format_ (str):
+            Optional. The format of the data. This is
+            used only for primitive datatypes. Supported
+            formats:
+
+             for NUMBER type: float, double
+             for INTEGER type: int32, int64
+             for STRING type: enum
+        description (str):
+            Optional. A brief description of the
+            parameter. This could contain examples of use.
+            Parameter description may be formatted as
+            Markdown.
+        nullable (bool):
+            Optional. Indicates if the value may be null.
+        enum (MutableSequence[str]):
+            Optional. Possible values of the element of Type.STRING with
+            enum format. For example we can define an Enum Direction as
+            : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH",
+            "WEST"]}
+        items (google.ai.generativelanguage_v1alpha.types.Schema):
+            Optional. Schema of the elements of
+            Type.ARRAY.
+
+            This field is a member of `oneof`_ ``_items``.
+        max_items (int):
+            Optional. Maximum number of the elements for
+            Type.ARRAY.
+        min_items (int):
+            Optional. Minimum number of the elements for
+            Type.ARRAY.
+        properties (MutableMapping[str, google.ai.generativelanguage_v1alpha.types.Schema]):
+            Optional. Properties of Type.OBJECT.
+        required (MutableSequence[str]):
+            Optional. Required properties of Type.OBJECT.
+    """
+
+    type_: "Type" = proto.Field(
+        proto.ENUM,
+        number=1,
+        enum="Type",
+    )
+    format_: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    description: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+    nullable: bool = proto.Field(
+        proto.BOOL,
+        number=4,
+    )
+    enum: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=5,
+    )
+    items: "Schema" = proto.Field(
+        proto.MESSAGE,
+        number=6,
+        optional=True,
+        message="Schema",
+    )
+    max_items: int = proto.Field(
+        proto.INT64,
+        number=21,
+    )
+    min_items: int = proto.Field(
+        proto.INT64,
+        number=22,
+    )
+    properties: MutableMapping[str, "Schema"] = proto.MapField(
+        proto.STRING,
+        proto.MESSAGE,
+        number=7,
+        message="Schema",
+    )
+    required: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=8,
+    )
+
+
+class GroundingPassage(proto.Message):
+    r"""Passage included inline with a grounding configuration.
+
+    Attributes:
+        id (str):
+            Identifier for the passage for attributing
+            this passage in grounded answers.
+        content (google.ai.generativelanguage_v1alpha.types.Content):
+            Content of the passage.
+    """
+
+    id: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    content: "Content" = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message="Content",
+    )
+
+
+class GroundingPassages(proto.Message):
+    r"""A repeated list of passages.
+
+    Attributes:
+        passages (MutableSequence[google.ai.generativelanguage_v1alpha.types.GroundingPassage]):
+            List of passages.
+    """
+
+    passages: MutableSequence["GroundingPassage"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="GroundingPassage",
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/model.py

@@ -0,0 +1,171 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+import proto  # type: ignore
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "Model",
+    },
+)
+
+
+class Model(proto.Message):
+    r"""Information about a Generative Language Model.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        name (str):
+            Required. The resource name of the ``Model``. Refer to
+            `Model
+            variants <https://ai.google.dev/gemini-api/docs/models/gemini#model-variations>`__
+            for all allowed values.
+
+            Format: ``models/{model}`` with a ``{model}`` naming
+            convention of:
+
+            -  "{base_model_id}-{version}"
+
+            Examples:
+
+            -  ``models/gemini-1.5-flash-001``
+        base_model_id (str):
+            Required. The name of the base model, pass this to the
+            generation request.
+
+            Examples:
+
+            -  ``gemini-1.5-flash``
+        version (str):
+            Required. The version number of the model.
+
+            This represents the major version (``1.0`` or ``1.5``)
+        display_name (str):
+            The human-readable name of the model. E.g.
+            "Gemini 1.5 Flash".
+            The name can be up to 128 characters long and
+            can consist of any UTF-8 characters.
+        description (str):
+            A short description of the model.
+        input_token_limit (int):
+            Maximum number of input tokens allowed for
+            this model.
+        output_token_limit (int):
+            Maximum number of output tokens available for
+            this model.
+        supported_generation_methods (MutableSequence[str]):
+            The model's supported generation methods.
+
+            The corresponding API method names are defined as Pascal
+            case strings, such as ``generateMessage`` and
+            ``generateContent``.
+        temperature (float):
+            Controls the randomness of the output.
+
+            Values can range over ``[0.0,max_temperature]``, inclusive.
+            A higher value will produce responses that are more varied,
+            while a value closer to ``0.0`` will typically result in
+            less surprising responses from the model. This value
+            specifies default to be used by the backend while making the
+            call to the model.
+
+            This field is a member of `oneof`_ ``_temperature``.
+        max_temperature (float):
+            The maximum temperature this model can use.
+
+            This field is a member of `oneof`_ ``_max_temperature``.
+        top_p (float):
+            For `Nucleus
+            sampling <https://ai.google.dev/gemini-api/docs/prompting-strategies#top-p>`__.
+
+            Nucleus sampling considers the smallest set of tokens whose
+            probability sum is at least ``top_p``. This value specifies
+            default to be used by the backend while making the call to
+            the model.
+
+            This field is a member of `oneof`_ ``_top_p``.
+        top_k (int):
+            For Top-k sampling.
+
+            Top-k sampling considers the set of ``top_k`` most probable
+            tokens. This value specifies default to be used by the
+            backend while making the call to the model. If empty,
+            indicates the model doesn't use top-k sampling, and
+            ``top_k`` isn't allowed as a generation parameter.
+
+            This field is a member of `oneof`_ ``_top_k``.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    base_model_id: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    version: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+    display_name: str = proto.Field(
+        proto.STRING,
+        number=4,
+    )
+    description: str = proto.Field(
+        proto.STRING,
+        number=5,
+    )
+    input_token_limit: int = proto.Field(
+        proto.INT32,
+        number=6,
+    )
+    output_token_limit: int = proto.Field(
+        proto.INT32,
+        number=7,
+    )
+    supported_generation_methods: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=8,
+    )
+    temperature: float = proto.Field(
+        proto.FLOAT,
+        number=9,
+        optional=True,
+    )
+    max_temperature: float = proto.Field(
+        proto.FLOAT,
+        number=13,
+        optional=True,
+    )
+    top_p: float = proto.Field(
+        proto.FLOAT,
+        number=10,
+        optional=True,
+    )
+    top_k: int = proto.Field(
+        proto.INT32,
+        number=11,
+        optional=True,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/model_service.py

@@ -0,0 +1,332 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import field_mask_pb2  # type: ignore
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1alpha.types import tuned_model as gag_tuned_model
+from google.ai.generativelanguage_v1alpha.types import model
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "GetModelRequest",
+        "ListModelsRequest",
+        "ListModelsResponse",
+        "GetTunedModelRequest",
+        "ListTunedModelsRequest",
+        "ListTunedModelsResponse",
+        "CreateTunedModelRequest",
+        "CreateTunedModelMetadata",
+        "UpdateTunedModelRequest",
+        "DeleteTunedModelRequest",
+    },
+)
+
+
+class GetModelRequest(proto.Message):
+    r"""Request for getting information about a specific Model.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the model.
+
+            This name should match a model name returned by the
+            ``ListModels`` method.
+
+            Format: ``models/{model}``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class ListModelsRequest(proto.Message):
+    r"""Request for listing all Models.
+
+    Attributes:
+        page_size (int):
+            The maximum number of ``Models`` to return (per page).
+
+            If unspecified, 50 models will be returned per page. This
+            method returns at most 1000 models per page, even if you
+            pass a larger page_size.
+        page_token (str):
+            A page token, received from a previous ``ListModels`` call.
+
+            Provide the ``page_token`` returned by one request as an
+            argument to the next request to retrieve the next page.
+
+            When paginating, all other parameters provided to
+            ``ListModels`` must match the call that provided the page
+            token.
+    """
+
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+
+
+class ListModelsResponse(proto.Message):
+    r"""Response from ``ListModel`` containing a paginated list of Models.
+
+    Attributes:
+        models (MutableSequence[google.ai.generativelanguage_v1alpha.types.Model]):
+            The returned Models.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page.
+
+            If this field is omitted, there are no more pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    models: MutableSequence[model.Model] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=model.Model,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class GetTunedModelRequest(proto.Message):
+    r"""Request for getting information about a specific Model.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the model.
+
+            Format: ``tunedModels/my-model-id``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class ListTunedModelsRequest(proto.Message):
+    r"""Request for listing TunedModels.
+
+    Attributes:
+        page_size (int):
+            Optional. The maximum number of ``TunedModels`` to return
+            (per page). The service may return fewer tuned models.
+
+            If unspecified, at most 10 tuned models will be returned.
+            This method returns at most 1000 models per page, even if
+            you pass a larger page_size.
+        page_token (str):
+            Optional. A page token, received from a previous
+            ``ListTunedModels`` call.
+
+            Provide the ``page_token`` returned by one request as an
+            argument to the next request to retrieve the next page.
+
+            When paginating, all other parameters provided to
+            ``ListTunedModels`` must match the call that provided the
+            page token.
+        filter (str):
+            Optional. A filter is a full text search over
+            the tuned model's description and display name.
+            By default, results will not include tuned
+            models shared with everyone.
+
+            Additional operators:
+
+              - owner:me
+              - writers:me
+              - readers:me
+              - readers:everyone
+
+            Examples:
+
+              "owner:me" returns all tuned models to which
+            caller has owner role   "readers:me" returns all
+            tuned models to which caller has reader role
+            "readers:everyone" returns all tuned models that
+            are shared with everyone
+    """
+
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    filter: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+
+
+class ListTunedModelsResponse(proto.Message):
+    r"""Response from ``ListTunedModels`` containing a paginated list of
+    Models.
+
+    Attributes:
+        tuned_models (MutableSequence[google.ai.generativelanguage_v1alpha.types.TunedModel]):
+            The returned Models.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page.
+
+            If this field is omitted, there are no more pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    tuned_models: MutableSequence[gag_tuned_model.TunedModel] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=gag_tuned_model.TunedModel,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class CreateTunedModelRequest(proto.Message):
+    r"""Request to create a TunedModel.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        tuned_model_id (str):
+            Optional. The unique id for the tuned model if specified.
+            This value should be up to 40 characters, the first
+            character must be a letter, the last could be a letter or a
+            number. The id must match the regular expression:
+            ``[a-z]([a-z0-9-]{0,38}[a-z0-9])?``.
+
+            This field is a member of `oneof`_ ``_tuned_model_id``.
+        tuned_model (google.ai.generativelanguage_v1alpha.types.TunedModel):
+            Required. The tuned model to create.
+    """
+
+    tuned_model_id: str = proto.Field(
+        proto.STRING,
+        number=1,
+        optional=True,
+    )
+    tuned_model: gag_tuned_model.TunedModel = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=gag_tuned_model.TunedModel,
+    )
+
+
+class CreateTunedModelMetadata(proto.Message):
+    r"""Metadata about the state and progress of creating a tuned
+    model returned from the long-running operation
+
+    Attributes:
+        tuned_model (str):
+            Name of the tuned model associated with the
+            tuning operation.
+        total_steps (int):
+            The total number of tuning steps.
+        completed_steps (int):
+            The number of steps completed.
+        completed_percent (float):
+            The completed percentage for the tuning
+            operation.
+        snapshots (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningSnapshot]):
+            Metrics collected during tuning.
+    """
+
+    tuned_model: str = proto.Field(
+        proto.STRING,
+        number=5,
+    )
+    total_steps: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+    completed_steps: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+    completed_percent: float = proto.Field(
+        proto.FLOAT,
+        number=3,
+    )
+    snapshots: MutableSequence[gag_tuned_model.TuningSnapshot] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=4,
+        message=gag_tuned_model.TuningSnapshot,
+    )
+
+
+class UpdateTunedModelRequest(proto.Message):
+    r"""Request to update a TunedModel.
+
+    Attributes:
+        tuned_model (google.ai.generativelanguage_v1alpha.types.TunedModel):
+            Required. The tuned model to update.
+        update_mask (google.protobuf.field_mask_pb2.FieldMask):
+            Optional. The list of fields to update.
+    """
+
+    tuned_model: gag_tuned_model.TunedModel = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=gag_tuned_model.TunedModel,
+    )
+    update_mask: field_mask_pb2.FieldMask = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=field_mask_pb2.FieldMask,
+    )
+
+
+class DeleteTunedModelRequest(proto.Message):
+    r"""Request to delete a TunedModel.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the model. Format:
+            ``tunedModels/my-model-id``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/prediction_service.py

@@ -0,0 +1,79 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import struct_pb2  # type: ignore
+import proto  # type: ignore
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "PredictRequest",
+        "PredictResponse",
+    },
+)
+
+
+class PredictRequest(proto.Message):
+    r"""Request message for
+    [PredictionService.Predict][google.ai.generativelanguage.v1alpha.PredictionService.Predict].
+
+    Attributes:
+        model (str):
+            Required. The name of the model for prediction. Format:
+            ``name=models/{model}``.
+        instances (MutableSequence[google.protobuf.struct_pb2.Value]):
+            Required. The instances that are the input to
+            the prediction call.
+        parameters (google.protobuf.struct_pb2.Value):
+            Optional. The parameters that govern the
+            prediction call.
+    """
+
+    model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    instances: MutableSequence[struct_pb2.Value] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message=struct_pb2.Value,
+    )
+    parameters: struct_pb2.Value = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        message=struct_pb2.Value,
+    )
+
+
+class PredictResponse(proto.Message):
+    r"""Response message for [PredictionService.Predict].
+
+    Attributes:
+        predictions (MutableSequence[google.protobuf.struct_pb2.Value]):
+            The outputs of the prediction call.
+    """
+
+    predictions: MutableSequence[struct_pb2.Value] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=struct_pb2.Value,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/retriever.py

@@ -0,0 +1,411 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import timestamp_pb2  # type: ignore
+import proto  # type: ignore
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "Corpus",
+        "Document",
+        "StringList",
+        "CustomMetadata",
+        "MetadataFilter",
+        "Condition",
+        "Chunk",
+        "ChunkData",
+    },
+)
+
+
+class Corpus(proto.Message):
+    r"""A ``Corpus`` is a collection of ``Document``\ s. A project can
+    create up to 5 corpora.
+
+    Attributes:
+        name (str):
+            Immutable. Identifier. The ``Corpus`` resource name. The ID
+            (name excluding the "corpora/" prefix) can contain up to 40
+            characters that are lowercase alphanumeric or dashes (-).
+            The ID cannot start or end with a dash. If the name is empty
+            on create, a unique name will be derived from
+            ``display_name`` along with a 12 character random suffix.
+            Example: ``corpora/my-awesome-corpora-123a456b789c``
+        display_name (str):
+            Optional. The human-readable display name for the
+            ``Corpus``. The display name must be no more than 512
+            characters in length, including spaces. Example: "Docs on
+            Semantic Retriever".
+        create_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Corpus`` was
+            created.
+        update_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Corpus`` was last
+            updated.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    display_name: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    create_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        message=timestamp_pb2.Timestamp,
+    )
+    update_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message=timestamp_pb2.Timestamp,
+    )
+
+
+class Document(proto.Message):
+    r"""A ``Document`` is a collection of ``Chunk``\ s. A ``Corpus`` can
+    have a maximum of 10,000 ``Document``\ s.
+
+    Attributes:
+        name (str):
+            Immutable. Identifier. The ``Document`` resource name. The
+            ID (name excluding the `corpora/*/documents/` prefix) can
+            contain up to 40 characters that are lowercase alphanumeric
+            or dashes (-). The ID cannot start or end with a dash. If
+            the name is empty on create, a unique name will be derived
+            from ``display_name`` along with a 12 character random
+            suffix. Example:
+            ``corpora/{corpus_id}/documents/my-awesome-doc-123a456b789c``
+        display_name (str):
+            Optional. The human-readable display name for the
+            ``Document``. The display name must be no more than 512
+            characters in length, including spaces. Example: "Semantic
+            Retriever Documentation".
+        custom_metadata (MutableSequence[google.ai.generativelanguage_v1alpha.types.CustomMetadata]):
+            Optional. User provided custom metadata stored as key-value
+            pairs used for querying. A ``Document`` can have a maximum
+            of 20 ``CustomMetadata``.
+        update_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Document`` was last
+            updated.
+        create_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Document`` was
+            created.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    display_name: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    custom_metadata: MutableSequence["CustomMetadata"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message="CustomMetadata",
+    )
+    update_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message=timestamp_pb2.Timestamp,
+    )
+    create_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=5,
+        message=timestamp_pb2.Timestamp,
+    )
+
+
+class StringList(proto.Message):
+    r"""User provided string values assigned to a single metadata
+    key.
+
+    Attributes:
+        values (MutableSequence[str]):
+            The string values of the metadata to store.
+    """
+
+    values: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=1,
+    )
+
+
+class CustomMetadata(proto.Message):
+    r"""User provided metadata stored as key-value pairs.
+
+    This message has `oneof`_ fields (mutually exclusive fields).
+    For each oneof, at most one member field can be set at the same time.
+    Setting any member of the oneof automatically clears all other
+    members.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        string_value (str):
+            The string value of the metadata to store.
+
+            This field is a member of `oneof`_ ``value``.
+        string_list_value (google.ai.generativelanguage_v1alpha.types.StringList):
+            The StringList value of the metadata to
+            store.
+
+            This field is a member of `oneof`_ ``value``.
+        numeric_value (float):
+            The numeric value of the metadata to store.
+
+            This field is a member of `oneof`_ ``value``.
+        key (str):
+            Required. The key of the metadata to store.
+    """
+
+    string_value: str = proto.Field(
+        proto.STRING,
+        number=2,
+        oneof="value",
+    )
+    string_list_value: "StringList" = proto.Field(
+        proto.MESSAGE,
+        number=6,
+        oneof="value",
+        message="StringList",
+    )
+    numeric_value: float = proto.Field(
+        proto.FLOAT,
+        number=7,
+        oneof="value",
+    )
+    key: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class MetadataFilter(proto.Message):
+    r"""User provided filter to limit retrieval based on ``Chunk`` or
+    ``Document`` level metadata values. Example (genre = drama OR genre
+    = action): key = "document.custom_metadata.genre" conditions =
+    [{string_value = "drama", operation = EQUAL}, {string_value =
+    "action", operation = EQUAL}]
+
+    Attributes:
+        key (str):
+            Required. The key of the metadata to filter
+            on.
+        conditions (MutableSequence[google.ai.generativelanguage_v1alpha.types.Condition]):
+            Required. The ``Condition``\ s for the given key that will
+            trigger this filter. Multiple ``Condition``\ s are joined by
+            logical ORs.
+    """
+
+    key: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    conditions: MutableSequence["Condition"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="Condition",
+    )
+
+
+class Condition(proto.Message):
+    r"""Filter condition applicable to a single key.
+
+    This message has `oneof`_ fields (mutually exclusive fields).
+    For each oneof, at most one member field can be set at the same time.
+    Setting any member of the oneof automatically clears all other
+    members.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        string_value (str):
+            The string value to filter the metadata on.
+
+            This field is a member of `oneof`_ ``value``.
+        numeric_value (float):
+            The numeric value to filter the metadata on.
+
+            This field is a member of `oneof`_ ``value``.
+        operation (google.ai.generativelanguage_v1alpha.types.Condition.Operator):
+            Required. Operator applied to the given
+            key-value pair to trigger the condition.
+    """
+
+    class Operator(proto.Enum):
+        r"""Defines the valid operators that can be applied to a
+        key-value pair.
+
+        Values:
+            OPERATOR_UNSPECIFIED (0):
+                The default value. This value is unused.
+            LESS (1):
+                Supported by numeric.
+            LESS_EQUAL (2):
+                Supported by numeric.
+            EQUAL (3):
+                Supported by numeric & string.
+            GREATER_EQUAL (4):
+                Supported by numeric.
+            GREATER (5):
+                Supported by numeric.
+            NOT_EQUAL (6):
+                Supported by numeric & string.
+            INCLUDES (7):
+                Supported by string only when ``CustomMetadata`` value type
+                for the given key has a ``string_list_value``.
+            EXCLUDES (8):
+                Supported by string only when ``CustomMetadata`` value type
+                for the given key has a ``string_list_value``.
+        """
+        OPERATOR_UNSPECIFIED = 0
+        LESS = 1
+        LESS_EQUAL = 2
+        EQUAL = 3
+        GREATER_EQUAL = 4
+        GREATER = 5
+        NOT_EQUAL = 6
+        INCLUDES = 7
+        EXCLUDES = 8
+
+    string_value: str = proto.Field(
+        proto.STRING,
+        number=1,
+        oneof="value",
+    )
+    numeric_value: float = proto.Field(
+        proto.FLOAT,
+        number=6,
+        oneof="value",
+    )
+    operation: Operator = proto.Field(
+        proto.ENUM,
+        number=5,
+        enum=Operator,
+    )
+
+
+class Chunk(proto.Message):
+    r"""A ``Chunk`` is a subpart of a ``Document`` that is treated as an
+    independent unit for the purposes of vector representation and
+    storage. A ``Corpus`` can have a maximum of 1 million ``Chunk``\ s.
+
+    Attributes:
+        name (str):
+            Immutable. Identifier. The ``Chunk`` resource name. The ID
+            (name excluding the "corpora/*/documents/*/chunks/" prefix)
+            can contain up to 40 characters that are lowercase
+            alphanumeric or dashes (-). The ID cannot start or end with
+            a dash. If the name is empty on create, a random
+            12-character unique ID will be generated. Example:
+            ``corpora/{corpus_id}/documents/{document_id}/chunks/123a456b789c``
+        data (google.ai.generativelanguage_v1alpha.types.ChunkData):
+            Required. The content for the ``Chunk``, such as the text
+            string. The maximum number of tokens per chunk is 2043.
+        custom_metadata (MutableSequence[google.ai.generativelanguage_v1alpha.types.CustomMetadata]):
+            Optional. User provided custom metadata stored as key-value
+            pairs. The maximum number of ``CustomMetadata`` per chunk is
+            20.
+        create_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Chunk`` was
+            created.
+        update_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The Timestamp of when the ``Chunk`` was last
+            updated.
+        state (google.ai.generativelanguage_v1alpha.types.Chunk.State):
+            Output only. Current state of the ``Chunk``.
+    """
+
+    class State(proto.Enum):
+        r"""States for the lifecycle of a ``Chunk``.
+
+        Values:
+            STATE_UNSPECIFIED (0):
+                The default value. This value is used if the
+                state is omitted.
+            STATE_PENDING_PROCESSING (1):
+                ``Chunk`` is being processed (embedding and vector storage).
+            STATE_ACTIVE (2):
+                ``Chunk`` is processed and available for querying.
+            STATE_FAILED (10):
+                ``Chunk`` failed processing.
+        """
+        STATE_UNSPECIFIED = 0
+        STATE_PENDING_PROCESSING = 1
+        STATE_ACTIVE = 2
+        STATE_FAILED = 10
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    data: "ChunkData" = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message="ChunkData",
+    )
+    custom_metadata: MutableSequence["CustomMetadata"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message="CustomMetadata",
+    )
+    create_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message=timestamp_pb2.Timestamp,
+    )
+    update_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=5,
+        message=timestamp_pb2.Timestamp,
+    )
+    state: State = proto.Field(
+        proto.ENUM,
+        number=6,
+        enum=State,
+    )
+
+
+class ChunkData(proto.Message):
+    r"""Extracted data that represents the ``Chunk`` content.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        string_value (str):
+            The ``Chunk`` content as a string. The maximum number of
+            tokens per chunk is 2043.
+
+            This field is a member of `oneof`_ ``data``.
+    """
+
+    string_value: str = proto.Field(
+        proto.STRING,
+        number=1,
+        oneof="data",
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/retriever_service.py

@@ -0,0 +1,793 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import field_mask_pb2  # type: ignore
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1alpha.types import retriever
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "CreateCorpusRequest",
+        "GetCorpusRequest",
+        "UpdateCorpusRequest",
+        "DeleteCorpusRequest",
+        "ListCorporaRequest",
+        "ListCorporaResponse",
+        "QueryCorpusRequest",
+        "QueryCorpusResponse",
+        "RelevantChunk",
+        "CreateDocumentRequest",
+        "GetDocumentRequest",
+        "UpdateDocumentRequest",
+        "DeleteDocumentRequest",
+        "ListDocumentsRequest",
+        "ListDocumentsResponse",
+        "QueryDocumentRequest",
+        "QueryDocumentResponse",
+        "CreateChunkRequest",
+        "BatchCreateChunksRequest",
+        "BatchCreateChunksResponse",
+        "GetChunkRequest",
+        "UpdateChunkRequest",
+        "BatchUpdateChunksRequest",
+        "BatchUpdateChunksResponse",
+        "DeleteChunkRequest",
+        "BatchDeleteChunksRequest",
+        "ListChunksRequest",
+        "ListChunksResponse",
+    },
+)
+
+
+class CreateCorpusRequest(proto.Message):
+    r"""Request to create a ``Corpus``.
+
+    Attributes:
+        corpus (google.ai.generativelanguage_v1alpha.types.Corpus):
+            Required. The ``Corpus`` to create.
+    """
+
+    corpus: retriever.Corpus = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Corpus,
+    )
+
+
+class GetCorpusRequest(proto.Message):
+    r"""Request for getting information about a specific ``Corpus``.
+
+    Attributes:
+        name (str):
+            Required. The name of the ``Corpus``. Example:
+            ``corpora/my-corpus-123``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class UpdateCorpusRequest(proto.Message):
+    r"""Request to update a ``Corpus``.
+
+    Attributes:
+        corpus (google.ai.generativelanguage_v1alpha.types.Corpus):
+            Required. The ``Corpus`` to update.
+        update_mask (google.protobuf.field_mask_pb2.FieldMask):
+            Required. The list of fields to update. Currently, this only
+            supports updating ``display_name``.
+    """
+
+    corpus: retriever.Corpus = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Corpus,
+    )
+    update_mask: field_mask_pb2.FieldMask = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=field_mask_pb2.FieldMask,
+    )
+
+
+class DeleteCorpusRequest(proto.Message):
+    r"""Request to delete a ``Corpus``.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the ``Corpus``. Example:
+            ``corpora/my-corpus-123``
+        force (bool):
+            Optional. If set to true, any ``Document``\ s and objects
+            related to this ``Corpus`` will also be deleted.
+
+            If false (the default), a ``FAILED_PRECONDITION`` error will
+            be returned if ``Corpus`` contains any ``Document``\ s.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    force: bool = proto.Field(
+        proto.BOOL,
+        number=2,
+    )
+
+
+class ListCorporaRequest(proto.Message):
+    r"""Request for listing ``Corpora``.
+
+    Attributes:
+        page_size (int):
+            Optional. The maximum number of ``Corpora`` to return (per
+            page). The service may return fewer ``Corpora``.
+
+            If unspecified, at most 10 ``Corpora`` will be returned. The
+            maximum size limit is 20 ``Corpora`` per page.
+        page_token (str):
+            Optional. A page token, received from a previous
+            ``ListCorpora`` call.
+
+            Provide the ``next_page_token`` returned in the response as
+            an argument to the next request to retrieve the next page.
+
+            When paginating, all other parameters provided to
+            ``ListCorpora`` must match the call that provided the page
+            token.
+    """
+
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class ListCorporaResponse(proto.Message):
+    r"""Response from ``ListCorpora`` containing a paginated list of
+    ``Corpora``. The results are sorted by ascending
+    ``corpus.create_time``.
+
+    Attributes:
+        corpora (MutableSequence[google.ai.generativelanguage_v1alpha.types.Corpus]):
+            The returned corpora.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page. If this field is omitted, there are no more
+            pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    corpora: MutableSequence[retriever.Corpus] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Corpus,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class QueryCorpusRequest(proto.Message):
+    r"""Request for querying a ``Corpus``.
+
+    Attributes:
+        name (str):
+            Required. The name of the ``Corpus`` to query. Example:
+            ``corpora/my-corpus-123``
+        query (str):
+            Required. Query string to perform semantic
+            search.
+        metadata_filters (MutableSequence[google.ai.generativelanguage_v1alpha.types.MetadataFilter]):
+            Optional. Filter for ``Chunk`` and ``Document`` metadata.
+            Each ``MetadataFilter`` object should correspond to a unique
+            key. Multiple ``MetadataFilter`` objects are joined by
+            logical "AND"s.
+
+            Example query at document level: (year >= 2020 OR year <
+            2010) AND (genre = drama OR genre = action)
+
+            ``MetadataFilter`` object list: metadata_filters = [ {key =
+            "document.custom_metadata.year" conditions = [{int_value =
+            2020, operation = GREATER_EQUAL}, {int_value = 2010,
+            operation = LESS}]}, {key = "document.custom_metadata.year"
+            conditions = [{int_value = 2020, operation = GREATER_EQUAL},
+            {int_value = 2010, operation = LESS}]}, {key =
+            "document.custom_metadata.genre" conditions = [{string_value
+            = "drama", operation = EQUAL}, {string_value = "action",
+            operation = EQUAL}]}]
+
+            Example query at chunk level for a numeric range of values:
+            (year > 2015 AND year <= 2020)
+
+            ``MetadataFilter`` object list: metadata_filters = [ {key =
+            "chunk.custom_metadata.year" conditions = [{int_value =
+            2015, operation = GREATER}]}, {key =
+            "chunk.custom_metadata.year" conditions = [{int_value =
+            2020, operation = LESS_EQUAL}]}]
+
+            Note: "AND"s for the same key are only supported for numeric
+            values. String values only support "OR"s for the same key.
+        results_count (int):
+            Optional. The maximum number of ``Chunk``\ s to return. The
+            service may return fewer ``Chunk``\ s.
+
+            If unspecified, at most 10 ``Chunk``\ s will be returned.
+            The maximum specified result count is 100.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    query: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    metadata_filters: MutableSequence[retriever.MetadataFilter] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message=retriever.MetadataFilter,
+    )
+    results_count: int = proto.Field(
+        proto.INT32,
+        number=4,
+    )
+
+
+class QueryCorpusResponse(proto.Message):
+    r"""Response from ``QueryCorpus`` containing a list of relevant chunks.
+
+    Attributes:
+        relevant_chunks (MutableSequence[google.ai.generativelanguage_v1alpha.types.RelevantChunk]):
+            The relevant chunks.
+    """
+
+    relevant_chunks: MutableSequence["RelevantChunk"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="RelevantChunk",
+    )
+
+
+class RelevantChunk(proto.Message):
+    r"""The information for a chunk relevant to a query.
+
+    Attributes:
+        chunk_relevance_score (float):
+            ``Chunk`` relevance to the query.
+        chunk (google.ai.generativelanguage_v1alpha.types.Chunk):
+            ``Chunk`` associated with the query.
+    """
+
+    chunk_relevance_score: float = proto.Field(
+        proto.FLOAT,
+        number=1,
+    )
+    chunk: retriever.Chunk = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=retriever.Chunk,
+    )
+
+
+class CreateDocumentRequest(proto.Message):
+    r"""Request to create a ``Document``.
+
+    Attributes:
+        parent (str):
+            Required. The name of the ``Corpus`` where this ``Document``
+            will be created. Example: ``corpora/my-corpus-123``
+        document (google.ai.generativelanguage_v1alpha.types.Document):
+            Required. The ``Document`` to create.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    document: retriever.Document = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=retriever.Document,
+    )
+
+
+class GetDocumentRequest(proto.Message):
+    r"""Request for getting information about a specific ``Document``.
+
+    Attributes:
+        name (str):
+            Required. The name of the ``Document`` to retrieve. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class UpdateDocumentRequest(proto.Message):
+    r"""Request to update a ``Document``.
+
+    Attributes:
+        document (google.ai.generativelanguage_v1alpha.types.Document):
+            Required. The ``Document`` to update.
+        update_mask (google.protobuf.field_mask_pb2.FieldMask):
+            Required. The list of fields to update. Currently, this only
+            supports updating ``display_name`` and ``custom_metadata``.
+    """
+
+    document: retriever.Document = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Document,
+    )
+    update_mask: field_mask_pb2.FieldMask = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=field_mask_pb2.FieldMask,
+    )
+
+
+class DeleteDocumentRequest(proto.Message):
+    r"""Request to delete a ``Document``.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the ``Document`` to delete.
+            Example: ``corpora/my-corpus-123/documents/the-doc-abc``
+        force (bool):
+            Optional. If set to true, any ``Chunk``\ s and objects
+            related to this ``Document`` will also be deleted.
+
+            If false (the default), a ``FAILED_PRECONDITION`` error will
+            be returned if ``Document`` contains any ``Chunk``\ s.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    force: bool = proto.Field(
+        proto.BOOL,
+        number=2,
+    )
+
+
+class ListDocumentsRequest(proto.Message):
+    r"""Request for listing ``Document``\ s.
+
+    Attributes:
+        parent (str):
+            Required. The name of the ``Corpus`` containing
+            ``Document``\ s. Example: ``corpora/my-corpus-123``
+        page_size (int):
+            Optional. The maximum number of ``Document``\ s to return
+            (per page). The service may return fewer ``Document``\ s.
+
+            If unspecified, at most 10 ``Document``\ s will be returned.
+            The maximum size limit is 20 ``Document``\ s per page.
+        page_token (str):
+            Optional. A page token, received from a previous
+            ``ListDocuments`` call.
+
+            Provide the ``next_page_token`` returned in the response as
+            an argument to the next request to retrieve the next page.
+
+            When paginating, all other parameters provided to
+            ``ListDocuments`` must match the call that provided the page
+            token.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+
+
+class ListDocumentsResponse(proto.Message):
+    r"""Response from ``ListDocuments`` containing a paginated list of
+    ``Document``\ s. The ``Document``\ s are sorted by ascending
+    ``document.create_time``.
+
+    Attributes:
+        documents (MutableSequence[google.ai.generativelanguage_v1alpha.types.Document]):
+            The returned ``Document``\ s.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page. If this field is omitted, there are no more
+            pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    documents: MutableSequence[retriever.Document] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Document,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class QueryDocumentRequest(proto.Message):
+    r"""Request for querying a ``Document``.
+
+    Attributes:
+        name (str):
+            Required. The name of the ``Document`` to query. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        query (str):
+            Required. Query string to perform semantic
+            search.
+        results_count (int):
+            Optional. The maximum number of ``Chunk``\ s to return. The
+            service may return fewer ``Chunk``\ s.
+
+            If unspecified, at most 10 ``Chunk``\ s will be returned.
+            The maximum specified result count is 100.
+        metadata_filters (MutableSequence[google.ai.generativelanguage_v1alpha.types.MetadataFilter]):
+            Optional. Filter for ``Chunk`` metadata. Each
+            ``MetadataFilter`` object should correspond to a unique key.
+            Multiple ``MetadataFilter`` objects are joined by logical
+            "AND"s.
+
+            Note: ``Document``-level filtering is not supported for this
+            request because a ``Document`` name is already specified.
+
+            Example query: (year >= 2020 OR year < 2010) AND (genre =
+            drama OR genre = action)
+
+            ``MetadataFilter`` object list: metadata_filters = [ {key =
+            "chunk.custom_metadata.year" conditions = [{int_value =
+            2020, operation = GREATER_EQUAL}, {int_value = 2010,
+            operation = LESS}}, {key = "chunk.custom_metadata.genre"
+            conditions = [{string_value = "drama", operation = EQUAL},
+            {string_value = "action", operation = EQUAL}}]
+
+            Example query for a numeric range of values: (year > 2015
+            AND year <= 2020)
+
+            ``MetadataFilter`` object list: metadata_filters = [ {key =
+            "chunk.custom_metadata.year" conditions = [{int_value =
+            2015, operation = GREATER}]}, {key =
+            "chunk.custom_metadata.year" conditions = [{int_value =
+            2020, operation = LESS_EQUAL}]}]
+
+            Note: "AND"s for the same key are only supported for numeric
+            values. String values only support "OR"s for the same key.
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    query: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+    results_count: int = proto.Field(
+        proto.INT32,
+        number=3,
+    )
+    metadata_filters: MutableSequence[retriever.MetadataFilter] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=4,
+        message=retriever.MetadataFilter,
+    )
+
+
+class QueryDocumentResponse(proto.Message):
+    r"""Response from ``QueryDocument`` containing a list of relevant
+    chunks.
+
+    Attributes:
+        relevant_chunks (MutableSequence[google.ai.generativelanguage_v1alpha.types.RelevantChunk]):
+            The returned relevant chunks.
+    """
+
+    relevant_chunks: MutableSequence["RelevantChunk"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="RelevantChunk",
+    )
+
+
+class CreateChunkRequest(proto.Message):
+    r"""Request to create a ``Chunk``.
+
+    Attributes:
+        parent (str):
+            Required. The name of the ``Document`` where this ``Chunk``
+            will be created. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        chunk (google.ai.generativelanguage_v1alpha.types.Chunk):
+            Required. The ``Chunk`` to create.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    chunk: retriever.Chunk = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=retriever.Chunk,
+    )
+
+
+class BatchCreateChunksRequest(proto.Message):
+    r"""Request to batch create ``Chunk``\ s.
+
+    Attributes:
+        parent (str):
+            Optional. The name of the ``Document`` where this batch of
+            ``Chunk``\ s will be created. The parent field in every
+            ``CreateChunkRequest`` must match this value. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        requests (MutableSequence[google.ai.generativelanguage_v1alpha.types.CreateChunkRequest]):
+            Required. The request messages specifying the ``Chunk``\ s
+            to create. A maximum of 100 ``Chunk``\ s can be created in a
+            batch.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    requests: MutableSequence["CreateChunkRequest"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="CreateChunkRequest",
+    )
+
+
+class BatchCreateChunksResponse(proto.Message):
+    r"""Response from ``BatchCreateChunks`` containing a list of created
+    ``Chunk``\ s.
+
+    Attributes:
+        chunks (MutableSequence[google.ai.generativelanguage_v1alpha.types.Chunk]):
+            ``Chunk``\ s created.
+    """
+
+    chunks: MutableSequence[retriever.Chunk] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Chunk,
+    )
+
+
+class GetChunkRequest(proto.Message):
+    r"""Request for getting information about a specific ``Chunk``.
+
+    Attributes:
+        name (str):
+            Required. The name of the ``Chunk`` to retrieve. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class UpdateChunkRequest(proto.Message):
+    r"""Request to update a ``Chunk``.
+
+    Attributes:
+        chunk (google.ai.generativelanguage_v1alpha.types.Chunk):
+            Required. The ``Chunk`` to update.
+        update_mask (google.protobuf.field_mask_pb2.FieldMask):
+            Required. The list of fields to update. Currently, this only
+            supports updating ``custom_metadata`` and ``data``.
+    """
+
+    chunk: retriever.Chunk = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Chunk,
+    )
+    update_mask: field_mask_pb2.FieldMask = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=field_mask_pb2.FieldMask,
+    )
+
+
+class BatchUpdateChunksRequest(proto.Message):
+    r"""Request to batch update ``Chunk``\ s.
+
+    Attributes:
+        parent (str):
+            Optional. The name of the ``Document`` containing the
+            ``Chunk``\ s to update. The parent field in every
+            ``UpdateChunkRequest`` must match this value. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        requests (MutableSequence[google.ai.generativelanguage_v1alpha.types.UpdateChunkRequest]):
+            Required. The request messages specifying the ``Chunk``\ s
+            to update. A maximum of 100 ``Chunk``\ s can be updated in a
+            batch.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    requests: MutableSequence["UpdateChunkRequest"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="UpdateChunkRequest",
+    )
+
+
+class BatchUpdateChunksResponse(proto.Message):
+    r"""Response from ``BatchUpdateChunks`` containing a list of updated
+    ``Chunk``\ s.
+
+    Attributes:
+        chunks (MutableSequence[google.ai.generativelanguage_v1alpha.types.Chunk]):
+            ``Chunk``\ s updated.
+    """
+
+    chunks: MutableSequence[retriever.Chunk] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Chunk,
+    )
+
+
+class DeleteChunkRequest(proto.Message):
+    r"""Request to delete a ``Chunk``.
+
+    Attributes:
+        name (str):
+            Required. The resource name of the ``Chunk`` to delete.
+            Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc/chunks/some-chunk``
+    """
+
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class BatchDeleteChunksRequest(proto.Message):
+    r"""Request to batch delete ``Chunk``\ s.
+
+    Attributes:
+        parent (str):
+            Optional. The name of the ``Document`` containing the
+            ``Chunk``\ s to delete. The parent field in every
+            ``DeleteChunkRequest`` must match this value. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        requests (MutableSequence[google.ai.generativelanguage_v1alpha.types.DeleteChunkRequest]):
+            Required. The request messages specifying the ``Chunk``\ s
+            to delete.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    requests: MutableSequence["DeleteChunkRequest"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="DeleteChunkRequest",
+    )
+
+
+class ListChunksRequest(proto.Message):
+    r"""Request for listing ``Chunk``\ s.
+
+    Attributes:
+        parent (str):
+            Required. The name of the ``Document`` containing
+            ``Chunk``\ s. Example:
+            ``corpora/my-corpus-123/documents/the-doc-abc``
+        page_size (int):
+            Optional. The maximum number of ``Chunk``\ s to return (per
+            page). The service may return fewer ``Chunk``\ s.
+
+            If unspecified, at most 10 ``Chunk``\ s will be returned.
+            The maximum size limit is 100 ``Chunk``\ s per page.
+        page_token (str):
+            Optional. A page token, received from a previous
+            ``ListChunks`` call.
+
+            Provide the ``next_page_token`` returned in the response as
+            an argument to the next request to retrieve the next page.
+
+            When paginating, all other parameters provided to
+            ``ListChunks`` must match the call that provided the page
+            token.
+    """
+
+    parent: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    page_size: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+    page_token: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+
+
+class ListChunksResponse(proto.Message):
+    r"""Response from ``ListChunks`` containing a paginated list of
+    ``Chunk``\ s. The ``Chunk``\ s are sorted by ascending
+    ``chunk.create_time``.
+
+    Attributes:
+        chunks (MutableSequence[google.ai.generativelanguage_v1alpha.types.Chunk]):
+            The returned ``Chunk``\ s.
+        next_page_token (str):
+            A token, which can be sent as ``page_token`` to retrieve the
+            next page. If this field is omitted, there are no more
+            pages.
+    """
+
+    @property
+    def raw_page(self):
+        return self
+
+    chunks: MutableSequence[retriever.Chunk] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message=retriever.Chunk,
+    )
+    next_page_token: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/text_service.py

@@ -0,0 +1,441 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1alpha.types import citation, safety
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "GenerateTextRequest",
+        "GenerateTextResponse",
+        "TextPrompt",
+        "TextCompletion",
+        "EmbedTextRequest",
+        "EmbedTextResponse",
+        "BatchEmbedTextRequest",
+        "BatchEmbedTextResponse",
+        "Embedding",
+        "CountTextTokensRequest",
+        "CountTextTokensResponse",
+    },
+)
+
+
+class GenerateTextRequest(proto.Message):
+    r"""Request to generate a text completion response from the
+    model.
+
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        model (str):
+            Required. The name of the ``Model`` or ``TunedModel`` to use
+            for generating the completion. Examples:
+            models/text-bison-001 tunedModels/sentence-translator-u3b7m
+        prompt (google.ai.generativelanguage_v1alpha.types.TextPrompt):
+            Required. The free-form input text given to
+            the model as a prompt.
+            Given a prompt, the model will generate a
+            TextCompletion response it predicts as the
+            completion of the input text.
+        temperature (float):
+            Optional. Controls the randomness of the output. Note: The
+            default value varies by model, see the ``Model.temperature``
+            attribute of the ``Model`` returned the ``getModel``
+            function.
+
+            Values can range from [0.0,1.0], inclusive. A value closer
+            to 1.0 will produce responses that are more varied and
+            creative, while a value closer to 0.0 will typically result
+            in more straightforward responses from the model.
+
+            This field is a member of `oneof`_ ``_temperature``.
+        candidate_count (int):
+            Optional. Number of generated responses to return.
+
+            This value must be between [1, 8], inclusive. If unset, this
+            will default to 1.
+
+            This field is a member of `oneof`_ ``_candidate_count``.
+        max_output_tokens (int):
+            Optional. The maximum number of tokens to include in a
+            candidate.
+
+            If unset, this will default to output_token_limit specified
+            in the ``Model`` specification.
+
+            This field is a member of `oneof`_ ``_max_output_tokens``.
+        top_p (float):
+            Optional. The maximum cumulative probability of tokens to
+            consider when sampling.
+
+            The model uses combined Top-k and nucleus sampling.
+
+            Tokens are sorted based on their assigned probabilities so
+            that only the most likely tokens are considered. Top-k
+            sampling directly limits the maximum number of tokens to
+            consider, while Nucleus sampling limits number of tokens
+            based on the cumulative probability.
+
+            Note: The default value varies by model, see the
+            ``Model.top_p`` attribute of the ``Model`` returned the
+            ``getModel`` function.
+
+            This field is a member of `oneof`_ ``_top_p``.
+        top_k (int):
+            Optional. The maximum number of tokens to consider when
+            sampling.
+
+            The model uses combined Top-k and nucleus sampling.
+
+            Top-k sampling considers the set of ``top_k`` most probable
+            tokens. Defaults to 40.
+
+            Note: The default value varies by model, see the
+            ``Model.top_k`` attribute of the ``Model`` returned the
+            ``getModel`` function.
+
+            This field is a member of `oneof`_ ``_top_k``.
+        safety_settings (MutableSequence[google.ai.generativelanguage_v1alpha.types.SafetySetting]):
+            Optional. A list of unique ``SafetySetting`` instances for
+            blocking unsafe content.
+
+            that will be enforced on the ``GenerateTextRequest.prompt``
+            and ``GenerateTextResponse.candidates``. There should not be
+            more than one setting for each ``SafetyCategory`` type. The
+            API will block any prompts and responses that fail to meet
+            the thresholds set by these settings. This list overrides
+            the default settings for each ``SafetyCategory`` specified
+            in the safety_settings. If there is no ``SafetySetting`` for
+            a given ``SafetyCategory`` provided in the list, the API
+            will use the default safety setting for that category. Harm
+            categories HARM_CATEGORY_DEROGATORY, HARM_CATEGORY_TOXICITY,
+            HARM_CATEGORY_VIOLENCE, HARM_CATEGORY_SEXUAL,
+            HARM_CATEGORY_MEDICAL, HARM_CATEGORY_DANGEROUS are supported
+            in text service.
+        stop_sequences (MutableSequence[str]):
+            The set of character sequences (up to 5) that
+            will stop output generation. If specified, the
+            API will stop at the first appearance of a stop
+            sequence. The stop sequence will not be included
+            as part of the response.
+    """
+
+    model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    prompt: "TextPrompt" = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message="TextPrompt",
+    )
+    temperature: float = proto.Field(
+        proto.FLOAT,
+        number=3,
+        optional=True,
+    )
+    candidate_count: int = proto.Field(
+        proto.INT32,
+        number=4,
+        optional=True,
+    )
+    max_output_tokens: int = proto.Field(
+        proto.INT32,
+        number=5,
+        optional=True,
+    )
+    top_p: float = proto.Field(
+        proto.FLOAT,
+        number=6,
+        optional=True,
+    )
+    top_k: int = proto.Field(
+        proto.INT32,
+        number=7,
+        optional=True,
+    )
+    safety_settings: MutableSequence[safety.SafetySetting] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=8,
+        message=safety.SafetySetting,
+    )
+    stop_sequences: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=9,
+    )
+
+
+class GenerateTextResponse(proto.Message):
+    r"""The response from the model, including candidate completions.
+
+    Attributes:
+        candidates (MutableSequence[google.ai.generativelanguage_v1alpha.types.TextCompletion]):
+            Candidate responses from the model.
+        filters (MutableSequence[google.ai.generativelanguage_v1alpha.types.ContentFilter]):
+            A set of content filtering metadata for the prompt and
+            response text.
+
+            This indicates which ``SafetyCategory``\ (s) blocked a
+            candidate from this response, the lowest ``HarmProbability``
+            that triggered a block, and the HarmThreshold setting for
+            that category. This indicates the smallest change to the
+            ``SafetySettings`` that would be necessary to unblock at
+            least 1 response.
+
+            The blocking is configured by the ``SafetySettings`` in the
+            request (or the default ``SafetySettings`` of the API).
+        safety_feedback (MutableSequence[google.ai.generativelanguage_v1alpha.types.SafetyFeedback]):
+            Returns any safety feedback related to
+            content filtering.
+    """
+
+    candidates: MutableSequence["TextCompletion"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="TextCompletion",
+    )
+    filters: MutableSequence[safety.ContentFilter] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message=safety.ContentFilter,
+    )
+    safety_feedback: MutableSequence[safety.SafetyFeedback] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=4,
+        message=safety.SafetyFeedback,
+    )
+
+
+class TextPrompt(proto.Message):
+    r"""Text given to the model as a prompt.
+
+    The Model will use this TextPrompt to Generate a text
+    completion.
+
+    Attributes:
+        text (str):
+            Required. The prompt text.
+    """
+
+    text: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+
+
+class TextCompletion(proto.Message):
+    r"""Output text returned from a model.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        output (str):
+            Output only. The generated text returned from
+            the model.
+        safety_ratings (MutableSequence[google.ai.generativelanguage_v1alpha.types.SafetyRating]):
+            Ratings for the safety of a response.
+
+            There is at most one rating per category.
+        citation_metadata (google.ai.generativelanguage_v1alpha.types.CitationMetadata):
+            Output only. Citation information for model-generated
+            ``output`` in this ``TextCompletion``.
+
+            This field may be populated with attribution information for
+            any text included in the ``output``.
+
+            This field is a member of `oneof`_ ``_citation_metadata``.
+    """
+
+    output: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    safety_ratings: MutableSequence[safety.SafetyRating] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message=safety.SafetyRating,
+    )
+    citation_metadata: citation.CitationMetadata = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        optional=True,
+        message=citation.CitationMetadata,
+    )
+
+
+class EmbedTextRequest(proto.Message):
+    r"""Request to get a text embedding from the model.
+
+    Attributes:
+        model (str):
+            Required. The model name to use with the
+            format model=models/{model}.
+        text (str):
+            Optional. The free-form input text that the
+            model will turn into an embedding.
+    """
+
+    model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    text: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class EmbedTextResponse(proto.Message):
+    r"""The response to a EmbedTextRequest.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        embedding (google.ai.generativelanguage_v1alpha.types.Embedding):
+            Output only. The embedding generated from the
+            input text.
+
+            This field is a member of `oneof`_ ``_embedding``.
+    """
+
+    embedding: "Embedding" = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        optional=True,
+        message="Embedding",
+    )
+
+
+class BatchEmbedTextRequest(proto.Message):
+    r"""Batch request to get a text embedding from the model.
+
+    Attributes:
+        model (str):
+            Required. The name of the ``Model`` to use for generating
+            the embedding. Examples: models/embedding-gecko-001
+        texts (MutableSequence[str]):
+            Optional. The free-form input texts that the
+            model will turn into an embedding. The current
+            limit is 100 texts, over which an error will be
+            thrown.
+        requests (MutableSequence[google.ai.generativelanguage_v1alpha.types.EmbedTextRequest]):
+            Optional. Embed requests for the batch. Only one of
+            ``texts`` or ``requests`` can be set.
+    """
+
+    model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    texts: MutableSequence[str] = proto.RepeatedField(
+        proto.STRING,
+        number=2,
+    )
+    requests: MutableSequence["EmbedTextRequest"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message="EmbedTextRequest",
+    )
+
+
+class BatchEmbedTextResponse(proto.Message):
+    r"""The response to a EmbedTextRequest.
+
+    Attributes:
+        embeddings (MutableSequence[google.ai.generativelanguage_v1alpha.types.Embedding]):
+            Output only. The embeddings generated from
+            the input text.
+    """
+
+    embeddings: MutableSequence["Embedding"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="Embedding",
+    )
+
+
+class Embedding(proto.Message):
+    r"""A list of floats representing the embedding.
+
+    Attributes:
+        value (MutableSequence[float]):
+            The embedding values.
+    """
+
+    value: MutableSequence[float] = proto.RepeatedField(
+        proto.FLOAT,
+        number=1,
+    )
+
+
+class CountTextTokensRequest(proto.Message):
+    r"""Counts the number of tokens in the ``prompt`` sent to a model.
+
+    Models may tokenize text differently, so each model may return a
+    different ``token_count``.
+
+    Attributes:
+        model (str):
+            Required. The model's resource name. This serves as an ID
+            for the Model to use.
+
+            This name should match a model name returned by the
+            ``ListModels`` method.
+
+            Format: ``models/{model}``
+        prompt (google.ai.generativelanguage_v1alpha.types.TextPrompt):
+            Required. The free-form input text given to
+            the model as a prompt.
+    """
+
+    model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    prompt: "TextPrompt" = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message="TextPrompt",
+    )
+
+
+class CountTextTokensResponse(proto.Message):
+    r"""A response from ``CountTextTokens``.
+
+    It returns the model's ``token_count`` for the ``prompt``.
+
+    Attributes:
+        token_count (int):
+            The number of tokens that the ``model`` tokenizes the
+            ``prompt`` into.
+
+            Always non-negative.
+    """
+
+    token_count: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1alpha/types/tuned_model.py

@@ -0,0 +1,542 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from __future__ import annotations
+
+from typing import MutableMapping, MutableSequence
+
+from google.protobuf import timestamp_pb2  # type: ignore
+import proto  # type: ignore
+
+__protobuf__ = proto.module(
+    package="google.ai.generativelanguage.v1alpha",
+    manifest={
+        "TunedModel",
+        "TunedModelSource",
+        "TuningTask",
+        "Hyperparameters",
+        "Dataset",
+        "TuningExamples",
+        "TuningPart",
+        "TuningContent",
+        "TuningMultiturnExample",
+        "TuningExample",
+        "TuningSnapshot",
+    },
+)
+
+
+class TunedModel(proto.Message):
+    r"""A fine-tuned model created using
+    ModelService.CreateTunedModel.
+
+    This message has `oneof`_ fields (mutually exclusive fields).
+    For each oneof, at most one member field can be set at the same time.
+    Setting any member of the oneof automatically clears all other
+    members.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        tuned_model_source (google.ai.generativelanguage_v1alpha.types.TunedModelSource):
+            Optional. TunedModel to use as the starting
+            point for training the new model.
+
+            This field is a member of `oneof`_ ``source_model``.
+        base_model (str):
+            Immutable. The name of the ``Model`` to tune. Example:
+            ``models/gemini-1.5-flash-001``
+
+            This field is a member of `oneof`_ ``source_model``.
+        name (str):
+            Output only. The tuned model name. A unique name will be
+            generated on create. Example: ``tunedModels/az2mb0bpw6i`` If
+            display_name is set on create, the id portion of the name
+            will be set by concatenating the words of the display_name
+            with hyphens and adding a random portion for uniqueness.
+
+            Example:
+
+            -  display_name = ``Sentence Translator``
+            -  name = ``tunedModels/sentence-translator-u3b7m``
+        display_name (str):
+            Optional. The name to display for this model
+            in user interfaces. The display name must be up
+            to 40 characters including spaces.
+        description (str):
+            Optional. A short description of this model.
+        temperature (float):
+            Optional. Controls the randomness of the output.
+
+            Values can range over ``[0.0,1.0]``, inclusive. A value
+            closer to ``1.0`` will produce responses that are more
+            varied, while a value closer to ``0.0`` will typically
+            result in less surprising responses from the model.
+
+            This value specifies default to be the one used by the base
+            model while creating the model.
+
+            This field is a member of `oneof`_ ``_temperature``.
+        top_p (float):
+            Optional. For Nucleus sampling.
+
+            Nucleus sampling considers the smallest set of tokens whose
+            probability sum is at least ``top_p``.
+
+            This value specifies default to be the one used by the base
+            model while creating the model.
+
+            This field is a member of `oneof`_ ``_top_p``.
+        top_k (int):
+            Optional. For Top-k sampling.
+
+            Top-k sampling considers the set of ``top_k`` most probable
+            tokens. This value specifies default to be used by the
+            backend while making the call to the model.
+
+            This value specifies default to be the one used by the base
+            model while creating the model.
+
+            This field is a member of `oneof`_ ``_top_k``.
+        state (google.ai.generativelanguage_v1alpha.types.TunedModel.State):
+            Output only. The state of the tuned model.
+        create_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The timestamp when this model
+            was created.
+        update_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The timestamp when this model
+            was updated.
+        tuning_task (google.ai.generativelanguage_v1alpha.types.TuningTask):
+            Required. The tuning task that creates the
+            tuned model.
+        reader_project_numbers (MutableSequence[int]):
+            Optional. List of project numbers that have
+            read access to the tuned model.
+    """
+
+    class State(proto.Enum):
+        r"""The state of the tuned model.
+
+        Values:
+            STATE_UNSPECIFIED (0):
+                The default value. This value is unused.
+            CREATING (1):
+                The model is being created.
+            ACTIVE (2):
+                The model is ready to be used.
+            FAILED (3):
+                The model failed to be created.
+        """
+        STATE_UNSPECIFIED = 0
+        CREATING = 1
+        ACTIVE = 2
+        FAILED = 3
+
+    tuned_model_source: "TunedModelSource" = proto.Field(
+        proto.MESSAGE,
+        number=3,
+        oneof="source_model",
+        message="TunedModelSource",
+    )
+    base_model: str = proto.Field(
+        proto.STRING,
+        number=4,
+        oneof="source_model",
+    )
+    name: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    display_name: str = proto.Field(
+        proto.STRING,
+        number=5,
+    )
+    description: str = proto.Field(
+        proto.STRING,
+        number=6,
+    )
+    temperature: float = proto.Field(
+        proto.FLOAT,
+        number=11,
+        optional=True,
+    )
+    top_p: float = proto.Field(
+        proto.FLOAT,
+        number=12,
+        optional=True,
+    )
+    top_k: int = proto.Field(
+        proto.INT32,
+        number=13,
+        optional=True,
+    )
+    state: State = proto.Field(
+        proto.ENUM,
+        number=7,
+        enum=State,
+    )
+    create_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=8,
+        message=timestamp_pb2.Timestamp,
+    )
+    update_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=9,
+        message=timestamp_pb2.Timestamp,
+    )
+    tuning_task: "TuningTask" = proto.Field(
+        proto.MESSAGE,
+        number=10,
+        message="TuningTask",
+    )
+    reader_project_numbers: MutableSequence[int] = proto.RepeatedField(
+        proto.INT64,
+        number=14,
+    )
+
+
+class TunedModelSource(proto.Message):
+    r"""Tuned model as a source for training a new model.
+
+    Attributes:
+        tuned_model (str):
+            Immutable. The name of the ``TunedModel`` to use as the
+            starting point for training the new model. Example:
+            ``tunedModels/my-tuned-model``
+        base_model (str):
+            Output only. The name of the base ``Model`` this
+            ``TunedModel`` was tuned from. Example:
+            ``models/gemini-1.5-flash-001``
+    """
+
+    tuned_model: str = proto.Field(
+        proto.STRING,
+        number=1,
+    )
+    base_model: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class TuningTask(proto.Message):
+    r"""Tuning tasks that create tuned models.
+
+    Attributes:
+        start_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The timestamp when tuning this
+            model started.
+        complete_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The timestamp when tuning this
+            model completed.
+        snapshots (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningSnapshot]):
+            Output only. Metrics collected during tuning.
+        training_data (google.ai.generativelanguage_v1alpha.types.Dataset):
+            Required. Input only. Immutable. The model
+            training data.
+        hyperparameters (google.ai.generativelanguage_v1alpha.types.Hyperparameters):
+            Immutable. Hyperparameters controlling the
+            tuning process. If not provided, default values
+            will be used.
+    """
+
+    start_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        message=timestamp_pb2.Timestamp,
+    )
+    complete_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=2,
+        message=timestamp_pb2.Timestamp,
+    )
+    snapshots: MutableSequence["TuningSnapshot"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=3,
+        message="TuningSnapshot",
+    )
+    training_data: "Dataset" = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message="Dataset",
+    )
+    hyperparameters: "Hyperparameters" = proto.Field(
+        proto.MESSAGE,
+        number=5,
+        message="Hyperparameters",
+    )
+
+
+class Hyperparameters(proto.Message):
+    r"""Hyperparameters controlling the tuning process. Read more at
+    https://ai.google.dev/docs/model_tuning_guidance
+
+    This message has `oneof`_ fields (mutually exclusive fields).
+    For each oneof, at most one member field can be set at the same time.
+    Setting any member of the oneof automatically clears all other
+    members.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        learning_rate (float):
+            Optional. Immutable. The learning rate
+            hyperparameter for tuning. If not set, a default
+            of 0.001 or 0.0002 will be calculated based on
+            the number of training examples.
+
+            This field is a member of `oneof`_ ``learning_rate_option``.
+        learning_rate_multiplier (float):
+            Optional. Immutable. The learning rate multiplier is used to
+            calculate a final learning_rate based on the default
+            (recommended) value. Actual learning rate :=
+            learning_rate_multiplier \* default learning rate Default
+            learning rate is dependent on base model and dataset size.
+            If not set, a default of 1.0 will be used.
+
+            This field is a member of `oneof`_ ``learning_rate_option``.
+        epoch_count (int):
+            Immutable. The number of training epochs. An
+            epoch is one pass through the training data. If
+            not set, a default of 5 will be used.
+
+            This field is a member of `oneof`_ ``_epoch_count``.
+        batch_size (int):
+            Immutable. The batch size hyperparameter for
+            tuning. If not set, a default of 4 or 16 will be
+            used based on the number of training examples.
+
+            This field is a member of `oneof`_ ``_batch_size``.
+    """
+
+    learning_rate: float = proto.Field(
+        proto.FLOAT,
+        number=16,
+        oneof="learning_rate_option",
+    )
+    learning_rate_multiplier: float = proto.Field(
+        proto.FLOAT,
+        number=17,
+        oneof="learning_rate_option",
+    )
+    epoch_count: int = proto.Field(
+        proto.INT32,
+        number=14,
+        optional=True,
+    )
+    batch_size: int = proto.Field(
+        proto.INT32,
+        number=15,
+        optional=True,
+    )
+
+
+class Dataset(proto.Message):
+    r"""Dataset for training or validation.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        examples (google.ai.generativelanguage_v1alpha.types.TuningExamples):
+            Optional. Inline examples with simple
+            input/output text.
+
+            This field is a member of `oneof`_ ``dataset``.
+    """
+
+    examples: "TuningExamples" = proto.Field(
+        proto.MESSAGE,
+        number=1,
+        oneof="dataset",
+        message="TuningExamples",
+    )
+
+
+class TuningExamples(proto.Message):
+    r"""A set of tuning examples. Can be training or validation data.
+
+    Attributes:
+        examples (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningExample]):
+            The examples. Example input can be for text
+            or discuss, but all examples in a set must be of
+            the same type.
+        multiturn_examples (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningMultiturnExample]):
+            Content examples. For multiturn
+            conversations.
+    """
+
+    examples: MutableSequence["TuningExample"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="TuningExample",
+    )
+    multiturn_examples: MutableSequence["TuningMultiturnExample"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=2,
+        message="TuningMultiturnExample",
+    )
+
+
+class TuningPart(proto.Message):
+    r"""A datatype containing data that is part of a multi-part
+    ``TuningContent`` message.
+
+    This is a subset of the Part used for model inference, with limited
+    type support.
+
+    A ``Part`` consists of data which has an associated datatype. A
+    ``Part`` can only contain one of the accepted types in
+    ``Part.data``.
+
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        text (str):
+            Inline text.
+
+            This field is a member of `oneof`_ ``data``.
+    """
+
+    text: str = proto.Field(
+        proto.STRING,
+        number=2,
+        oneof="data",
+    )
+
+
+class TuningContent(proto.Message):
+    r"""The structured datatype containing multi-part content of an example
+    message.
+
+    This is a subset of the Content proto used during model inference
+    with limited type support. 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.
+
+    Attributes:
+        parts (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningPart]):
+            Ordered ``Parts`` that constitute a single message. Parts
+            may have different MIME types.
+        role (str):
+            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.
+    """
+
+    parts: MutableSequence["TuningPart"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="TuningPart",
+    )
+    role: str = proto.Field(
+        proto.STRING,
+        number=2,
+    )
+
+
+class TuningMultiturnExample(proto.Message):
+    r"""A tuning example with multiturn input.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        system_instruction (google.ai.generativelanguage_v1alpha.types.TuningContent):
+            Optional. Developer set system instructions.
+            Currently, text only.
+
+            This field is a member of `oneof`_ ``_system_instruction``.
+        contents (MutableSequence[google.ai.generativelanguage_v1alpha.types.TuningContent]):
+            Each Content represents a turn in the
+            conversation.
+    """
+
+    system_instruction: "TuningContent" = proto.Field(
+        proto.MESSAGE,
+        number=8,
+        optional=True,
+        message="TuningContent",
+    )
+    contents: MutableSequence["TuningContent"] = proto.RepeatedField(
+        proto.MESSAGE,
+        number=1,
+        message="TuningContent",
+    )
+
+
+class TuningExample(proto.Message):
+    r"""A single example for tuning.
+
+    .. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
+
+    Attributes:
+        text_input (str):
+            Optional. Text model input.
+
+            This field is a member of `oneof`_ ``model_input``.
+        output (str):
+            Required. The expected model output.
+    """
+
+    text_input: str = proto.Field(
+        proto.STRING,
+        number=1,
+        oneof="model_input",
+    )
+    output: str = proto.Field(
+        proto.STRING,
+        number=3,
+    )
+
+
+class TuningSnapshot(proto.Message):
+    r"""Record for a single tuning step.
+
+    Attributes:
+        step (int):
+            Output only. The tuning step.
+        epoch (int):
+            Output only. The epoch this step was part of.
+        mean_loss (float):
+            Output only. The mean loss of the training
+            examples for this step.
+        compute_time (google.protobuf.timestamp_pb2.Timestamp):
+            Output only. The timestamp when this metric
+            was computed.
+    """
+
+    step: int = proto.Field(
+        proto.INT32,
+        number=1,
+    )
+    epoch: int = proto.Field(
+        proto.INT32,
+        number=2,
+    )
+    mean_loss: float = proto.Field(
+        proto.FLOAT,
+        number=3,
+    )
+    compute_time: timestamp_pb2.Timestamp = proto.Field(
+        proto.MESSAGE,
+        number=4,
+        message=timestamp_pb2.Timestamp,
+    )
+
+
+__all__ = tuple(sorted(__protobuf__.manifest))

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/__init__.py

@@ -0,0 +1,22 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from .async_client import DiscussServiceAsyncClient
+from .client import DiscussServiceClient
+
+__all__ = (
+    "DiscussServiceClient",
+    "DiscussServiceAsyncClient",
+)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/async_client.py

@@ -0,0 +1,630 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from collections import OrderedDict
+import logging as std_logging
+import re
+from typing import (
+    Callable,
+    Dict,
+    Mapping,
+    MutableMapping,
+    MutableSequence,
+    Optional,
+    Sequence,
+    Tuple,
+    Type,
+    Union,
+)
+
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1
+from google.api_core import retry_async as retries
+from google.api_core.client_options import ClientOptions
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.oauth2 import service_account  # type: ignore
+
+from google.ai.generativelanguage_v1beta3 import gapic_version as package_version
+
+try:
+    OptionalRetry = Union[retries.AsyncRetry, gapic_v1.method._MethodDefault, None]
+except AttributeError:  # pragma: NO COVER
+    OptionalRetry = Union[retries.AsyncRetry, object, None]  # type: ignore
+
+from google.longrunning import operations_pb2  # type: ignore
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service, safety
+
+from .client import DiscussServiceClient
+from .transports.base import DEFAULT_CLIENT_INFO, DiscussServiceTransport
+from .transports.grpc_asyncio import DiscussServiceGrpcAsyncIOTransport
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = std_logging.getLogger(__name__)
+
+
+class DiscussServiceAsyncClient:
+    """An API for using Generative Language Models (GLMs) in dialog
+    applications.
+    Also known as large language models (LLMs), this API provides
+    models that are trained for multi-turn dialog.
+    """
+
+    _client: DiscussServiceClient
+
+    # Copy defaults from the synchronous client for use here.
+    # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
+    DEFAULT_ENDPOINT = DiscussServiceClient.DEFAULT_ENDPOINT
+    DEFAULT_MTLS_ENDPOINT = DiscussServiceClient.DEFAULT_MTLS_ENDPOINT
+    _DEFAULT_ENDPOINT_TEMPLATE = DiscussServiceClient._DEFAULT_ENDPOINT_TEMPLATE
+    _DEFAULT_UNIVERSE = DiscussServiceClient._DEFAULT_UNIVERSE
+
+    model_path = staticmethod(DiscussServiceClient.model_path)
+    parse_model_path = staticmethod(DiscussServiceClient.parse_model_path)
+    common_billing_account_path = staticmethod(
+        DiscussServiceClient.common_billing_account_path
+    )
+    parse_common_billing_account_path = staticmethod(
+        DiscussServiceClient.parse_common_billing_account_path
+    )
+    common_folder_path = staticmethod(DiscussServiceClient.common_folder_path)
+    parse_common_folder_path = staticmethod(
+        DiscussServiceClient.parse_common_folder_path
+    )
+    common_organization_path = staticmethod(
+        DiscussServiceClient.common_organization_path
+    )
+    parse_common_organization_path = staticmethod(
+        DiscussServiceClient.parse_common_organization_path
+    )
+    common_project_path = staticmethod(DiscussServiceClient.common_project_path)
+    parse_common_project_path = staticmethod(
+        DiscussServiceClient.parse_common_project_path
+    )
+    common_location_path = staticmethod(DiscussServiceClient.common_location_path)
+    parse_common_location_path = staticmethod(
+        DiscussServiceClient.parse_common_location_path
+    )
+
+    @classmethod
+    def from_service_account_info(cls, info: dict, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            info.
+
+        Args:
+            info (dict): The service account private key info.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            DiscussServiceAsyncClient: The constructed client.
+        """
+        return DiscussServiceClient.from_service_account_info.__func__(DiscussServiceAsyncClient, info, *args, **kwargs)  # type: ignore
+
+    @classmethod
+    def from_service_account_file(cls, filename: str, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            file.
+
+        Args:
+            filename (str): The path to the service account private key json
+                file.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            DiscussServiceAsyncClient: The constructed client.
+        """
+        return DiscussServiceClient.from_service_account_file.__func__(DiscussServiceAsyncClient, filename, *args, **kwargs)  # type: ignore
+
+    from_service_account_json = from_service_account_file
+
+    @classmethod
+    def get_mtls_endpoint_and_cert_source(
+        cls, client_options: Optional[ClientOptions] = None
+    ):
+        """Return the API endpoint and client cert source for mutual TLS.
+
+        The client cert source is determined in the following order:
+        (1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
+        client cert source is None.
+        (2) if `client_options.client_cert_source` is provided, use the provided one; if the
+        default client cert source exists, use the default one; otherwise the client cert
+        source is None.
+
+        The API endpoint is determined in the following order:
+        (1) if `client_options.api_endpoint` if provided, use the provided one.
+        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
+        default mTLS endpoint; if the environment variable is "never", use the default API
+        endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
+        use the default API endpoint.
+
+        More details can be found at https://google.aip.dev/auth/4114.
+
+        Args:
+            client_options (google.api_core.client_options.ClientOptions): Custom options for the
+                client. Only the `api_endpoint` and `client_cert_source` properties may be used
+                in this method.
+
+        Returns:
+            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
+                client cert source to use.
+
+        Raises:
+            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
+        """
+        return DiscussServiceClient.get_mtls_endpoint_and_cert_source(client_options)  # type: ignore
+
+    @property
+    def transport(self) -> DiscussServiceTransport:
+        """Returns the transport used by the client instance.
+
+        Returns:
+            DiscussServiceTransport: The transport used by the client instance.
+        """
+        return self._client.transport
+
+    @property
+    def api_endpoint(self):
+        """Return the API endpoint used by the client instance.
+
+        Returns:
+            str: The API endpoint used by the client instance.
+        """
+        return self._client._api_endpoint
+
+    @property
+    def universe_domain(self) -> str:
+        """Return the universe domain used by the client instance.
+
+        Returns:
+            str: The universe domain used
+                by the client instance.
+        """
+        return self._client._universe_domain
+
+    get_transport_class = DiscussServiceClient.get_transport_class
+
+    def __init__(
+        self,
+        *,
+        credentials: Optional[ga_credentials.Credentials] = None,
+        transport: Optional[
+            Union[str, DiscussServiceTransport, Callable[..., DiscussServiceTransport]]
+        ] = "grpc_asyncio",
+        client_options: Optional[ClientOptions] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+    ) -> None:
+        """Instantiates the discuss service async client.
+
+        Args:
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+            transport (Optional[Union[str,DiscussServiceTransport,Callable[..., DiscussServiceTransport]]]):
+                The transport to use, or a Callable that constructs and returns a new transport to use.
+                If a Callable is given, it will be called with the same set of initialization
+                arguments as used in the DiscussServiceTransport constructor.
+                If set to None, a transport is chosen automatically.
+            client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
+                Custom options for the client.
+
+                1. The ``api_endpoint`` property can be used to override the
+                default endpoint provided by the client when ``transport`` is
+                not explicitly provided. Only if this property is not set and
+                ``transport`` was not explicitly provided, the endpoint is
+                determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
+                variable, which have one of the following values:
+                "always" (always use the default mTLS endpoint), "never" (always
+                use the default regular endpoint) and "auto" (auto-switch to the
+                default mTLS endpoint if client certificate is present; this is
+                the default value).
+
+                2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
+                is "true", then the ``client_cert_source`` property can be used
+                to provide a client certificate for mTLS transport. If
+                not provided, the default SSL client certificate will be used if
+                present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
+                set, no client certificate will be used.
+
+                3. The ``universe_domain`` property can be used to override the
+                default "googleapis.com" universe. Note that ``api_endpoint``
+                property still takes precedence; and ``universe_domain`` is
+                currently not supported for mTLS.
+
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+
+        Raises:
+            google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport
+                creation failed for any reason.
+        """
+        self._client = DiscussServiceClient(
+            credentials=credentials,
+            transport=transport,
+            client_options=client_options,
+            client_info=client_info,
+        )
+
+        if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+            std_logging.DEBUG
+        ):  # pragma: NO COVER
+            _LOGGER.debug(
+                "Created client `google.ai.generativelanguage_v1beta3.DiscussServiceAsyncClient`.",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "universeDomain": getattr(
+                        self._client._transport._credentials, "universe_domain", ""
+                    ),
+                    "credentialsType": f"{type(self._client._transport._credentials).__module__}.{type(self._client._transport._credentials).__qualname__}",
+                    "credentialsInfo": getattr(
+                        self.transport._credentials, "get_cred_info", lambda: None
+                    )(),
+                }
+                if hasattr(self._client._transport, "_credentials")
+                else {
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "credentialsType": None,
+                },
+            )
+
+    async def generate_message(
+        self,
+        request: Optional[Union[discuss_service.GenerateMessageRequest, dict]] = None,
+        *,
+        model: Optional[str] = None,
+        prompt: Optional[discuss_service.MessagePrompt] = None,
+        temperature: Optional[float] = None,
+        candidate_count: Optional[int] = None,
+        top_p: Optional[float] = None,
+        top_k: Optional[int] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> discuss_service.GenerateMessageResponse:
+        r"""Generates a response from the model given an input
+        ``MessagePrompt``.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_generate_message():
+                # Create a client
+                client = generativelanguage_v1beta3.DiscussServiceAsyncClient()
+
+                # Initialize request argument(s)
+                prompt = generativelanguage_v1beta3.MessagePrompt()
+                prompt.messages.content = "content_value"
+
+                request = generativelanguage_v1beta3.GenerateMessageRequest(
+                    model="model_value",
+                    prompt=prompt,
+                )
+
+                # Make the request
+                response = await client.generate_message(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.GenerateMessageRequest, dict]]):
+                The request object. Request to generate a message
+                response from the model.
+            model (:class:`str`):
+                Required. The name of the model to use.
+
+                Format: ``name=models/{model}``.
+
+                This corresponds to the ``model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            prompt (:class:`google.ai.generativelanguage_v1beta3.types.MessagePrompt`):
+                Required. The structured textual
+                input given to the model as a prompt.
+                Given a
+                prompt, the model will return what it
+                predicts is the next message in the
+                discussion.
+
+                This corresponds to the ``prompt`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            temperature (:class:`float`):
+                Optional. Controls the randomness of the output.
+
+                Values can range over ``[0.0,1.0]``, inclusive. A value
+                closer to ``1.0`` will produce responses that are more
+                varied, while a value closer to ``0.0`` will typically
+                result in less surprising responses from the model.
+
+                This corresponds to the ``temperature`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            candidate_count (:class:`int`):
+                Optional. The number of generated response messages to
+                return.
+
+                This value must be between ``[1, 8]``, inclusive. If
+                unset, this will default to ``1``.
+
+                This corresponds to the ``candidate_count`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            top_p (:class:`float`):
+                Optional. The maximum cumulative probability of tokens
+                to consider when sampling.
+
+                The model uses combined Top-k and nucleus sampling.
+
+                Nucleus sampling considers the smallest set of tokens
+                whose probability sum is at least ``top_p``.
+
+                This corresponds to the ``top_p`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            top_k (:class:`int`):
+                Optional. The maximum number of tokens to consider when
+                sampling.
+
+                The model uses combined Top-k and nucleus sampling.
+
+                Top-k sampling considers the set of ``top_k`` most
+                probable tokens.
+
+                This corresponds to the ``top_k`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.GenerateMessageResponse:
+                The response from the model.
+
+                This includes candidate messages and
+                conversation history in the form of
+                chronologically-ordered messages.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any(
+            [model, prompt, temperature, candidate_count, top_p, top_k]
+        )
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, discuss_service.GenerateMessageRequest):
+            request = discuss_service.GenerateMessageRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if model is not None:
+            request.model = model
+        if prompt is not None:
+            request.prompt = prompt
+        if temperature is not None:
+            request.temperature = temperature
+        if candidate_count is not None:
+            request.candidate_count = candidate_count
+        if top_p is not None:
+            request.top_p = top_p
+        if top_k is not None:
+            request.top_k = top_k
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.generate_message
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def count_message_tokens(
+        self,
+        request: Optional[
+            Union[discuss_service.CountMessageTokensRequest, dict]
+        ] = None,
+        *,
+        model: Optional[str] = None,
+        prompt: Optional[discuss_service.MessagePrompt] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> discuss_service.CountMessageTokensResponse:
+        r"""Runs a model's tokenizer on a string and returns the
+        token count.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_count_message_tokens():
+                # Create a client
+                client = generativelanguage_v1beta3.DiscussServiceAsyncClient()
+
+                # Initialize request argument(s)
+                prompt = generativelanguage_v1beta3.MessagePrompt()
+                prompt.messages.content = "content_value"
+
+                request = generativelanguage_v1beta3.CountMessageTokensRequest(
+                    model="model_value",
+                    prompt=prompt,
+                )
+
+                # Make the request
+                response = await client.count_message_tokens(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.CountMessageTokensRequest, dict]]):
+                The request object. Counts the number of tokens in the ``prompt`` sent to a
+                model.
+
+                Models may tokenize text differently, so each model may
+                return a different ``token_count``.
+            model (:class:`str`):
+                Required. The model's resource name. This serves as an
+                ID for the Model to use.
+
+                This name should match a model name returned by the
+                ``ListModels`` method.
+
+                Format: ``models/{model}``
+
+                This corresponds to the ``model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            prompt (:class:`google.ai.generativelanguage_v1beta3.types.MessagePrompt`):
+                Required. The prompt, whose token
+                count is to be returned.
+
+                This corresponds to the ``prompt`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.CountMessageTokensResponse:
+                A response from CountMessageTokens.
+
+                   It returns the model's token_count for the prompt.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([model, prompt])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, discuss_service.CountMessageTokensRequest):
+            request = discuss_service.CountMessageTokensRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if model is not None:
+            request.model = model
+        if prompt is not None:
+            request.prompt = prompt
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.count_message_tokens
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def __aenter__(self) -> "DiscussServiceAsyncClient":
+        return self
+
+    async def __aexit__(self, exc_type, exc, tb):
+        await self.transport.close()
+
+
+DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
+    gapic_version=package_version.__version__
+)
+
+
+__all__ = ("DiscussServiceAsyncClient",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/client.py

@@ -0,0 +1,1018 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from collections import OrderedDict
+import logging as std_logging
+import os
+import re
+from typing import (
+    Callable,
+    Dict,
+    Mapping,
+    MutableMapping,
+    MutableSequence,
+    Optional,
+    Sequence,
+    Tuple,
+    Type,
+    Union,
+    cast,
+)
+import warnings
+
+from google.api_core import client_options as client_options_lib
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1
+from google.api_core import retry as retries
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.auth.exceptions import MutualTLSChannelError  # type: ignore
+from google.auth.transport import mtls  # type: ignore
+from google.auth.transport.grpc import SslCredentials  # type: ignore
+from google.oauth2 import service_account  # type: ignore
+
+from google.ai.generativelanguage_v1beta3 import gapic_version as package_version
+
+try:
+    OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None]
+except AttributeError:  # pragma: NO COVER
+    OptionalRetry = Union[retries.Retry, object, None]  # type: ignore
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = std_logging.getLogger(__name__)
+
+from google.longrunning import operations_pb2  # type: ignore
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service, safety
+
+from .transports.base import DEFAULT_CLIENT_INFO, DiscussServiceTransport
+from .transports.grpc import DiscussServiceGrpcTransport
+from .transports.grpc_asyncio import DiscussServiceGrpcAsyncIOTransport
+from .transports.rest import DiscussServiceRestTransport
+
+
+class DiscussServiceClientMeta(type):
+    """Metaclass for the DiscussService client.
+
+    This provides class-level methods for building and retrieving
+    support objects (e.g. transport) without polluting the client instance
+    objects.
+    """
+
+    _transport_registry = (
+        OrderedDict()
+    )  # type: Dict[str, Type[DiscussServiceTransport]]
+    _transport_registry["grpc"] = DiscussServiceGrpcTransport
+    _transport_registry["grpc_asyncio"] = DiscussServiceGrpcAsyncIOTransport
+    _transport_registry["rest"] = DiscussServiceRestTransport
+
+    def get_transport_class(
+        cls,
+        label: Optional[str] = None,
+    ) -> Type[DiscussServiceTransport]:
+        """Returns an appropriate transport class.
+
+        Args:
+            label: The name of the desired transport. If none is
+                provided, then the first transport in the registry is used.
+
+        Returns:
+            The transport class to use.
+        """
+        # If a specific transport is requested, return that one.
+        if label:
+            return cls._transport_registry[label]
+
+        # No transport is requested; return the default (that is, the first one
+        # in the dictionary).
+        return next(iter(cls._transport_registry.values()))
+
+
+class DiscussServiceClient(metaclass=DiscussServiceClientMeta):
+    """An API for using Generative Language Models (GLMs) in dialog
+    applications.
+    Also known as large language models (LLMs), this API provides
+    models that are trained for multi-turn dialog.
+    """
+
+    @staticmethod
+    def _get_default_mtls_endpoint(api_endpoint):
+        """Converts api endpoint to mTLS endpoint.
+
+        Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
+        "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
+        Args:
+            api_endpoint (Optional[str]): the api endpoint to convert.
+        Returns:
+            str: converted mTLS api endpoint.
+        """
+        if not api_endpoint:
+            return api_endpoint
+
+        mtls_endpoint_re = re.compile(
+            r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
+        )
+
+        m = mtls_endpoint_re.match(api_endpoint)
+        name, mtls, sandbox, googledomain = m.groups()
+        if mtls or not googledomain:
+            return api_endpoint
+
+        if sandbox:
+            return api_endpoint.replace(
+                "sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
+            )
+
+        return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")
+
+    # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
+    DEFAULT_ENDPOINT = "generativelanguage.googleapis.com"
+    DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__(  # type: ignore
+        DEFAULT_ENDPOINT
+    )
+
+    _DEFAULT_ENDPOINT_TEMPLATE = "generativelanguage.{UNIVERSE_DOMAIN}"
+    _DEFAULT_UNIVERSE = "googleapis.com"
+
+    @classmethod
+    def from_service_account_info(cls, info: dict, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            info.
+
+        Args:
+            info (dict): The service account private key info.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            DiscussServiceClient: The constructed client.
+        """
+        credentials = service_account.Credentials.from_service_account_info(info)
+        kwargs["credentials"] = credentials
+        return cls(*args, **kwargs)
+
+    @classmethod
+    def from_service_account_file(cls, filename: str, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            file.
+
+        Args:
+            filename (str): The path to the service account private key json
+                file.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            DiscussServiceClient: The constructed client.
+        """
+        credentials = service_account.Credentials.from_service_account_file(filename)
+        kwargs["credentials"] = credentials
+        return cls(*args, **kwargs)
+
+    from_service_account_json = from_service_account_file
+
+    @property
+    def transport(self) -> DiscussServiceTransport:
+        """Returns the transport used by the client instance.
+
+        Returns:
+            DiscussServiceTransport: The transport used by the client
+                instance.
+        """
+        return self._transport
+
+    @staticmethod
+    def model_path(
+        model: str,
+    ) -> str:
+        """Returns a fully-qualified model string."""
+        return "models/{model}".format(
+            model=model,
+        )
+
+    @staticmethod
+    def parse_model_path(path: str) -> Dict[str, str]:
+        """Parses a model path into its component segments."""
+        m = re.match(r"^models/(?P<model>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @staticmethod
+    def common_billing_account_path(
+        billing_account: str,
+    ) -> str:
+        """Returns a fully-qualified billing_account string."""
+        return "billingAccounts/{billing_account}".format(
+            billing_account=billing_account,
+        )
+
+    @staticmethod
+    def parse_common_billing_account_path(path: str) -> Dict[str, str]:
+        """Parse a billing_account path into its component segments."""
+        m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @staticmethod
+    def common_folder_path(
+        folder: str,
+    ) -> str:
+        """Returns a fully-qualified folder string."""
+        return "folders/{folder}".format(
+            folder=folder,
+        )
+
+    @staticmethod
+    def parse_common_folder_path(path: str) -> Dict[str, str]:
+        """Parse a folder path into its component segments."""
+        m = re.match(r"^folders/(?P<folder>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @staticmethod
+    def common_organization_path(
+        organization: str,
+    ) -> str:
+        """Returns a fully-qualified organization string."""
+        return "organizations/{organization}".format(
+            organization=organization,
+        )
+
+    @staticmethod
+    def parse_common_organization_path(path: str) -> Dict[str, str]:
+        """Parse a organization path into its component segments."""
+        m = re.match(r"^organizations/(?P<organization>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @staticmethod
+    def common_project_path(
+        project: str,
+    ) -> str:
+        """Returns a fully-qualified project string."""
+        return "projects/{project}".format(
+            project=project,
+        )
+
+    @staticmethod
+    def parse_common_project_path(path: str) -> Dict[str, str]:
+        """Parse a project path into its component segments."""
+        m = re.match(r"^projects/(?P<project>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @staticmethod
+    def common_location_path(
+        project: str,
+        location: str,
+    ) -> str:
+        """Returns a fully-qualified location string."""
+        return "projects/{project}/locations/{location}".format(
+            project=project,
+            location=location,
+        )
+
+    @staticmethod
+    def parse_common_location_path(path: str) -> Dict[str, str]:
+        """Parse a location path into its component segments."""
+        m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
+        return m.groupdict() if m else {}
+
+    @classmethod
+    def get_mtls_endpoint_and_cert_source(
+        cls, client_options: Optional[client_options_lib.ClientOptions] = None
+    ):
+        """Deprecated. Return the API endpoint and client cert source for mutual TLS.
+
+        The client cert source is determined in the following order:
+        (1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
+        client cert source is None.
+        (2) if `client_options.client_cert_source` is provided, use the provided one; if the
+        default client cert source exists, use the default one; otherwise the client cert
+        source is None.
+
+        The API endpoint is determined in the following order:
+        (1) if `client_options.api_endpoint` if provided, use the provided one.
+        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
+        default mTLS endpoint; if the environment variable is "never", use the default API
+        endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
+        use the default API endpoint.
+
+        More details can be found at https://google.aip.dev/auth/4114.
+
+        Args:
+            client_options (google.api_core.client_options.ClientOptions): Custom options for the
+                client. Only the `api_endpoint` and `client_cert_source` properties may be used
+                in this method.
+
+        Returns:
+            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
+                client cert source to use.
+
+        Raises:
+            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
+        """
+
+        warnings.warn(
+            "get_mtls_endpoint_and_cert_source is deprecated. Use the api_endpoint property instead.",
+            DeprecationWarning,
+        )
+        if client_options is None:
+            client_options = client_options_lib.ClientOptions()
+        use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")
+        use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
+        if use_client_cert not in ("true", "false"):
+            raise ValueError(
+                "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
+            )
+        if use_mtls_endpoint not in ("auto", "never", "always"):
+            raise MutualTLSChannelError(
+                "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
+            )
+
+        # Figure out the client cert source to use.
+        client_cert_source = None
+        if use_client_cert == "true":
+            if client_options.client_cert_source:
+                client_cert_source = client_options.client_cert_source
+            elif mtls.has_default_client_cert_source():
+                client_cert_source = mtls.default_client_cert_source()
+
+        # Figure out which api endpoint to use.
+        if client_options.api_endpoint is not None:
+            api_endpoint = client_options.api_endpoint
+        elif use_mtls_endpoint == "always" or (
+            use_mtls_endpoint == "auto" and client_cert_source
+        ):
+            api_endpoint = cls.DEFAULT_MTLS_ENDPOINT
+        else:
+            api_endpoint = cls.DEFAULT_ENDPOINT
+
+        return api_endpoint, client_cert_source
+
+    @staticmethod
+    def _read_environment_variables():
+        """Returns the environment variables used by the client.
+
+        Returns:
+            Tuple[bool, str, str]: returns the GOOGLE_API_USE_CLIENT_CERTIFICATE,
+            GOOGLE_API_USE_MTLS_ENDPOINT, and GOOGLE_CLOUD_UNIVERSE_DOMAIN environment variables.
+
+        Raises:
+            ValueError: If GOOGLE_API_USE_CLIENT_CERTIFICATE is not
+                any of ["true", "false"].
+            google.auth.exceptions.MutualTLSChannelError: If GOOGLE_API_USE_MTLS_ENDPOINT
+                is not any of ["auto", "never", "always"].
+        """
+        use_client_cert = os.getenv(
+            "GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"
+        ).lower()
+        use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower()
+        universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN")
+        if use_client_cert not in ("true", "false"):
+            raise ValueError(
+                "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
+            )
+        if use_mtls_endpoint not in ("auto", "never", "always"):
+            raise MutualTLSChannelError(
+                "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
+            )
+        return use_client_cert == "true", use_mtls_endpoint, universe_domain_env
+
+    @staticmethod
+    def _get_client_cert_source(provided_cert_source, use_cert_flag):
+        """Return the client cert source to be used by the client.
+
+        Args:
+            provided_cert_source (bytes): The client certificate source provided.
+            use_cert_flag (bool): A flag indicating whether to use the client certificate.
+
+        Returns:
+            bytes or None: The client cert source to be used by the client.
+        """
+        client_cert_source = None
+        if use_cert_flag:
+            if provided_cert_source:
+                client_cert_source = provided_cert_source
+            elif mtls.has_default_client_cert_source():
+                client_cert_source = mtls.default_client_cert_source()
+        return client_cert_source
+
+    @staticmethod
+    def _get_api_endpoint(
+        api_override, client_cert_source, universe_domain, use_mtls_endpoint
+    ):
+        """Return the API endpoint used by the client.
+
+        Args:
+            api_override (str): The API endpoint override. If specified, this is always
+                the return value of this function and the other arguments are not used.
+            client_cert_source (bytes): The client certificate source used by the client.
+            universe_domain (str): The universe domain used by the client.
+            use_mtls_endpoint (str): How to use the mTLS endpoint, which depends also on the other parameters.
+                Possible values are "always", "auto", or "never".
+
+        Returns:
+            str: The API endpoint to be used by the client.
+        """
+        if api_override is not None:
+            api_endpoint = api_override
+        elif use_mtls_endpoint == "always" or (
+            use_mtls_endpoint == "auto" and client_cert_source
+        ):
+            _default_universe = DiscussServiceClient._DEFAULT_UNIVERSE
+            if universe_domain != _default_universe:
+                raise MutualTLSChannelError(
+                    f"mTLS is not supported in any universe other than {_default_universe}."
+                )
+            api_endpoint = DiscussServiceClient.DEFAULT_MTLS_ENDPOINT
+        else:
+            api_endpoint = DiscussServiceClient._DEFAULT_ENDPOINT_TEMPLATE.format(
+                UNIVERSE_DOMAIN=universe_domain
+            )
+        return api_endpoint
+
+    @staticmethod
+    def _get_universe_domain(
+        client_universe_domain: Optional[str], universe_domain_env: Optional[str]
+    ) -> str:
+        """Return the universe domain used by the client.
+
+        Args:
+            client_universe_domain (Optional[str]): The universe domain configured via the client options.
+            universe_domain_env (Optional[str]): The universe domain configured via the "GOOGLE_CLOUD_UNIVERSE_DOMAIN" environment variable.
+
+        Returns:
+            str: The universe domain to be used by the client.
+
+        Raises:
+            ValueError: If the universe domain is an empty string.
+        """
+        universe_domain = DiscussServiceClient._DEFAULT_UNIVERSE
+        if client_universe_domain is not None:
+            universe_domain = client_universe_domain
+        elif universe_domain_env is not None:
+            universe_domain = universe_domain_env
+        if len(universe_domain.strip()) == 0:
+            raise ValueError("Universe Domain cannot be an empty string.")
+        return universe_domain
+
+    def _validate_universe_domain(self):
+        """Validates client's and credentials' universe domains are consistent.
+
+        Returns:
+            bool: True iff the configured universe domain is valid.
+
+        Raises:
+            ValueError: If the configured universe domain is not valid.
+        """
+
+        # NOTE (b/349488459): universe validation is disabled until further notice.
+        return True
+
+    @property
+    def api_endpoint(self):
+        """Return the API endpoint used by the client instance.
+
+        Returns:
+            str: The API endpoint used by the client instance.
+        """
+        return self._api_endpoint
+
+    @property
+    def universe_domain(self) -> str:
+        """Return the universe domain used by the client instance.
+
+        Returns:
+            str: The universe domain used by the client instance.
+        """
+        return self._universe_domain
+
+    def __init__(
+        self,
+        *,
+        credentials: Optional[ga_credentials.Credentials] = None,
+        transport: Optional[
+            Union[str, DiscussServiceTransport, Callable[..., DiscussServiceTransport]]
+        ] = None,
+        client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+    ) -> None:
+        """Instantiates the discuss service client.
+
+        Args:
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+            transport (Optional[Union[str,DiscussServiceTransport,Callable[..., DiscussServiceTransport]]]):
+                The transport to use, or a Callable that constructs and returns a new transport.
+                If a Callable is given, it will be called with the same set of initialization
+                arguments as used in the DiscussServiceTransport constructor.
+                If set to None, a transport is chosen automatically.
+            client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
+                Custom options for the client.
+
+                1. The ``api_endpoint`` property can be used to override the
+                default endpoint provided by the client when ``transport`` is
+                not explicitly provided. Only if this property is not set and
+                ``transport`` was not explicitly provided, the endpoint is
+                determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
+                variable, which have one of the following values:
+                "always" (always use the default mTLS endpoint), "never" (always
+                use the default regular endpoint) and "auto" (auto-switch to the
+                default mTLS endpoint if client certificate is present; this is
+                the default value).
+
+                2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
+                is "true", then the ``client_cert_source`` property can be used
+                to provide a client certificate for mTLS transport. If
+                not provided, the default SSL client certificate will be used if
+                present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
+                set, no client certificate will be used.
+
+                3. The ``universe_domain`` property can be used to override the
+                default "googleapis.com" universe. Note that the ``api_endpoint``
+                property still takes precedence; and ``universe_domain`` is
+                currently not supported for mTLS.
+
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+
+        Raises:
+            google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
+                creation failed for any reason.
+        """
+        self._client_options = client_options
+        if isinstance(self._client_options, dict):
+            self._client_options = client_options_lib.from_dict(self._client_options)
+        if self._client_options is None:
+            self._client_options = client_options_lib.ClientOptions()
+        self._client_options = cast(
+            client_options_lib.ClientOptions, self._client_options
+        )
+
+        universe_domain_opt = getattr(self._client_options, "universe_domain", None)
+
+        (
+            self._use_client_cert,
+            self._use_mtls_endpoint,
+            self._universe_domain_env,
+        ) = DiscussServiceClient._read_environment_variables()
+        self._client_cert_source = DiscussServiceClient._get_client_cert_source(
+            self._client_options.client_cert_source, self._use_client_cert
+        )
+        self._universe_domain = DiscussServiceClient._get_universe_domain(
+            universe_domain_opt, self._universe_domain_env
+        )
+        self._api_endpoint = None  # updated below, depending on `transport`
+
+        # Initialize the universe domain validation.
+        self._is_universe_domain_valid = False
+
+        if CLIENT_LOGGING_SUPPORTED:  # pragma: NO COVER
+            # Setup logging.
+            client_logging.initialize_logging()
+
+        api_key_value = getattr(self._client_options, "api_key", None)
+        if api_key_value and credentials:
+            raise ValueError(
+                "client_options.api_key and credentials are mutually exclusive"
+            )
+
+        # Save or instantiate the transport.
+        # Ordinarily, we provide the transport, but allowing a custom transport
+        # instance provides an extensibility point for unusual situations.
+        transport_provided = isinstance(transport, DiscussServiceTransport)
+        if transport_provided:
+            # transport is a DiscussServiceTransport instance.
+            if credentials or self._client_options.credentials_file or api_key_value:
+                raise ValueError(
+                    "When providing a transport instance, "
+                    "provide its credentials directly."
+                )
+            if self._client_options.scopes:
+                raise ValueError(
+                    "When providing a transport instance, provide its scopes "
+                    "directly."
+                )
+            self._transport = cast(DiscussServiceTransport, transport)
+            self._api_endpoint = self._transport.host
+
+        self._api_endpoint = (
+            self._api_endpoint
+            or DiscussServiceClient._get_api_endpoint(
+                self._client_options.api_endpoint,
+                self._client_cert_source,
+                self._universe_domain,
+                self._use_mtls_endpoint,
+            )
+        )
+
+        if not transport_provided:
+            import google.auth._default  # type: ignore
+
+            if api_key_value and hasattr(
+                google.auth._default, "get_api_key_credentials"
+            ):
+                credentials = google.auth._default.get_api_key_credentials(
+                    api_key_value
+                )
+
+            transport_init: Union[
+                Type[DiscussServiceTransport], Callable[..., DiscussServiceTransport]
+            ] = (
+                DiscussServiceClient.get_transport_class(transport)
+                if isinstance(transport, str) or transport is None
+                else cast(Callable[..., DiscussServiceTransport], transport)
+            )
+            # initialize with the provided callable or the passed in class
+            self._transport = transport_init(
+                credentials=credentials,
+                credentials_file=self._client_options.credentials_file,
+                host=self._api_endpoint,
+                scopes=self._client_options.scopes,
+                client_cert_source_for_mtls=self._client_cert_source,
+                quota_project_id=self._client_options.quota_project_id,
+                client_info=client_info,
+                always_use_jwt_access=True,
+                api_audience=self._client_options.api_audience,
+            )
+
+        if "async" not in str(self._transport):
+            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+                std_logging.DEBUG
+            ):  # pragma: NO COVER
+                _LOGGER.debug(
+                    "Created client `google.ai.generativelanguage_v1beta3.DiscussServiceClient`.",
+                    extra={
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "universeDomain": getattr(
+                            self._transport._credentials, "universe_domain", ""
+                        ),
+                        "credentialsType": f"{type(self._transport._credentials).__module__}.{type(self._transport._credentials).__qualname__}",
+                        "credentialsInfo": getattr(
+                            self.transport._credentials, "get_cred_info", lambda: None
+                        )(),
+                    }
+                    if hasattr(self._transport, "_credentials")
+                    else {
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "credentialsType": None,
+                    },
+                )
+
+    def generate_message(
+        self,
+        request: Optional[Union[discuss_service.GenerateMessageRequest, dict]] = None,
+        *,
+        model: Optional[str] = None,
+        prompt: Optional[discuss_service.MessagePrompt] = None,
+        temperature: Optional[float] = None,
+        candidate_count: Optional[int] = None,
+        top_p: Optional[float] = None,
+        top_k: Optional[int] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> discuss_service.GenerateMessageResponse:
+        r"""Generates a response from the model given an input
+        ``MessagePrompt``.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            def sample_generate_message():
+                # Create a client
+                client = generativelanguage_v1beta3.DiscussServiceClient()
+
+                # Initialize request argument(s)
+                prompt = generativelanguage_v1beta3.MessagePrompt()
+                prompt.messages.content = "content_value"
+
+                request = generativelanguage_v1beta3.GenerateMessageRequest(
+                    model="model_value",
+                    prompt=prompt,
+                )
+
+                # Make the request
+                response = client.generate_message(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.ai.generativelanguage_v1beta3.types.GenerateMessageRequest, dict]):
+                The request object. Request to generate a message
+                response from the model.
+            model (str):
+                Required. The name of the model to use.
+
+                Format: ``name=models/{model}``.
+
+                This corresponds to the ``model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            prompt (google.ai.generativelanguage_v1beta3.types.MessagePrompt):
+                Required. The structured textual
+                input given to the model as a prompt.
+                Given a
+                prompt, the model will return what it
+                predicts is the next message in the
+                discussion.
+
+                This corresponds to the ``prompt`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            temperature (float):
+                Optional. Controls the randomness of the output.
+
+                Values can range over ``[0.0,1.0]``, inclusive. A value
+                closer to ``1.0`` will produce responses that are more
+                varied, while a value closer to ``0.0`` will typically
+                result in less surprising responses from the model.
+
+                This corresponds to the ``temperature`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            candidate_count (int):
+                Optional. The number of generated response messages to
+                return.
+
+                This value must be between ``[1, 8]``, inclusive. If
+                unset, this will default to ``1``.
+
+                This corresponds to the ``candidate_count`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            top_p (float):
+                Optional. The maximum cumulative probability of tokens
+                to consider when sampling.
+
+                The model uses combined Top-k and nucleus sampling.
+
+                Nucleus sampling considers the smallest set of tokens
+                whose probability sum is at least ``top_p``.
+
+                This corresponds to the ``top_p`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            top_k (int):
+                Optional. The maximum number of tokens to consider when
+                sampling.
+
+                The model uses combined Top-k and nucleus sampling.
+
+                Top-k sampling considers the set of ``top_k`` most
+                probable tokens.
+
+                This corresponds to the ``top_k`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.GenerateMessageResponse:
+                The response from the model.
+
+                This includes candidate messages and
+                conversation history in the form of
+                chronologically-ordered messages.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any(
+            [model, prompt, temperature, candidate_count, top_p, top_k]
+        )
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, discuss_service.GenerateMessageRequest):
+            request = discuss_service.GenerateMessageRequest(request)
+            # If we have keyword arguments corresponding to fields on the
+            # request, apply these.
+            if model is not None:
+                request.model = model
+            if prompt is not None:
+                request.prompt = prompt
+            if temperature is not None:
+                request.temperature = temperature
+            if candidate_count is not None:
+                request.candidate_count = candidate_count
+            if top_p is not None:
+                request.top_p = top_p
+            if top_k is not None:
+                request.top_k = top_k
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[self._transport.generate_message]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)),
+        )
+
+        # Validate the universe domain.
+        self._validate_universe_domain()
+
+        # Send the request.
+        response = rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    def count_message_tokens(
+        self,
+        request: Optional[
+            Union[discuss_service.CountMessageTokensRequest, dict]
+        ] = None,
+        *,
+        model: Optional[str] = None,
+        prompt: Optional[discuss_service.MessagePrompt] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> discuss_service.CountMessageTokensResponse:
+        r"""Runs a model's tokenizer on a string and returns the
+        token count.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            def sample_count_message_tokens():
+                # Create a client
+                client = generativelanguage_v1beta3.DiscussServiceClient()
+
+                # Initialize request argument(s)
+                prompt = generativelanguage_v1beta3.MessagePrompt()
+                prompt.messages.content = "content_value"
+
+                request = generativelanguage_v1beta3.CountMessageTokensRequest(
+                    model="model_value",
+                    prompt=prompt,
+                )
+
+                # Make the request
+                response = client.count_message_tokens(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Union[google.ai.generativelanguage_v1beta3.types.CountMessageTokensRequest, dict]):
+                The request object. Counts the number of tokens in the ``prompt`` sent to a
+                model.
+
+                Models may tokenize text differently, so each model may
+                return a different ``token_count``.
+            model (str):
+                Required. The model's resource name. This serves as an
+                ID for the Model to use.
+
+                This name should match a model name returned by the
+                ``ListModels`` method.
+
+                Format: ``models/{model}``
+
+                This corresponds to the ``model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            prompt (google.ai.generativelanguage_v1beta3.types.MessagePrompt):
+                Required. The prompt, whose token
+                count is to be returned.
+
+                This corresponds to the ``prompt`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.CountMessageTokensResponse:
+                A response from CountMessageTokens.
+
+                   It returns the model's token_count for the prompt.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([model, prompt])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, discuss_service.CountMessageTokensRequest):
+            request = discuss_service.CountMessageTokensRequest(request)
+            # If we have keyword arguments corresponding to fields on the
+            # request, apply these.
+            if model is not None:
+                request.model = model
+            if prompt is not None:
+                request.prompt = prompt
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._transport._wrapped_methods[self._transport.count_message_tokens]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)),
+        )
+
+        # Validate the universe domain.
+        self._validate_universe_domain()
+
+        # Send the request.
+        response = rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    def __enter__(self) -> "DiscussServiceClient":
+        return self
+
+    def __exit__(self, type, value, traceback):
+        """Releases underlying transport's resources.
+
+        .. warning::
+            ONLY use as a context manager if the transport is NOT shared
+            with other clients! Exiting the with block will CLOSE the transport
+            and may cause errors in other clients!
+        """
+        self.transport.close()
+
+
+DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
+    gapic_version=package_version.__version__
+)
+
+
+__all__ = ("DiscussServiceClient",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/__init__.py

@@ -0,0 +1,36 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from collections import OrderedDict
+from typing import Dict, Type
+
+from .base import DiscussServiceTransport
+from .grpc import DiscussServiceGrpcTransport
+from .grpc_asyncio import DiscussServiceGrpcAsyncIOTransport
+from .rest import DiscussServiceRestInterceptor, DiscussServiceRestTransport
+
+# Compile a registry of transports.
+_transport_registry = OrderedDict()  # type: Dict[str, Type[DiscussServiceTransport]]
+_transport_registry["grpc"] = DiscussServiceGrpcTransport
+_transport_registry["grpc_asyncio"] = DiscussServiceGrpcAsyncIOTransport
+_transport_registry["rest"] = DiscussServiceRestTransport
+
+__all__ = (
+    "DiscussServiceTransport",
+    "DiscussServiceGrpcTransport",
+    "DiscussServiceGrpcAsyncIOTransport",
+    "DiscussServiceRestTransport",
+    "DiscussServiceRestInterceptor",
+)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/base.py

@@ -0,0 +1,182 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import abc
+from typing import Awaitable, Callable, Dict, Optional, Sequence, Union
+
+import google.api_core
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1
+from google.api_core import retry as retries
+import google.auth  # type: ignore
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.longrunning import operations_pb2  # type: ignore
+from google.oauth2 import service_account  # type: ignore
+
+from google.ai.generativelanguage_v1beta3 import gapic_version as package_version
+from google.ai.generativelanguage_v1beta3.types import discuss_service
+
+DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
+    gapic_version=package_version.__version__
+)
+
+
+class DiscussServiceTransport(abc.ABC):
+    """Abstract transport class for DiscussService."""
+
+    AUTH_SCOPES = ()
+
+    DEFAULT_HOST: str = "generativelanguage.googleapis.com"
+
+    def __init__(
+        self,
+        *,
+        host: str = DEFAULT_HOST,
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        quota_project_id: Optional[str] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+        always_use_jwt_access: Optional[bool] = False,
+        api_audience: Optional[str] = None,
+        **kwargs,
+    ) -> None:
+        """Instantiate the transport.
+
+        Args:
+            host (Optional[str]):
+                 The hostname to connect to (default: 'generativelanguage.googleapis.com').
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+                This argument is mutually exclusive with credentials.
+            scopes (Optional[Sequence[str]]): A list of scopes.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
+                be used for service account credentials.
+        """
+
+        scopes_kwargs = {"scopes": scopes, "default_scopes": self.AUTH_SCOPES}
+
+        # Save the scopes.
+        self._scopes = scopes
+        if not hasattr(self, "_ignore_credentials"):
+            self._ignore_credentials: bool = False
+
+        # If no credentials are provided, then determine the appropriate
+        # defaults.
+        if credentials and credentials_file:
+            raise core_exceptions.DuplicateCredentialArgs(
+                "'credentials_file' and 'credentials' are mutually exclusive"
+            )
+
+        if credentials_file is not None:
+            credentials, _ = google.auth.load_credentials_from_file(
+                credentials_file, **scopes_kwargs, quota_project_id=quota_project_id
+            )
+        elif credentials is None and not self._ignore_credentials:
+            credentials, _ = google.auth.default(
+                **scopes_kwargs, quota_project_id=quota_project_id
+            )
+            # Don't apply audience if the credentials file passed from user.
+            if hasattr(credentials, "with_gdch_audience"):
+                credentials = credentials.with_gdch_audience(
+                    api_audience if api_audience else host
+                )
+
+        # If the credentials are service account credentials, then always try to use self signed JWT.
+        if (
+            always_use_jwt_access
+            and isinstance(credentials, service_account.Credentials)
+            and hasattr(service_account.Credentials, "with_always_use_jwt_access")
+        ):
+            credentials = credentials.with_always_use_jwt_access(True)
+
+        # Save the credentials.
+        self._credentials = credentials
+
+        # Save the hostname. Default to port 443 (HTTPS) if none is specified.
+        if ":" not in host:
+            host += ":443"
+        self._host = host
+
+    @property
+    def host(self):
+        return self._host
+
+    def _prep_wrapped_messages(self, client_info):
+        # Precompute the wrapped methods.
+        self._wrapped_methods = {
+            self.generate_message: gapic_v1.method.wrap_method(
+                self.generate_message,
+                default_timeout=None,
+                client_info=client_info,
+            ),
+            self.count_message_tokens: gapic_v1.method.wrap_method(
+                self.count_message_tokens,
+                default_timeout=None,
+                client_info=client_info,
+            ),
+        }
+
+    def close(self):
+        """Closes resources associated with the transport.
+
+        .. warning::
+             Only call this method if the transport is NOT shared
+             with other clients - this may cause errors in other clients!
+        """
+        raise NotImplementedError()
+
+    @property
+    def generate_message(
+        self,
+    ) -> Callable[
+        [discuss_service.GenerateMessageRequest],
+        Union[
+            discuss_service.GenerateMessageResponse,
+            Awaitable[discuss_service.GenerateMessageResponse],
+        ],
+    ]:
+        raise NotImplementedError()
+
+    @property
+    def count_message_tokens(
+        self,
+    ) -> Callable[
+        [discuss_service.CountMessageTokensRequest],
+        Union[
+            discuss_service.CountMessageTokensResponse,
+            Awaitable[discuss_service.CountMessageTokensResponse],
+        ],
+    ]:
+        raise NotImplementedError()
+
+    @property
+    def kind(self) -> str:
+        raise NotImplementedError()
+
+
+__all__ = ("DiscussServiceTransport",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/grpc.py

@@ -0,0 +1,395 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import json
+import logging as std_logging
+import pickle
+from typing import Callable, Dict, Optional, Sequence, Tuple, Union
+import warnings
+
+from google.api_core import gapic_v1, grpc_helpers
+import google.auth  # type: ignore
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.auth.transport.grpc import SslCredentials  # type: ignore
+from google.longrunning import operations_pb2  # type: ignore
+from google.protobuf.json_format import MessageToJson
+import google.protobuf.message
+import grpc  # type: ignore
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service
+
+from .base import DEFAULT_CLIENT_INFO, DiscussServiceTransport
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = std_logging.getLogger(__name__)
+
+
+class _LoggingClientInterceptor(grpc.UnaryUnaryClientInterceptor):  # pragma: NO COVER
+    def intercept_unary_unary(self, continuation, client_call_details, request):
+        logging_enabled = CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+            std_logging.DEBUG
+        )
+        if logging_enabled:  # pragma: NO COVER
+            request_metadata = client_call_details.metadata
+            if isinstance(request, proto.Message):
+                request_payload = type(request).to_json(request)
+            elif isinstance(request, google.protobuf.message.Message):
+                request_payload = MessageToJson(request)
+            else:
+                request_payload = f"{type(request).__name__}: {pickle.dumps(request)}"
+
+            request_metadata = {
+                key: value.decode("utf-8") if isinstance(value, bytes) else value
+                for key, value in request_metadata
+            }
+            grpc_request = {
+                "payload": request_payload,
+                "requestMethod": "grpc",
+                "metadata": dict(request_metadata),
+            }
+            _LOGGER.debug(
+                f"Sending request for {client_call_details.method}",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "rpcName": client_call_details.method,
+                    "request": grpc_request,
+                    "metadata": grpc_request["metadata"],
+                },
+            )
+
+        response = continuation(client_call_details, request)
+        if logging_enabled:  # pragma: NO COVER
+            response_metadata = response.trailing_metadata()
+            # Convert gRPC metadata `<class 'grpc.aio._metadata.Metadata'>` to list of tuples
+            metadata = (
+                dict([(k, str(v)) for k, v in response_metadata])
+                if response_metadata
+                else None
+            )
+            result = response.result()
+            if isinstance(result, proto.Message):
+                response_payload = type(result).to_json(result)
+            elif isinstance(result, google.protobuf.message.Message):
+                response_payload = MessageToJson(result)
+            else:
+                response_payload = f"{type(result).__name__}: {pickle.dumps(result)}"
+            grpc_response = {
+                "payload": response_payload,
+                "metadata": metadata,
+                "status": "OK",
+            }
+            _LOGGER.debug(
+                f"Received response for {client_call_details.method}.",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "rpcName": client_call_details.method,
+                    "response": grpc_response,
+                    "metadata": grpc_response["metadata"],
+                },
+            )
+        return response
+
+
+class DiscussServiceGrpcTransport(DiscussServiceTransport):
+    """gRPC backend transport for DiscussService.
+
+    An API for using Generative Language Models (GLMs) in dialog
+    applications.
+    Also known as large language models (LLMs), this API provides
+    models that are trained for multi-turn dialog.
+
+    This class defines the same methods as the primary client, so the
+    primary client can load the underlying transport implementation
+    and call it.
+
+    It sends protocol buffers over the wire using gRPC (which is built on
+    top of HTTP/2); the ``grpcio`` package must be installed.
+    """
+
+    _stubs: Dict[str, Callable]
+
+    def __init__(
+        self,
+        *,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        channel: Optional[Union[grpc.Channel, Callable[..., grpc.Channel]]] = None,
+        api_mtls_endpoint: Optional[str] = None,
+        client_cert_source: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
+        ssl_channel_credentials: Optional[grpc.ChannelCredentials] = None,
+        client_cert_source_for_mtls: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
+        quota_project_id: Optional[str] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+        always_use_jwt_access: Optional[bool] = False,
+        api_audience: Optional[str] = None,
+    ) -> None:
+        """Instantiate the transport.
+
+        Args:
+            host (Optional[str]):
+                 The hostname to connect to (default: 'generativelanguage.googleapis.com').
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+                This argument is ignored if a ``channel`` instance is provided.
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+                This argument is ignored if a ``channel`` instance is provided.
+            scopes (Optional(Sequence[str])): A list of scopes. This argument is
+                ignored if a ``channel`` instance is provided.
+            channel (Optional[Union[grpc.Channel, Callable[..., grpc.Channel]]]):
+                A ``Channel`` instance through which to make calls, or a Callable
+                that constructs and returns one. If set to None, ``self.create_channel``
+                is used to create the channel. If a Callable is given, it will be called
+                with the same arguments as used in ``self.create_channel``.
+            api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
+                If provided, it overrides the ``host`` argument and tries to create
+                a mutual TLS channel with client SSL credentials from
+                ``client_cert_source`` or application default SSL credentials.
+            client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
+                Deprecated. A callback to provide client SSL certificate bytes and
+                private key bytes, both in PEM format. It is ignored if
+                ``api_mtls_endpoint`` is None.
+            ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
+                for the grpc channel. It is ignored if a ``channel`` instance is provided.
+            client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]):
+                A callback to provide client certificate bytes and private key bytes,
+                both in PEM format. It is used to configure a mutual TLS channel. It is
+                ignored if a ``channel`` instance or ``ssl_channel_credentials`` is provided.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
+                be used for service account credentials.
+
+        Raises:
+          google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
+              creation failed for any reason.
+          google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
+              and ``credentials_file`` are passed.
+        """
+        self._grpc_channel = None
+        self._ssl_channel_credentials = ssl_channel_credentials
+        self._stubs: Dict[str, Callable] = {}
+
+        if api_mtls_endpoint:
+            warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning)
+        if client_cert_source:
+            warnings.warn("client_cert_source is deprecated", DeprecationWarning)
+
+        if isinstance(channel, grpc.Channel):
+            # Ignore credentials if a channel was passed.
+            credentials = None
+            self._ignore_credentials = True
+            # If a channel was explicitly provided, set it.
+            self._grpc_channel = channel
+            self._ssl_channel_credentials = None
+
+        else:
+            if api_mtls_endpoint:
+                host = api_mtls_endpoint
+
+                # Create SSL credentials with client_cert_source or application
+                # default SSL credentials.
+                if client_cert_source:
+                    cert, key = client_cert_source()
+                    self._ssl_channel_credentials = grpc.ssl_channel_credentials(
+                        certificate_chain=cert, private_key=key
+                    )
+                else:
+                    self._ssl_channel_credentials = SslCredentials().ssl_credentials
+
+            else:
+                if client_cert_source_for_mtls and not ssl_channel_credentials:
+                    cert, key = client_cert_source_for_mtls()
+                    self._ssl_channel_credentials = grpc.ssl_channel_credentials(
+                        certificate_chain=cert, private_key=key
+                    )
+
+        # The base transport sets the host, credentials and scopes
+        super().__init__(
+            host=host,
+            credentials=credentials,
+            credentials_file=credentials_file,
+            scopes=scopes,
+            quota_project_id=quota_project_id,
+            client_info=client_info,
+            always_use_jwt_access=always_use_jwt_access,
+            api_audience=api_audience,
+        )
+
+        if not self._grpc_channel:
+            # initialize with the provided callable or the default channel
+            channel_init = channel or type(self).create_channel
+            self._grpc_channel = channel_init(
+                self._host,
+                # use the credentials which are saved
+                credentials=self._credentials,
+                # Set ``credentials_file`` to ``None`` here as
+                # the credentials that we saved earlier should be used.
+                credentials_file=None,
+                scopes=self._scopes,
+                ssl_credentials=self._ssl_channel_credentials,
+                quota_project_id=quota_project_id,
+                options=[
+                    ("grpc.max_send_message_length", -1),
+                    ("grpc.max_receive_message_length", -1),
+                ],
+            )
+
+        self._interceptor = _LoggingClientInterceptor()
+        self._logged_channel = grpc.intercept_channel(
+            self._grpc_channel, self._interceptor
+        )
+
+        # Wrap messages. This must be done after self._logged_channel exists
+        self._prep_wrapped_messages(client_info)
+
+    @classmethod
+    def create_channel(
+        cls,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        quota_project_id: Optional[str] = None,
+        **kwargs,
+    ) -> grpc.Channel:
+        """Create and return a gRPC channel object.
+        Args:
+            host (Optional[str]): The host for the channel to use.
+            credentials (Optional[~.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify this application to the service. If
+                none are specified, the client will attempt to ascertain
+                the credentials from the environment.
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+                This argument is mutually exclusive with credentials.
+            scopes (Optional[Sequence[str]]): A optional list of scopes needed for this
+                service. These are only used when credentials are not specified and
+                are passed to :func:`google.auth.default`.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            kwargs (Optional[dict]): Keyword arguments, which are passed to the
+                channel creation.
+        Returns:
+            grpc.Channel: A gRPC channel object.
+
+        Raises:
+            google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
+              and ``credentials_file`` are passed.
+        """
+
+        return grpc_helpers.create_channel(
+            host,
+            credentials=credentials,
+            credentials_file=credentials_file,
+            quota_project_id=quota_project_id,
+            default_scopes=cls.AUTH_SCOPES,
+            scopes=scopes,
+            default_host=cls.DEFAULT_HOST,
+            **kwargs,
+        )
+
+    @property
+    def grpc_channel(self) -> grpc.Channel:
+        """Return the channel designed to connect to this service."""
+        return self._grpc_channel
+
+    @property
+    def generate_message(
+        self,
+    ) -> Callable[
+        [discuss_service.GenerateMessageRequest],
+        discuss_service.GenerateMessageResponse,
+    ]:
+        r"""Return a callable for the generate message method over gRPC.
+
+        Generates a response from the model given an input
+        ``MessagePrompt``.
+
+        Returns:
+            Callable[[~.GenerateMessageRequest],
+                    ~.GenerateMessageResponse]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "generate_message" not in self._stubs:
+            self._stubs["generate_message"] = self._logged_channel.unary_unary(
+                "/google.ai.generativelanguage.v1beta3.DiscussService/GenerateMessage",
+                request_serializer=discuss_service.GenerateMessageRequest.serialize,
+                response_deserializer=discuss_service.GenerateMessageResponse.deserialize,
+            )
+        return self._stubs["generate_message"]
+
+    @property
+    def count_message_tokens(
+        self,
+    ) -> Callable[
+        [discuss_service.CountMessageTokensRequest],
+        discuss_service.CountMessageTokensResponse,
+    ]:
+        r"""Return a callable for the count message tokens method over gRPC.
+
+        Runs a model's tokenizer on a string and returns the
+        token count.
+
+        Returns:
+            Callable[[~.CountMessageTokensRequest],
+                    ~.CountMessageTokensResponse]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "count_message_tokens" not in self._stubs:
+            self._stubs["count_message_tokens"] = self._logged_channel.unary_unary(
+                "/google.ai.generativelanguage.v1beta3.DiscussService/CountMessageTokens",
+                request_serializer=discuss_service.CountMessageTokensRequest.serialize,
+                response_deserializer=discuss_service.CountMessageTokensResponse.deserialize,
+            )
+        return self._stubs["count_message_tokens"]
+
+    def close(self):
+        self._logged_channel.close()
+
+    @property
+    def kind(self) -> str:
+        return "grpc"
+
+
+__all__ = ("DiscussServiceGrpcTransport",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/grpc_asyncio.py

@@ -0,0 +1,422 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import inspect
+import json
+import logging as std_logging
+import pickle
+from typing import Awaitable, Callable, Dict, Optional, Sequence, Tuple, Union
+import warnings
+
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1, grpc_helpers_async
+from google.api_core import retry_async as retries
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.auth.transport.grpc import SslCredentials  # type: ignore
+from google.longrunning import operations_pb2  # type: ignore
+from google.protobuf.json_format import MessageToJson
+import google.protobuf.message
+import grpc  # type: ignore
+from grpc.experimental import aio  # type: ignore
+import proto  # type: ignore
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service
+
+from .base import DEFAULT_CLIENT_INFO, DiscussServiceTransport
+from .grpc import DiscussServiceGrpcTransport
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = std_logging.getLogger(__name__)
+
+
+class _LoggingClientAIOInterceptor(
+    grpc.aio.UnaryUnaryClientInterceptor
+):  # pragma: NO COVER
+    async def intercept_unary_unary(self, continuation, client_call_details, request):
+        logging_enabled = CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+            std_logging.DEBUG
+        )
+        if logging_enabled:  # pragma: NO COVER
+            request_metadata = client_call_details.metadata
+            if isinstance(request, proto.Message):
+                request_payload = type(request).to_json(request)
+            elif isinstance(request, google.protobuf.message.Message):
+                request_payload = MessageToJson(request)
+            else:
+                request_payload = f"{type(request).__name__}: {pickle.dumps(request)}"
+
+            request_metadata = {
+                key: value.decode("utf-8") if isinstance(value, bytes) else value
+                for key, value in request_metadata
+            }
+            grpc_request = {
+                "payload": request_payload,
+                "requestMethod": "grpc",
+                "metadata": dict(request_metadata),
+            }
+            _LOGGER.debug(
+                f"Sending request for {client_call_details.method}",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "rpcName": str(client_call_details.method),
+                    "request": grpc_request,
+                    "metadata": grpc_request["metadata"],
+                },
+            )
+        response = await continuation(client_call_details, request)
+        if logging_enabled:  # pragma: NO COVER
+            response_metadata = await response.trailing_metadata()
+            # Convert gRPC metadata `<class 'grpc.aio._metadata.Metadata'>` to list of tuples
+            metadata = (
+                dict([(k, str(v)) for k, v in response_metadata])
+                if response_metadata
+                else None
+            )
+            result = await response
+            if isinstance(result, proto.Message):
+                response_payload = type(result).to_json(result)
+            elif isinstance(result, google.protobuf.message.Message):
+                response_payload = MessageToJson(result)
+            else:
+                response_payload = f"{type(result).__name__}: {pickle.dumps(result)}"
+            grpc_response = {
+                "payload": response_payload,
+                "metadata": metadata,
+                "status": "OK",
+            }
+            _LOGGER.debug(
+                f"Received response to rpc {client_call_details.method}.",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                    "rpcName": str(client_call_details.method),
+                    "response": grpc_response,
+                    "metadata": grpc_response["metadata"],
+                },
+            )
+        return response
+
+
+class DiscussServiceGrpcAsyncIOTransport(DiscussServiceTransport):
+    """gRPC AsyncIO backend transport for DiscussService.
+
+    An API for using Generative Language Models (GLMs) in dialog
+    applications.
+    Also known as large language models (LLMs), this API provides
+    models that are trained for multi-turn dialog.
+
+    This class defines the same methods as the primary client, so the
+    primary client can load the underlying transport implementation
+    and call it.
+
+    It sends protocol buffers over the wire using gRPC (which is built on
+    top of HTTP/2); the ``grpcio`` package must be installed.
+    """
+
+    _grpc_channel: aio.Channel
+    _stubs: Dict[str, Callable] = {}
+
+    @classmethod
+    def create_channel(
+        cls,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        quota_project_id: Optional[str] = None,
+        **kwargs,
+    ) -> aio.Channel:
+        """Create and return a gRPC AsyncIO channel object.
+        Args:
+            host (Optional[str]): The host for the channel to use.
+            credentials (Optional[~.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify this application to the service. If
+                none are specified, the client will attempt to ascertain
+                the credentials from the environment.
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+            scopes (Optional[Sequence[str]]): A optional list of scopes needed for this
+                service. These are only used when credentials are not specified and
+                are passed to :func:`google.auth.default`.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            kwargs (Optional[dict]): Keyword arguments, which are passed to the
+                channel creation.
+        Returns:
+            aio.Channel: A gRPC AsyncIO channel object.
+        """
+
+        return grpc_helpers_async.create_channel(
+            host,
+            credentials=credentials,
+            credentials_file=credentials_file,
+            quota_project_id=quota_project_id,
+            default_scopes=cls.AUTH_SCOPES,
+            scopes=scopes,
+            default_host=cls.DEFAULT_HOST,
+            **kwargs,
+        )
+
+    def __init__(
+        self,
+        *,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        channel: Optional[Union[aio.Channel, Callable[..., aio.Channel]]] = None,
+        api_mtls_endpoint: Optional[str] = None,
+        client_cert_source: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
+        ssl_channel_credentials: Optional[grpc.ChannelCredentials] = None,
+        client_cert_source_for_mtls: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
+        quota_project_id: Optional[str] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+        always_use_jwt_access: Optional[bool] = False,
+        api_audience: Optional[str] = None,
+    ) -> None:
+        """Instantiate the transport.
+
+        Args:
+            host (Optional[str]):
+                 The hostname to connect to (default: 'generativelanguage.googleapis.com').
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+                This argument is ignored if a ``channel`` instance is provided.
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+                This argument is ignored if a ``channel`` instance is provided.
+            scopes (Optional[Sequence[str]]): A optional list of scopes needed for this
+                service. These are only used when credentials are not specified and
+                are passed to :func:`google.auth.default`.
+            channel (Optional[Union[aio.Channel, Callable[..., aio.Channel]]]):
+                A ``Channel`` instance through which to make calls, or a Callable
+                that constructs and returns one. If set to None, ``self.create_channel``
+                is used to create the channel. If a Callable is given, it will be called
+                with the same arguments as used in ``self.create_channel``.
+            api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
+                If provided, it overrides the ``host`` argument and tries to create
+                a mutual TLS channel with client SSL credentials from
+                ``client_cert_source`` or application default SSL credentials.
+            client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
+                Deprecated. A callback to provide client SSL certificate bytes and
+                private key bytes, both in PEM format. It is ignored if
+                ``api_mtls_endpoint`` is None.
+            ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
+                for the grpc channel. It is ignored if a ``channel`` instance is provided.
+            client_cert_source_for_mtls (Optional[Callable[[], Tuple[bytes, bytes]]]):
+                A callback to provide client certificate bytes and private key bytes,
+                both in PEM format. It is used to configure a mutual TLS channel. It is
+                ignored if a ``channel`` instance or ``ssl_channel_credentials`` is provided.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
+                be used for service account credentials.
+
+        Raises:
+            google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport
+              creation failed for any reason.
+          google.api_core.exceptions.DuplicateCredentialArgs: If both ``credentials``
+              and ``credentials_file`` are passed.
+        """
+        self._grpc_channel = None
+        self._ssl_channel_credentials = ssl_channel_credentials
+        self._stubs: Dict[str, Callable] = {}
+
+        if api_mtls_endpoint:
+            warnings.warn("api_mtls_endpoint is deprecated", DeprecationWarning)
+        if client_cert_source:
+            warnings.warn("client_cert_source is deprecated", DeprecationWarning)
+
+        if isinstance(channel, aio.Channel):
+            # Ignore credentials if a channel was passed.
+            credentials = None
+            self._ignore_credentials = True
+            # If a channel was explicitly provided, set it.
+            self._grpc_channel = channel
+            self._ssl_channel_credentials = None
+        else:
+            if api_mtls_endpoint:
+                host = api_mtls_endpoint
+
+                # Create SSL credentials with client_cert_source or application
+                # default SSL credentials.
+                if client_cert_source:
+                    cert, key = client_cert_source()
+                    self._ssl_channel_credentials = grpc.ssl_channel_credentials(
+                        certificate_chain=cert, private_key=key
+                    )
+                else:
+                    self._ssl_channel_credentials = SslCredentials().ssl_credentials
+
+            else:
+                if client_cert_source_for_mtls and not ssl_channel_credentials:
+                    cert, key = client_cert_source_for_mtls()
+                    self._ssl_channel_credentials = grpc.ssl_channel_credentials(
+                        certificate_chain=cert, private_key=key
+                    )
+
+        # The base transport sets the host, credentials and scopes
+        super().__init__(
+            host=host,
+            credentials=credentials,
+            credentials_file=credentials_file,
+            scopes=scopes,
+            quota_project_id=quota_project_id,
+            client_info=client_info,
+            always_use_jwt_access=always_use_jwt_access,
+            api_audience=api_audience,
+        )
+
+        if not self._grpc_channel:
+            # initialize with the provided callable or the default channel
+            channel_init = channel or type(self).create_channel
+            self._grpc_channel = channel_init(
+                self._host,
+                # use the credentials which are saved
+                credentials=self._credentials,
+                # Set ``credentials_file`` to ``None`` here as
+                # the credentials that we saved earlier should be used.
+                credentials_file=None,
+                scopes=self._scopes,
+                ssl_credentials=self._ssl_channel_credentials,
+                quota_project_id=quota_project_id,
+                options=[
+                    ("grpc.max_send_message_length", -1),
+                    ("grpc.max_receive_message_length", -1),
+                ],
+            )
+
+        self._interceptor = _LoggingClientAIOInterceptor()
+        self._grpc_channel._unary_unary_interceptors.append(self._interceptor)
+        self._logged_channel = self._grpc_channel
+        self._wrap_with_kind = (
+            "kind" in inspect.signature(gapic_v1.method_async.wrap_method).parameters
+        )
+        # Wrap messages. This must be done after self._logged_channel exists
+        self._prep_wrapped_messages(client_info)
+
+    @property
+    def grpc_channel(self) -> aio.Channel:
+        """Create the channel designed to connect to this service.
+
+        This property caches on the instance; repeated calls return
+        the same channel.
+        """
+        # Return the channel from cache.
+        return self._grpc_channel
+
+    @property
+    def generate_message(
+        self,
+    ) -> Callable[
+        [discuss_service.GenerateMessageRequest],
+        Awaitable[discuss_service.GenerateMessageResponse],
+    ]:
+        r"""Return a callable for the generate message method over gRPC.
+
+        Generates a response from the model given an input
+        ``MessagePrompt``.
+
+        Returns:
+            Callable[[~.GenerateMessageRequest],
+                    Awaitable[~.GenerateMessageResponse]]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "generate_message" not in self._stubs:
+            self._stubs["generate_message"] = self._logged_channel.unary_unary(
+                "/google.ai.generativelanguage.v1beta3.DiscussService/GenerateMessage",
+                request_serializer=discuss_service.GenerateMessageRequest.serialize,
+                response_deserializer=discuss_service.GenerateMessageResponse.deserialize,
+            )
+        return self._stubs["generate_message"]
+
+    @property
+    def count_message_tokens(
+        self,
+    ) -> Callable[
+        [discuss_service.CountMessageTokensRequest],
+        Awaitable[discuss_service.CountMessageTokensResponse],
+    ]:
+        r"""Return a callable for the count message tokens method over gRPC.
+
+        Runs a model's tokenizer on a string and returns the
+        token count.
+
+        Returns:
+            Callable[[~.CountMessageTokensRequest],
+                    Awaitable[~.CountMessageTokensResponse]]:
+                A function that, when called, will call the underlying RPC
+                on the server.
+        """
+        # Generate a "stub function" on-the-fly which will actually make
+        # the request.
+        # gRPC handles serialization and deserialization, so we just need
+        # to pass in the functions for each.
+        if "count_message_tokens" not in self._stubs:
+            self._stubs["count_message_tokens"] = self._logged_channel.unary_unary(
+                "/google.ai.generativelanguage.v1beta3.DiscussService/CountMessageTokens",
+                request_serializer=discuss_service.CountMessageTokensRequest.serialize,
+                response_deserializer=discuss_service.CountMessageTokensResponse.deserialize,
+            )
+        return self._stubs["count_message_tokens"]
+
+    def _prep_wrapped_messages(self, client_info):
+        """Precompute the wrapped methods, overriding the base class method to use async wrappers."""
+        self._wrapped_methods = {
+            self.generate_message: self._wrap_method(
+                self.generate_message,
+                default_timeout=None,
+                client_info=client_info,
+            ),
+            self.count_message_tokens: self._wrap_method(
+                self.count_message_tokens,
+                default_timeout=None,
+                client_info=client_info,
+            ),
+        }
+
+    def _wrap_method(self, func, *args, **kwargs):
+        if self._wrap_with_kind:  # pragma: NO COVER
+            kwargs["kind"] = self.kind
+        return gapic_v1.method_async.wrap_method(func, *args, **kwargs)
+
+    def close(self):
+        return self._logged_channel.close()
+
+    @property
+    def kind(self) -> str:
+        return "grpc_asyncio"
+
+
+__all__ = ("DiscussServiceGrpcAsyncIOTransport",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/rest.py

@@ -0,0 +1,579 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import dataclasses
+import json  # type: ignore
+import logging
+from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
+import warnings
+
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1, rest_helpers, rest_streaming
+from google.api_core import retry as retries
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.auth.transport.requests import AuthorizedSession  # type: ignore
+from google.longrunning import operations_pb2  # type: ignore
+from google.protobuf import json_format
+from requests import __version__ as requests_version
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service
+
+from .base import DEFAULT_CLIENT_INFO as BASE_DEFAULT_CLIENT_INFO
+from .rest_base import _BaseDiscussServiceRestTransport
+
+try:
+    OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None]
+except AttributeError:  # pragma: NO COVER
+    OptionalRetry = Union[retries.Retry, object, None]  # type: ignore
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = logging.getLogger(__name__)
+
+DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
+    gapic_version=BASE_DEFAULT_CLIENT_INFO.gapic_version,
+    grpc_version=None,
+    rest_version=f"requests@{requests_version}",
+)
+
+
+class DiscussServiceRestInterceptor:
+    """Interceptor for DiscussService.
+
+    Interceptors are used to manipulate requests, request metadata, and responses
+    in arbitrary ways.
+    Example use cases include:
+    * Logging
+    * Verifying requests according to service or custom semantics
+    * Stripping extraneous information from responses
+
+    These use cases and more can be enabled by injecting an
+    instance of a custom subclass when constructing the DiscussServiceRestTransport.
+
+    .. code-block:: python
+        class MyCustomDiscussServiceInterceptor(DiscussServiceRestInterceptor):
+            def pre_count_message_tokens(self, request, metadata):
+                logging.log(f"Received request: {request}")
+                return request, metadata
+
+            def post_count_message_tokens(self, response):
+                logging.log(f"Received response: {response}")
+                return response
+
+            def pre_generate_message(self, request, metadata):
+                logging.log(f"Received request: {request}")
+                return request, metadata
+
+            def post_generate_message(self, response):
+                logging.log(f"Received response: {response}")
+                return response
+
+        transport = DiscussServiceRestTransport(interceptor=MyCustomDiscussServiceInterceptor())
+        client = DiscussServiceClient(transport=transport)
+
+
+    """
+
+    def pre_count_message_tokens(
+        self,
+        request: discuss_service.CountMessageTokensRequest,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]],
+    ) -> Tuple[
+        discuss_service.CountMessageTokensRequest,
+        Sequence[Tuple[str, Union[str, bytes]]],
+    ]:
+        """Pre-rpc interceptor for count_message_tokens
+
+        Override in a subclass to manipulate the request or metadata
+        before they are sent to the DiscussService server.
+        """
+        return request, metadata
+
+    def post_count_message_tokens(
+        self, response: discuss_service.CountMessageTokensResponse
+    ) -> discuss_service.CountMessageTokensResponse:
+        """Post-rpc interceptor for count_message_tokens
+
+        Override in a subclass to manipulate the response
+        after it is returned by the DiscussService server but before
+        it is returned to user code.
+        """
+        return response
+
+    def pre_generate_message(
+        self,
+        request: discuss_service.GenerateMessageRequest,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]],
+    ) -> Tuple[
+        discuss_service.GenerateMessageRequest, Sequence[Tuple[str, Union[str, bytes]]]
+    ]:
+        """Pre-rpc interceptor for generate_message
+
+        Override in a subclass to manipulate the request or metadata
+        before they are sent to the DiscussService server.
+        """
+        return request, metadata
+
+    def post_generate_message(
+        self, response: discuss_service.GenerateMessageResponse
+    ) -> discuss_service.GenerateMessageResponse:
+        """Post-rpc interceptor for generate_message
+
+        Override in a subclass to manipulate the response
+        after it is returned by the DiscussService server but before
+        it is returned to user code.
+        """
+        return response
+
+
+@dataclasses.dataclass
+class DiscussServiceRestStub:
+    _session: AuthorizedSession
+    _host: str
+    _interceptor: DiscussServiceRestInterceptor
+
+
+class DiscussServiceRestTransport(_BaseDiscussServiceRestTransport):
+    """REST backend synchronous transport for DiscussService.
+
+    An API for using Generative Language Models (GLMs) in dialog
+    applications.
+    Also known as large language models (LLMs), this API provides
+    models that are trained for multi-turn dialog.
+
+    This class defines the same methods as the primary client, so the
+    primary client can load the underlying transport implementation
+    and call it.
+
+    It sends JSON representations of protocol buffers over HTTP/1.1
+    """
+
+    def __init__(
+        self,
+        *,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[ga_credentials.Credentials] = None,
+        credentials_file: Optional[str] = None,
+        scopes: Optional[Sequence[str]] = None,
+        client_cert_source_for_mtls: Optional[Callable[[], Tuple[bytes, bytes]]] = None,
+        quota_project_id: Optional[str] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+        always_use_jwt_access: Optional[bool] = False,
+        url_scheme: str = "https",
+        interceptor: Optional[DiscussServiceRestInterceptor] = None,
+        api_audience: Optional[str] = None,
+    ) -> None:
+        """Instantiate the transport.
+
+        Args:
+            host (Optional[str]):
+                 The hostname to connect to (default: 'generativelanguage.googleapis.com').
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+
+            credentials_file (Optional[str]): A file with credentials that can
+                be loaded with :func:`google.auth.load_credentials_from_file`.
+                This argument is ignored if ``channel`` is provided.
+            scopes (Optional(Sequence[str])): A list of scopes. This argument is
+                ignored if ``channel`` is provided.
+            client_cert_source_for_mtls (Callable[[], Tuple[bytes, bytes]]): Client
+                certificate to configure mutual TLS HTTP channel. It is ignored
+                if ``channel`` is provided.
+            quota_project_id (Optional[str]): An optional project to use for billing
+                and quota.
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you are developing
+                your own client library.
+            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
+                be used for service account credentials.
+            url_scheme: the protocol scheme for the API endpoint.  Normally
+                "https", but for testing or local servers,
+                "http" can be specified.
+        """
+        # Run the base constructor
+        # TODO(yon-mg): resolve other ctor params i.e. scopes, quota, etc.
+        # TODO: When custom host (api_endpoint) is set, `scopes` must *also* be set on the
+        # credentials object
+        super().__init__(
+            host=host,
+            credentials=credentials,
+            client_info=client_info,
+            always_use_jwt_access=always_use_jwt_access,
+            url_scheme=url_scheme,
+            api_audience=api_audience,
+        )
+        self._session = AuthorizedSession(
+            self._credentials, default_host=self.DEFAULT_HOST
+        )
+        if client_cert_source_for_mtls:
+            self._session.configure_mtls_channel(client_cert_source_for_mtls)
+        self._interceptor = interceptor or DiscussServiceRestInterceptor()
+        self._prep_wrapped_messages(client_info)
+
+    class _CountMessageTokens(
+        _BaseDiscussServiceRestTransport._BaseCountMessageTokens, DiscussServiceRestStub
+    ):
+        def __hash__(self):
+            return hash("DiscussServiceRestTransport.CountMessageTokens")
+
+        @staticmethod
+        def _get_response(
+            host,
+            metadata,
+            query_params,
+            session,
+            timeout,
+            transcoded_request,
+            body=None,
+        ):
+            uri = transcoded_request["uri"]
+            method = transcoded_request["method"]
+            headers = dict(metadata)
+            headers["Content-Type"] = "application/json"
+            response = getattr(session, method)(
+                "{host}{uri}".format(host=host, uri=uri),
+                timeout=timeout,
+                headers=headers,
+                params=rest_helpers.flatten_query_params(query_params, strict=True),
+                data=body,
+            )
+            return response
+
+        def __call__(
+            self,
+            request: discuss_service.CountMessageTokensRequest,
+            *,
+            retry: OptionalRetry = gapic_v1.method.DEFAULT,
+            timeout: Optional[float] = None,
+            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+        ) -> discuss_service.CountMessageTokensResponse:
+            r"""Call the count message tokens method over HTTP.
+
+            Args:
+                request (~.discuss_service.CountMessageTokensRequest):
+                    The request object. Counts the number of tokens in the ``prompt`` sent to a
+                model.
+
+                Models may tokenize text differently, so each model may
+                return a different ``token_count``.
+                retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                    should be retried.
+                timeout (float): The timeout for this request.
+                metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                    sent along with the request as metadata. Normally, each value must be of type `str`,
+                    but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                    be of type `bytes`.
+
+            Returns:
+                ~.discuss_service.CountMessageTokensResponse:
+                    A response from ``CountMessageTokens``.
+
+                It returns the model's ``token_count`` for the
+                ``prompt``.
+
+            """
+
+            http_options = (
+                _BaseDiscussServiceRestTransport._BaseCountMessageTokens._get_http_options()
+            )
+
+            request, metadata = self._interceptor.pre_count_message_tokens(
+                request, metadata
+            )
+            transcoded_request = _BaseDiscussServiceRestTransport._BaseCountMessageTokens._get_transcoded_request(
+                http_options, request
+            )
+
+            body = _BaseDiscussServiceRestTransport._BaseCountMessageTokens._get_request_body_json(
+                transcoded_request
+            )
+
+            # Jsonify the query params
+            query_params = _BaseDiscussServiceRestTransport._BaseCountMessageTokens._get_query_params_json(
+                transcoded_request
+            )
+
+            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+                logging.DEBUG
+            ):  # pragma: NO COVER
+                request_url = "{host}{uri}".format(
+                    host=self._host, uri=transcoded_request["uri"]
+                )
+                method = transcoded_request["method"]
+                try:
+                    request_payload = type(request).to_json(request)
+                except:
+                    request_payload = None
+                http_request = {
+                    "payload": request_payload,
+                    "requestMethod": method,
+                    "requestUrl": request_url,
+                    "headers": dict(metadata),
+                }
+                _LOGGER.debug(
+                    f"Sending request for google.ai.generativelanguage_v1beta3.DiscussServiceClient.CountMessageTokens",
+                    extra={
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "rpcName": "CountMessageTokens",
+                        "httpRequest": http_request,
+                        "metadata": http_request["headers"],
+                    },
+                )
+
+            # Send the request
+            response = DiscussServiceRestTransport._CountMessageTokens._get_response(
+                self._host,
+                metadata,
+                query_params,
+                self._session,
+                timeout,
+                transcoded_request,
+                body,
+            )
+
+            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
+            # subclass.
+            if response.status_code >= 400:
+                raise core_exceptions.from_http_response(response)
+
+            # Return the response
+            resp = discuss_service.CountMessageTokensResponse()
+            pb_resp = discuss_service.CountMessageTokensResponse.pb(resp)
+
+            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)
+
+            resp = self._interceptor.post_count_message_tokens(resp)
+            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+                logging.DEBUG
+            ):  # pragma: NO COVER
+                try:
+                    response_payload = (
+                        discuss_service.CountMessageTokensResponse.to_json(response)
+                    )
+                except:
+                    response_payload = None
+                http_response = {
+                    "payload": response_payload,
+                    "headers": dict(response.headers),
+                    "status": response.status_code,
+                }
+                _LOGGER.debug(
+                    "Received response for google.ai.generativelanguage_v1beta3.DiscussServiceClient.count_message_tokens",
+                    extra={
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "rpcName": "CountMessageTokens",
+                        "metadata": http_response["headers"],
+                        "httpResponse": http_response,
+                    },
+                )
+            return resp
+
+    class _GenerateMessage(
+        _BaseDiscussServiceRestTransport._BaseGenerateMessage, DiscussServiceRestStub
+    ):
+        def __hash__(self):
+            return hash("DiscussServiceRestTransport.GenerateMessage")
+
+        @staticmethod
+        def _get_response(
+            host,
+            metadata,
+            query_params,
+            session,
+            timeout,
+            transcoded_request,
+            body=None,
+        ):
+            uri = transcoded_request["uri"]
+            method = transcoded_request["method"]
+            headers = dict(metadata)
+            headers["Content-Type"] = "application/json"
+            response = getattr(session, method)(
+                "{host}{uri}".format(host=host, uri=uri),
+                timeout=timeout,
+                headers=headers,
+                params=rest_helpers.flatten_query_params(query_params, strict=True),
+                data=body,
+            )
+            return response
+
+        def __call__(
+            self,
+            request: discuss_service.GenerateMessageRequest,
+            *,
+            retry: OptionalRetry = gapic_v1.method.DEFAULT,
+            timeout: Optional[float] = None,
+            metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+        ) -> discuss_service.GenerateMessageResponse:
+            r"""Call the generate message method over HTTP.
+
+            Args:
+                request (~.discuss_service.GenerateMessageRequest):
+                    The request object. Request to generate a message
+                response from the model.
+                retry (google.api_core.retry.Retry): Designation of what errors, if any,
+                    should be retried.
+                timeout (float): The timeout for this request.
+                metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                    sent along with the request as metadata. Normally, each value must be of type `str`,
+                    but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                    be of type `bytes`.
+
+            Returns:
+                ~.discuss_service.GenerateMessageResponse:
+                    The response from the model.
+
+                This includes candidate messages and
+                conversation history in the form of
+                chronologically-ordered messages.
+
+            """
+
+            http_options = (
+                _BaseDiscussServiceRestTransport._BaseGenerateMessage._get_http_options()
+            )
+
+            request, metadata = self._interceptor.pre_generate_message(
+                request, metadata
+            )
+            transcoded_request = _BaseDiscussServiceRestTransport._BaseGenerateMessage._get_transcoded_request(
+                http_options, request
+            )
+
+            body = _BaseDiscussServiceRestTransport._BaseGenerateMessage._get_request_body_json(
+                transcoded_request
+            )
+
+            # Jsonify the query params
+            query_params = _BaseDiscussServiceRestTransport._BaseGenerateMessage._get_query_params_json(
+                transcoded_request
+            )
+
+            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+                logging.DEBUG
+            ):  # pragma: NO COVER
+                request_url = "{host}{uri}".format(
+                    host=self._host, uri=transcoded_request["uri"]
+                )
+                method = transcoded_request["method"]
+                try:
+                    request_payload = type(request).to_json(request)
+                except:
+                    request_payload = None
+                http_request = {
+                    "payload": request_payload,
+                    "requestMethod": method,
+                    "requestUrl": request_url,
+                    "headers": dict(metadata),
+                }
+                _LOGGER.debug(
+                    f"Sending request for google.ai.generativelanguage_v1beta3.DiscussServiceClient.GenerateMessage",
+                    extra={
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "rpcName": "GenerateMessage",
+                        "httpRequest": http_request,
+                        "metadata": http_request["headers"],
+                    },
+                )
+
+            # Send the request
+            response = DiscussServiceRestTransport._GenerateMessage._get_response(
+                self._host,
+                metadata,
+                query_params,
+                self._session,
+                timeout,
+                transcoded_request,
+                body,
+            )
+
+            # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception
+            # subclass.
+            if response.status_code >= 400:
+                raise core_exceptions.from_http_response(response)
+
+            # Return the response
+            resp = discuss_service.GenerateMessageResponse()
+            pb_resp = discuss_service.GenerateMessageResponse.pb(resp)
+
+            json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)
+
+            resp = self._interceptor.post_generate_message(resp)
+            if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+                logging.DEBUG
+            ):  # pragma: NO COVER
+                try:
+                    response_payload = discuss_service.GenerateMessageResponse.to_json(
+                        response
+                    )
+                except:
+                    response_payload = None
+                http_response = {
+                    "payload": response_payload,
+                    "headers": dict(response.headers),
+                    "status": response.status_code,
+                }
+                _LOGGER.debug(
+                    "Received response for google.ai.generativelanguage_v1beta3.DiscussServiceClient.generate_message",
+                    extra={
+                        "serviceName": "google.ai.generativelanguage.v1beta3.DiscussService",
+                        "rpcName": "GenerateMessage",
+                        "metadata": http_response["headers"],
+                        "httpResponse": http_response,
+                    },
+                )
+            return resp
+
+    @property
+    def count_message_tokens(
+        self,
+    ) -> Callable[
+        [discuss_service.CountMessageTokensRequest],
+        discuss_service.CountMessageTokensResponse,
+    ]:
+        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
+        # In C++ this would require a dynamic_cast
+        return self._CountMessageTokens(self._session, self._host, self._interceptor)  # type: ignore
+
+    @property
+    def generate_message(
+        self,
+    ) -> Callable[
+        [discuss_service.GenerateMessageRequest],
+        discuss_service.GenerateMessageResponse,
+    ]:
+        # The return type is fine, but mypy isn't sophisticated enough to determine what's going on here.
+        # In C++ this would require a dynamic_cast
+        return self._GenerateMessage(self._session, self._host, self._interceptor)  # type: ignore
+
+    @property
+    def kind(self) -> str:
+        return "rest"
+
+    def close(self):
+        self._session.close()
+
+
+__all__ = ("DiscussServiceRestTransport",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/discuss_service/transports/rest_base.py

@@ -0,0 +1,206 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+import json  # type: ignore
+import re
+from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
+
+from google.api_core import gapic_v1, path_template
+from google.longrunning import operations_pb2  # type: ignore
+from google.protobuf import json_format
+
+from google.ai.generativelanguage_v1beta3.types import discuss_service
+
+from .base import DEFAULT_CLIENT_INFO, DiscussServiceTransport
+
+
+class _BaseDiscussServiceRestTransport(DiscussServiceTransport):
+    """Base REST backend transport for DiscussService.
+
+    Note: This class is not meant to be used directly. Use its sync and
+    async sub-classes instead.
+
+    This class defines the same methods as the primary client, so the
+    primary client can load the underlying transport implementation
+    and call it.
+
+    It sends JSON representations of protocol buffers over HTTP/1.1
+    """
+
+    def __init__(
+        self,
+        *,
+        host: str = "generativelanguage.googleapis.com",
+        credentials: Optional[Any] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+        always_use_jwt_access: Optional[bool] = False,
+        url_scheme: str = "https",
+        api_audience: Optional[str] = None,
+    ) -> None:
+        """Instantiate the transport.
+        Args:
+            host (Optional[str]):
+                 The hostname to connect to (default: 'generativelanguage.googleapis.com').
+            credentials (Optional[Any]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you are developing
+                your own client library.
+            always_use_jwt_access (Optional[bool]): Whether self signed JWT should
+                be used for service account credentials.
+            url_scheme: the protocol scheme for the API endpoint.  Normally
+                "https", but for testing or local servers,
+                "http" can be specified.
+        """
+        # Run the base constructor
+        maybe_url_match = re.match("^(?P<scheme>http(?:s)?://)?(?P<host>.*)$", host)
+        if maybe_url_match is None:
+            raise ValueError(
+                f"Unexpected hostname structure: {host}"
+            )  # pragma: NO COVER
+
+        url_match_items = maybe_url_match.groupdict()
+
+        host = f"{url_scheme}://{host}" if not url_match_items["scheme"] else host
+
+        super().__init__(
+            host=host,
+            credentials=credentials,
+            client_info=client_info,
+            always_use_jwt_access=always_use_jwt_access,
+            api_audience=api_audience,
+        )
+
+    class _BaseCountMessageTokens:
+        def __hash__(self):  # pragma: NO COVER
+            return NotImplementedError("__hash__ must be implemented.")
+
+        __REQUIRED_FIELDS_DEFAULT_VALUES: Dict[str, Any] = {}
+
+        @classmethod
+        def _get_unset_required_fields(cls, message_dict):
+            return {
+                k: v
+                for k, v in cls.__REQUIRED_FIELDS_DEFAULT_VALUES.items()
+                if k not in message_dict
+            }
+
+        @staticmethod
+        def _get_http_options():
+            http_options: List[Dict[str, str]] = [
+                {
+                    "method": "post",
+                    "uri": "/v1beta3/{model=models/*}:countMessageTokens",
+                    "body": "*",
+                },
+            ]
+            return http_options
+
+        @staticmethod
+        def _get_transcoded_request(http_options, request):
+            pb_request = discuss_service.CountMessageTokensRequest.pb(request)
+            transcoded_request = path_template.transcode(http_options, pb_request)
+            return transcoded_request
+
+        @staticmethod
+        def _get_request_body_json(transcoded_request):
+            # Jsonify the request body
+
+            body = json_format.MessageToJson(
+                transcoded_request["body"], use_integers_for_enums=True
+            )
+            return body
+
+        @staticmethod
+        def _get_query_params_json(transcoded_request):
+            query_params = json.loads(
+                json_format.MessageToJson(
+                    transcoded_request["query_params"],
+                    use_integers_for_enums=True,
+                )
+            )
+            query_params.update(
+                _BaseDiscussServiceRestTransport._BaseCountMessageTokens._get_unset_required_fields(
+                    query_params
+                )
+            )
+
+            query_params["$alt"] = "json;enum-encoding=int"
+            return query_params
+
+    class _BaseGenerateMessage:
+        def __hash__(self):  # pragma: NO COVER
+            return NotImplementedError("__hash__ must be implemented.")
+
+        __REQUIRED_FIELDS_DEFAULT_VALUES: Dict[str, Any] = {}
+
+        @classmethod
+        def _get_unset_required_fields(cls, message_dict):
+            return {
+                k: v
+                for k, v in cls.__REQUIRED_FIELDS_DEFAULT_VALUES.items()
+                if k not in message_dict
+            }
+
+        @staticmethod
+        def _get_http_options():
+            http_options: List[Dict[str, str]] = [
+                {
+                    "method": "post",
+                    "uri": "/v1beta3/{model=models/*}:generateMessage",
+                    "body": "*",
+                },
+            ]
+            return http_options
+
+        @staticmethod
+        def _get_transcoded_request(http_options, request):
+            pb_request = discuss_service.GenerateMessageRequest.pb(request)
+            transcoded_request = path_template.transcode(http_options, pb_request)
+            return transcoded_request
+
+        @staticmethod
+        def _get_request_body_json(transcoded_request):
+            # Jsonify the request body
+
+            body = json_format.MessageToJson(
+                transcoded_request["body"], use_integers_for_enums=True
+            )
+            return body
+
+        @staticmethod
+        def _get_query_params_json(transcoded_request):
+            query_params = json.loads(
+                json_format.MessageToJson(
+                    transcoded_request["query_params"],
+                    use_integers_for_enums=True,
+                )
+            )
+            query_params.update(
+                _BaseDiscussServiceRestTransport._BaseGenerateMessage._get_unset_required_fields(
+                    query_params
+                )
+            )
+
+            query_params["$alt"] = "json;enum-encoding=int"
+            return query_params
+
+
+__all__ = ("_BaseDiscussServiceRestTransport",)

.venv/lib/python3.11/site-packages/google/ai/generativelanguage_v1beta3/services/model_service/async_client.py

@@ -0,0 +1,1156 @@
+# -*- coding: utf-8 -*-
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+from collections import OrderedDict
+import logging as std_logging
+import re
+from typing import (
+    Callable,
+    Dict,
+    Mapping,
+    MutableMapping,
+    MutableSequence,
+    Optional,
+    Sequence,
+    Tuple,
+    Type,
+    Union,
+)
+
+from google.api_core import exceptions as core_exceptions
+from google.api_core import gapic_v1
+from google.api_core import retry_async as retries
+from google.api_core.client_options import ClientOptions
+from google.auth import credentials as ga_credentials  # type: ignore
+from google.oauth2 import service_account  # type: ignore
+
+from google.ai.generativelanguage_v1beta3 import gapic_version as package_version
+
+try:
+    OptionalRetry = Union[retries.AsyncRetry, gapic_v1.method._MethodDefault, None]
+except AttributeError:  # pragma: NO COVER
+    OptionalRetry = Union[retries.AsyncRetry, object, None]  # type: ignore
+
+from google.api_core import operation  # type: ignore
+from google.api_core import operation_async  # type: ignore
+from google.longrunning import operations_pb2  # type: ignore
+from google.protobuf import field_mask_pb2  # type: ignore
+from google.protobuf import timestamp_pb2  # type: ignore
+
+from google.ai.generativelanguage_v1beta3.services.model_service import pagers
+from google.ai.generativelanguage_v1beta3.types import tuned_model as gag_tuned_model
+from google.ai.generativelanguage_v1beta3.types import model, model_service
+from google.ai.generativelanguage_v1beta3.types import tuned_model
+
+from .client import ModelServiceClient
+from .transports.base import DEFAULT_CLIENT_INFO, ModelServiceTransport
+from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport
+
+try:
+    from google.api_core import client_logging  # type: ignore
+
+    CLIENT_LOGGING_SUPPORTED = True  # pragma: NO COVER
+except ImportError:  # pragma: NO COVER
+    CLIENT_LOGGING_SUPPORTED = False
+
+_LOGGER = std_logging.getLogger(__name__)
+
+
+class ModelServiceAsyncClient:
+    """Provides methods for getting metadata information about
+    Generative Models.
+    """
+
+    _client: ModelServiceClient
+
+    # Copy defaults from the synchronous client for use here.
+    # Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
+    DEFAULT_ENDPOINT = ModelServiceClient.DEFAULT_ENDPOINT
+    DEFAULT_MTLS_ENDPOINT = ModelServiceClient.DEFAULT_MTLS_ENDPOINT
+    _DEFAULT_ENDPOINT_TEMPLATE = ModelServiceClient._DEFAULT_ENDPOINT_TEMPLATE
+    _DEFAULT_UNIVERSE = ModelServiceClient._DEFAULT_UNIVERSE
+
+    model_path = staticmethod(ModelServiceClient.model_path)
+    parse_model_path = staticmethod(ModelServiceClient.parse_model_path)
+    tuned_model_path = staticmethod(ModelServiceClient.tuned_model_path)
+    parse_tuned_model_path = staticmethod(ModelServiceClient.parse_tuned_model_path)
+    common_billing_account_path = staticmethod(
+        ModelServiceClient.common_billing_account_path
+    )
+    parse_common_billing_account_path = staticmethod(
+        ModelServiceClient.parse_common_billing_account_path
+    )
+    common_folder_path = staticmethod(ModelServiceClient.common_folder_path)
+    parse_common_folder_path = staticmethod(ModelServiceClient.parse_common_folder_path)
+    common_organization_path = staticmethod(ModelServiceClient.common_organization_path)
+    parse_common_organization_path = staticmethod(
+        ModelServiceClient.parse_common_organization_path
+    )
+    common_project_path = staticmethod(ModelServiceClient.common_project_path)
+    parse_common_project_path = staticmethod(
+        ModelServiceClient.parse_common_project_path
+    )
+    common_location_path = staticmethod(ModelServiceClient.common_location_path)
+    parse_common_location_path = staticmethod(
+        ModelServiceClient.parse_common_location_path
+    )
+
+    @classmethod
+    def from_service_account_info(cls, info: dict, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            info.
+
+        Args:
+            info (dict): The service account private key info.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            ModelServiceAsyncClient: The constructed client.
+        """
+        return ModelServiceClient.from_service_account_info.__func__(ModelServiceAsyncClient, info, *args, **kwargs)  # type: ignore
+
+    @classmethod
+    def from_service_account_file(cls, filename: str, *args, **kwargs):
+        """Creates an instance of this client using the provided credentials
+            file.
+
+        Args:
+            filename (str): The path to the service account private key json
+                file.
+            args: Additional arguments to pass to the constructor.
+            kwargs: Additional arguments to pass to the constructor.
+
+        Returns:
+            ModelServiceAsyncClient: The constructed client.
+        """
+        return ModelServiceClient.from_service_account_file.__func__(ModelServiceAsyncClient, filename, *args, **kwargs)  # type: ignore
+
+    from_service_account_json = from_service_account_file
+
+    @classmethod
+    def get_mtls_endpoint_and_cert_source(
+        cls, client_options: Optional[ClientOptions] = None
+    ):
+        """Return the API endpoint and client cert source for mutual TLS.
+
+        The client cert source is determined in the following order:
+        (1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
+        client cert source is None.
+        (2) if `client_options.client_cert_source` is provided, use the provided one; if the
+        default client cert source exists, use the default one; otherwise the client cert
+        source is None.
+
+        The API endpoint is determined in the following order:
+        (1) if `client_options.api_endpoint` if provided, use the provided one.
+        (2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
+        default mTLS endpoint; if the environment variable is "never", use the default API
+        endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
+        use the default API endpoint.
+
+        More details can be found at https://google.aip.dev/auth/4114.
+
+        Args:
+            client_options (google.api_core.client_options.ClientOptions): Custom options for the
+                client. Only the `api_endpoint` and `client_cert_source` properties may be used
+                in this method.
+
+        Returns:
+            Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
+                client cert source to use.
+
+        Raises:
+            google.auth.exceptions.MutualTLSChannelError: If any errors happen.
+        """
+        return ModelServiceClient.get_mtls_endpoint_and_cert_source(client_options)  # type: ignore
+
+    @property
+    def transport(self) -> ModelServiceTransport:
+        """Returns the transport used by the client instance.
+
+        Returns:
+            ModelServiceTransport: The transport used by the client instance.
+        """
+        return self._client.transport
+
+    @property
+    def api_endpoint(self):
+        """Return the API endpoint used by the client instance.
+
+        Returns:
+            str: The API endpoint used by the client instance.
+        """
+        return self._client._api_endpoint
+
+    @property
+    def universe_domain(self) -> str:
+        """Return the universe domain used by the client instance.
+
+        Returns:
+            str: The universe domain used
+                by the client instance.
+        """
+        return self._client._universe_domain
+
+    get_transport_class = ModelServiceClient.get_transport_class
+
+    def __init__(
+        self,
+        *,
+        credentials: Optional[ga_credentials.Credentials] = None,
+        transport: Optional[
+            Union[str, ModelServiceTransport, Callable[..., ModelServiceTransport]]
+        ] = "grpc_asyncio",
+        client_options: Optional[ClientOptions] = None,
+        client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
+    ) -> None:
+        """Instantiates the model service async client.
+
+        Args:
+            credentials (Optional[google.auth.credentials.Credentials]): The
+                authorization credentials to attach to requests. These
+                credentials identify the application to the service; if none
+                are specified, the client will attempt to ascertain the
+                credentials from the environment.
+            transport (Optional[Union[str,ModelServiceTransport,Callable[..., ModelServiceTransport]]]):
+                The transport to use, or a Callable that constructs and returns a new transport to use.
+                If a Callable is given, it will be called with the same set of initialization
+                arguments as used in the ModelServiceTransport constructor.
+                If set to None, a transport is chosen automatically.
+            client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
+                Custom options for the client.
+
+                1. The ``api_endpoint`` property can be used to override the
+                default endpoint provided by the client when ``transport`` is
+                not explicitly provided. Only if this property is not set and
+                ``transport`` was not explicitly provided, the endpoint is
+                determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
+                variable, which have one of the following values:
+                "always" (always use the default mTLS endpoint), "never" (always
+                use the default regular endpoint) and "auto" (auto-switch to the
+                default mTLS endpoint if client certificate is present; this is
+                the default value).
+
+                2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
+                is "true", then the ``client_cert_source`` property can be used
+                to provide a client certificate for mTLS transport. If
+                not provided, the default SSL client certificate will be used if
+                present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
+                set, no client certificate will be used.
+
+                3. The ``universe_domain`` property can be used to override the
+                default "googleapis.com" universe. Note that ``api_endpoint``
+                property still takes precedence; and ``universe_domain`` is
+                currently not supported for mTLS.
+
+            client_info (google.api_core.gapic_v1.client_info.ClientInfo):
+                The client info used to send a user-agent string along with
+                API requests. If ``None``, then default info will be used.
+                Generally, you only need to set this if you're developing
+                your own client library.
+
+        Raises:
+            google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport
+                creation failed for any reason.
+        """
+        self._client = ModelServiceClient(
+            credentials=credentials,
+            transport=transport,
+            client_options=client_options,
+            client_info=client_info,
+        )
+
+        if CLIENT_LOGGING_SUPPORTED and _LOGGER.isEnabledFor(
+            std_logging.DEBUG
+        ):  # pragma: NO COVER
+            _LOGGER.debug(
+                "Created client `google.ai.generativelanguage_v1beta3.ModelServiceAsyncClient`.",
+                extra={
+                    "serviceName": "google.ai.generativelanguage.v1beta3.ModelService",
+                    "universeDomain": getattr(
+                        self._client._transport._credentials, "universe_domain", ""
+                    ),
+                    "credentialsType": f"{type(self._client._transport._credentials).__module__}.{type(self._client._transport._credentials).__qualname__}",
+                    "credentialsInfo": getattr(
+                        self.transport._credentials, "get_cred_info", lambda: None
+                    )(),
+                }
+                if hasattr(self._client._transport, "_credentials")
+                else {
+                    "serviceName": "google.ai.generativelanguage.v1beta3.ModelService",
+                    "credentialsType": None,
+                },
+            )
+
+    async def get_model(
+        self,
+        request: Optional[Union[model_service.GetModelRequest, dict]] = None,
+        *,
+        name: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> model.Model:
+        r"""Gets information about a specific Model.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_get_model():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = generativelanguage_v1beta3.GetModelRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                response = await client.get_model(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.GetModelRequest, dict]]):
+                The request object. Request for getting information about
+                a specific Model.
+            name (:class:`str`):
+                Required. The resource name of the model.
+
+                This name should match a model name returned by the
+                ``ListModels`` method.
+
+                Format: ``models/{model}``
+
+                This corresponds to the ``name`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.Model:
+                Information about a Generative
+                Language Model.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([name])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.GetModelRequest):
+            request = model_service.GetModelRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if name is not None:
+            request.name = name
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.get_model
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def list_models(
+        self,
+        request: Optional[Union[model_service.ListModelsRequest, dict]] = None,
+        *,
+        page_size: Optional[int] = None,
+        page_token: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> pagers.ListModelsAsyncPager:
+        r"""Lists models available through the API.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_list_models():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = generativelanguage_v1beta3.ListModelsRequest(
+                )
+
+                # Make the request
+                page_result = client.list_models(request=request)
+
+                # Handle the response
+                async for response in page_result:
+                    print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.ListModelsRequest, dict]]):
+                The request object. Request for listing all Models.
+            page_size (:class:`int`):
+                The maximum number of ``Models`` to return (per page).
+
+                The service may return fewer models. If unspecified, at
+                most 50 models will be returned per page. This method
+                returns at most 1000 models per page, even if you pass a
+                larger page_size.
+
+                This corresponds to the ``page_size`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            page_token (:class:`str`):
+                A page token, received from a previous ``ListModels``
+                call.
+
+                Provide the ``page_token`` returned by one request as an
+                argument to the next request to retrieve the next page.
+
+                When paginating, all other parameters provided to
+                ``ListModels`` must match the call that provided the
+                page token.
+
+                This corresponds to the ``page_token`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.services.model_service.pagers.ListModelsAsyncPager:
+                Response from ListModel containing a paginated list of
+                Models.
+
+                Iterating over this object will yield results and
+                resolve additional pages automatically.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([page_size, page_token])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.ListModelsRequest):
+            request = model_service.ListModelsRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if page_size is not None:
+            request.page_size = page_size
+        if page_token is not None:
+            request.page_token = page_token
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.list_models
+        ]
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # This method is paged; wrap the response in a pager, which provides
+        # an `__aiter__` convenience method.
+        response = pagers.ListModelsAsyncPager(
+            method=rpc,
+            request=request,
+            response=response,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def get_tuned_model(
+        self,
+        request: Optional[Union[model_service.GetTunedModelRequest, dict]] = None,
+        *,
+        name: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> tuned_model.TunedModel:
+        r"""Gets information about a specific TunedModel.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_get_tuned_model():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = generativelanguage_v1beta3.GetTunedModelRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                response = await client.get_tuned_model(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.GetTunedModelRequest, dict]]):
+                The request object. Request for getting information about
+                a specific Model.
+            name (:class:`str`):
+                Required. The resource name of the model.
+
+                Format: ``tunedModels/my-model-id``
+
+                This corresponds to the ``name`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.TunedModel:
+                A fine-tuned model created using
+                ModelService.CreateTunedModel.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([name])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.GetTunedModelRequest):
+            request = model_service.GetTunedModelRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if name is not None:
+            request.name = name
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.get_tuned_model
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def list_tuned_models(
+        self,
+        request: Optional[Union[model_service.ListTunedModelsRequest, dict]] = None,
+        *,
+        page_size: Optional[int] = None,
+        page_token: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> pagers.ListTunedModelsAsyncPager:
+        r"""Lists tuned models owned by the user.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_list_tuned_models():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = generativelanguage_v1beta3.ListTunedModelsRequest(
+                )
+
+                # Make the request
+                page_result = client.list_tuned_models(request=request)
+
+                # Handle the response
+                async for response in page_result:
+                    print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.ListTunedModelsRequest, dict]]):
+                The request object. Request for listing TunedModels.
+            page_size (:class:`int`):
+                Optional. The maximum number of ``TunedModels`` to
+                return (per page). The service may return fewer tuned
+                models.
+
+                If unspecified, at most 10 tuned models will be
+                returned. This method returns at most 1000 models per
+                page, even if you pass a larger page_size.
+
+                This corresponds to the ``page_size`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            page_token (:class:`str`):
+                Optional. A page token, received from a previous
+                ``ListTunedModels`` call.
+
+                Provide the ``page_token`` returned by one request as an
+                argument to the next request to retrieve the next page.
+
+                When paginating, all other parameters provided to
+                ``ListTunedModels`` must match the call that provided
+                the page token.
+
+                This corresponds to the ``page_token`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.services.model_service.pagers.ListTunedModelsAsyncPager:
+                Response from ListTunedModels containing a paginated
+                list of Models.
+
+                Iterating over this object will yield results and
+                resolve additional pages automatically.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([page_size, page_token])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.ListTunedModelsRequest):
+            request = model_service.ListTunedModelsRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if page_size is not None:
+            request.page_size = page_size
+        if page_token is not None:
+            request.page_token = page_token
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.list_tuned_models
+        ]
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # This method is paged; wrap the response in a pager, which provides
+        # an `__aiter__` convenience method.
+        response = pagers.ListTunedModelsAsyncPager(
+            method=rpc,
+            request=request,
+            response=response,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def create_tuned_model(
+        self,
+        request: Optional[Union[model_service.CreateTunedModelRequest, dict]] = None,
+        *,
+        tuned_model: Optional[gag_tuned_model.TunedModel] = None,
+        tuned_model_id: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> operation_async.AsyncOperation:
+        r"""Creates a tuned model. Intermediate tuning progress (if any) is
+        accessed through the [google.longrunning.Operations] service.
+
+        Status and results can be accessed through the Operations
+        service. Example: GET
+        /v1/tunedModels/az2mb0bpw6i/operations/000-111-222
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_create_tuned_model():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                tuned_model = generativelanguage_v1beta3.TunedModel()
+                tuned_model.tuning_task.training_data.examples.examples.text_input = "text_input_value"
+                tuned_model.tuning_task.training_data.examples.examples.output = "output_value"
+
+                request = generativelanguage_v1beta3.CreateTunedModelRequest(
+                    tuned_model=tuned_model,
+                )
+
+                # Make the request
+                operation = client.create_tuned_model(request=request)
+
+                print("Waiting for operation to complete...")
+
+                response = (await operation).result()
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.CreateTunedModelRequest, dict]]):
+                The request object. Request to create a TunedModel.
+            tuned_model (:class:`google.ai.generativelanguage_v1beta3.types.TunedModel`):
+                Required. The tuned model to create.
+                This corresponds to the ``tuned_model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            tuned_model_id (:class:`str`):
+                Optional. The unique id for the tuned model if
+                specified. This value should be up to 40 characters, the
+                first character must be a letter, the last could be a
+                letter or a number. The id must match the regular
+                expression: `a-z <[a-z0-9-]{0,38}[a-z0-9]>`__?.
+
+                This corresponds to the ``tuned_model_id`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.api_core.operation_async.AsyncOperation:
+                An object representing a long-running operation.
+
+                The result type for the operation will be
+                :class:`google.ai.generativelanguage_v1beta3.types.TunedModel`
+                A fine-tuned model created using
+                ModelService.CreateTunedModel.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([tuned_model, tuned_model_id])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.CreateTunedModelRequest):
+            request = model_service.CreateTunedModelRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if tuned_model is not None:
+            request.tuned_model = tuned_model
+        if tuned_model_id is not None:
+            request.tuned_model_id = tuned_model_id
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.create_tuned_model
+        ]
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Wrap the response in an operation future.
+        response = operation_async.from_gapic(
+            response,
+            self._client._transport.operations_client,
+            gag_tuned_model.TunedModel,
+            metadata_type=model_service.CreateTunedModelMetadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def update_tuned_model(
+        self,
+        request: Optional[Union[model_service.UpdateTunedModelRequest, dict]] = None,
+        *,
+        tuned_model: Optional[gag_tuned_model.TunedModel] = None,
+        update_mask: Optional[field_mask_pb2.FieldMask] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> gag_tuned_model.TunedModel:
+        r"""Updates a tuned model.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_update_tuned_model():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                tuned_model = generativelanguage_v1beta3.TunedModel()
+                tuned_model.tuning_task.training_data.examples.examples.text_input = "text_input_value"
+                tuned_model.tuning_task.training_data.examples.examples.output = "output_value"
+
+                request = generativelanguage_v1beta3.UpdateTunedModelRequest(
+                    tuned_model=tuned_model,
+                )
+
+                # Make the request
+                response = await client.update_tuned_model(request=request)
+
+                # Handle the response
+                print(response)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.UpdateTunedModelRequest, dict]]):
+                The request object. Request to update a TunedModel.
+            tuned_model (:class:`google.ai.generativelanguage_v1beta3.types.TunedModel`):
+                Required. The tuned model to update.
+                This corresponds to the ``tuned_model`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
+                Required. The list of fields to
+                update.
+
+                This corresponds to the ``update_mask`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+
+        Returns:
+            google.ai.generativelanguage_v1beta3.types.TunedModel:
+                A fine-tuned model created using
+                ModelService.CreateTunedModel.
+
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([tuned_model, update_mask])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.UpdateTunedModelRequest):
+            request = model_service.UpdateTunedModelRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if tuned_model is not None:
+            request.tuned_model = tuned_model
+        if update_mask is not None:
+            request.update_mask = update_mask
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.update_tuned_model
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata(
+                (("tuned_model.name", request.tuned_model.name),)
+            ),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        response = await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+        # Done; return the response.
+        return response
+
+    async def delete_tuned_model(
+        self,
+        request: Optional[Union[model_service.DeleteTunedModelRequest, dict]] = None,
+        *,
+        name: Optional[str] = None,
+        retry: OptionalRetry = gapic_v1.method.DEFAULT,
+        timeout: Union[float, object] = gapic_v1.method.DEFAULT,
+        metadata: Sequence[Tuple[str, Union[str, bytes]]] = (),
+    ) -> None:
+        r"""Deletes a tuned model.
+
+        .. code-block:: python
+
+            # This snippet has been automatically generated and should be regarded as a
+            # code template only.
+            # It will require modifications to work:
+            # - It may require correct/in-range values for request initialization.
+            # - It may require specifying regional endpoints when creating the service
+            #   client as shown in:
+            #   https://googleapis.dev/python/google-api-core/latest/client_options.html
+            from google.ai import generativelanguage_v1beta3
+
+            async def sample_delete_tuned_model():
+                # Create a client
+                client = generativelanguage_v1beta3.ModelServiceAsyncClient()
+
+                # Initialize request argument(s)
+                request = generativelanguage_v1beta3.DeleteTunedModelRequest(
+                    name="name_value",
+                )
+
+                # Make the request
+                await client.delete_tuned_model(request=request)
+
+        Args:
+            request (Optional[Union[google.ai.generativelanguage_v1beta3.types.DeleteTunedModelRequest, dict]]):
+                The request object. Request to delete a TunedModel.
+            name (:class:`str`):
+                Required. The resource name of the model. Format:
+                ``tunedModels/my-model-id``
+
+                This corresponds to the ``name`` field
+                on the ``request`` instance; if ``request`` is provided, this
+                should not be set.
+            retry (google.api_core.retry_async.AsyncRetry): Designation of what errors, if any,
+                should be retried.
+            timeout (float): The timeout for this request.
+            metadata (Sequence[Tuple[str, Union[str, bytes]]]): Key/value pairs which should be
+                sent along with the request as metadata. Normally, each value must be of type `str`,
+                but for metadata keys ending with the suffix `-bin`, the corresponding values must
+                be of type `bytes`.
+        """
+        # Create or coerce a protobuf request object.
+        # - Quick check: If we got a request object, we should *not* have
+        #   gotten any keyword arguments that map to the request.
+        has_flattened_params = any([name])
+        if request is not None and has_flattened_params:
+            raise ValueError(
+                "If the `request` argument is set, then none of "
+                "the individual field arguments should be set."
+            )
+
+        # - Use the request object if provided (there's no risk of modifying the input as
+        #   there are no flattened fields), or create one.
+        if not isinstance(request, model_service.DeleteTunedModelRequest):
+            request = model_service.DeleteTunedModelRequest(request)
+
+        # If we have keyword arguments corresponding to fields on the
+        # request, apply these.
+        if name is not None:
+            request.name = name
+
+        # Wrap the RPC method; this adds retry and timeout information,
+        # and friendly error handling.
+        rpc = self._client._transport._wrapped_methods[
+            self._client._transport.delete_tuned_model
+        ]
+
+        # Certain fields should be provided within the metadata header;
+        # add these here.
+        metadata = tuple(metadata) + (
+            gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
+        )
+
+        # Validate the universe domain.
+        self._client._validate_universe_domain()
+
+        # Send the request.
+        await rpc(
+            request,
+            retry=retry,
+            timeout=timeout,
+            metadata=metadata,
+        )
+
+    async def __aenter__(self) -> "ModelServiceAsyncClient":
+        return self
+
+    async def __aexit__(self, exc_type, exc, tb):
+        await self.transport.close()
+
+
+DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
+    gapic_version=package_version.__version__
+)
+
+
+__all__ = ("ModelServiceAsyncClient",)