langfuse.api
1# This file was auto-generated by Fern from our API Definition. 2 3from .resources import ( 4 AccessDeniedError, 5 AnnotationQueue, 6 AnnotationQueueAssignmentRequest, 7 AnnotationQueueItem, 8 AnnotationQueueObjectType, 9 AnnotationQueueStatus, 10 ApiKeyDeletionResponse, 11 ApiKeyList, 12 ApiKeyResponse, 13 ApiKeySummary, 14 AuthenticationScheme, 15 BaseEvent, 16 BasePrompt, 17 BaseScore, 18 BaseScoreV1, 19 BooleanScore, 20 BooleanScoreV1, 21 BulkConfig, 22 CategoricalScore, 23 CategoricalScoreV1, 24 ChatMessage, 25 ChatMessageWithPlaceholders, 26 ChatMessageWithPlaceholders_Chatmessage, 27 ChatMessageWithPlaceholders_Placeholder, 28 ChatPrompt, 29 Comment, 30 CommentObjectType, 31 ConfigCategory, 32 CreateAnnotationQueueAssignmentResponse, 33 CreateAnnotationQueueItemRequest, 34 CreateAnnotationQueueRequest, 35 CreateChatPromptRequest, 36 CreateCommentRequest, 37 CreateCommentResponse, 38 CreateDatasetItemRequest, 39 CreateDatasetRequest, 40 CreateDatasetRunItemRequest, 41 CreateEventBody, 42 CreateEventEvent, 43 CreateGenerationBody, 44 CreateGenerationEvent, 45 CreateModelRequest, 46 CreateObservationEvent, 47 CreatePromptRequest, 48 CreatePromptRequest_Chat, 49 CreatePromptRequest_Text, 50 CreateScoreConfigRequest, 51 CreateScoreRequest, 52 CreateScoreResponse, 53 CreateScoreValue, 54 CreateSpanBody, 55 CreateSpanEvent, 56 CreateTextPromptRequest, 57 Dataset, 58 DatasetItem, 59 DatasetRun, 60 DatasetRunItem, 61 DatasetRunWithItems, 62 DatasetStatus, 63 DeleteAnnotationQueueAssignmentResponse, 64 DeleteAnnotationQueueItemResponse, 65 DeleteDatasetItemResponse, 66 DeleteDatasetRunResponse, 67 DeleteTraceResponse, 68 EmptyResponse, 69 Error, 70 FilterConfig, 71 GetCommentsResponse, 72 GetMediaResponse, 73 GetMediaUploadUrlRequest, 74 GetMediaUploadUrlResponse, 75 GetScoresResponse, 76 GetScoresResponseData, 77 GetScoresResponseDataBoolean, 78 GetScoresResponseDataCategorical, 79 GetScoresResponseDataNumeric, 80 GetScoresResponseData_Boolean, 81 GetScoresResponseData_Categorical, 82 GetScoresResponseData_Numeric, 83 GetScoresResponseTraceData, 84 HealthResponse, 85 IngestionError, 86 IngestionEvent, 87 IngestionEvent_EventCreate, 88 IngestionEvent_GenerationCreate, 89 IngestionEvent_GenerationUpdate, 90 IngestionEvent_ObservationCreate, 91 IngestionEvent_ObservationUpdate, 92 IngestionEvent_ScoreCreate, 93 IngestionEvent_SdkLog, 94 IngestionEvent_SpanCreate, 95 IngestionEvent_SpanUpdate, 96 IngestionEvent_TraceCreate, 97 IngestionResponse, 98 IngestionSuccess, 99 IngestionUsage, 100 LlmAdapter, 101 LlmConnection, 102 MapValue, 103 MediaContentType, 104 MembershipRequest, 105 MembershipResponse, 106 MembershipRole, 107 MembershipsResponse, 108 MethodNotAllowedError, 109 MetricsResponse, 110 Model, 111 ModelPrice, 112 ModelUsageUnit, 113 NotFoundError, 114 NumericScore, 115 NumericScoreV1, 116 Observation, 117 ObservationBody, 118 ObservationLevel, 119 ObservationType, 120 Observations, 121 ObservationsView, 122 ObservationsViews, 123 OpenAiCompletionUsageSchema, 124 OpenAiResponseUsageSchema, 125 OpenAiUsage, 126 OptionalObservationBody, 127 OrganizationProject, 128 OrganizationProjectsResponse, 129 PaginatedAnnotationQueueItems, 130 PaginatedAnnotationQueues, 131 PaginatedDatasetItems, 132 PaginatedDatasetRunItems, 133 PaginatedDatasetRuns, 134 PaginatedDatasets, 135 PaginatedLlmConnections, 136 PaginatedModels, 137 PaginatedSessions, 138 PatchMediaBody, 139 PlaceholderMessage, 140 Project, 141 ProjectDeletionResponse, 142 Projects, 143 Prompt, 144 PromptMeta, 145 PromptMetaListResponse, 146 Prompt_Chat, 147 Prompt_Text, 148 ResourceMeta, 149 ResourceType, 150 ResourceTypesResponse, 151 SchemaExtension, 152 SchemaResource, 153 SchemasResponse, 154 ScimEmail, 155 ScimFeatureSupport, 156 ScimName, 157 ScimUser, 158 ScimUsersListResponse, 159 Score, 160 ScoreBody, 161 ScoreConfig, 162 ScoreConfigs, 163 ScoreDataType, 164 ScoreEvent, 165 ScoreSource, 166 ScoreV1, 167 ScoreV1_Boolean, 168 ScoreV1_Categorical, 169 ScoreV1_Numeric, 170 Score_Boolean, 171 Score_Categorical, 172 Score_Numeric, 173 SdkLogBody, 174 SdkLogEvent, 175 ServiceProviderConfig, 176 ServiceUnavailableError, 177 Session, 178 SessionWithTraces, 179 Sort, 180 TextPrompt, 181 Trace, 182 TraceBody, 183 TraceEvent, 184 TraceWithDetails, 185 TraceWithFullDetails, 186 Traces, 187 UnauthorizedError, 188 UpdateAnnotationQueueItemRequest, 189 UpdateEventBody, 190 UpdateGenerationBody, 191 UpdateGenerationEvent, 192 UpdateObservationEvent, 193 UpdateSpanBody, 194 UpdateSpanEvent, 195 UpsertLlmConnectionRequest, 196 Usage, 197 UsageDetails, 198 UserMeta, 199 annotation_queues, 200 comments, 201 commons, 202 dataset_items, 203 dataset_run_items, 204 datasets, 205 health, 206 ingestion, 207 llm_connections, 208 media, 209 metrics, 210 models, 211 observations, 212 organizations, 213 projects, 214 prompt_version, 215 prompts, 216 scim, 217 score, 218 score_configs, 219 score_v_2, 220 sessions, 221 trace, 222 utils, 223) 224 225__all__ = [ 226 "AccessDeniedError", 227 "AnnotationQueue", 228 "AnnotationQueueAssignmentRequest", 229 "AnnotationQueueItem", 230 "AnnotationQueueObjectType", 231 "AnnotationQueueStatus", 232 "ApiKeyDeletionResponse", 233 "ApiKeyList", 234 "ApiKeyResponse", 235 "ApiKeySummary", 236 "AuthenticationScheme", 237 "BaseEvent", 238 "BasePrompt", 239 "BaseScore", 240 "BaseScoreV1", 241 "BooleanScore", 242 "BooleanScoreV1", 243 "BulkConfig", 244 "CategoricalScore", 245 "CategoricalScoreV1", 246 "ChatMessage", 247 "ChatMessageWithPlaceholders", 248 "ChatMessageWithPlaceholders_Chatmessage", 249 "ChatMessageWithPlaceholders_Placeholder", 250 "ChatPrompt", 251 "Comment", 252 "CommentObjectType", 253 "ConfigCategory", 254 "CreateAnnotationQueueAssignmentResponse", 255 "CreateAnnotationQueueItemRequest", 256 "CreateAnnotationQueueRequest", 257 "CreateChatPromptRequest", 258 "CreateCommentRequest", 259 "CreateCommentResponse", 260 "CreateDatasetItemRequest", 261 "CreateDatasetRequest", 262 "CreateDatasetRunItemRequest", 263 "CreateEventBody", 264 "CreateEventEvent", 265 "CreateGenerationBody", 266 "CreateGenerationEvent", 267 "CreateModelRequest", 268 "CreateObservationEvent", 269 "CreatePromptRequest", 270 "CreatePromptRequest_Chat", 271 "CreatePromptRequest_Text", 272 "CreateScoreConfigRequest", 273 "CreateScoreRequest", 274 "CreateScoreResponse", 275 "CreateScoreValue", 276 "CreateSpanBody", 277 "CreateSpanEvent", 278 "CreateTextPromptRequest", 279 "Dataset", 280 "DatasetItem", 281 "DatasetRun", 282 "DatasetRunItem", 283 "DatasetRunWithItems", 284 "DatasetStatus", 285 "DeleteAnnotationQueueAssignmentResponse", 286 "DeleteAnnotationQueueItemResponse", 287 "DeleteDatasetItemResponse", 288 "DeleteDatasetRunResponse", 289 "DeleteTraceResponse", 290 "EmptyResponse", 291 "Error", 292 "FilterConfig", 293 "GetCommentsResponse", 294 "GetMediaResponse", 295 "GetMediaUploadUrlRequest", 296 "GetMediaUploadUrlResponse", 297 "GetScoresResponse", 298 "GetScoresResponseData", 299 "GetScoresResponseDataBoolean", 300 "GetScoresResponseDataCategorical", 301 "GetScoresResponseDataNumeric", 302 "GetScoresResponseData_Boolean", 303 "GetScoresResponseData_Categorical", 304 "GetScoresResponseData_Numeric", 305 "GetScoresResponseTraceData", 306 "HealthResponse", 307 "IngestionError", 308 "IngestionEvent", 309 "IngestionEvent_EventCreate", 310 "IngestionEvent_GenerationCreate", 311 "IngestionEvent_GenerationUpdate", 312 "IngestionEvent_ObservationCreate", 313 "IngestionEvent_ObservationUpdate", 314 "IngestionEvent_ScoreCreate", 315 "IngestionEvent_SdkLog", 316 "IngestionEvent_SpanCreate", 317 "IngestionEvent_SpanUpdate", 318 "IngestionEvent_TraceCreate", 319 "IngestionResponse", 320 "IngestionSuccess", 321 "IngestionUsage", 322 "LlmAdapter", 323 "LlmConnection", 324 "MapValue", 325 "MediaContentType", 326 "MembershipRequest", 327 "MembershipResponse", 328 "MembershipRole", 329 "MembershipsResponse", 330 "MethodNotAllowedError", 331 "MetricsResponse", 332 "Model", 333 "ModelPrice", 334 "ModelUsageUnit", 335 "NotFoundError", 336 "NumericScore", 337 "NumericScoreV1", 338 "Observation", 339 "ObservationBody", 340 "ObservationLevel", 341 "ObservationType", 342 "Observations", 343 "ObservationsView", 344 "ObservationsViews", 345 "OpenAiCompletionUsageSchema", 346 "OpenAiResponseUsageSchema", 347 "OpenAiUsage", 348 "OptionalObservationBody", 349 "OrganizationProject", 350 "OrganizationProjectsResponse", 351 "PaginatedAnnotationQueueItems", 352 "PaginatedAnnotationQueues", 353 "PaginatedDatasetItems", 354 "PaginatedDatasetRunItems", 355 "PaginatedDatasetRuns", 356 "PaginatedDatasets", 357 "PaginatedLlmConnections", 358 "PaginatedModels", 359 "PaginatedSessions", 360 "PatchMediaBody", 361 "PlaceholderMessage", 362 "Project", 363 "ProjectDeletionResponse", 364 "Projects", 365 "Prompt", 366 "PromptMeta", 367 "PromptMetaListResponse", 368 "Prompt_Chat", 369 "Prompt_Text", 370 "ResourceMeta", 371 "ResourceType", 372 "ResourceTypesResponse", 373 "SchemaExtension", 374 "SchemaResource", 375 "SchemasResponse", 376 "ScimEmail", 377 "ScimFeatureSupport", 378 "ScimName", 379 "ScimUser", 380 "ScimUsersListResponse", 381 "Score", 382 "ScoreBody", 383 "ScoreConfig", 384 "ScoreConfigs", 385 "ScoreDataType", 386 "ScoreEvent", 387 "ScoreSource", 388 "ScoreV1", 389 "ScoreV1_Boolean", 390 "ScoreV1_Categorical", 391 "ScoreV1_Numeric", 392 "Score_Boolean", 393 "Score_Categorical", 394 "Score_Numeric", 395 "SdkLogBody", 396 "SdkLogEvent", 397 "ServiceProviderConfig", 398 "ServiceUnavailableError", 399 "Session", 400 "SessionWithTraces", 401 "Sort", 402 "TextPrompt", 403 "Trace", 404 "TraceBody", 405 "TraceEvent", 406 "TraceWithDetails", 407 "TraceWithFullDetails", 408 "Traces", 409 "UnauthorizedError", 410 "UpdateAnnotationQueueItemRequest", 411 "UpdateEventBody", 412 "UpdateGenerationBody", 413 "UpdateGenerationEvent", 414 "UpdateObservationEvent", 415 "UpdateSpanBody", 416 "UpdateSpanEvent", 417 "UpsertLlmConnectionRequest", 418 "Usage", 419 "UsageDetails", 420 "UserMeta", 421 "annotation_queues", 422 "comments", 423 "commons", 424 "dataset_items", 425 "dataset_run_items", 426 "datasets", 427 "health", 428 "ingestion", 429 "llm_connections", 430 "media", 431 "metrics", 432 "models", 433 "observations", 434 "organizations", 435 "projects", 436 "prompt_version", 437 "prompts", 438 "scim", 439 "score", 440 "score_configs", 441 "score_v_2", 442 "sessions", 443 "trace", 444 "utils", 445]
9class AccessDeniedError(ApiError): 10 def __init__(self, body: typing.Any): 11 super().__init__(status_code=403, body=body)
Common base class for all non-exit exceptions.
11class AnnotationQueue(pydantic_v1.BaseModel): 12 id: str 13 name: str 14 description: typing.Optional[str] = None 15 score_config_ids: typing.List[str] = pydantic_v1.Field(alias="scoreConfigIds") 16 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 17 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 18 19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults) 26 27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 ) 43 44 class Config: 45 frozen = True 46 smart_union = True 47 allow_population_by_field_name = True 48 populate_by_name = True 49 extra = pydantic_v1.Extra.allow 50 json_encoders = {dt.datetime: serialize_datetime}
19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class AnnotationQueueAssignmentRequest(pydantic_v1.BaseModel): 12 user_id: str = pydantic_v1.Field(alias="userId") 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 allow_population_by_field_name = True 43 populate_by_name = True 44 extra = pydantic_v1.Extra.allow 45 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class AnnotationQueueItem(pydantic_v1.BaseModel): 14 id: str 15 queue_id: str = pydantic_v1.Field(alias="queueId") 16 object_id: str = pydantic_v1.Field(alias="objectId") 17 object_type: AnnotationQueueObjectType = pydantic_v1.Field(alias="objectType") 18 status: AnnotationQueueStatus 19 completed_at: typing.Optional[dt.datetime] = pydantic_v1.Field( 20 alias="completedAt", default=None 21 ) 22 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 23 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 24 25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults) 32 33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 ) 49 50 class Config: 51 frozen = True 52 smart_union = True 53 allow_population_by_field_name = True 54 populate_by_name = True 55 extra = pydantic_v1.Extra.allow 56 json_encoders = {dt.datetime: serialize_datetime}
25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class AnnotationQueueObjectType(str, enum.Enum): 11 TRACE = "TRACE" 12 OBSERVATION = "OBSERVATION" 13 14 def visit( 15 self, 16 trace: typing.Callable[[], T_Result], 17 observation: typing.Callable[[], T_Result], 18 ) -> T_Result: 19 if self is AnnotationQueueObjectType.TRACE: 20 return trace() 21 if self is AnnotationQueueObjectType.OBSERVATION: 22 return observation()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
10class AnnotationQueueStatus(str, enum.Enum): 11 PENDING = "PENDING" 12 COMPLETED = "COMPLETED" 13 14 def visit( 15 self, 16 pending: typing.Callable[[], T_Result], 17 completed: typing.Callable[[], T_Result], 18 ) -> T_Result: 19 if self is AnnotationQueueStatus.PENDING: 20 return pending() 21 if self is AnnotationQueueStatus.COMPLETED: 22 return completed()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
11class ApiKeyDeletionResponse(pydantic_v1.BaseModel): 12 """ 13 Response for API key deletion 14 """ 15 16 success: bool 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
Response for API key deletion
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class ApiKeyList(pydantic_v1.BaseModel): 13 """ 14 List of API keys for a project 15 """ 16 17 api_keys: typing.List[ApiKeySummary] = pydantic_v1.Field(alias="apiKeys") 18 19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults) 26 27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 ) 43 44 class Config: 45 frozen = True 46 smart_union = True 47 allow_population_by_field_name = True 48 populate_by_name = True 49 extra = pydantic_v1.Extra.allow 50 json_encoders = {dt.datetime: serialize_datetime}
List of API keys for a project
19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ApiKeyResponse(pydantic_v1.BaseModel): 12 """ 13 Response for API key creation 14 """ 15 16 id: str 17 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 18 public_key: str = pydantic_v1.Field(alias="publicKey") 19 secret_key: str = pydantic_v1.Field(alias="secretKey") 20 display_secret_key: str = pydantic_v1.Field(alias="displaySecretKey") 21 note: typing.Optional[str] = None 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
Response for API key creation
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ApiKeySummary(pydantic_v1.BaseModel): 12 """ 13 Summary of an API key 14 """ 15 16 id: str 17 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 18 expires_at: typing.Optional[dt.datetime] = pydantic_v1.Field( 19 alias="expiresAt", default=None 20 ) 21 last_used_at: typing.Optional[dt.datetime] = pydantic_v1.Field( 22 alias="lastUsedAt", default=None 23 ) 24 note: typing.Optional[str] = None 25 public_key: str = pydantic_v1.Field(alias="publicKey") 26 display_secret_key: str = pydantic_v1.Field(alias="displaySecretKey") 27 28 def json(self, **kwargs: typing.Any) -> str: 29 kwargs_with_defaults: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 return super().json(**kwargs_with_defaults) 35 36 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 37 kwargs_with_defaults_exclude_unset: typing.Any = { 38 "by_alias": True, 39 "exclude_unset": True, 40 **kwargs, 41 } 42 kwargs_with_defaults_exclude_none: typing.Any = { 43 "by_alias": True, 44 "exclude_none": True, 45 **kwargs, 46 } 47 48 return deep_union_pydantic_dicts( 49 super().dict(**kwargs_with_defaults_exclude_unset), 50 super().dict(**kwargs_with_defaults_exclude_none), 51 ) 52 53 class Config: 54 frozen = True 55 smart_union = True 56 allow_population_by_field_name = True 57 populate_by_name = True 58 extra = pydantic_v1.Extra.allow 59 json_encoders = {dt.datetime: serialize_datetime}
Summary of an API key
28 def json(self, **kwargs: typing.Any) -> str: 29 kwargs_with_defaults: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
36 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 37 kwargs_with_defaults_exclude_unset: typing.Any = { 38 "by_alias": True, 39 "exclude_unset": True, 40 **kwargs, 41 } 42 kwargs_with_defaults_exclude_none: typing.Any = { 43 "by_alias": True, 44 "exclude_none": True, 45 **kwargs, 46 } 47 48 return deep_union_pydantic_dicts( 49 super().dict(**kwargs_with_defaults_exclude_unset), 50 super().dict(**kwargs_with_defaults_exclude_none), 51 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class AuthenticationScheme(pydantic_v1.BaseModel): 12 name: str 13 description: str 14 spec_uri: str = pydantic_v1.Field(alias="specUri") 15 type: str 16 primary: bool 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class BaseEvent(pydantic_v1.BaseModel): 12 id: str = pydantic_v1.Field() 13 """ 14 UUID v4 that identifies the event 15 """ 16 17 timestamp: str = pydantic_v1.Field() 18 """ 19 Datetime (ISO 8601) of event creation in client. Should be as close to actual event creation in client as possible, this timestamp will be used for ordering of events in future release. Resolution: milliseconds (required), microseconds (optimal). 20 """ 21 22 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 23 """ 24 Optional. Metadata field used by the Langfuse SDKs for debugging. 25 """ 26 27 def json(self, **kwargs: typing.Any) -> str: 28 kwargs_with_defaults: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 return super().json(**kwargs_with_defaults) 34 35 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 36 kwargs_with_defaults_exclude_unset: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 kwargs_with_defaults_exclude_none: typing.Any = { 42 "by_alias": True, 43 "exclude_none": True, 44 **kwargs, 45 } 46 47 return deep_union_pydantic_dicts( 48 super().dict(**kwargs_with_defaults_exclude_unset), 49 super().dict(**kwargs_with_defaults_exclude_none), 50 ) 51 52 class Config: 53 frozen = True 54 smart_union = True 55 extra = pydantic_v1.Extra.allow 56 json_encoders = {dt.datetime: serialize_datetime}
Datetime (ISO 8601) of event creation in client. Should be as close to actual event creation in client as possible, this timestamp will be used for ordering of events in future release. Resolution: milliseconds (required), microseconds (optimal).
27 def json(self, **kwargs: typing.Any) -> str: 28 kwargs_with_defaults: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
35 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 36 kwargs_with_defaults_exclude_unset: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 kwargs_with_defaults_exclude_none: typing.Any = { 42 "by_alias": True, 43 "exclude_none": True, 44 **kwargs, 45 } 46 47 return deep_union_pydantic_dicts( 48 super().dict(**kwargs_with_defaults_exclude_unset), 49 super().dict(**kwargs_with_defaults_exclude_none), 50 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class BasePrompt(pydantic_v1.BaseModel): 12 name: str 13 version: int 14 config: typing.Any 15 labels: typing.List[str] = pydantic_v1.Field() 16 """ 17 List of deployment labels of this prompt version. 18 """ 19 20 tags: typing.List[str] = pydantic_v1.Field() 21 """ 22 List of tags. Used to filter via UI and API. The same across versions of a prompt. 23 """ 24 25 commit_message: typing.Optional[str] = pydantic_v1.Field( 26 alias="commitMessage", default=None 27 ) 28 """ 29 Commit message for this prompt version. 30 """ 31 32 resolution_graph: typing.Optional[typing.Dict[str, typing.Any]] = pydantic_v1.Field( 33 alias="resolutionGraph", default=None 34 ) 35 """ 36 The dependency resolution graph for the current prompt. Null if prompt has no dependencies. 37 """ 38 39 def json(self, **kwargs: typing.Any) -> str: 40 kwargs_with_defaults: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 return super().json(**kwargs_with_defaults) 46 47 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 48 kwargs_with_defaults_exclude_unset: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 kwargs_with_defaults_exclude_none: typing.Any = { 54 "by_alias": True, 55 "exclude_none": True, 56 **kwargs, 57 } 58 59 return deep_union_pydantic_dicts( 60 super().dict(**kwargs_with_defaults_exclude_unset), 61 super().dict(**kwargs_with_defaults_exclude_none), 62 ) 63 64 class Config: 65 frozen = True 66 smart_union = True 67 allow_population_by_field_name = True 68 populate_by_name = True 69 extra = pydantic_v1.Extra.allow 70 json_encoders = {dt.datetime: serialize_datetime}
The dependency resolution graph for the current prompt. Null if prompt has no dependencies.
39 def json(self, **kwargs: typing.Any) -> str: 40 kwargs_with_defaults: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
47 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 48 kwargs_with_defaults_exclude_unset: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 kwargs_with_defaults_exclude_none: typing.Any = { 54 "by_alias": True, 55 "exclude_none": True, 56 **kwargs, 57 } 58 59 return deep_union_pydantic_dicts( 60 super().dict(**kwargs_with_defaults_exclude_unset), 61 super().dict(**kwargs_with_defaults_exclude_none), 62 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class BaseScore(pydantic_v1.BaseModel): 13 id: str 14 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 15 session_id: typing.Optional[str] = pydantic_v1.Field( 16 alias="sessionId", default=None 17 ) 18 observation_id: typing.Optional[str] = pydantic_v1.Field( 19 alias="observationId", default=None 20 ) 21 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 22 alias="datasetRunId", default=None 23 ) 24 name: str 25 source: ScoreSource 26 timestamp: dt.datetime 27 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 28 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 29 author_user_id: typing.Optional[str] = pydantic_v1.Field( 30 alias="authorUserId", default=None 31 ) 32 comment: typing.Optional[str] = None 33 metadata: typing.Optional[typing.Any] = None 34 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 35 """ 36 Reference a score config on a score. When set, config and score name must be equal and value must comply to optionally defined numerical range 37 """ 38 39 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 40 """ 41 Reference an annotation queue on a score. Populated if the score was initially created in an annotation queue. 42 """ 43 44 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 45 """ 46 The environment from which this score originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'. 47 """ 48 49 def json(self, **kwargs: typing.Any) -> str: 50 kwargs_with_defaults: typing.Any = { 51 "by_alias": True, 52 "exclude_unset": True, 53 **kwargs, 54 } 55 return super().json(**kwargs_with_defaults) 56 57 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 58 kwargs_with_defaults_exclude_unset: typing.Any = { 59 "by_alias": True, 60 "exclude_unset": True, 61 **kwargs, 62 } 63 kwargs_with_defaults_exclude_none: typing.Any = { 64 "by_alias": True, 65 "exclude_none": True, 66 **kwargs, 67 } 68 69 return deep_union_pydantic_dicts( 70 super().dict(**kwargs_with_defaults_exclude_unset), 71 super().dict(**kwargs_with_defaults_exclude_none), 72 ) 73 74 class Config: 75 frozen = True 76 smart_union = True 77 allow_population_by_field_name = True 78 populate_by_name = True 79 extra = pydantic_v1.Extra.allow 80 json_encoders = {dt.datetime: serialize_datetime}
Reference a score config on a score. When set, config and score name must be equal and value must comply to optionally defined numerical range
Reference an annotation queue on a score. Populated if the score was initially created in an annotation queue.
The environment from which this score originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'.
49 def json(self, **kwargs: typing.Any) -> str: 50 kwargs_with_defaults: typing.Any = { 51 "by_alias": True, 52 "exclude_unset": True, 53 **kwargs, 54 } 55 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
57 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 58 kwargs_with_defaults_exclude_unset: typing.Any = { 59 "by_alias": True, 60 "exclude_unset": True, 61 **kwargs, 62 } 63 kwargs_with_defaults_exclude_none: typing.Any = { 64 "by_alias": True, 65 "exclude_none": True, 66 **kwargs, 67 } 68 69 return deep_union_pydantic_dicts( 70 super().dict(**kwargs_with_defaults_exclude_unset), 71 super().dict(**kwargs_with_defaults_exclude_none), 72 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class BaseScoreV1(pydantic_v1.BaseModel): 13 id: str 14 trace_id: str = pydantic_v1.Field(alias="traceId") 15 name: str 16 source: ScoreSource 17 observation_id: typing.Optional[str] = pydantic_v1.Field( 18 alias="observationId", default=None 19 ) 20 timestamp: dt.datetime 21 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 22 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 23 author_user_id: typing.Optional[str] = pydantic_v1.Field( 24 alias="authorUserId", default=None 25 ) 26 comment: typing.Optional[str] = None 27 metadata: typing.Optional[typing.Any] = None 28 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 29 """ 30 Reference a score config on a score. When set, config and score name must be equal and value must comply to optionally defined numerical range 31 """ 32 33 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 34 """ 35 Reference an annotation queue on a score. Populated if the score was initially created in an annotation queue. 36 """ 37 38 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 39 """ 40 The environment from which this score originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'. 41 """ 42 43 def json(self, **kwargs: typing.Any) -> str: 44 kwargs_with_defaults: typing.Any = { 45 "by_alias": True, 46 "exclude_unset": True, 47 **kwargs, 48 } 49 return super().json(**kwargs_with_defaults) 50 51 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 52 kwargs_with_defaults_exclude_unset: typing.Any = { 53 "by_alias": True, 54 "exclude_unset": True, 55 **kwargs, 56 } 57 kwargs_with_defaults_exclude_none: typing.Any = { 58 "by_alias": True, 59 "exclude_none": True, 60 **kwargs, 61 } 62 63 return deep_union_pydantic_dicts( 64 super().dict(**kwargs_with_defaults_exclude_unset), 65 super().dict(**kwargs_with_defaults_exclude_none), 66 ) 67 68 class Config: 69 frozen = True 70 smart_union = True 71 allow_population_by_field_name = True 72 populate_by_name = True 73 extra = pydantic_v1.Extra.allow 74 json_encoders = {dt.datetime: serialize_datetime}
Reference a score config on a score. When set, config and score name must be equal and value must comply to optionally defined numerical range
Reference an annotation queue on a score. Populated if the score was initially created in an annotation queue.
The environment from which this score originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'.
43 def json(self, **kwargs: typing.Any) -> str: 44 kwargs_with_defaults: typing.Any = { 45 "by_alias": True, 46 "exclude_unset": True, 47 **kwargs, 48 } 49 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
51 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 52 kwargs_with_defaults_exclude_unset: typing.Any = { 53 "by_alias": True, 54 "exclude_unset": True, 55 **kwargs, 56 } 57 kwargs_with_defaults_exclude_none: typing.Any = { 58 "by_alias": True, 59 "exclude_none": True, 60 **kwargs, 61 } 62 63 return deep_union_pydantic_dicts( 64 super().dict(**kwargs_with_defaults_exclude_unset), 65 super().dict(**kwargs_with_defaults_exclude_none), 66 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class BooleanScore(BaseScore): 13 value: float = pydantic_v1.Field() 14 """ 15 The numeric value of the score. Equals 1 for "True" and 0 for "False" 16 """ 17 18 string_value: str = pydantic_v1.Field(alias="stringValue") 19 """ 20 The string representation of the score value. Is inferred from the numeric value and equals "True" or "False" 21 """ 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
The string representation of the score value. Is inferred from the numeric value and equals "True" or "False"
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class BooleanScoreV1(BaseScoreV1): 13 value: float = pydantic_v1.Field() 14 """ 15 The numeric value of the score. Equals 1 for "True" and 0 for "False" 16 """ 17 18 string_value: str = pydantic_v1.Field(alias="stringValue") 19 """ 20 The string representation of the score value. Is inferred from the numeric value and equals "True" or "False" 21 """ 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
The string representation of the score value. Is inferred from the numeric value and equals "True" or "False"
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class BulkConfig(pydantic_v1.BaseModel): 12 supported: bool 13 max_operations: int = pydantic_v1.Field(alias="maxOperations") 14 max_payload_size: int = pydantic_v1.Field(alias="maxPayloadSize") 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CategoricalScore(BaseScore): 13 value: typing.Optional[float] = pydantic_v1.Field(default=None) 14 """ 15 Only defined if a config is linked. Represents the numeric category mapping of the stringValue 16 """ 17 18 string_value: str = pydantic_v1.Field(alias="stringValue") 19 """ 20 The string representation of the score value. If no config is linked, can be any string. Otherwise, must map to a config category 21 """ 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
Only defined if a config is linked. Represents the numeric category mapping of the stringValue
The string representation of the score value. If no config is linked, can be any string. Otherwise, must map to a config category
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CategoricalScoreV1(BaseScoreV1): 13 value: typing.Optional[float] = pydantic_v1.Field(default=None) 14 """ 15 Only defined if a config is linked. Represents the numeric category mapping of the stringValue 16 """ 17 18 string_value: str = pydantic_v1.Field(alias="stringValue") 19 """ 20 The string representation of the score value. If no config is linked, can be any string. Otherwise, must map to a config category 21 """ 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
Only defined if a config is linked. Represents the numeric category mapping of the stringValue
The string representation of the score value. If no config is linked, can be any string. Otherwise, must map to a config category
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ChatMessage(pydantic_v1.BaseModel): 12 role: str 13 content: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ChatMessageWithPlaceholders_Chatmessage(pydantic_v1.BaseModel): 14 role: str 15 content: str 16 type: typing.Literal["chatmessage"] = "chatmessage" 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
50class ChatMessageWithPlaceholders_Placeholder(pydantic_v1.BaseModel): 51 name: str 52 type: typing.Literal["placeholder"] = "placeholder" 53 54 def json(self, **kwargs: typing.Any) -> str: 55 kwargs_with_defaults: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 return super().json(**kwargs_with_defaults) 61 62 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 63 kwargs_with_defaults_exclude_unset: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 kwargs_with_defaults_exclude_none: typing.Any = { 69 "by_alias": True, 70 "exclude_none": True, 71 **kwargs, 72 } 73 74 return deep_union_pydantic_dicts( 75 super().dict(**kwargs_with_defaults_exclude_unset), 76 super().dict(**kwargs_with_defaults_exclude_none), 77 ) 78 79 class Config: 80 frozen = True 81 smart_union = True 82 extra = pydantic_v1.Extra.allow 83 json_encoders = {dt.datetime: serialize_datetime}
54 def json(self, **kwargs: typing.Any) -> str: 55 kwargs_with_defaults: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
62 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 63 kwargs_with_defaults_exclude_unset: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 kwargs_with_defaults_exclude_none: typing.Any = { 69 "by_alias": True, 70 "exclude_none": True, 71 **kwargs, 72 } 73 74 return deep_union_pydantic_dicts( 75 super().dict(**kwargs_with_defaults_exclude_unset), 76 super().dict(**kwargs_with_defaults_exclude_none), 77 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ChatPrompt(BasePrompt): 14 prompt: typing.List[ChatMessageWithPlaceholders] 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class Comment(pydantic_v1.BaseModel): 13 id: str 14 project_id: str = pydantic_v1.Field(alias="projectId") 15 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 16 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 17 object_type: CommentObjectType = pydantic_v1.Field(alias="objectType") 18 object_id: str = pydantic_v1.Field(alias="objectId") 19 content: str 20 author_user_id: typing.Optional[str] = pydantic_v1.Field( 21 alias="authorUserId", default=None 22 ) 23 24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults) 31 32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 ) 48 49 class Config: 50 frozen = True 51 smart_union = True 52 allow_population_by_field_name = True 53 populate_by_name = True 54 extra = pydantic_v1.Extra.allow 55 json_encoders = {dt.datetime: serialize_datetime}
24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class CommentObjectType(str, enum.Enum): 11 TRACE = "TRACE" 12 OBSERVATION = "OBSERVATION" 13 SESSION = "SESSION" 14 PROMPT = "PROMPT" 15 16 def visit( 17 self, 18 trace: typing.Callable[[], T_Result], 19 observation: typing.Callable[[], T_Result], 20 session: typing.Callable[[], T_Result], 21 prompt: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is CommentObjectType.TRACE: 24 return trace() 25 if self is CommentObjectType.OBSERVATION: 26 return observation() 27 if self is CommentObjectType.SESSION: 28 return session() 29 if self is CommentObjectType.PROMPT: 30 return prompt()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
16 def visit( 17 self, 18 trace: typing.Callable[[], T_Result], 19 observation: typing.Callable[[], T_Result], 20 session: typing.Callable[[], T_Result], 21 prompt: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is CommentObjectType.TRACE: 24 return trace() 25 if self is CommentObjectType.OBSERVATION: 26 return observation() 27 if self is CommentObjectType.SESSION: 28 return session() 29 if self is CommentObjectType.PROMPT: 30 return prompt()
11class ConfigCategory(pydantic_v1.BaseModel): 12 value: float 13 label: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateAnnotationQueueAssignmentResponse(pydantic_v1.BaseModel): 12 user_id: str = pydantic_v1.Field(alias="userId") 13 queue_id: str = pydantic_v1.Field(alias="queueId") 14 project_id: str = pydantic_v1.Field(alias="projectId") 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateAnnotationQueueItemRequest(pydantic_v1.BaseModel): 14 object_id: str = pydantic_v1.Field(alias="objectId") 15 object_type: AnnotationQueueObjectType = pydantic_v1.Field(alias="objectType") 16 status: typing.Optional[AnnotationQueueStatus] = pydantic_v1.Field(default=None) 17 """ 18 Defaults to PENDING for new queue items 19 """ 20 21 def json(self, **kwargs: typing.Any) -> str: 22 kwargs_with_defaults: typing.Any = { 23 "by_alias": True, 24 "exclude_unset": True, 25 **kwargs, 26 } 27 return super().json(**kwargs_with_defaults) 28 29 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 30 kwargs_with_defaults_exclude_unset: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 kwargs_with_defaults_exclude_none: typing.Any = { 36 "by_alias": True, 37 "exclude_none": True, 38 **kwargs, 39 } 40 41 return deep_union_pydantic_dicts( 42 super().dict(**kwargs_with_defaults_exclude_unset), 43 super().dict(**kwargs_with_defaults_exclude_none), 44 ) 45 46 class Config: 47 frozen = True 48 smart_union = True 49 allow_population_by_field_name = True 50 populate_by_name = True 51 extra = pydantic_v1.Extra.allow 52 json_encoders = {dt.datetime: serialize_datetime}
21 def json(self, **kwargs: typing.Any) -> str: 22 kwargs_with_defaults: typing.Any = { 23 "by_alias": True, 24 "exclude_unset": True, 25 **kwargs, 26 } 27 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
29 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 30 kwargs_with_defaults_exclude_unset: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 kwargs_with_defaults_exclude_none: typing.Any = { 36 "by_alias": True, 37 "exclude_none": True, 38 **kwargs, 39 } 40 41 return deep_union_pydantic_dicts( 42 super().dict(**kwargs_with_defaults_exclude_unset), 43 super().dict(**kwargs_with_defaults_exclude_none), 44 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateAnnotationQueueRequest(pydantic_v1.BaseModel): 12 name: str 13 description: typing.Optional[str] = None 14 score_config_ids: typing.List[str] = pydantic_v1.Field(alias="scoreConfigIds") 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CreateChatPromptRequest(pydantic_v1.BaseModel): 13 name: str 14 prompt: typing.List[ChatMessageWithPlaceholders] 15 config: typing.Optional[typing.Any] = None 16 labels: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 17 """ 18 List of deployment labels of this prompt version. 19 """ 20 21 tags: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 22 """ 23 List of tags to apply to all versions of this prompt. 24 """ 25 26 commit_message: typing.Optional[str] = pydantic_v1.Field( 27 alias="commitMessage", default=None 28 ) 29 """ 30 Commit message for this prompt version. 31 """ 32 33 def json(self, **kwargs: typing.Any) -> str: 34 kwargs_with_defaults: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 return super().json(**kwargs_with_defaults) 40 41 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 42 kwargs_with_defaults_exclude_unset: typing.Any = { 43 "by_alias": True, 44 "exclude_unset": True, 45 **kwargs, 46 } 47 kwargs_with_defaults_exclude_none: typing.Any = { 48 "by_alias": True, 49 "exclude_none": True, 50 **kwargs, 51 } 52 53 return deep_union_pydantic_dicts( 54 super().dict(**kwargs_with_defaults_exclude_unset), 55 super().dict(**kwargs_with_defaults_exclude_none), 56 ) 57 58 class Config: 59 frozen = True 60 smart_union = True 61 allow_population_by_field_name = True 62 populate_by_name = True 63 extra = pydantic_v1.Extra.allow 64 json_encoders = {dt.datetime: serialize_datetime}
33 def json(self, **kwargs: typing.Any) -> str: 34 kwargs_with_defaults: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
41 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 42 kwargs_with_defaults_exclude_unset: typing.Any = { 43 "by_alias": True, 44 "exclude_unset": True, 45 **kwargs, 46 } 47 kwargs_with_defaults_exclude_none: typing.Any = { 48 "by_alias": True, 49 "exclude_none": True, 50 **kwargs, 51 } 52 53 return deep_union_pydantic_dicts( 54 super().dict(**kwargs_with_defaults_exclude_unset), 55 super().dict(**kwargs_with_defaults_exclude_none), 56 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateCommentRequest(pydantic_v1.BaseModel): 12 project_id: str = pydantic_v1.Field(alias="projectId") 13 """ 14 The id of the project to attach the comment to. 15 """ 16 17 object_type: str = pydantic_v1.Field(alias="objectType") 18 """ 19 The type of the object to attach the comment to (trace, observation, session, prompt). 20 """ 21 22 object_id: str = pydantic_v1.Field(alias="objectId") 23 """ 24 The id of the object to attach the comment to. If this does not reference a valid existing object, an error will be thrown. 25 """ 26 27 content: str = pydantic_v1.Field() 28 """ 29 The content of the comment. May include markdown. Currently limited to 3000 characters. 30 """ 31 32 author_user_id: typing.Optional[str] = pydantic_v1.Field( 33 alias="authorUserId", default=None 34 ) 35 """ 36 The id of the user who created the comment. 37 """ 38 39 def json(self, **kwargs: typing.Any) -> str: 40 kwargs_with_defaults: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 return super().json(**kwargs_with_defaults) 46 47 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 48 kwargs_with_defaults_exclude_unset: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 kwargs_with_defaults_exclude_none: typing.Any = { 54 "by_alias": True, 55 "exclude_none": True, 56 **kwargs, 57 } 58 59 return deep_union_pydantic_dicts( 60 super().dict(**kwargs_with_defaults_exclude_unset), 61 super().dict(**kwargs_with_defaults_exclude_none), 62 ) 63 64 class Config: 65 frozen = True 66 smart_union = True 67 allow_population_by_field_name = True 68 populate_by_name = True 69 extra = pydantic_v1.Extra.allow 70 json_encoders = {dt.datetime: serialize_datetime}
The type of the object to attach the comment to (trace, observation, session, prompt).
The id of the object to attach the comment to. If this does not reference a valid existing object, an error will be thrown.
The content of the comment. May include markdown. Currently limited to 3000 characters.
39 def json(self, **kwargs: typing.Any) -> str: 40 kwargs_with_defaults: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
47 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 48 kwargs_with_defaults_exclude_unset: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 kwargs_with_defaults_exclude_none: typing.Any = { 54 "by_alias": True, 55 "exclude_none": True, 56 **kwargs, 57 } 58 59 return deep_union_pydantic_dicts( 60 super().dict(**kwargs_with_defaults_exclude_unset), 61 super().dict(**kwargs_with_defaults_exclude_none), 62 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateCommentResponse(pydantic_v1.BaseModel): 12 id: str = pydantic_v1.Field() 13 """ 14 The id of the created object in Langfuse 15 """ 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CreateDatasetItemRequest(pydantic_v1.BaseModel): 13 dataset_name: str = pydantic_v1.Field(alias="datasetName") 14 input: typing.Optional[typing.Any] = None 15 expected_output: typing.Optional[typing.Any] = pydantic_v1.Field( 16 alias="expectedOutput", default=None 17 ) 18 metadata: typing.Optional[typing.Any] = None 19 source_trace_id: typing.Optional[str] = pydantic_v1.Field( 20 alias="sourceTraceId", default=None 21 ) 22 source_observation_id: typing.Optional[str] = pydantic_v1.Field( 23 alias="sourceObservationId", default=None 24 ) 25 id: typing.Optional[str] = pydantic_v1.Field(default=None) 26 """ 27 Dataset items are upserted on their id. Id needs to be unique (project-level) and cannot be reused across datasets. 28 """ 29 30 status: typing.Optional[DatasetStatus] = pydantic_v1.Field(default=None) 31 """ 32 Defaults to ACTIVE for newly created items 33 """ 34 35 def json(self, **kwargs: typing.Any) -> str: 36 kwargs_with_defaults: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 return super().json(**kwargs_with_defaults) 42 43 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 44 kwargs_with_defaults_exclude_unset: typing.Any = { 45 "by_alias": True, 46 "exclude_unset": True, 47 **kwargs, 48 } 49 kwargs_with_defaults_exclude_none: typing.Any = { 50 "by_alias": True, 51 "exclude_none": True, 52 **kwargs, 53 } 54 55 return deep_union_pydantic_dicts( 56 super().dict(**kwargs_with_defaults_exclude_unset), 57 super().dict(**kwargs_with_defaults_exclude_none), 58 ) 59 60 class Config: 61 frozen = True 62 smart_union = True 63 allow_population_by_field_name = True 64 populate_by_name = True 65 extra = pydantic_v1.Extra.allow 66 json_encoders = {dt.datetime: serialize_datetime}
Dataset items are upserted on their id. Id needs to be unique (project-level) and cannot be reused across datasets.
35 def json(self, **kwargs: typing.Any) -> str: 36 kwargs_with_defaults: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
43 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 44 kwargs_with_defaults_exclude_unset: typing.Any = { 45 "by_alias": True, 46 "exclude_unset": True, 47 **kwargs, 48 } 49 kwargs_with_defaults_exclude_none: typing.Any = { 50 "by_alias": True, 51 "exclude_none": True, 52 **kwargs, 53 } 54 55 return deep_union_pydantic_dicts( 56 super().dict(**kwargs_with_defaults_exclude_unset), 57 super().dict(**kwargs_with_defaults_exclude_none), 58 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateDatasetRequest(pydantic_v1.BaseModel): 12 name: str 13 description: typing.Optional[str] = None 14 metadata: typing.Optional[typing.Any] = None 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 extra = pydantic_v1.Extra.allow 45 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateDatasetRunItemRequest(pydantic_v1.BaseModel): 12 run_name: str = pydantic_v1.Field(alias="runName") 13 run_description: typing.Optional[str] = pydantic_v1.Field( 14 alias="runDescription", default=None 15 ) 16 """ 17 Description of the run. If run exists, description will be updated. 18 """ 19 20 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 21 """ 22 Metadata of the dataset run, updates run if run already exists 23 """ 24 25 dataset_item_id: str = pydantic_v1.Field(alias="datasetItemId") 26 observation_id: typing.Optional[str] = pydantic_v1.Field( 27 alias="observationId", default=None 28 ) 29 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 30 """ 31 traceId should always be provided. For compatibility with older SDK versions it can also be inferred from the provided observationId. 32 """ 33 34 def json(self, **kwargs: typing.Any) -> str: 35 kwargs_with_defaults: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 return super().json(**kwargs_with_defaults) 41 42 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 43 kwargs_with_defaults_exclude_unset: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 kwargs_with_defaults_exclude_none: typing.Any = { 49 "by_alias": True, 50 "exclude_none": True, 51 **kwargs, 52 } 53 54 return deep_union_pydantic_dicts( 55 super().dict(**kwargs_with_defaults_exclude_unset), 56 super().dict(**kwargs_with_defaults_exclude_none), 57 ) 58 59 class Config: 60 frozen = True 61 smart_union = True 62 allow_population_by_field_name = True 63 populate_by_name = True 64 extra = pydantic_v1.Extra.allow 65 json_encoders = {dt.datetime: serialize_datetime}
traceId should always be provided. For compatibility with older SDK versions it can also be inferred from the provided observationId.
34 def json(self, **kwargs: typing.Any) -> str: 35 kwargs_with_defaults: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
42 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 43 kwargs_with_defaults_exclude_unset: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 kwargs_with_defaults_exclude_none: typing.Any = { 49 "by_alias": True, 50 "exclude_none": True, 51 **kwargs, 52 } 53 54 return deep_union_pydantic_dicts( 55 super().dict(**kwargs_with_defaults_exclude_unset), 56 super().dict(**kwargs_with_defaults_exclude_none), 57 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CreateEventBody(OptionalObservationBody): 13 id: typing.Optional[str] = None 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateEventEvent(BaseEvent): 14 body: CreateEventBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
15class CreateGenerationBody(CreateSpanBody): 16 completion_start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 17 alias="completionStartTime", default=None 18 ) 19 model: typing.Optional[str] = None 20 model_parameters: typing.Optional[typing.Dict[str, MapValue]] = pydantic_v1.Field( 21 alias="modelParameters", default=None 22 ) 23 usage: typing.Optional[IngestionUsage] = None 24 usage_details: typing.Optional[UsageDetails] = pydantic_v1.Field( 25 alias="usageDetails", default=None 26 ) 27 cost_details: typing.Optional[typing.Dict[str, float]] = pydantic_v1.Field( 28 alias="costDetails", default=None 29 ) 30 prompt_name: typing.Optional[str] = pydantic_v1.Field( 31 alias="promptName", default=None 32 ) 33 prompt_version: typing.Optional[int] = pydantic_v1.Field( 34 alias="promptVersion", default=None 35 ) 36 37 def json(self, **kwargs: typing.Any) -> str: 38 kwargs_with_defaults: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 return super().json(**kwargs_with_defaults) 44 45 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 46 kwargs_with_defaults_exclude_unset: typing.Any = { 47 "by_alias": True, 48 "exclude_unset": True, 49 **kwargs, 50 } 51 kwargs_with_defaults_exclude_none: typing.Any = { 52 "by_alias": True, 53 "exclude_none": True, 54 **kwargs, 55 } 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), 59 super().dict(**kwargs_with_defaults_exclude_none), 60 ) 61 62 class Config: 63 frozen = True 64 smart_union = True 65 allow_population_by_field_name = True 66 populate_by_name = True 67 extra = pydantic_v1.Extra.allow 68 json_encoders = {dt.datetime: serialize_datetime}
37 def json(self, **kwargs: typing.Any) -> str: 38 kwargs_with_defaults: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
45 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 46 kwargs_with_defaults_exclude_unset: typing.Any = { 47 "by_alias": True, 48 "exclude_unset": True, 49 **kwargs, 50 } 51 kwargs_with_defaults_exclude_none: typing.Any = { 52 "by_alias": True, 53 "exclude_none": True, 54 **kwargs, 55 } 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), 59 super().dict(**kwargs_with_defaults_exclude_none), 60 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateGenerationEvent(BaseEvent): 14 body: CreateGenerationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CreateModelRequest(pydantic_v1.BaseModel): 13 model_name: str = pydantic_v1.Field(alias="modelName") 14 """ 15 Name of the model definition. If multiple with the same name exist, they are applied in the following order: (1) custom over built-in, (2) newest according to startTime where model.startTime<observation.startTime 16 """ 17 18 match_pattern: str = pydantic_v1.Field(alias="matchPattern") 19 """ 20 Regex pattern which matches this model definition to generation.model. Useful in case of fine-tuned models. If you want to exact match, use `(?i)^modelname$` 21 """ 22 23 start_date: typing.Optional[dt.datetime] = pydantic_v1.Field( 24 alias="startDate", default=None 25 ) 26 """ 27 Apply only to generations which are newer than this ISO date. 28 """ 29 30 unit: typing.Optional[ModelUsageUnit] = pydantic_v1.Field(default=None) 31 """ 32 Unit used by this model. 33 """ 34 35 input_price: typing.Optional[float] = pydantic_v1.Field( 36 alias="inputPrice", default=None 37 ) 38 """ 39 Price (USD) per input unit 40 """ 41 42 output_price: typing.Optional[float] = pydantic_v1.Field( 43 alias="outputPrice", default=None 44 ) 45 """ 46 Price (USD) per output unit 47 """ 48 49 total_price: typing.Optional[float] = pydantic_v1.Field( 50 alias="totalPrice", default=None 51 ) 52 """ 53 Price (USD) per total units. Cannot be set if input or output price is set. 54 """ 55 56 tokenizer_id: typing.Optional[str] = pydantic_v1.Field( 57 alias="tokenizerId", default=None 58 ) 59 """ 60 Optional. Tokenizer to be applied to observations which match to this model. See docs for more details. 61 """ 62 63 tokenizer_config: typing.Optional[typing.Any] = pydantic_v1.Field( 64 alias="tokenizerConfig", default=None 65 ) 66 """ 67 Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details. 68 """ 69 70 def json(self, **kwargs: typing.Any) -> str: 71 kwargs_with_defaults: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 return super().json(**kwargs_with_defaults) 77 78 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 79 kwargs_with_defaults_exclude_unset: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 kwargs_with_defaults_exclude_none: typing.Any = { 85 "by_alias": True, 86 "exclude_none": True, 87 **kwargs, 88 } 89 90 return deep_union_pydantic_dicts( 91 super().dict(**kwargs_with_defaults_exclude_unset), 92 super().dict(**kwargs_with_defaults_exclude_none), 93 ) 94 95 class Config: 96 frozen = True 97 smart_union = True 98 allow_population_by_field_name = True 99 populate_by_name = True 100 extra = pydantic_v1.Extra.allow 101 json_encoders = {dt.datetime: serialize_datetime}
Name of the model definition. If multiple with the same name exist, they are applied in the following order: (1) custom over built-in, (2) newest according to startTime where model.startTime
Regex pattern which matches this model definition to generation.model. Useful in case of fine-tuned models. If you want to exact match, use (?i)^modelname$
Apply only to generations which are newer than this ISO date.
Price (USD) per total units. Cannot be set if input or output price is set.
Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
70 def json(self, **kwargs: typing.Any) -> str: 71 kwargs_with_defaults: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
78 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 79 kwargs_with_defaults_exclude_unset: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 kwargs_with_defaults_exclude_none: typing.Any = { 85 "by_alias": True, 86 "exclude_none": True, 87 **kwargs, 88 } 89 90 return deep_union_pydantic_dicts( 91 super().dict(**kwargs_with_defaults_exclude_unset), 92 super().dict(**kwargs_with_defaults_exclude_none), 93 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateObservationEvent(BaseEvent): 14 body: ObservationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class CreatePromptRequest_Chat(pydantic_v1.BaseModel): 15 name: str 16 prompt: typing.List[ChatMessageWithPlaceholders] 17 config: typing.Optional[typing.Any] = None 18 labels: typing.Optional[typing.List[str]] = None 19 tags: typing.Optional[typing.List[str]] = None 20 commit_message: typing.Optional[str] = pydantic_v1.Field( 21 alias="commitMessage", default=None 22 ) 23 type: typing.Literal["chat"] = "chat" 24 25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults) 32 33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 ) 49 50 class Config: 51 frozen = True 52 smart_union = True 53 allow_population_by_field_name = True 54 populate_by_name = True 55 extra = pydantic_v1.Extra.allow 56 json_encoders = {dt.datetime: serialize_datetime}
25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
59class CreatePromptRequest_Text(pydantic_v1.BaseModel): 60 name: str 61 prompt: str 62 config: typing.Optional[typing.Any] = None 63 labels: typing.Optional[typing.List[str]] = None 64 tags: typing.Optional[typing.List[str]] = None 65 commit_message: typing.Optional[str] = pydantic_v1.Field( 66 alias="commitMessage", default=None 67 ) 68 type: typing.Literal["text"] = "text" 69 70 def json(self, **kwargs: typing.Any) -> str: 71 kwargs_with_defaults: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 return super().json(**kwargs_with_defaults) 77 78 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 79 kwargs_with_defaults_exclude_unset: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 kwargs_with_defaults_exclude_none: typing.Any = { 85 "by_alias": True, 86 "exclude_none": True, 87 **kwargs, 88 } 89 90 return deep_union_pydantic_dicts( 91 super().dict(**kwargs_with_defaults_exclude_unset), 92 super().dict(**kwargs_with_defaults_exclude_none), 93 ) 94 95 class Config: 96 frozen = True 97 smart_union = True 98 allow_population_by_field_name = True 99 populate_by_name = True 100 extra = pydantic_v1.Extra.allow 101 json_encoders = {dt.datetime: serialize_datetime}
70 def json(self, **kwargs: typing.Any) -> str: 71 kwargs_with_defaults: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
78 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 79 kwargs_with_defaults_exclude_unset: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 kwargs_with_defaults_exclude_none: typing.Any = { 85 "by_alias": True, 86 "exclude_none": True, 87 **kwargs, 88 } 89 90 return deep_union_pydantic_dicts( 91 super().dict(**kwargs_with_defaults_exclude_unset), 92 super().dict(**kwargs_with_defaults_exclude_none), 93 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateScoreConfigRequest(pydantic_v1.BaseModel): 14 name: str 15 data_type: ScoreDataType = pydantic_v1.Field(alias="dataType") 16 categories: typing.Optional[typing.List[ConfigCategory]] = pydantic_v1.Field( 17 default=None 18 ) 19 """ 20 Configure custom categories for categorical scores. Pass a list of objects with `label` and `value` properties. Categories are autogenerated for boolean configs and cannot be passed 21 """ 22 23 min_value: typing.Optional[float] = pydantic_v1.Field( 24 alias="minValue", default=None 25 ) 26 """ 27 Configure a minimum value for numerical scores. If not set, the minimum value defaults to -∞ 28 """ 29 30 max_value: typing.Optional[float] = pydantic_v1.Field( 31 alias="maxValue", default=None 32 ) 33 """ 34 Configure a maximum value for numerical scores. If not set, the maximum value defaults to +∞ 35 """ 36 37 description: typing.Optional[str] = pydantic_v1.Field(default=None) 38 """ 39 Description is shown across the Langfuse UI and can be used to e.g. explain the config categories in detail, why a numeric range was set, or provide additional context on config name or usage 40 """ 41 42 def json(self, **kwargs: typing.Any) -> str: 43 kwargs_with_defaults: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 return super().json(**kwargs_with_defaults) 49 50 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 51 kwargs_with_defaults_exclude_unset: typing.Any = { 52 "by_alias": True, 53 "exclude_unset": True, 54 **kwargs, 55 } 56 kwargs_with_defaults_exclude_none: typing.Any = { 57 "by_alias": True, 58 "exclude_none": True, 59 **kwargs, 60 } 61 62 return deep_union_pydantic_dicts( 63 super().dict(**kwargs_with_defaults_exclude_unset), 64 super().dict(**kwargs_with_defaults_exclude_none), 65 ) 66 67 class Config: 68 frozen = True 69 smart_union = True 70 allow_population_by_field_name = True 71 populate_by_name = True 72 extra = pydantic_v1.Extra.allow 73 json_encoders = {dt.datetime: serialize_datetime}
Configure custom categories for categorical scores. Pass a list of objects with label
and value
properties. Categories are autogenerated for boolean configs and cannot be passed
Configure a minimum value for numerical scores. If not set, the minimum value defaults to -∞
Configure a maximum value for numerical scores. If not set, the maximum value defaults to +∞
Description is shown across the Langfuse UI and can be used to e.g. explain the config categories in detail, why a numeric range was set, or provide additional context on config name or usage
42 def json(self, **kwargs: typing.Any) -> str: 43 kwargs_with_defaults: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
50 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 51 kwargs_with_defaults_exclude_unset: typing.Any = { 52 "by_alias": True, 53 "exclude_unset": True, 54 **kwargs, 55 } 56 kwargs_with_defaults_exclude_none: typing.Any = { 57 "by_alias": True, 58 "exclude_none": True, 59 **kwargs, 60 } 61 62 return deep_union_pydantic_dicts( 63 super().dict(**kwargs_with_defaults_exclude_unset), 64 super().dict(**kwargs_with_defaults_exclude_none), 65 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateScoreRequest(pydantic_v1.BaseModel): 14 """ 15 Examples 16 -------- 17 from langfuse import CreateScoreRequest 18 19 CreateScoreRequest( 20 name="novelty", 21 value=0.9, 22 trace_id="cdef-1234-5678-90ab", 23 ) 24 """ 25 26 id: typing.Optional[str] = None 27 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 28 session_id: typing.Optional[str] = pydantic_v1.Field( 29 alias="sessionId", default=None 30 ) 31 observation_id: typing.Optional[str] = pydantic_v1.Field( 32 alias="observationId", default=None 33 ) 34 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 35 alias="datasetRunId", default=None 36 ) 37 name: str 38 value: CreateScoreValue = pydantic_v1.Field() 39 """ 40 The value of the score. Must be passed as string for categorical scores, and numeric for boolean and numeric scores. Boolean score values must equal either 1 or 0 (true or false) 41 """ 42 43 comment: typing.Optional[str] = None 44 metadata: typing.Optional[typing.Any] = None 45 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 46 """ 47 The environment of the score. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'. 48 """ 49 50 data_type: typing.Optional[ScoreDataType] = pydantic_v1.Field( 51 alias="dataType", default=None 52 ) 53 """ 54 The data type of the score. When passing a configId this field is inferred. Otherwise, this field must be passed or will default to numeric. 55 """ 56 57 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 58 """ 59 Reference a score config on a score. The unique langfuse identifier of a score config. When passing this field, the dataType and stringValue fields are automatically populated. 60 """ 61 62 def json(self, **kwargs: typing.Any) -> str: 63 kwargs_with_defaults: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 return super().json(**kwargs_with_defaults) 69 70 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 71 kwargs_with_defaults_exclude_unset: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 kwargs_with_defaults_exclude_none: typing.Any = { 77 "by_alias": True, 78 "exclude_none": True, 79 **kwargs, 80 } 81 82 return deep_union_pydantic_dicts( 83 super().dict(**kwargs_with_defaults_exclude_unset), 84 super().dict(**kwargs_with_defaults_exclude_none), 85 ) 86 87 class Config: 88 frozen = True 89 smart_union = True 90 allow_population_by_field_name = True 91 populate_by_name = True 92 extra = pydantic_v1.Extra.allow 93 json_encoders = {dt.datetime: serialize_datetime}
Examples
from langfuse import CreateScoreRequest
CreateScoreRequest( name="novelty", value=0.9, trace_id="cdef-1234-5678-90ab", )
The value of the score. Must be passed as string for categorical scores, and numeric for boolean and numeric scores. Boolean score values must equal either 1 or 0 (true or false)
The environment of the score. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'.
The data type of the score. When passing a configId this field is inferred. Otherwise, this field must be passed or will default to numeric.
Reference a score config on a score. The unique langfuse identifier of a score config. When passing this field, the dataType and stringValue fields are automatically populated.
62 def json(self, **kwargs: typing.Any) -> str: 63 kwargs_with_defaults: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
70 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 71 kwargs_with_defaults_exclude_unset: typing.Any = { 72 "by_alias": True, 73 "exclude_unset": True, 74 **kwargs, 75 } 76 kwargs_with_defaults_exclude_none: typing.Any = { 77 "by_alias": True, 78 "exclude_none": True, 79 **kwargs, 80 } 81 82 return deep_union_pydantic_dicts( 83 super().dict(**kwargs_with_defaults_exclude_unset), 84 super().dict(**kwargs_with_defaults_exclude_none), 85 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateScoreResponse(pydantic_v1.BaseModel): 12 id: str = pydantic_v1.Field() 13 """ 14 The id of the created object in Langfuse 15 """ 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class CreateSpanBody(CreateEventBody): 13 end_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 14 alias="endTime", default=None 15 ) 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 allow_population_by_field_name = True 46 populate_by_name = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class CreateSpanEvent(BaseEvent): 14 body: CreateSpanBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class CreateTextPromptRequest(pydantic_v1.BaseModel): 12 name: str 13 prompt: str 14 config: typing.Optional[typing.Any] = None 15 labels: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 16 """ 17 List of deployment labels of this prompt version. 18 """ 19 20 tags: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 21 """ 22 List of tags to apply to all versions of this prompt. 23 """ 24 25 commit_message: typing.Optional[str] = pydantic_v1.Field( 26 alias="commitMessage", default=None 27 ) 28 """ 29 Commit message for this prompt version. 30 """ 31 32 def json(self, **kwargs: typing.Any) -> str: 33 kwargs_with_defaults: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 return super().json(**kwargs_with_defaults) 39 40 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 41 kwargs_with_defaults_exclude_unset: typing.Any = { 42 "by_alias": True, 43 "exclude_unset": True, 44 **kwargs, 45 } 46 kwargs_with_defaults_exclude_none: typing.Any = { 47 "by_alias": True, 48 "exclude_none": True, 49 **kwargs, 50 } 51 52 return deep_union_pydantic_dicts( 53 super().dict(**kwargs_with_defaults_exclude_unset), 54 super().dict(**kwargs_with_defaults_exclude_none), 55 ) 56 57 class Config: 58 frozen = True 59 smart_union = True 60 allow_population_by_field_name = True 61 populate_by_name = True 62 extra = pydantic_v1.Extra.allow 63 json_encoders = {dt.datetime: serialize_datetime}
32 def json(self, **kwargs: typing.Any) -> str: 33 kwargs_with_defaults: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
40 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 41 kwargs_with_defaults_exclude_unset: typing.Any = { 42 "by_alias": True, 43 "exclude_unset": True, 44 **kwargs, 45 } 46 kwargs_with_defaults_exclude_none: typing.Any = { 47 "by_alias": True, 48 "exclude_none": True, 49 **kwargs, 50 } 51 52 return deep_union_pydantic_dicts( 53 super().dict(**kwargs_with_defaults_exclude_unset), 54 super().dict(**kwargs_with_defaults_exclude_none), 55 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class Dataset(pydantic_v1.BaseModel): 12 id: str 13 name: str 14 description: typing.Optional[str] = None 15 metadata: typing.Optional[typing.Any] = None 16 project_id: str = pydantic_v1.Field(alias="projectId") 17 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 18 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 19 20 def json(self, **kwargs: typing.Any) -> str: 21 kwargs_with_defaults: typing.Any = { 22 "by_alias": True, 23 "exclude_unset": True, 24 **kwargs, 25 } 26 return super().json(**kwargs_with_defaults) 27 28 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 29 kwargs_with_defaults_exclude_unset: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 kwargs_with_defaults_exclude_none: typing.Any = { 35 "by_alias": True, 36 "exclude_none": True, 37 **kwargs, 38 } 39 40 return deep_union_pydantic_dicts( 41 super().dict(**kwargs_with_defaults_exclude_unset), 42 super().dict(**kwargs_with_defaults_exclude_none), 43 ) 44 45 class Config: 46 frozen = True 47 smart_union = True 48 allow_population_by_field_name = True 49 populate_by_name = True 50 extra = pydantic_v1.Extra.allow 51 json_encoders = {dt.datetime: serialize_datetime}
20 def json(self, **kwargs: typing.Any) -> str: 21 kwargs_with_defaults: typing.Any = { 22 "by_alias": True, 23 "exclude_unset": True, 24 **kwargs, 25 } 26 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
28 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 29 kwargs_with_defaults_exclude_unset: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 kwargs_with_defaults_exclude_none: typing.Any = { 35 "by_alias": True, 36 "exclude_none": True, 37 **kwargs, 38 } 39 40 return deep_union_pydantic_dicts( 41 super().dict(**kwargs_with_defaults_exclude_unset), 42 super().dict(**kwargs_with_defaults_exclude_none), 43 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class DatasetItem(pydantic_v1.BaseModel): 13 id: str 14 status: DatasetStatus 15 input: typing.Optional[typing.Any] = None 16 expected_output: typing.Optional[typing.Any] = pydantic_v1.Field( 17 alias="expectedOutput", default=None 18 ) 19 metadata: typing.Optional[typing.Any] = None 20 source_trace_id: typing.Optional[str] = pydantic_v1.Field( 21 alias="sourceTraceId", default=None 22 ) 23 source_observation_id: typing.Optional[str] = pydantic_v1.Field( 24 alias="sourceObservationId", default=None 25 ) 26 dataset_id: str = pydantic_v1.Field(alias="datasetId") 27 dataset_name: str = pydantic_v1.Field(alias="datasetName") 28 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 29 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 30 31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults) 38 39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 ) 55 56 class Config: 57 frozen = True 58 smart_union = True 59 allow_population_by_field_name = True 60 populate_by_name = True 61 extra = pydantic_v1.Extra.allow 62 json_encoders = {dt.datetime: serialize_datetime}
31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DatasetRun(pydantic_v1.BaseModel): 12 id: str = pydantic_v1.Field() 13 """ 14 Unique identifier of the dataset run 15 """ 16 17 name: str = pydantic_v1.Field() 18 """ 19 Name of the dataset run 20 """ 21 22 description: typing.Optional[str] = pydantic_v1.Field(default=None) 23 """ 24 Description of the run 25 """ 26 27 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 28 """ 29 Metadata of the dataset run 30 """ 31 32 dataset_id: str = pydantic_v1.Field(alias="datasetId") 33 """ 34 Id of the associated dataset 35 """ 36 37 dataset_name: str = pydantic_v1.Field(alias="datasetName") 38 """ 39 Name of the associated dataset 40 """ 41 42 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 43 """ 44 The date and time when the dataset run was created 45 """ 46 47 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 48 """ 49 The date and time when the dataset run was last updated 50 """ 51 52 def json(self, **kwargs: typing.Any) -> str: 53 kwargs_with_defaults: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 return super().json(**kwargs_with_defaults) 59 60 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 61 kwargs_with_defaults_exclude_unset: typing.Any = { 62 "by_alias": True, 63 "exclude_unset": True, 64 **kwargs, 65 } 66 kwargs_with_defaults_exclude_none: typing.Any = { 67 "by_alias": True, 68 "exclude_none": True, 69 **kwargs, 70 } 71 72 return deep_union_pydantic_dicts( 73 super().dict(**kwargs_with_defaults_exclude_unset), 74 super().dict(**kwargs_with_defaults_exclude_none), 75 ) 76 77 class Config: 78 frozen = True 79 smart_union = True 80 allow_population_by_field_name = True 81 populate_by_name = True 82 extra = pydantic_v1.Extra.allow 83 json_encoders = {dt.datetime: serialize_datetime}
52 def json(self, **kwargs: typing.Any) -> str: 53 kwargs_with_defaults: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
60 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 61 kwargs_with_defaults_exclude_unset: typing.Any = { 62 "by_alias": True, 63 "exclude_unset": True, 64 **kwargs, 65 } 66 kwargs_with_defaults_exclude_none: typing.Any = { 67 "by_alias": True, 68 "exclude_none": True, 69 **kwargs, 70 } 71 72 return deep_union_pydantic_dicts( 73 super().dict(**kwargs_with_defaults_exclude_unset), 74 super().dict(**kwargs_with_defaults_exclude_none), 75 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DatasetRunItem(pydantic_v1.BaseModel): 12 id: str 13 dataset_run_id: str = pydantic_v1.Field(alias="datasetRunId") 14 dataset_run_name: str = pydantic_v1.Field(alias="datasetRunName") 15 dataset_item_id: str = pydantic_v1.Field(alias="datasetItemId") 16 trace_id: str = pydantic_v1.Field(alias="traceId") 17 observation_id: typing.Optional[str] = pydantic_v1.Field( 18 alias="observationId", default=None 19 ) 20 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 21 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 22 23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults) 30 31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 ) 47 48 class Config: 49 frozen = True 50 smart_union = True 51 allow_population_by_field_name = True 52 populate_by_name = True 53 extra = pydantic_v1.Extra.allow 54 json_encoders = {dt.datetime: serialize_datetime}
23 def json(self, **kwargs: typing.Any) -> str: 24 kwargs_with_defaults: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
31 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 32 kwargs_with_defaults_exclude_unset: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 kwargs_with_defaults_exclude_none: typing.Any = { 38 "by_alias": True, 39 "exclude_none": True, 40 **kwargs, 41 } 42 43 return deep_union_pydantic_dicts( 44 super().dict(**kwargs_with_defaults_exclude_unset), 45 super().dict(**kwargs_with_defaults_exclude_none), 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class DatasetRunWithItems(DatasetRun): 14 dataset_run_items: typing.List[DatasetRunItem] = pydantic_v1.Field( 15 alias="datasetRunItems" 16 ) 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class DatasetStatus(str, enum.Enum): 11 ACTIVE = "ACTIVE" 12 ARCHIVED = "ARCHIVED" 13 14 def visit( 15 self, 16 active: typing.Callable[[], T_Result], 17 archived: typing.Callable[[], T_Result], 18 ) -> T_Result: 19 if self is DatasetStatus.ACTIVE: 20 return active() 21 if self is DatasetStatus.ARCHIVED: 22 return archived()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
11class DeleteAnnotationQueueAssignmentResponse(pydantic_v1.BaseModel): 12 success: bool 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DeleteAnnotationQueueItemResponse(pydantic_v1.BaseModel): 12 success: bool 13 message: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DeleteDatasetItemResponse(pydantic_v1.BaseModel): 12 message: str = pydantic_v1.Field() 13 """ 14 Success message after deletion 15 """ 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DeleteDatasetRunResponse(pydantic_v1.BaseModel): 12 message: str 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class DeleteTraceResponse(pydantic_v1.BaseModel): 12 message: str 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class EmptyResponse(pydantic_v1.BaseModel): 12 """ 13 Empty response for 204 No Content responses 14 """ 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 extra = pydantic_v1.Extra.allow 45 json_encoders = {dt.datetime: serialize_datetime}
Empty response for 204 No Content responses
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
9class Error(ApiError): 10 def __init__(self, body: typing.Any): 11 super().__init__(status_code=400, body=body)
Common base class for all non-exit exceptions.
11class FilterConfig(pydantic_v1.BaseModel): 12 supported: bool 13 max_results: int = pydantic_v1.Field(alias="maxResults") 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class GetCommentsResponse(pydantic_v1.BaseModel): 14 data: typing.List[Comment] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class GetMediaResponse(pydantic_v1.BaseModel): 12 media_id: str = pydantic_v1.Field(alias="mediaId") 13 """ 14 The unique langfuse identifier of a media record 15 """ 16 17 content_type: str = pydantic_v1.Field(alias="contentType") 18 """ 19 The MIME type of the media record 20 """ 21 22 content_length: int = pydantic_v1.Field(alias="contentLength") 23 """ 24 The size of the media record in bytes 25 """ 26 27 uploaded_at: dt.datetime = pydantic_v1.Field(alias="uploadedAt") 28 """ 29 The date and time when the media record was uploaded 30 """ 31 32 url: str = pydantic_v1.Field() 33 """ 34 The download URL of the media record 35 """ 36 37 url_expiry: str = pydantic_v1.Field(alias="urlExpiry") 38 """ 39 The expiry date and time of the media record download URL 40 """ 41 42 def json(self, **kwargs: typing.Any) -> str: 43 kwargs_with_defaults: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 return super().json(**kwargs_with_defaults) 49 50 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 51 kwargs_with_defaults_exclude_unset: typing.Any = { 52 "by_alias": True, 53 "exclude_unset": True, 54 **kwargs, 55 } 56 kwargs_with_defaults_exclude_none: typing.Any = { 57 "by_alias": True, 58 "exclude_none": True, 59 **kwargs, 60 } 61 62 return deep_union_pydantic_dicts( 63 super().dict(**kwargs_with_defaults_exclude_unset), 64 super().dict(**kwargs_with_defaults_exclude_none), 65 ) 66 67 class Config: 68 frozen = True 69 smart_union = True 70 allow_population_by_field_name = True 71 populate_by_name = True 72 extra = pydantic_v1.Extra.allow 73 json_encoders = {dt.datetime: serialize_datetime}
42 def json(self, **kwargs: typing.Any) -> str: 43 kwargs_with_defaults: typing.Any = { 44 "by_alias": True, 45 "exclude_unset": True, 46 **kwargs, 47 } 48 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
50 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 51 kwargs_with_defaults_exclude_unset: typing.Any = { 52 "by_alias": True, 53 "exclude_unset": True, 54 **kwargs, 55 } 56 kwargs_with_defaults_exclude_none: typing.Any = { 57 "by_alias": True, 58 "exclude_none": True, 59 **kwargs, 60 } 61 62 return deep_union_pydantic_dicts( 63 super().dict(**kwargs_with_defaults_exclude_unset), 64 super().dict(**kwargs_with_defaults_exclude_none), 65 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class GetMediaUploadUrlRequest(pydantic_v1.BaseModel): 13 trace_id: str = pydantic_v1.Field(alias="traceId") 14 """ 15 The trace ID associated with the media record 16 """ 17 18 observation_id: typing.Optional[str] = pydantic_v1.Field( 19 alias="observationId", default=None 20 ) 21 """ 22 The observation ID associated with the media record. If the media record is associated directly with a trace, this will be null. 23 """ 24 25 content_type: MediaContentType = pydantic_v1.Field(alias="contentType") 26 content_length: int = pydantic_v1.Field(alias="contentLength") 27 """ 28 The size of the media record in bytes 29 """ 30 31 sha_256_hash: str = pydantic_v1.Field(alias="sha256Hash") 32 """ 33 The SHA-256 hash of the media record 34 """ 35 36 field: str = pydantic_v1.Field() 37 """ 38 The trace / observation field the media record is associated with. This can be one of `input`, `output`, `metadata` 39 """ 40 41 def json(self, **kwargs: typing.Any) -> str: 42 kwargs_with_defaults: typing.Any = { 43 "by_alias": True, 44 "exclude_unset": True, 45 **kwargs, 46 } 47 return super().json(**kwargs_with_defaults) 48 49 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 50 kwargs_with_defaults_exclude_unset: typing.Any = { 51 "by_alias": True, 52 "exclude_unset": True, 53 **kwargs, 54 } 55 kwargs_with_defaults_exclude_none: typing.Any = { 56 "by_alias": True, 57 "exclude_none": True, 58 **kwargs, 59 } 60 61 return deep_union_pydantic_dicts( 62 super().dict(**kwargs_with_defaults_exclude_unset), 63 super().dict(**kwargs_with_defaults_exclude_none), 64 ) 65 66 class Config: 67 frozen = True 68 smart_union = True 69 allow_population_by_field_name = True 70 populate_by_name = True 71 extra = pydantic_v1.Extra.allow 72 json_encoders = {dt.datetime: serialize_datetime}
The observation ID associated with the media record. If the media record is associated directly with a trace, this will be null.
The trace / observation field the media record is associated with. This can be one of input
, output
, metadata
41 def json(self, **kwargs: typing.Any) -> str: 42 kwargs_with_defaults: typing.Any = { 43 "by_alias": True, 44 "exclude_unset": True, 45 **kwargs, 46 } 47 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
49 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 50 kwargs_with_defaults_exclude_unset: typing.Any = { 51 "by_alias": True, 52 "exclude_unset": True, 53 **kwargs, 54 } 55 kwargs_with_defaults_exclude_none: typing.Any = { 56 "by_alias": True, 57 "exclude_none": True, 58 **kwargs, 59 } 60 61 return deep_union_pydantic_dicts( 62 super().dict(**kwargs_with_defaults_exclude_unset), 63 super().dict(**kwargs_with_defaults_exclude_none), 64 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class GetMediaUploadUrlResponse(pydantic_v1.BaseModel): 12 upload_url: typing.Optional[str] = pydantic_v1.Field( 13 alias="uploadUrl", default=None 14 ) 15 """ 16 The presigned upload URL. If the asset is already uploaded, this will be null 17 """ 18 19 media_id: str = pydantic_v1.Field(alias="mediaId") 20 """ 21 The unique langfuse identifier of a media record 22 """ 23 24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults) 31 32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 ) 48 49 class Config: 50 frozen = True 51 smart_union = True 52 allow_population_by_field_name = True 53 populate_by_name = True 54 extra = pydantic_v1.Extra.allow 55 json_encoders = {dt.datetime: serialize_datetime}
The presigned upload URL. If the asset is already uploaded, this will be null
24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class GetScoresResponse(pydantic_v1.BaseModel): 14 data: typing.List[GetScoresResponseData] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class GetScoresResponseDataBoolean(BooleanScore): 14 trace: typing.Optional[GetScoresResponseTraceData] = None 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class GetScoresResponseDataCategorical(CategoricalScore): 14 trace: typing.Optional[GetScoresResponseTraceData] = None 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class GetScoresResponseDataNumeric(NumericScore): 14 trace: typing.Optional[GetScoresResponseTraceData] = None 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
146class GetScoresResponseData_Boolean(pydantic_v1.BaseModel): 147 trace: typing.Optional[GetScoresResponseTraceData] = None 148 value: float 149 string_value: str = pydantic_v1.Field(alias="stringValue") 150 id: str 151 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 152 session_id: typing.Optional[str] = pydantic_v1.Field( 153 alias="sessionId", default=None 154 ) 155 observation_id: typing.Optional[str] = pydantic_v1.Field( 156 alias="observationId", default=None 157 ) 158 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 159 alias="datasetRunId", default=None 160 ) 161 name: str 162 source: ScoreSource 163 timestamp: dt.datetime 164 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 165 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 166 author_user_id: typing.Optional[str] = pydantic_v1.Field( 167 alias="authorUserId", default=None 168 ) 169 comment: typing.Optional[str] = None 170 metadata: typing.Optional[typing.Any] = None 171 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 172 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 173 environment: typing.Optional[str] = None 174 data_type: typing.Literal["BOOLEAN"] = pydantic_v1.Field( 175 alias="dataType", default="BOOLEAN" 176 ) 177 178 def json(self, **kwargs: typing.Any) -> str: 179 kwargs_with_defaults: typing.Any = { 180 "by_alias": True, 181 "exclude_unset": True, 182 **kwargs, 183 } 184 return super().json(**kwargs_with_defaults) 185 186 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 187 kwargs_with_defaults_exclude_unset: typing.Any = { 188 "by_alias": True, 189 "exclude_unset": True, 190 **kwargs, 191 } 192 kwargs_with_defaults_exclude_none: typing.Any = { 193 "by_alias": True, 194 "exclude_none": True, 195 **kwargs, 196 } 197 198 return deep_union_pydantic_dicts( 199 super().dict(**kwargs_with_defaults_exclude_unset), 200 super().dict(**kwargs_with_defaults_exclude_none), 201 ) 202 203 class Config: 204 frozen = True 205 smart_union = True 206 allow_population_by_field_name = True 207 populate_by_name = True 208 extra = pydantic_v1.Extra.allow 209 json_encoders = {dt.datetime: serialize_datetime}
178 def json(self, **kwargs: typing.Any) -> str: 179 kwargs_with_defaults: typing.Any = { 180 "by_alias": True, 181 "exclude_unset": True, 182 **kwargs, 183 } 184 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
186 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 187 kwargs_with_defaults_exclude_unset: typing.Any = { 188 "by_alias": True, 189 "exclude_unset": True, 190 **kwargs, 191 } 192 kwargs_with_defaults_exclude_none: typing.Any = { 193 "by_alias": True, 194 "exclude_none": True, 195 **kwargs, 196 } 197 198 return deep_union_pydantic_dicts( 199 super().dict(**kwargs_with_defaults_exclude_unset), 200 super().dict(**kwargs_with_defaults_exclude_none), 201 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
80class GetScoresResponseData_Categorical(pydantic_v1.BaseModel): 81 trace: typing.Optional[GetScoresResponseTraceData] = None 82 value: typing.Optional[float] = None 83 string_value: str = pydantic_v1.Field(alias="stringValue") 84 id: str 85 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 86 session_id: typing.Optional[str] = pydantic_v1.Field( 87 alias="sessionId", default=None 88 ) 89 observation_id: typing.Optional[str] = pydantic_v1.Field( 90 alias="observationId", default=None 91 ) 92 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 93 alias="datasetRunId", default=None 94 ) 95 name: str 96 source: ScoreSource 97 timestamp: dt.datetime 98 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 99 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 100 author_user_id: typing.Optional[str] = pydantic_v1.Field( 101 alias="authorUserId", default=None 102 ) 103 comment: typing.Optional[str] = None 104 metadata: typing.Optional[typing.Any] = None 105 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 106 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 107 environment: typing.Optional[str] = None 108 data_type: typing.Literal["CATEGORICAL"] = pydantic_v1.Field( 109 alias="dataType", default="CATEGORICAL" 110 ) 111 112 def json(self, **kwargs: typing.Any) -> str: 113 kwargs_with_defaults: typing.Any = { 114 "by_alias": True, 115 "exclude_unset": True, 116 **kwargs, 117 } 118 return super().json(**kwargs_with_defaults) 119 120 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 121 kwargs_with_defaults_exclude_unset: typing.Any = { 122 "by_alias": True, 123 "exclude_unset": True, 124 **kwargs, 125 } 126 kwargs_with_defaults_exclude_none: typing.Any = { 127 "by_alias": True, 128 "exclude_none": True, 129 **kwargs, 130 } 131 132 return deep_union_pydantic_dicts( 133 super().dict(**kwargs_with_defaults_exclude_unset), 134 super().dict(**kwargs_with_defaults_exclude_none), 135 ) 136 137 class Config: 138 frozen = True 139 smart_union = True 140 allow_population_by_field_name = True 141 populate_by_name = True 142 extra = pydantic_v1.Extra.allow 143 json_encoders = {dt.datetime: serialize_datetime}
112 def json(self, **kwargs: typing.Any) -> str: 113 kwargs_with_defaults: typing.Any = { 114 "by_alias": True, 115 "exclude_unset": True, 116 **kwargs, 117 } 118 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
120 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 121 kwargs_with_defaults_exclude_unset: typing.Any = { 122 "by_alias": True, 123 "exclude_unset": True, 124 **kwargs, 125 } 126 kwargs_with_defaults_exclude_none: typing.Any = { 127 "by_alias": True, 128 "exclude_none": True, 129 **kwargs, 130 } 131 132 return deep_union_pydantic_dicts( 133 super().dict(**kwargs_with_defaults_exclude_unset), 134 super().dict(**kwargs_with_defaults_exclude_none), 135 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
15class GetScoresResponseData_Numeric(pydantic_v1.BaseModel): 16 trace: typing.Optional[GetScoresResponseTraceData] = None 17 value: float 18 id: str 19 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 20 session_id: typing.Optional[str] = pydantic_v1.Field( 21 alias="sessionId", default=None 22 ) 23 observation_id: typing.Optional[str] = pydantic_v1.Field( 24 alias="observationId", default=None 25 ) 26 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 27 alias="datasetRunId", default=None 28 ) 29 name: str 30 source: ScoreSource 31 timestamp: dt.datetime 32 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 33 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 34 author_user_id: typing.Optional[str] = pydantic_v1.Field( 35 alias="authorUserId", default=None 36 ) 37 comment: typing.Optional[str] = None 38 metadata: typing.Optional[typing.Any] = None 39 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 40 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 41 environment: typing.Optional[str] = None 42 data_type: typing.Literal["NUMERIC"] = pydantic_v1.Field( 43 alias="dataType", default="NUMERIC" 44 ) 45 46 def json(self, **kwargs: typing.Any) -> str: 47 kwargs_with_defaults: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 return super().json(**kwargs_with_defaults) 53 54 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 55 kwargs_with_defaults_exclude_unset: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 kwargs_with_defaults_exclude_none: typing.Any = { 61 "by_alias": True, 62 "exclude_none": True, 63 **kwargs, 64 } 65 66 return deep_union_pydantic_dicts( 67 super().dict(**kwargs_with_defaults_exclude_unset), 68 super().dict(**kwargs_with_defaults_exclude_none), 69 ) 70 71 class Config: 72 frozen = True 73 smart_union = True 74 allow_population_by_field_name = True 75 populate_by_name = True 76 extra = pydantic_v1.Extra.allow 77 json_encoders = {dt.datetime: serialize_datetime}
46 def json(self, **kwargs: typing.Any) -> str: 47 kwargs_with_defaults: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
54 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 55 kwargs_with_defaults_exclude_unset: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 kwargs_with_defaults_exclude_none: typing.Any = { 61 "by_alias": True, 62 "exclude_none": True, 63 **kwargs, 64 } 65 66 return deep_union_pydantic_dicts( 67 super().dict(**kwargs_with_defaults_exclude_unset), 68 super().dict(**kwargs_with_defaults_exclude_none), 69 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class GetScoresResponseTraceData(pydantic_v1.BaseModel): 12 user_id: typing.Optional[str] = pydantic_v1.Field(alias="userId", default=None) 13 """ 14 The user ID associated with the trace referenced by score 15 """ 16 17 tags: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 18 """ 19 A list of tags associated with the trace referenced by score 20 """ 21 22 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 23 """ 24 The environment of the trace referenced by score 25 """ 26 27 def json(self, **kwargs: typing.Any) -> str: 28 kwargs_with_defaults: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 return super().json(**kwargs_with_defaults) 34 35 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 36 kwargs_with_defaults_exclude_unset: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 kwargs_with_defaults_exclude_none: typing.Any = { 42 "by_alias": True, 43 "exclude_none": True, 44 **kwargs, 45 } 46 47 return deep_union_pydantic_dicts( 48 super().dict(**kwargs_with_defaults_exclude_unset), 49 super().dict(**kwargs_with_defaults_exclude_none), 50 ) 51 52 class Config: 53 frozen = True 54 smart_union = True 55 allow_population_by_field_name = True 56 populate_by_name = True 57 extra = pydantic_v1.Extra.allow 58 json_encoders = {dt.datetime: serialize_datetime}
27 def json(self, **kwargs: typing.Any) -> str: 28 kwargs_with_defaults: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
35 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 36 kwargs_with_defaults_exclude_unset: typing.Any = { 37 "by_alias": True, 38 "exclude_unset": True, 39 **kwargs, 40 } 41 kwargs_with_defaults_exclude_none: typing.Any = { 42 "by_alias": True, 43 "exclude_none": True, 44 **kwargs, 45 } 46 47 return deep_union_pydantic_dicts( 48 super().dict(**kwargs_with_defaults_exclude_unset), 49 super().dict(**kwargs_with_defaults_exclude_none), 50 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class HealthResponse(pydantic_v1.BaseModel): 12 """ 13 Examples 14 -------- 15 from langfuse import HealthResponse 16 17 HealthResponse( 18 version="1.25.0", 19 status="OK", 20 ) 21 """ 22 23 version: str = pydantic_v1.Field() 24 """ 25 Langfuse server version 26 """ 27 28 status: str 29 30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 return super().json(**kwargs_with_defaults) 37 38 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 39 kwargs_with_defaults_exclude_unset: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 kwargs_with_defaults_exclude_none: typing.Any = { 45 "by_alias": True, 46 "exclude_none": True, 47 **kwargs, 48 } 49 50 return deep_union_pydantic_dicts( 51 super().dict(**kwargs_with_defaults_exclude_unset), 52 super().dict(**kwargs_with_defaults_exclude_none), 53 ) 54 55 class Config: 56 frozen = True 57 smart_union = True 58 extra = pydantic_v1.Extra.allow 59 json_encoders = {dt.datetime: serialize_datetime}
Examples
from langfuse import HealthResponse
HealthResponse( version="1.25.0", status="OK", )
30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
38 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 39 kwargs_with_defaults_exclude_unset: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 kwargs_with_defaults_exclude_none: typing.Any = { 45 "by_alias": True, 46 "exclude_none": True, 47 **kwargs, 48 } 49 50 return deep_union_pydantic_dicts( 51 super().dict(**kwargs_with_defaults_exclude_unset), 52 super().dict(**kwargs_with_defaults_exclude_none), 53 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class IngestionError(pydantic_v1.BaseModel): 12 id: str 13 status: int 14 message: typing.Optional[str] = None 15 error: typing.Optional[typing.Any] = None 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
256class IngestionEvent_EventCreate(pydantic_v1.BaseModel): 257 body: CreateEventBody 258 id: str 259 timestamp: str 260 metadata: typing.Optional[typing.Any] = None 261 type: typing.Literal["event-create"] = "event-create" 262 263 def json(self, **kwargs: typing.Any) -> str: 264 kwargs_with_defaults: typing.Any = { 265 "by_alias": True, 266 "exclude_unset": True, 267 **kwargs, 268 } 269 return super().json(**kwargs_with_defaults) 270 271 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 272 kwargs_with_defaults_exclude_unset: typing.Any = { 273 "by_alias": True, 274 "exclude_unset": True, 275 **kwargs, 276 } 277 kwargs_with_defaults_exclude_none: typing.Any = { 278 "by_alias": True, 279 "exclude_none": True, 280 **kwargs, 281 } 282 283 return deep_union_pydantic_dicts( 284 super().dict(**kwargs_with_defaults_exclude_unset), 285 super().dict(**kwargs_with_defaults_exclude_none), 286 ) 287 288 class Config: 289 frozen = True 290 smart_union = True 291 extra = pydantic_v1.Extra.allow 292 json_encoders = {dt.datetime: serialize_datetime}
263 def json(self, **kwargs: typing.Any) -> str: 264 kwargs_with_defaults: typing.Any = { 265 "by_alias": True, 266 "exclude_unset": True, 267 **kwargs, 268 } 269 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
271 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 272 kwargs_with_defaults_exclude_unset: typing.Any = { 273 "by_alias": True, 274 "exclude_unset": True, 275 **kwargs, 276 } 277 kwargs_with_defaults_exclude_none: typing.Any = { 278 "by_alias": True, 279 "exclude_none": True, 280 **kwargs, 281 } 282 283 return deep_union_pydantic_dicts( 284 super().dict(**kwargs_with_defaults_exclude_unset), 285 super().dict(**kwargs_with_defaults_exclude_none), 286 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
178class IngestionEvent_GenerationCreate(pydantic_v1.BaseModel): 179 body: CreateGenerationBody 180 id: str 181 timestamp: str 182 metadata: typing.Optional[typing.Any] = None 183 type: typing.Literal["generation-create"] = "generation-create" 184 185 def json(self, **kwargs: typing.Any) -> str: 186 kwargs_with_defaults: typing.Any = { 187 "by_alias": True, 188 "exclude_unset": True, 189 **kwargs, 190 } 191 return super().json(**kwargs_with_defaults) 192 193 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 194 kwargs_with_defaults_exclude_unset: typing.Any = { 195 "by_alias": True, 196 "exclude_unset": True, 197 **kwargs, 198 } 199 kwargs_with_defaults_exclude_none: typing.Any = { 200 "by_alias": True, 201 "exclude_none": True, 202 **kwargs, 203 } 204 205 return deep_union_pydantic_dicts( 206 super().dict(**kwargs_with_defaults_exclude_unset), 207 super().dict(**kwargs_with_defaults_exclude_none), 208 ) 209 210 class Config: 211 frozen = True 212 smart_union = True 213 extra = pydantic_v1.Extra.allow 214 json_encoders = {dt.datetime: serialize_datetime}
185 def json(self, **kwargs: typing.Any) -> str: 186 kwargs_with_defaults: typing.Any = { 187 "by_alias": True, 188 "exclude_unset": True, 189 **kwargs, 190 } 191 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
193 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 194 kwargs_with_defaults_exclude_unset: typing.Any = { 195 "by_alias": True, 196 "exclude_unset": True, 197 **kwargs, 198 } 199 kwargs_with_defaults_exclude_none: typing.Any = { 200 "by_alias": True, 201 "exclude_none": True, 202 **kwargs, 203 } 204 205 return deep_union_pydantic_dicts( 206 super().dict(**kwargs_with_defaults_exclude_unset), 207 super().dict(**kwargs_with_defaults_exclude_none), 208 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
217class IngestionEvent_GenerationUpdate(pydantic_v1.BaseModel): 218 body: UpdateGenerationBody 219 id: str 220 timestamp: str 221 metadata: typing.Optional[typing.Any] = None 222 type: typing.Literal["generation-update"] = "generation-update" 223 224 def json(self, **kwargs: typing.Any) -> str: 225 kwargs_with_defaults: typing.Any = { 226 "by_alias": True, 227 "exclude_unset": True, 228 **kwargs, 229 } 230 return super().json(**kwargs_with_defaults) 231 232 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 233 kwargs_with_defaults_exclude_unset: typing.Any = { 234 "by_alias": True, 235 "exclude_unset": True, 236 **kwargs, 237 } 238 kwargs_with_defaults_exclude_none: typing.Any = { 239 "by_alias": True, 240 "exclude_none": True, 241 **kwargs, 242 } 243 244 return deep_union_pydantic_dicts( 245 super().dict(**kwargs_with_defaults_exclude_unset), 246 super().dict(**kwargs_with_defaults_exclude_none), 247 ) 248 249 class Config: 250 frozen = True 251 smart_union = True 252 extra = pydantic_v1.Extra.allow 253 json_encoders = {dt.datetime: serialize_datetime}
224 def json(self, **kwargs: typing.Any) -> str: 225 kwargs_with_defaults: typing.Any = { 226 "by_alias": True, 227 "exclude_unset": True, 228 **kwargs, 229 } 230 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
232 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 233 kwargs_with_defaults_exclude_unset: typing.Any = { 234 "by_alias": True, 235 "exclude_unset": True, 236 **kwargs, 237 } 238 kwargs_with_defaults_exclude_none: typing.Any = { 239 "by_alias": True, 240 "exclude_none": True, 241 **kwargs, 242 } 243 244 return deep_union_pydantic_dicts( 245 super().dict(**kwargs_with_defaults_exclude_unset), 246 super().dict(**kwargs_with_defaults_exclude_none), 247 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
334class IngestionEvent_ObservationCreate(pydantic_v1.BaseModel): 335 body: ObservationBody 336 id: str 337 timestamp: str 338 metadata: typing.Optional[typing.Any] = None 339 type: typing.Literal["observation-create"] = "observation-create" 340 341 def json(self, **kwargs: typing.Any) -> str: 342 kwargs_with_defaults: typing.Any = { 343 "by_alias": True, 344 "exclude_unset": True, 345 **kwargs, 346 } 347 return super().json(**kwargs_with_defaults) 348 349 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 350 kwargs_with_defaults_exclude_unset: typing.Any = { 351 "by_alias": True, 352 "exclude_unset": True, 353 **kwargs, 354 } 355 kwargs_with_defaults_exclude_none: typing.Any = { 356 "by_alias": True, 357 "exclude_none": True, 358 **kwargs, 359 } 360 361 return deep_union_pydantic_dicts( 362 super().dict(**kwargs_with_defaults_exclude_unset), 363 super().dict(**kwargs_with_defaults_exclude_none), 364 ) 365 366 class Config: 367 frozen = True 368 smart_union = True 369 extra = pydantic_v1.Extra.allow 370 json_encoders = {dt.datetime: serialize_datetime}
341 def json(self, **kwargs: typing.Any) -> str: 342 kwargs_with_defaults: typing.Any = { 343 "by_alias": True, 344 "exclude_unset": True, 345 **kwargs, 346 } 347 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
349 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 350 kwargs_with_defaults_exclude_unset: typing.Any = { 351 "by_alias": True, 352 "exclude_unset": True, 353 **kwargs, 354 } 355 kwargs_with_defaults_exclude_none: typing.Any = { 356 "by_alias": True, 357 "exclude_none": True, 358 **kwargs, 359 } 360 361 return deep_union_pydantic_dicts( 362 super().dict(**kwargs_with_defaults_exclude_unset), 363 super().dict(**kwargs_with_defaults_exclude_none), 364 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
373class IngestionEvent_ObservationUpdate(pydantic_v1.BaseModel): 374 body: ObservationBody 375 id: str 376 timestamp: str 377 metadata: typing.Optional[typing.Any] = None 378 type: typing.Literal["observation-update"] = "observation-update" 379 380 def json(self, **kwargs: typing.Any) -> str: 381 kwargs_with_defaults: typing.Any = { 382 "by_alias": True, 383 "exclude_unset": True, 384 **kwargs, 385 } 386 return super().json(**kwargs_with_defaults) 387 388 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 389 kwargs_with_defaults_exclude_unset: typing.Any = { 390 "by_alias": True, 391 "exclude_unset": True, 392 **kwargs, 393 } 394 kwargs_with_defaults_exclude_none: typing.Any = { 395 "by_alias": True, 396 "exclude_none": True, 397 **kwargs, 398 } 399 400 return deep_union_pydantic_dicts( 401 super().dict(**kwargs_with_defaults_exclude_unset), 402 super().dict(**kwargs_with_defaults_exclude_none), 403 ) 404 405 class Config: 406 frozen = True 407 smart_union = True 408 extra = pydantic_v1.Extra.allow 409 json_encoders = {dt.datetime: serialize_datetime}
380 def json(self, **kwargs: typing.Any) -> str: 381 kwargs_with_defaults: typing.Any = { 382 "by_alias": True, 383 "exclude_unset": True, 384 **kwargs, 385 } 386 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
388 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 389 kwargs_with_defaults_exclude_unset: typing.Any = { 390 "by_alias": True, 391 "exclude_unset": True, 392 **kwargs, 393 } 394 kwargs_with_defaults_exclude_none: typing.Any = { 395 "by_alias": True, 396 "exclude_none": True, 397 **kwargs, 398 } 399 400 return deep_union_pydantic_dicts( 401 super().dict(**kwargs_with_defaults_exclude_unset), 402 super().dict(**kwargs_with_defaults_exclude_none), 403 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
61class IngestionEvent_ScoreCreate(pydantic_v1.BaseModel): 62 body: ScoreBody 63 id: str 64 timestamp: str 65 metadata: typing.Optional[typing.Any] = None 66 type: typing.Literal["score-create"] = "score-create" 67 68 def json(self, **kwargs: typing.Any) -> str: 69 kwargs_with_defaults: typing.Any = { 70 "by_alias": True, 71 "exclude_unset": True, 72 **kwargs, 73 } 74 return super().json(**kwargs_with_defaults) 75 76 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 77 kwargs_with_defaults_exclude_unset: typing.Any = { 78 "by_alias": True, 79 "exclude_unset": True, 80 **kwargs, 81 } 82 kwargs_with_defaults_exclude_none: typing.Any = { 83 "by_alias": True, 84 "exclude_none": True, 85 **kwargs, 86 } 87 88 return deep_union_pydantic_dicts( 89 super().dict(**kwargs_with_defaults_exclude_unset), 90 super().dict(**kwargs_with_defaults_exclude_none), 91 ) 92 93 class Config: 94 frozen = True 95 smart_union = True 96 extra = pydantic_v1.Extra.allow 97 json_encoders = {dt.datetime: serialize_datetime}
68 def json(self, **kwargs: typing.Any) -> str: 69 kwargs_with_defaults: typing.Any = { 70 "by_alias": True, 71 "exclude_unset": True, 72 **kwargs, 73 } 74 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
76 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 77 kwargs_with_defaults_exclude_unset: typing.Any = { 78 "by_alias": True, 79 "exclude_unset": True, 80 **kwargs, 81 } 82 kwargs_with_defaults_exclude_none: typing.Any = { 83 "by_alias": True, 84 "exclude_none": True, 85 **kwargs, 86 } 87 88 return deep_union_pydantic_dicts( 89 super().dict(**kwargs_with_defaults_exclude_unset), 90 super().dict(**kwargs_with_defaults_exclude_none), 91 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
295class IngestionEvent_SdkLog(pydantic_v1.BaseModel): 296 body: SdkLogBody 297 id: str 298 timestamp: str 299 metadata: typing.Optional[typing.Any] = None 300 type: typing.Literal["sdk-log"] = "sdk-log" 301 302 def json(self, **kwargs: typing.Any) -> str: 303 kwargs_with_defaults: typing.Any = { 304 "by_alias": True, 305 "exclude_unset": True, 306 **kwargs, 307 } 308 return super().json(**kwargs_with_defaults) 309 310 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 311 kwargs_with_defaults_exclude_unset: typing.Any = { 312 "by_alias": True, 313 "exclude_unset": True, 314 **kwargs, 315 } 316 kwargs_with_defaults_exclude_none: typing.Any = { 317 "by_alias": True, 318 "exclude_none": True, 319 **kwargs, 320 } 321 322 return deep_union_pydantic_dicts( 323 super().dict(**kwargs_with_defaults_exclude_unset), 324 super().dict(**kwargs_with_defaults_exclude_none), 325 ) 326 327 class Config: 328 frozen = True 329 smart_union = True 330 extra = pydantic_v1.Extra.allow 331 json_encoders = {dt.datetime: serialize_datetime}
302 def json(self, **kwargs: typing.Any) -> str: 303 kwargs_with_defaults: typing.Any = { 304 "by_alias": True, 305 "exclude_unset": True, 306 **kwargs, 307 } 308 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
310 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 311 kwargs_with_defaults_exclude_unset: typing.Any = { 312 "by_alias": True, 313 "exclude_unset": True, 314 **kwargs, 315 } 316 kwargs_with_defaults_exclude_none: typing.Any = { 317 "by_alias": True, 318 "exclude_none": True, 319 **kwargs, 320 } 321 322 return deep_union_pydantic_dicts( 323 super().dict(**kwargs_with_defaults_exclude_unset), 324 super().dict(**kwargs_with_defaults_exclude_none), 325 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
100class IngestionEvent_SpanCreate(pydantic_v1.BaseModel): 101 body: CreateSpanBody 102 id: str 103 timestamp: str 104 metadata: typing.Optional[typing.Any] = None 105 type: typing.Literal["span-create"] = "span-create" 106 107 def json(self, **kwargs: typing.Any) -> str: 108 kwargs_with_defaults: typing.Any = { 109 "by_alias": True, 110 "exclude_unset": True, 111 **kwargs, 112 } 113 return super().json(**kwargs_with_defaults) 114 115 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 116 kwargs_with_defaults_exclude_unset: typing.Any = { 117 "by_alias": True, 118 "exclude_unset": True, 119 **kwargs, 120 } 121 kwargs_with_defaults_exclude_none: typing.Any = { 122 "by_alias": True, 123 "exclude_none": True, 124 **kwargs, 125 } 126 127 return deep_union_pydantic_dicts( 128 super().dict(**kwargs_with_defaults_exclude_unset), 129 super().dict(**kwargs_with_defaults_exclude_none), 130 ) 131 132 class Config: 133 frozen = True 134 smart_union = True 135 extra = pydantic_v1.Extra.allow 136 json_encoders = {dt.datetime: serialize_datetime}
107 def json(self, **kwargs: typing.Any) -> str: 108 kwargs_with_defaults: typing.Any = { 109 "by_alias": True, 110 "exclude_unset": True, 111 **kwargs, 112 } 113 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
115 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 116 kwargs_with_defaults_exclude_unset: typing.Any = { 117 "by_alias": True, 118 "exclude_unset": True, 119 **kwargs, 120 } 121 kwargs_with_defaults_exclude_none: typing.Any = { 122 "by_alias": True, 123 "exclude_none": True, 124 **kwargs, 125 } 126 127 return deep_union_pydantic_dicts( 128 super().dict(**kwargs_with_defaults_exclude_unset), 129 super().dict(**kwargs_with_defaults_exclude_none), 130 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
139class IngestionEvent_SpanUpdate(pydantic_v1.BaseModel): 140 body: UpdateSpanBody 141 id: str 142 timestamp: str 143 metadata: typing.Optional[typing.Any] = None 144 type: typing.Literal["span-update"] = "span-update" 145 146 def json(self, **kwargs: typing.Any) -> str: 147 kwargs_with_defaults: typing.Any = { 148 "by_alias": True, 149 "exclude_unset": True, 150 **kwargs, 151 } 152 return super().json(**kwargs_with_defaults) 153 154 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 155 kwargs_with_defaults_exclude_unset: typing.Any = { 156 "by_alias": True, 157 "exclude_unset": True, 158 **kwargs, 159 } 160 kwargs_with_defaults_exclude_none: typing.Any = { 161 "by_alias": True, 162 "exclude_none": True, 163 **kwargs, 164 } 165 166 return deep_union_pydantic_dicts( 167 super().dict(**kwargs_with_defaults_exclude_unset), 168 super().dict(**kwargs_with_defaults_exclude_none), 169 ) 170 171 class Config: 172 frozen = True 173 smart_union = True 174 extra = pydantic_v1.Extra.allow 175 json_encoders = {dt.datetime: serialize_datetime}
146 def json(self, **kwargs: typing.Any) -> str: 147 kwargs_with_defaults: typing.Any = { 148 "by_alias": True, 149 "exclude_unset": True, 150 **kwargs, 151 } 152 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
154 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 155 kwargs_with_defaults_exclude_unset: typing.Any = { 156 "by_alias": True, 157 "exclude_unset": True, 158 **kwargs, 159 } 160 kwargs_with_defaults_exclude_none: typing.Any = { 161 "by_alias": True, 162 "exclude_none": True, 163 **kwargs, 164 } 165 166 return deep_union_pydantic_dicts( 167 super().dict(**kwargs_with_defaults_exclude_unset), 168 super().dict(**kwargs_with_defaults_exclude_none), 169 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
22class IngestionEvent_TraceCreate(pydantic_v1.BaseModel): 23 body: TraceBody 24 id: str 25 timestamp: str 26 metadata: typing.Optional[typing.Any] = None 27 type: typing.Literal["trace-create"] = "trace-create" 28 29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 return super().json(**kwargs_with_defaults) 36 37 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 38 kwargs_with_defaults_exclude_unset: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 kwargs_with_defaults_exclude_none: typing.Any = { 44 "by_alias": True, 45 "exclude_none": True, 46 **kwargs, 47 } 48 49 return deep_union_pydantic_dicts( 50 super().dict(**kwargs_with_defaults_exclude_unset), 51 super().dict(**kwargs_with_defaults_exclude_none), 52 ) 53 54 class Config: 55 frozen = True 56 smart_union = True 57 extra = pydantic_v1.Extra.allow 58 json_encoders = {dt.datetime: serialize_datetime}
29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
37 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 38 kwargs_with_defaults_exclude_unset: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 kwargs_with_defaults_exclude_none: typing.Any = { 44 "by_alias": True, 45 "exclude_none": True, 46 **kwargs, 47 } 48 49 return deep_union_pydantic_dicts( 50 super().dict(**kwargs_with_defaults_exclude_unset), 51 super().dict(**kwargs_with_defaults_exclude_none), 52 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class IngestionResponse(pydantic_v1.BaseModel): 14 successes: typing.List[IngestionSuccess] 15 errors: typing.List[IngestionError] 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class IngestionSuccess(pydantic_v1.BaseModel): 12 id: str 13 status: int 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class LlmAdapter(str, enum.Enum): 11 ANTHROPIC = "anthropic" 12 OPEN_AI = "openai" 13 AZURE = "azure" 14 BEDROCK = "bedrock" 15 GOOGLE_VERTEX_AI = "google-vertex-ai" 16 GOOGLE_AI_STUDIO = "google-ai-studio" 17 18 def visit( 19 self, 20 anthropic: typing.Callable[[], T_Result], 21 open_ai: typing.Callable[[], T_Result], 22 azure: typing.Callable[[], T_Result], 23 bedrock: typing.Callable[[], T_Result], 24 google_vertex_ai: typing.Callable[[], T_Result], 25 google_ai_studio: typing.Callable[[], T_Result], 26 ) -> T_Result: 27 if self is LlmAdapter.ANTHROPIC: 28 return anthropic() 29 if self is LlmAdapter.OPEN_AI: 30 return open_ai() 31 if self is LlmAdapter.AZURE: 32 return azure() 33 if self is LlmAdapter.BEDROCK: 34 return bedrock() 35 if self is LlmAdapter.GOOGLE_VERTEX_AI: 36 return google_vertex_ai() 37 if self is LlmAdapter.GOOGLE_AI_STUDIO: 38 return google_ai_studio()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
18 def visit( 19 self, 20 anthropic: typing.Callable[[], T_Result], 21 open_ai: typing.Callable[[], T_Result], 22 azure: typing.Callable[[], T_Result], 23 bedrock: typing.Callable[[], T_Result], 24 google_vertex_ai: typing.Callable[[], T_Result], 25 google_ai_studio: typing.Callable[[], T_Result], 26 ) -> T_Result: 27 if self is LlmAdapter.ANTHROPIC: 28 return anthropic() 29 if self is LlmAdapter.OPEN_AI: 30 return open_ai() 31 if self is LlmAdapter.AZURE: 32 return azure() 33 if self is LlmAdapter.BEDROCK: 34 return bedrock() 35 if self is LlmAdapter.GOOGLE_VERTEX_AI: 36 return google_vertex_ai() 37 if self is LlmAdapter.GOOGLE_AI_STUDIO: 38 return google_ai_studio()
11class LlmConnection(pydantic_v1.BaseModel): 12 """ 13 LLM API connection configuration (secrets excluded) 14 """ 15 16 id: str 17 provider: str = pydantic_v1.Field() 18 """ 19 Provider name (e.g., 'openai', 'my-gateway'). Must be unique in project, used for upserting. 20 """ 21 22 adapter: str = pydantic_v1.Field() 23 """ 24 The adapter used to interface with the LLM 25 """ 26 27 display_secret_key: str = pydantic_v1.Field(alias="displaySecretKey") 28 """ 29 Masked version of the secret key for display purposes 30 """ 31 32 base_url: typing.Optional[str] = pydantic_v1.Field(alias="baseURL", default=None) 33 """ 34 Custom base URL for the LLM API 35 """ 36 37 custom_models: typing.List[str] = pydantic_v1.Field(alias="customModels") 38 """ 39 List of custom model names available for this connection 40 """ 41 42 with_default_models: bool = pydantic_v1.Field(alias="withDefaultModels") 43 """ 44 Whether to include default models for this adapter 45 """ 46 47 extra_header_keys: typing.List[str] = pydantic_v1.Field(alias="extraHeaderKeys") 48 """ 49 Keys of extra headers sent with requests (values excluded for security) 50 """ 51 52 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 53 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 54 55 def json(self, **kwargs: typing.Any) -> str: 56 kwargs_with_defaults: typing.Any = { 57 "by_alias": True, 58 "exclude_unset": True, 59 **kwargs, 60 } 61 return super().json(**kwargs_with_defaults) 62 63 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 64 kwargs_with_defaults_exclude_unset: typing.Any = { 65 "by_alias": True, 66 "exclude_unset": True, 67 **kwargs, 68 } 69 kwargs_with_defaults_exclude_none: typing.Any = { 70 "by_alias": True, 71 "exclude_none": True, 72 **kwargs, 73 } 74 75 return deep_union_pydantic_dicts( 76 super().dict(**kwargs_with_defaults_exclude_unset), 77 super().dict(**kwargs_with_defaults_exclude_none), 78 ) 79 80 class Config: 81 frozen = True 82 smart_union = True 83 allow_population_by_field_name = True 84 populate_by_name = True 85 extra = pydantic_v1.Extra.allow 86 json_encoders = {dt.datetime: serialize_datetime}
LLM API connection configuration (secrets excluded)
Provider name (e.g., 'openai', 'my-gateway'). Must be unique in project, used for upserting.
Keys of extra headers sent with requests (values excluded for security)
55 def json(self, **kwargs: typing.Any) -> str: 56 kwargs_with_defaults: typing.Any = { 57 "by_alias": True, 58 "exclude_unset": True, 59 **kwargs, 60 } 61 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
63 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 64 kwargs_with_defaults_exclude_unset: typing.Any = { 65 "by_alias": True, 66 "exclude_unset": True, 67 **kwargs, 68 } 69 kwargs_with_defaults_exclude_none: typing.Any = { 70 "by_alias": True, 71 "exclude_none": True, 72 **kwargs, 73 } 74 75 return deep_union_pydantic_dicts( 76 super().dict(**kwargs_with_defaults_exclude_unset), 77 super().dict(**kwargs_with_defaults_exclude_none), 78 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class MediaContentType(str, enum.Enum): 11 """ 12 The MIME type of the media record 13 """ 14 15 IMAGE_PNG = "image/png" 16 IMAGE_JPEG = "image/jpeg" 17 IMAGE_JPG = "image/jpg" 18 IMAGE_WEBP = "image/webp" 19 IMAGE_GIF = "image/gif" 20 IMAGE_SVG_XML = "image/svg+xml" 21 IMAGE_TIFF = "image/tiff" 22 IMAGE_BMP = "image/bmp" 23 AUDIO_MPEG = "audio/mpeg" 24 AUDIO_MP_3 = "audio/mp3" 25 AUDIO_WAV = "audio/wav" 26 AUDIO_OGG = "audio/ogg" 27 AUDIO_OGA = "audio/oga" 28 AUDIO_AAC = "audio/aac" 29 AUDIO_MP_4 = "audio/mp4" 30 AUDIO_FLAC = "audio/flac" 31 VIDEO_MP_4 = "video/mp4" 32 VIDEO_WEBM = "video/webm" 33 TEXT_PLAIN = "text/plain" 34 TEXT_HTML = "text/html" 35 TEXT_CSS = "text/css" 36 TEXT_CSV = "text/csv" 37 APPLICATION_PDF = "application/pdf" 38 APPLICATION_MSWORD = "application/msword" 39 APPLICATION_MS_EXCEL = "application/vnd.ms-excel" 40 APPLICATION_ZIP = "application/zip" 41 APPLICATION_JSON = "application/json" 42 APPLICATION_XML = "application/xml" 43 APPLICATION_OCTET_STREAM = "application/octet-stream" 44 45 def visit( 46 self, 47 image_png: typing.Callable[[], T_Result], 48 image_jpeg: typing.Callable[[], T_Result], 49 image_jpg: typing.Callable[[], T_Result], 50 image_webp: typing.Callable[[], T_Result], 51 image_gif: typing.Callable[[], T_Result], 52 image_svg_xml: typing.Callable[[], T_Result], 53 image_tiff: typing.Callable[[], T_Result], 54 image_bmp: typing.Callable[[], T_Result], 55 audio_mpeg: typing.Callable[[], T_Result], 56 audio_mp_3: typing.Callable[[], T_Result], 57 audio_wav: typing.Callable[[], T_Result], 58 audio_ogg: typing.Callable[[], T_Result], 59 audio_oga: typing.Callable[[], T_Result], 60 audio_aac: typing.Callable[[], T_Result], 61 audio_mp_4: typing.Callable[[], T_Result], 62 audio_flac: typing.Callable[[], T_Result], 63 video_mp_4: typing.Callable[[], T_Result], 64 video_webm: typing.Callable[[], T_Result], 65 text_plain: typing.Callable[[], T_Result], 66 text_html: typing.Callable[[], T_Result], 67 text_css: typing.Callable[[], T_Result], 68 text_csv: typing.Callable[[], T_Result], 69 application_pdf: typing.Callable[[], T_Result], 70 application_msword: typing.Callable[[], T_Result], 71 application_ms_excel: typing.Callable[[], T_Result], 72 application_zip: typing.Callable[[], T_Result], 73 application_json: typing.Callable[[], T_Result], 74 application_xml: typing.Callable[[], T_Result], 75 application_octet_stream: typing.Callable[[], T_Result], 76 ) -> T_Result: 77 if self is MediaContentType.IMAGE_PNG: 78 return image_png() 79 if self is MediaContentType.IMAGE_JPEG: 80 return image_jpeg() 81 if self is MediaContentType.IMAGE_JPG: 82 return image_jpg() 83 if self is MediaContentType.IMAGE_WEBP: 84 return image_webp() 85 if self is MediaContentType.IMAGE_GIF: 86 return image_gif() 87 if self is MediaContentType.IMAGE_SVG_XML: 88 return image_svg_xml() 89 if self is MediaContentType.IMAGE_TIFF: 90 return image_tiff() 91 if self is MediaContentType.IMAGE_BMP: 92 return image_bmp() 93 if self is MediaContentType.AUDIO_MPEG: 94 return audio_mpeg() 95 if self is MediaContentType.AUDIO_MP_3: 96 return audio_mp_3() 97 if self is MediaContentType.AUDIO_WAV: 98 return audio_wav() 99 if self is MediaContentType.AUDIO_OGG: 100 return audio_ogg() 101 if self is MediaContentType.AUDIO_OGA: 102 return audio_oga() 103 if self is MediaContentType.AUDIO_AAC: 104 return audio_aac() 105 if self is MediaContentType.AUDIO_MP_4: 106 return audio_mp_4() 107 if self is MediaContentType.AUDIO_FLAC: 108 return audio_flac() 109 if self is MediaContentType.VIDEO_MP_4: 110 return video_mp_4() 111 if self is MediaContentType.VIDEO_WEBM: 112 return video_webm() 113 if self is MediaContentType.TEXT_PLAIN: 114 return text_plain() 115 if self is MediaContentType.TEXT_HTML: 116 return text_html() 117 if self is MediaContentType.TEXT_CSS: 118 return text_css() 119 if self is MediaContentType.TEXT_CSV: 120 return text_csv() 121 if self is MediaContentType.APPLICATION_PDF: 122 return application_pdf() 123 if self is MediaContentType.APPLICATION_MSWORD: 124 return application_msword() 125 if self is MediaContentType.APPLICATION_MS_EXCEL: 126 return application_ms_excel() 127 if self is MediaContentType.APPLICATION_ZIP: 128 return application_zip() 129 if self is MediaContentType.APPLICATION_JSON: 130 return application_json() 131 if self is MediaContentType.APPLICATION_XML: 132 return application_xml() 133 if self is MediaContentType.APPLICATION_OCTET_STREAM: 134 return application_octet_stream()
The MIME type of the media record
45 def visit( 46 self, 47 image_png: typing.Callable[[], T_Result], 48 image_jpeg: typing.Callable[[], T_Result], 49 image_jpg: typing.Callable[[], T_Result], 50 image_webp: typing.Callable[[], T_Result], 51 image_gif: typing.Callable[[], T_Result], 52 image_svg_xml: typing.Callable[[], T_Result], 53 image_tiff: typing.Callable[[], T_Result], 54 image_bmp: typing.Callable[[], T_Result], 55 audio_mpeg: typing.Callable[[], T_Result], 56 audio_mp_3: typing.Callable[[], T_Result], 57 audio_wav: typing.Callable[[], T_Result], 58 audio_ogg: typing.Callable[[], T_Result], 59 audio_oga: typing.Callable[[], T_Result], 60 audio_aac: typing.Callable[[], T_Result], 61 audio_mp_4: typing.Callable[[], T_Result], 62 audio_flac: typing.Callable[[], T_Result], 63 video_mp_4: typing.Callable[[], T_Result], 64 video_webm: typing.Callable[[], T_Result], 65 text_plain: typing.Callable[[], T_Result], 66 text_html: typing.Callable[[], T_Result], 67 text_css: typing.Callable[[], T_Result], 68 text_csv: typing.Callable[[], T_Result], 69 application_pdf: typing.Callable[[], T_Result], 70 application_msword: typing.Callable[[], T_Result], 71 application_ms_excel: typing.Callable[[], T_Result], 72 application_zip: typing.Callable[[], T_Result], 73 application_json: typing.Callable[[], T_Result], 74 application_xml: typing.Callable[[], T_Result], 75 application_octet_stream: typing.Callable[[], T_Result], 76 ) -> T_Result: 77 if self is MediaContentType.IMAGE_PNG: 78 return image_png() 79 if self is MediaContentType.IMAGE_JPEG: 80 return image_jpeg() 81 if self is MediaContentType.IMAGE_JPG: 82 return image_jpg() 83 if self is MediaContentType.IMAGE_WEBP: 84 return image_webp() 85 if self is MediaContentType.IMAGE_GIF: 86 return image_gif() 87 if self is MediaContentType.IMAGE_SVG_XML: 88 return image_svg_xml() 89 if self is MediaContentType.IMAGE_TIFF: 90 return image_tiff() 91 if self is MediaContentType.IMAGE_BMP: 92 return image_bmp() 93 if self is MediaContentType.AUDIO_MPEG: 94 return audio_mpeg() 95 if self is MediaContentType.AUDIO_MP_3: 96 return audio_mp_3() 97 if self is MediaContentType.AUDIO_WAV: 98 return audio_wav() 99 if self is MediaContentType.AUDIO_OGG: 100 return audio_ogg() 101 if self is MediaContentType.AUDIO_OGA: 102 return audio_oga() 103 if self is MediaContentType.AUDIO_AAC: 104 return audio_aac() 105 if self is MediaContentType.AUDIO_MP_4: 106 return audio_mp_4() 107 if self is MediaContentType.AUDIO_FLAC: 108 return audio_flac() 109 if self is MediaContentType.VIDEO_MP_4: 110 return video_mp_4() 111 if self is MediaContentType.VIDEO_WEBM: 112 return video_webm() 113 if self is MediaContentType.TEXT_PLAIN: 114 return text_plain() 115 if self is MediaContentType.TEXT_HTML: 116 return text_html() 117 if self is MediaContentType.TEXT_CSS: 118 return text_css() 119 if self is MediaContentType.TEXT_CSV: 120 return text_csv() 121 if self is MediaContentType.APPLICATION_PDF: 122 return application_pdf() 123 if self is MediaContentType.APPLICATION_MSWORD: 124 return application_msword() 125 if self is MediaContentType.APPLICATION_MS_EXCEL: 126 return application_ms_excel() 127 if self is MediaContentType.APPLICATION_ZIP: 128 return application_zip() 129 if self is MediaContentType.APPLICATION_JSON: 130 return application_json() 131 if self is MediaContentType.APPLICATION_XML: 132 return application_xml() 133 if self is MediaContentType.APPLICATION_OCTET_STREAM: 134 return application_octet_stream()
12class MembershipRequest(pydantic_v1.BaseModel): 13 user_id: str = pydantic_v1.Field(alias="userId") 14 role: MembershipRole 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class MembershipResponse(pydantic_v1.BaseModel): 13 user_id: str = pydantic_v1.Field(alias="userId") 14 role: MembershipRole 15 email: str 16 name: str 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class MembershipRole(str, enum.Enum): 11 OWNER = "OWNER" 12 ADMIN = "ADMIN" 13 MEMBER = "MEMBER" 14 VIEWER = "VIEWER" 15 16 def visit( 17 self, 18 owner: typing.Callable[[], T_Result], 19 admin: typing.Callable[[], T_Result], 20 member: typing.Callable[[], T_Result], 21 viewer: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is MembershipRole.OWNER: 24 return owner() 25 if self is MembershipRole.ADMIN: 26 return admin() 27 if self is MembershipRole.MEMBER: 28 return member() 29 if self is MembershipRole.VIEWER: 30 return viewer()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
16 def visit( 17 self, 18 owner: typing.Callable[[], T_Result], 19 admin: typing.Callable[[], T_Result], 20 member: typing.Callable[[], T_Result], 21 viewer: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is MembershipRole.OWNER: 24 return owner() 25 if self is MembershipRole.ADMIN: 26 return admin() 27 if self is MembershipRole.MEMBER: 28 return member() 29 if self is MembershipRole.VIEWER: 30 return viewer()
12class MembershipsResponse(pydantic_v1.BaseModel): 13 memberships: typing.List[MembershipResponse] 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
9class MethodNotAllowedError(ApiError): 10 def __init__(self, body: typing.Any): 11 super().__init__(status_code=405, body=body)
Common base class for all non-exit exceptions.
11class MetricsResponse(pydantic_v1.BaseModel): 12 data: typing.List[typing.Dict[str, typing.Any]] = pydantic_v1.Field() 13 """ 14 The metrics data. Each item in the list contains the metric values and dimensions requested in the query. 15 Format varies based on the query parameters. 16 Histograms will return an array with [lower, upper, height] tuples. 17 """ 18 19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults) 26 27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 ) 43 44 class Config: 45 frozen = True 46 smart_union = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
The metrics data. Each item in the list contains the metric values and dimensions requested in the query. Format varies based on the query parameters. Histograms will return an array with [lower, upper, height] tuples.
19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class Model(pydantic_v1.BaseModel): 14 """ 15 Model definition used for transforming usage into USD cost and/or tokenization. 16 """ 17 18 id: str 19 model_name: str = pydantic_v1.Field(alias="modelName") 20 """ 21 Name of the model definition. If multiple with the same name exist, they are applied in the following order: (1) custom over built-in, (2) newest according to startTime where model.startTime<observation.startTime 22 """ 23 24 match_pattern: str = pydantic_v1.Field(alias="matchPattern") 25 """ 26 Regex pattern which matches this model definition to generation.model. Useful in case of fine-tuned models. If you want to exact match, use `(?i)^modelname$` 27 """ 28 29 start_date: typing.Optional[dt.datetime] = pydantic_v1.Field( 30 alias="startDate", default=None 31 ) 32 """ 33 Apply only to generations which are newer than this ISO date. 34 """ 35 36 unit: typing.Optional[ModelUsageUnit] = pydantic_v1.Field(default=None) 37 """ 38 Unit used by this model. 39 """ 40 41 input_price: typing.Optional[float] = pydantic_v1.Field( 42 alias="inputPrice", default=None 43 ) 44 """ 45 Deprecated. See 'prices' instead. Price (USD) per input unit 46 """ 47 48 output_price: typing.Optional[float] = pydantic_v1.Field( 49 alias="outputPrice", default=None 50 ) 51 """ 52 Deprecated. See 'prices' instead. Price (USD) per output unit 53 """ 54 55 total_price: typing.Optional[float] = pydantic_v1.Field( 56 alias="totalPrice", default=None 57 ) 58 """ 59 Deprecated. See 'prices' instead. Price (USD) per total unit. Cannot be set if input or output price is set. 60 """ 61 62 tokenizer_id: typing.Optional[str] = pydantic_v1.Field( 63 alias="tokenizerId", default=None 64 ) 65 """ 66 Optional. Tokenizer to be applied to observations which match to this model. See docs for more details. 67 """ 68 69 tokenizer_config: typing.Optional[typing.Any] = pydantic_v1.Field( 70 alias="tokenizerConfig", default=None 71 ) 72 """ 73 Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details. 74 """ 75 76 is_langfuse_managed: bool = pydantic_v1.Field(alias="isLangfuseManaged") 77 prices: typing.Dict[str, ModelPrice] = pydantic_v1.Field() 78 """ 79 Price (USD) by usage type 80 """ 81 82 def json(self, **kwargs: typing.Any) -> str: 83 kwargs_with_defaults: typing.Any = { 84 "by_alias": True, 85 "exclude_unset": True, 86 **kwargs, 87 } 88 return super().json(**kwargs_with_defaults) 89 90 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 91 kwargs_with_defaults_exclude_unset: typing.Any = { 92 "by_alias": True, 93 "exclude_unset": True, 94 **kwargs, 95 } 96 kwargs_with_defaults_exclude_none: typing.Any = { 97 "by_alias": True, 98 "exclude_none": True, 99 **kwargs, 100 } 101 102 return deep_union_pydantic_dicts( 103 super().dict(**kwargs_with_defaults_exclude_unset), 104 super().dict(**kwargs_with_defaults_exclude_none), 105 ) 106 107 class Config: 108 frozen = True 109 smart_union = True 110 allow_population_by_field_name = True 111 populate_by_name = True 112 extra = pydantic_v1.Extra.allow 113 json_encoders = {dt.datetime: serialize_datetime}
Model definition used for transforming usage into USD cost and/or tokenization.
Name of the model definition. If multiple with the same name exist, they are applied in the following order: (1) custom over built-in, (2) newest according to startTime where model.startTime
Regex pattern which matches this model definition to generation.model. Useful in case of fine-tuned models. If you want to exact match, use (?i)^modelname$
Apply only to generations which are newer than this ISO date.
Deprecated. See 'prices' instead. Price (USD) per total unit. Cannot be set if input or output price is set.
Optional. Tokenizer to be applied to observations which match to this model. See docs for more details.
Optional. Configuration for the selected tokenizer. Needs to be JSON. See docs for more details.
82 def json(self, **kwargs: typing.Any) -> str: 83 kwargs_with_defaults: typing.Any = { 84 "by_alias": True, 85 "exclude_unset": True, 86 **kwargs, 87 } 88 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
90 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 91 kwargs_with_defaults_exclude_unset: typing.Any = { 92 "by_alias": True, 93 "exclude_unset": True, 94 **kwargs, 95 } 96 kwargs_with_defaults_exclude_none: typing.Any = { 97 "by_alias": True, 98 "exclude_none": True, 99 **kwargs, 100 } 101 102 return deep_union_pydantic_dicts( 103 super().dict(**kwargs_with_defaults_exclude_unset), 104 super().dict(**kwargs_with_defaults_exclude_none), 105 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ModelPrice(pydantic_v1.BaseModel): 12 price: float 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class ModelUsageUnit(str, enum.Enum): 11 """ 12 Unit of usage in Langfuse 13 """ 14 15 CHARACTERS = "CHARACTERS" 16 TOKENS = "TOKENS" 17 MILLISECONDS = "MILLISECONDS" 18 SECONDS = "SECONDS" 19 IMAGES = "IMAGES" 20 REQUESTS = "REQUESTS" 21 22 def visit( 23 self, 24 characters: typing.Callable[[], T_Result], 25 tokens: typing.Callable[[], T_Result], 26 milliseconds: typing.Callable[[], T_Result], 27 seconds: typing.Callable[[], T_Result], 28 images: typing.Callable[[], T_Result], 29 requests: typing.Callable[[], T_Result], 30 ) -> T_Result: 31 if self is ModelUsageUnit.CHARACTERS: 32 return characters() 33 if self is ModelUsageUnit.TOKENS: 34 return tokens() 35 if self is ModelUsageUnit.MILLISECONDS: 36 return milliseconds() 37 if self is ModelUsageUnit.SECONDS: 38 return seconds() 39 if self is ModelUsageUnit.IMAGES: 40 return images() 41 if self is ModelUsageUnit.REQUESTS: 42 return requests()
Unit of usage in Langfuse
22 def visit( 23 self, 24 characters: typing.Callable[[], T_Result], 25 tokens: typing.Callable[[], T_Result], 26 milliseconds: typing.Callable[[], T_Result], 27 seconds: typing.Callable[[], T_Result], 28 images: typing.Callable[[], T_Result], 29 requests: typing.Callable[[], T_Result], 30 ) -> T_Result: 31 if self is ModelUsageUnit.CHARACTERS: 32 return characters() 33 if self is ModelUsageUnit.TOKENS: 34 return tokens() 35 if self is ModelUsageUnit.MILLISECONDS: 36 return milliseconds() 37 if self is ModelUsageUnit.SECONDS: 38 return seconds() 39 if self is ModelUsageUnit.IMAGES: 40 return images() 41 if self is ModelUsageUnit.REQUESTS: 42 return requests()
9class NotFoundError(ApiError): 10 def __init__(self, body: typing.Any): 11 super().__init__(status_code=404, body=body)
Common base class for all non-exit exceptions.
12class NumericScore(BaseScore): 13 value: float = pydantic_v1.Field() 14 """ 15 The numeric value of the score 16 """ 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class NumericScoreV1(BaseScoreV1): 13 value: float = pydantic_v1.Field() 14 """ 15 The numeric value of the score 16 """ 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class Observation(pydantic_v1.BaseModel): 15 id: str = pydantic_v1.Field() 16 """ 17 The unique identifier of the observation 18 """ 19 20 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 21 """ 22 The trace ID associated with the observation 23 """ 24 25 type: str = pydantic_v1.Field() 26 """ 27 The type of the observation 28 """ 29 30 name: typing.Optional[str] = pydantic_v1.Field(default=None) 31 """ 32 The name of the observation 33 """ 34 35 start_time: dt.datetime = pydantic_v1.Field(alias="startTime") 36 """ 37 The start time of the observation 38 """ 39 40 end_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 41 alias="endTime", default=None 42 ) 43 """ 44 The end time of the observation. 45 """ 46 47 completion_start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 48 alias="completionStartTime", default=None 49 ) 50 """ 51 The completion start time of the observation 52 """ 53 54 model: typing.Optional[str] = pydantic_v1.Field(default=None) 55 """ 56 The model used for the observation 57 """ 58 59 model_parameters: typing.Optional[typing.Dict[str, MapValue]] = pydantic_v1.Field( 60 alias="modelParameters", default=None 61 ) 62 """ 63 The parameters of the model used for the observation 64 """ 65 66 input: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 67 """ 68 The input data of the observation 69 """ 70 71 version: typing.Optional[str] = pydantic_v1.Field(default=None) 72 """ 73 The version of the observation 74 """ 75 76 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 77 """ 78 Additional metadata of the observation 79 """ 80 81 output: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 82 """ 83 The output data of the observation 84 """ 85 86 usage: typing.Optional[Usage] = pydantic_v1.Field(default=None) 87 """ 88 (Deprecated. Use usageDetails and costDetails instead.) The usage data of the observation 89 """ 90 91 level: ObservationLevel = pydantic_v1.Field() 92 """ 93 The level of the observation 94 """ 95 96 status_message: typing.Optional[str] = pydantic_v1.Field( 97 alias="statusMessage", default=None 98 ) 99 """ 100 The status message of the observation 101 """ 102 103 parent_observation_id: typing.Optional[str] = pydantic_v1.Field( 104 alias="parentObservationId", default=None 105 ) 106 """ 107 The parent observation ID 108 """ 109 110 prompt_id: typing.Optional[str] = pydantic_v1.Field(alias="promptId", default=None) 111 """ 112 The prompt ID associated with the observation 113 """ 114 115 usage_details: typing.Optional[typing.Dict[str, int]] = pydantic_v1.Field( 116 alias="usageDetails", default=None 117 ) 118 """ 119 The usage details of the observation. Key is the name of the usage metric, value is the number of units consumed. The total key is the sum of all (non-total) usage metrics or the total value ingested. 120 """ 121 122 cost_details: typing.Optional[typing.Dict[str, float]] = pydantic_v1.Field( 123 alias="costDetails", default=None 124 ) 125 """ 126 The cost details of the observation. Key is the name of the cost metric, value is the cost in USD. The total key is the sum of all (non-total) cost metrics or the total value ingested. 127 """ 128 129 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 130 """ 131 The environment from which this observation originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'. 132 """ 133 134 def json(self, **kwargs: typing.Any) -> str: 135 kwargs_with_defaults: typing.Any = { 136 "by_alias": True, 137 "exclude_unset": True, 138 **kwargs, 139 } 140 return super().json(**kwargs_with_defaults) 141 142 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 143 kwargs_with_defaults_exclude_unset: typing.Any = { 144 "by_alias": True, 145 "exclude_unset": True, 146 **kwargs, 147 } 148 kwargs_with_defaults_exclude_none: typing.Any = { 149 "by_alias": True, 150 "exclude_none": True, 151 **kwargs, 152 } 153 154 return deep_union_pydantic_dicts( 155 super().dict(**kwargs_with_defaults_exclude_unset), 156 super().dict(**kwargs_with_defaults_exclude_none), 157 ) 158 159 class Config: 160 frozen = True 161 smart_union = True 162 allow_population_by_field_name = True 163 populate_by_name = True 164 extra = pydantic_v1.Extra.allow 165 json_encoders = {dt.datetime: serialize_datetime}
The parameters of the model used for the observation
(Deprecated. Use usageDetails and costDetails instead.) The usage data of the observation
The usage details of the observation. Key is the name of the usage metric, value is the number of units consumed. The total key is the sum of all (non-total) usage metrics or the total value ingested.
The cost details of the observation. Key is the name of the cost metric, value is the cost in USD. The total key is the sum of all (non-total) cost metrics or the total value ingested.
The environment from which this observation originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'.
134 def json(self, **kwargs: typing.Any) -> str: 135 kwargs_with_defaults: typing.Any = { 136 "by_alias": True, 137 "exclude_unset": True, 138 **kwargs, 139 } 140 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
142 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 143 kwargs_with_defaults_exclude_unset: typing.Any = { 144 "by_alias": True, 145 "exclude_unset": True, 146 **kwargs, 147 } 148 kwargs_with_defaults_exclude_none: typing.Any = { 149 "by_alias": True, 150 "exclude_none": True, 151 **kwargs, 152 } 153 154 return deep_union_pydantic_dicts( 155 super().dict(**kwargs_with_defaults_exclude_unset), 156 super().dict(**kwargs_with_defaults_exclude_none), 157 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
15class ObservationBody(pydantic_v1.BaseModel): 16 id: typing.Optional[str] = None 17 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 18 type: ObservationType 19 name: typing.Optional[str] = None 20 start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 21 alias="startTime", default=None 22 ) 23 end_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 24 alias="endTime", default=None 25 ) 26 completion_start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 27 alias="completionStartTime", default=None 28 ) 29 model: typing.Optional[str] = None 30 model_parameters: typing.Optional[typing.Dict[str, MapValue]] = pydantic_v1.Field( 31 alias="modelParameters", default=None 32 ) 33 input: typing.Optional[typing.Any] = None 34 version: typing.Optional[str] = None 35 metadata: typing.Optional[typing.Any] = None 36 output: typing.Optional[typing.Any] = None 37 usage: typing.Optional[Usage] = None 38 level: typing.Optional[ObservationLevel] = None 39 status_message: typing.Optional[str] = pydantic_v1.Field( 40 alias="statusMessage", default=None 41 ) 42 parent_observation_id: typing.Optional[str] = pydantic_v1.Field( 43 alias="parentObservationId", default=None 44 ) 45 environment: typing.Optional[str] = None 46 47 def json(self, **kwargs: typing.Any) -> str: 48 kwargs_with_defaults: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 return super().json(**kwargs_with_defaults) 54 55 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 56 kwargs_with_defaults_exclude_unset: typing.Any = { 57 "by_alias": True, 58 "exclude_unset": True, 59 **kwargs, 60 } 61 kwargs_with_defaults_exclude_none: typing.Any = { 62 "by_alias": True, 63 "exclude_none": True, 64 **kwargs, 65 } 66 67 return deep_union_pydantic_dicts( 68 super().dict(**kwargs_with_defaults_exclude_unset), 69 super().dict(**kwargs_with_defaults_exclude_none), 70 ) 71 72 class Config: 73 frozen = True 74 smart_union = True 75 allow_population_by_field_name = True 76 populate_by_name = True 77 extra = pydantic_v1.Extra.allow 78 json_encoders = {dt.datetime: serialize_datetime}
47 def json(self, **kwargs: typing.Any) -> str: 48 kwargs_with_defaults: typing.Any = { 49 "by_alias": True, 50 "exclude_unset": True, 51 **kwargs, 52 } 53 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
55 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 56 kwargs_with_defaults_exclude_unset: typing.Any = { 57 "by_alias": True, 58 "exclude_unset": True, 59 **kwargs, 60 } 61 kwargs_with_defaults_exclude_none: typing.Any = { 62 "by_alias": True, 63 "exclude_none": True, 64 **kwargs, 65 } 66 67 return deep_union_pydantic_dicts( 68 super().dict(**kwargs_with_defaults_exclude_unset), 69 super().dict(**kwargs_with_defaults_exclude_none), 70 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class ObservationLevel(str, enum.Enum): 11 DEBUG = "DEBUG" 12 DEFAULT = "DEFAULT" 13 WARNING = "WARNING" 14 ERROR = "ERROR" 15 16 def visit( 17 self, 18 debug: typing.Callable[[], T_Result], 19 default: typing.Callable[[], T_Result], 20 warning: typing.Callable[[], T_Result], 21 error: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is ObservationLevel.DEBUG: 24 return debug() 25 if self is ObservationLevel.DEFAULT: 26 return default() 27 if self is ObservationLevel.WARNING: 28 return warning() 29 if self is ObservationLevel.ERROR: 30 return error()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
16 def visit( 17 self, 18 debug: typing.Callable[[], T_Result], 19 default: typing.Callable[[], T_Result], 20 warning: typing.Callable[[], T_Result], 21 error: typing.Callable[[], T_Result], 22 ) -> T_Result: 23 if self is ObservationLevel.DEBUG: 24 return debug() 25 if self is ObservationLevel.DEFAULT: 26 return default() 27 if self is ObservationLevel.WARNING: 28 return warning() 29 if self is ObservationLevel.ERROR: 30 return error()
10class ObservationType(str, enum.Enum): 11 SPAN = "SPAN" 12 GENERATION = "GENERATION" 13 EVENT = "EVENT" 14 AGENT = "AGENT" 15 TOOL = "TOOL" 16 CHAIN = "CHAIN" 17 RETRIEVER = "RETRIEVER" 18 EVALUATOR = "EVALUATOR" 19 EMBEDDING = "EMBEDDING" 20 GUARDRAIL = "GUARDRAIL" 21 22 def visit( 23 self, 24 span: typing.Callable[[], T_Result], 25 generation: typing.Callable[[], T_Result], 26 event: typing.Callable[[], T_Result], 27 agent: typing.Callable[[], T_Result], 28 tool: typing.Callable[[], T_Result], 29 chain: typing.Callable[[], T_Result], 30 retriever: typing.Callable[[], T_Result], 31 evaluator: typing.Callable[[], T_Result], 32 embedding: typing.Callable[[], T_Result], 33 guardrail: typing.Callable[[], T_Result], 34 ) -> T_Result: 35 if self is ObservationType.SPAN: 36 return span() 37 if self is ObservationType.GENERATION: 38 return generation() 39 if self is ObservationType.EVENT: 40 return event() 41 if self is ObservationType.AGENT: 42 return agent() 43 if self is ObservationType.TOOL: 44 return tool() 45 if self is ObservationType.CHAIN: 46 return chain() 47 if self is ObservationType.RETRIEVER: 48 return retriever() 49 if self is ObservationType.EVALUATOR: 50 return evaluator() 51 if self is ObservationType.EMBEDDING: 52 return embedding() 53 if self is ObservationType.GUARDRAIL: 54 return guardrail()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
22 def visit( 23 self, 24 span: typing.Callable[[], T_Result], 25 generation: typing.Callable[[], T_Result], 26 event: typing.Callable[[], T_Result], 27 agent: typing.Callable[[], T_Result], 28 tool: typing.Callable[[], T_Result], 29 chain: typing.Callable[[], T_Result], 30 retriever: typing.Callable[[], T_Result], 31 evaluator: typing.Callable[[], T_Result], 32 embedding: typing.Callable[[], T_Result], 33 guardrail: typing.Callable[[], T_Result], 34 ) -> T_Result: 35 if self is ObservationType.SPAN: 36 return span() 37 if self is ObservationType.GENERATION: 38 return generation() 39 if self is ObservationType.EVENT: 40 return event() 41 if self is ObservationType.AGENT: 42 return agent() 43 if self is ObservationType.TOOL: 44 return tool() 45 if self is ObservationType.CHAIN: 46 return chain() 47 if self is ObservationType.RETRIEVER: 48 return retriever() 49 if self is ObservationType.EVALUATOR: 50 return evaluator() 51 if self is ObservationType.EMBEDDING: 52 return embedding() 53 if self is ObservationType.GUARDRAIL: 54 return guardrail()
13class Observations(pydantic_v1.BaseModel): 14 data: typing.List[Observation] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class ObservationsView(Observation): 13 prompt_name: typing.Optional[str] = pydantic_v1.Field( 14 alias="promptName", default=None 15 ) 16 """ 17 The name of the prompt associated with the observation 18 """ 19 20 prompt_version: typing.Optional[int] = pydantic_v1.Field( 21 alias="promptVersion", default=None 22 ) 23 """ 24 The version of the prompt associated with the observation 25 """ 26 27 model_id: typing.Optional[str] = pydantic_v1.Field(alias="modelId", default=None) 28 """ 29 The unique identifier of the model 30 """ 31 32 input_price: typing.Optional[float] = pydantic_v1.Field( 33 alias="inputPrice", default=None 34 ) 35 """ 36 The price of the input in USD 37 """ 38 39 output_price: typing.Optional[float] = pydantic_v1.Field( 40 alias="outputPrice", default=None 41 ) 42 """ 43 The price of the output in USD. 44 """ 45 46 total_price: typing.Optional[float] = pydantic_v1.Field( 47 alias="totalPrice", default=None 48 ) 49 """ 50 The total price in USD. 51 """ 52 53 calculated_input_cost: typing.Optional[float] = pydantic_v1.Field( 54 alias="calculatedInputCost", default=None 55 ) 56 """ 57 (Deprecated. Use usageDetails and costDetails instead.) The calculated cost of the input in USD 58 """ 59 60 calculated_output_cost: typing.Optional[float] = pydantic_v1.Field( 61 alias="calculatedOutputCost", default=None 62 ) 63 """ 64 (Deprecated. Use usageDetails and costDetails instead.) The calculated cost of the output in USD 65 """ 66 67 calculated_total_cost: typing.Optional[float] = pydantic_v1.Field( 68 alias="calculatedTotalCost", default=None 69 ) 70 """ 71 (Deprecated. Use usageDetails and costDetails instead.) The calculated total cost in USD 72 """ 73 74 latency: typing.Optional[float] = pydantic_v1.Field(default=None) 75 """ 76 The latency in seconds. 77 """ 78 79 time_to_first_token: typing.Optional[float] = pydantic_v1.Field( 80 alias="timeToFirstToken", default=None 81 ) 82 """ 83 The time to the first token in seconds 84 """ 85 86 def json(self, **kwargs: typing.Any) -> str: 87 kwargs_with_defaults: typing.Any = { 88 "by_alias": True, 89 "exclude_unset": True, 90 **kwargs, 91 } 92 return super().json(**kwargs_with_defaults) 93 94 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 95 kwargs_with_defaults_exclude_unset: typing.Any = { 96 "by_alias": True, 97 "exclude_unset": True, 98 **kwargs, 99 } 100 kwargs_with_defaults_exclude_none: typing.Any = { 101 "by_alias": True, 102 "exclude_none": True, 103 **kwargs, 104 } 105 106 return deep_union_pydantic_dicts( 107 super().dict(**kwargs_with_defaults_exclude_unset), 108 super().dict(**kwargs_with_defaults_exclude_none), 109 ) 110 111 class Config: 112 frozen = True 113 smart_union = True 114 allow_population_by_field_name = True 115 populate_by_name = True 116 extra = pydantic_v1.Extra.allow 117 json_encoders = {dt.datetime: serialize_datetime}
(Deprecated. Use usageDetails and costDetails instead.) The calculated cost of the input in USD
(Deprecated. Use usageDetails and costDetails instead.) The calculated cost of the output in USD
(Deprecated. Use usageDetails and costDetails instead.) The calculated total cost in USD
86 def json(self, **kwargs: typing.Any) -> str: 87 kwargs_with_defaults: typing.Any = { 88 "by_alias": True, 89 "exclude_unset": True, 90 **kwargs, 91 } 92 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
94 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 95 kwargs_with_defaults_exclude_unset: typing.Any = { 96 "by_alias": True, 97 "exclude_unset": True, 98 **kwargs, 99 } 100 kwargs_with_defaults_exclude_none: typing.Any = { 101 "by_alias": True, 102 "exclude_none": True, 103 **kwargs, 104 } 105 106 return deep_union_pydantic_dicts( 107 super().dict(**kwargs_with_defaults_exclude_unset), 108 super().dict(**kwargs_with_defaults_exclude_none), 109 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ObservationsViews(pydantic_v1.BaseModel): 14 data: typing.List[ObservationsView] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class OpenAiCompletionUsageSchema(pydantic_v1.BaseModel): 12 """ 13 OpenAI Usage schema from (Chat-)Completion APIs 14 """ 15 16 prompt_tokens: int 17 completion_tokens: int 18 total_tokens: int 19 prompt_tokens_details: typing.Optional[typing.Dict[str, typing.Optional[int]]] = ( 20 None 21 ) 22 completion_tokens_details: typing.Optional[ 23 typing.Dict[str, typing.Optional[int]] 24 ] = None 25 26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults) 33 34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 ) 50 51 class Config: 52 frozen = True 53 smart_union = True 54 extra = pydantic_v1.Extra.allow 55 json_encoders = {dt.datetime: serialize_datetime}
OpenAI Usage schema from (Chat-)Completion APIs
26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class OpenAiResponseUsageSchema(pydantic_v1.BaseModel): 12 """ 13 OpenAI Usage schema from Response API 14 """ 15 16 input_tokens: int 17 output_tokens: int 18 total_tokens: int 19 input_tokens_details: typing.Optional[typing.Dict[str, typing.Optional[int]]] = None 20 output_tokens_details: typing.Optional[typing.Dict[str, typing.Optional[int]]] = ( 21 None 22 ) 23 24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults) 31 32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 ) 48 49 class Config: 50 frozen = True 51 smart_union = True 52 extra = pydantic_v1.Extra.allow 53 json_encoders = {dt.datetime: serialize_datetime}
OpenAI Usage schema from Response API
24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
32 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 33 kwargs_with_defaults_exclude_unset: typing.Any = { 34 "by_alias": True, 35 "exclude_unset": True, 36 **kwargs, 37 } 38 kwargs_with_defaults_exclude_none: typing.Any = { 39 "by_alias": True, 40 "exclude_none": True, 41 **kwargs, 42 } 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 46 super().dict(**kwargs_with_defaults_exclude_none), 47 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class OpenAiUsage(pydantic_v1.BaseModel): 12 """ 13 Usage interface of OpenAI for improved compatibility. 14 """ 15 16 prompt_tokens: typing.Optional[int] = pydantic_v1.Field( 17 alias="promptTokens", default=None 18 ) 19 completion_tokens: typing.Optional[int] = pydantic_v1.Field( 20 alias="completionTokens", default=None 21 ) 22 total_tokens: typing.Optional[int] = pydantic_v1.Field( 23 alias="totalTokens", default=None 24 ) 25 26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults) 33 34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 ) 50 51 class Config: 52 frozen = True 53 smart_union = True 54 allow_population_by_field_name = True 55 populate_by_name = True 56 extra = pydantic_v1.Extra.allow 57 json_encoders = {dt.datetime: serialize_datetime}
Usage interface of OpenAI for improved compatibility.
26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class OptionalObservationBody(pydantic_v1.BaseModel): 13 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 14 name: typing.Optional[str] = None 15 start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 16 alias="startTime", default=None 17 ) 18 metadata: typing.Optional[typing.Any] = None 19 input: typing.Optional[typing.Any] = None 20 output: typing.Optional[typing.Any] = None 21 level: typing.Optional[ObservationLevel] = None 22 status_message: typing.Optional[str] = pydantic_v1.Field( 23 alias="statusMessage", default=None 24 ) 25 parent_observation_id: typing.Optional[str] = pydantic_v1.Field( 26 alias="parentObservationId", default=None 27 ) 28 version: typing.Optional[str] = None 29 environment: typing.Optional[str] = None 30 31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults) 38 39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 ) 55 56 class Config: 57 frozen = True 58 smart_union = True 59 allow_population_by_field_name = True 60 populate_by_name = True 61 extra = pydantic_v1.Extra.allow 62 json_encoders = {dt.datetime: serialize_datetime}
31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class OrganizationProject(pydantic_v1.BaseModel): 12 id: str 13 name: str 14 metadata: typing.Optional[typing.Dict[str, typing.Any]] = None 15 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 16 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class OrganizationProjectsResponse(pydantic_v1.BaseModel): 13 projects: typing.List[OrganizationProject] 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedAnnotationQueueItems(pydantic_v1.BaseModel): 14 data: typing.List[AnnotationQueueItem] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedAnnotationQueues(pydantic_v1.BaseModel): 14 data: typing.List[AnnotationQueue] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedDatasetItems(pydantic_v1.BaseModel): 14 data: typing.List[DatasetItem] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedDatasetRunItems(pydantic_v1.BaseModel): 14 data: typing.List[DatasetRunItem] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedDatasetRuns(pydantic_v1.BaseModel): 14 data: typing.List[DatasetRun] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedDatasets(pydantic_v1.BaseModel): 14 data: typing.List[Dataset] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedLlmConnections(pydantic_v1.BaseModel): 14 data: typing.List[LlmConnection] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedModels(pydantic_v1.BaseModel): 14 data: typing.List[Model] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PaginatedSessions(pydantic_v1.BaseModel): 14 data: typing.List[Session] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class PatchMediaBody(pydantic_v1.BaseModel): 12 uploaded_at: dt.datetime = pydantic_v1.Field(alias="uploadedAt") 13 """ 14 The date and time when the media record was uploaded 15 """ 16 17 upload_http_status: int = pydantic_v1.Field(alias="uploadHttpStatus") 18 """ 19 The HTTP status code of the upload 20 """ 21 22 upload_http_error: typing.Optional[str] = pydantic_v1.Field( 23 alias="uploadHttpError", default=None 24 ) 25 """ 26 The HTTP error message of the upload 27 """ 28 29 upload_time_ms: typing.Optional[int] = pydantic_v1.Field( 30 alias="uploadTimeMs", default=None 31 ) 32 """ 33 The time in milliseconds it took to upload the media record 34 """ 35 36 def json(self, **kwargs: typing.Any) -> str: 37 kwargs_with_defaults: typing.Any = { 38 "by_alias": True, 39 "exclude_unset": True, 40 **kwargs, 41 } 42 return super().json(**kwargs_with_defaults) 43 44 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 45 kwargs_with_defaults_exclude_unset: typing.Any = { 46 "by_alias": True, 47 "exclude_unset": True, 48 **kwargs, 49 } 50 kwargs_with_defaults_exclude_none: typing.Any = { 51 "by_alias": True, 52 "exclude_none": True, 53 **kwargs, 54 } 55 56 return deep_union_pydantic_dicts( 57 super().dict(**kwargs_with_defaults_exclude_unset), 58 super().dict(**kwargs_with_defaults_exclude_none), 59 ) 60 61 class Config: 62 frozen = True 63 smart_union = True 64 allow_population_by_field_name = True 65 populate_by_name = True 66 extra = pydantic_v1.Extra.allow 67 json_encoders = {dt.datetime: serialize_datetime}
36 def json(self, **kwargs: typing.Any) -> str: 37 kwargs_with_defaults: typing.Any = { 38 "by_alias": True, 39 "exclude_unset": True, 40 **kwargs, 41 } 42 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
44 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 45 kwargs_with_defaults_exclude_unset: typing.Any = { 46 "by_alias": True, 47 "exclude_unset": True, 48 **kwargs, 49 } 50 kwargs_with_defaults_exclude_none: typing.Any = { 51 "by_alias": True, 52 "exclude_none": True, 53 **kwargs, 54 } 55 56 return deep_union_pydantic_dicts( 57 super().dict(**kwargs_with_defaults_exclude_unset), 58 super().dict(**kwargs_with_defaults_exclude_none), 59 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class PlaceholderMessage(pydantic_v1.BaseModel): 12 name: str 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class Project(pydantic_v1.BaseModel): 12 id: str 13 name: str 14 metadata: typing.Dict[str, typing.Any] = pydantic_v1.Field() 15 """ 16 Metadata for the project 17 """ 18 19 retention_days: typing.Optional[int] = pydantic_v1.Field( 20 alias="retentionDays", default=None 21 ) 22 """ 23 Number of days to retain data. Null or 0 means no retention. Omitted if no retention is configured. 24 """ 25 26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults) 33 34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 ) 50 51 class Config: 52 frozen = True 53 smart_union = True 54 allow_population_by_field_name = True 55 populate_by_name = True 56 extra = pydantic_v1.Extra.allow 57 json_encoders = {dt.datetime: serialize_datetime}
Number of days to retain data. Null or 0 means no retention. Omitted if no retention is configured.
26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
34 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 35 kwargs_with_defaults_exclude_unset: typing.Any = { 36 "by_alias": True, 37 "exclude_unset": True, 38 **kwargs, 39 } 40 kwargs_with_defaults_exclude_none: typing.Any = { 41 "by_alias": True, 42 "exclude_none": True, 43 **kwargs, 44 } 45 46 return deep_union_pydantic_dicts( 47 super().dict(**kwargs_with_defaults_exclude_unset), 48 super().dict(**kwargs_with_defaults_exclude_none), 49 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ProjectDeletionResponse(pydantic_v1.BaseModel): 12 success: bool 13 message: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class Projects(pydantic_v1.BaseModel): 13 data: typing.List[Project] 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class PromptMeta(pydantic_v1.BaseModel): 12 name: str 13 versions: typing.List[int] 14 labels: typing.List[str] 15 tags: typing.List[str] 16 last_updated_at: dt.datetime = pydantic_v1.Field(alias="lastUpdatedAt") 17 last_config: typing.Any = pydantic_v1.Field(alias="lastConfig") 18 """ 19 Config object of the most recent prompt version that matches the filters (if any are provided) 20 """ 21 22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 return super().json(**kwargs_with_defaults) 29 30 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 31 kwargs_with_defaults_exclude_unset: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 kwargs_with_defaults_exclude_none: typing.Any = { 37 "by_alias": True, 38 "exclude_none": True, 39 **kwargs, 40 } 41 42 return deep_union_pydantic_dicts( 43 super().dict(**kwargs_with_defaults_exclude_unset), 44 super().dict(**kwargs_with_defaults_exclude_none), 45 ) 46 47 class Config: 48 frozen = True 49 smart_union = True 50 allow_population_by_field_name = True 51 populate_by_name = True 52 extra = pydantic_v1.Extra.allow 53 json_encoders = {dt.datetime: serialize_datetime}
Config object of the most recent prompt version that matches the filters (if any are provided)
22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
30 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 31 kwargs_with_defaults_exclude_unset: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 kwargs_with_defaults_exclude_none: typing.Any = { 37 "by_alias": True, 38 "exclude_none": True, 39 **kwargs, 40 } 41 42 return deep_union_pydantic_dicts( 43 super().dict(**kwargs_with_defaults_exclude_unset), 44 super().dict(**kwargs_with_defaults_exclude_none), 45 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class PromptMetaListResponse(pydantic_v1.BaseModel): 14 data: typing.List[PromptMeta] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class Prompt_Chat(pydantic_v1.BaseModel): 15 prompt: typing.List[ChatMessageWithPlaceholders] 16 name: str 17 version: int 18 config: typing.Any 19 labels: typing.List[str] 20 tags: typing.List[str] 21 commit_message: typing.Optional[str] = pydantic_v1.Field( 22 alias="commitMessage", default=None 23 ) 24 resolution_graph: typing.Optional[typing.Dict[str, typing.Any]] = pydantic_v1.Field( 25 alias="resolutionGraph", default=None 26 ) 27 type: typing.Literal["chat"] = "chat" 28 29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 return super().json(**kwargs_with_defaults) 36 37 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 38 kwargs_with_defaults_exclude_unset: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 kwargs_with_defaults_exclude_none: typing.Any = { 44 "by_alias": True, 45 "exclude_none": True, 46 **kwargs, 47 } 48 49 return deep_union_pydantic_dicts( 50 super().dict(**kwargs_with_defaults_exclude_unset), 51 super().dict(**kwargs_with_defaults_exclude_none), 52 ) 53 54 class Config: 55 frozen = True 56 smart_union = True 57 allow_population_by_field_name = True 58 populate_by_name = True 59 extra = pydantic_v1.Extra.allow 60 json_encoders = {dt.datetime: serialize_datetime}
29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = { 31 "by_alias": True, 32 "exclude_unset": True, 33 **kwargs, 34 } 35 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
37 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 38 kwargs_with_defaults_exclude_unset: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 kwargs_with_defaults_exclude_none: typing.Any = { 44 "by_alias": True, 45 "exclude_none": True, 46 **kwargs, 47 } 48 49 return deep_union_pydantic_dicts( 50 super().dict(**kwargs_with_defaults_exclude_unset), 51 super().dict(**kwargs_with_defaults_exclude_none), 52 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
63class Prompt_Text(pydantic_v1.BaseModel): 64 prompt: str 65 name: str 66 version: int 67 config: typing.Any 68 labels: typing.List[str] 69 tags: typing.List[str] 70 commit_message: typing.Optional[str] = pydantic_v1.Field( 71 alias="commitMessage", default=None 72 ) 73 resolution_graph: typing.Optional[typing.Dict[str, typing.Any]] = pydantic_v1.Field( 74 alias="resolutionGraph", default=None 75 ) 76 type: typing.Literal["text"] = "text" 77 78 def json(self, **kwargs: typing.Any) -> str: 79 kwargs_with_defaults: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 return super().json(**kwargs_with_defaults) 85 86 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 87 kwargs_with_defaults_exclude_unset: typing.Any = { 88 "by_alias": True, 89 "exclude_unset": True, 90 **kwargs, 91 } 92 kwargs_with_defaults_exclude_none: typing.Any = { 93 "by_alias": True, 94 "exclude_none": True, 95 **kwargs, 96 } 97 98 return deep_union_pydantic_dicts( 99 super().dict(**kwargs_with_defaults_exclude_unset), 100 super().dict(**kwargs_with_defaults_exclude_none), 101 ) 102 103 class Config: 104 frozen = True 105 smart_union = True 106 allow_population_by_field_name = True 107 populate_by_name = True 108 extra = pydantic_v1.Extra.allow 109 json_encoders = {dt.datetime: serialize_datetime}
78 def json(self, **kwargs: typing.Any) -> str: 79 kwargs_with_defaults: typing.Any = { 80 "by_alias": True, 81 "exclude_unset": True, 82 **kwargs, 83 } 84 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
86 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 87 kwargs_with_defaults_exclude_unset: typing.Any = { 88 "by_alias": True, 89 "exclude_unset": True, 90 **kwargs, 91 } 92 kwargs_with_defaults_exclude_none: typing.Any = { 93 "by_alias": True, 94 "exclude_none": True, 95 **kwargs, 96 } 97 98 return deep_union_pydantic_dicts( 99 super().dict(**kwargs_with_defaults_exclude_unset), 100 super().dict(**kwargs_with_defaults_exclude_none), 101 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ResourceMeta(pydantic_v1.BaseModel): 12 resource_type: str = pydantic_v1.Field(alias="resourceType") 13 location: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ResourceType(pydantic_v1.BaseModel): 14 schemas: typing.Optional[typing.List[str]] = None 15 id: str 16 name: str 17 endpoint: str 18 description: str 19 schema_: str = pydantic_v1.Field(alias="schema") 20 schema_extensions: typing.List[SchemaExtension] = pydantic_v1.Field( 21 alias="schemaExtensions" 22 ) 23 meta: ResourceMeta 24 25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults) 32 33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 ) 49 50 class Config: 51 frozen = True 52 smart_union = True 53 allow_population_by_field_name = True 54 populate_by_name = True 55 extra = pydantic_v1.Extra.allow 56 json_encoders = {dt.datetime: serialize_datetime}
25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
33 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 34 kwargs_with_defaults_exclude_unset: typing.Any = { 35 "by_alias": True, 36 "exclude_unset": True, 37 **kwargs, 38 } 39 kwargs_with_defaults_exclude_none: typing.Any = { 40 "by_alias": True, 41 "exclude_none": True, 42 **kwargs, 43 } 44 45 return deep_union_pydantic_dicts( 46 super().dict(**kwargs_with_defaults_exclude_unset), 47 super().dict(**kwargs_with_defaults_exclude_none), 48 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class ResourceTypesResponse(pydantic_v1.BaseModel): 13 schemas: typing.List[str] 14 total_results: int = pydantic_v1.Field(alias="totalResults") 15 resources: typing.List[ResourceType] = pydantic_v1.Field(alias="Resources") 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 allow_population_by_field_name = True 46 populate_by_name = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class SchemaExtension(pydantic_v1.BaseModel): 12 schema_: str = pydantic_v1.Field(alias="schema") 13 required: bool 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class SchemaResource(pydantic_v1.BaseModel): 13 id: str 14 name: str 15 description: str 16 attributes: typing.List[typing.Any] 17 meta: ResourceMeta 18 19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults) 26 27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 ) 43 44 class Config: 45 frozen = True 46 smart_union = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class SchemasResponse(pydantic_v1.BaseModel): 13 schemas: typing.List[str] 14 total_results: int = pydantic_v1.Field(alias="totalResults") 15 resources: typing.List[SchemaResource] = pydantic_v1.Field(alias="Resources") 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 allow_population_by_field_name = True 46 populate_by_name = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ScimEmail(pydantic_v1.BaseModel): 12 primary: bool 13 value: str 14 type: str 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 extra = pydantic_v1.Extra.allow 45 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ScimFeatureSupport(pydantic_v1.BaseModel): 12 supported: bool 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class ScimName(pydantic_v1.BaseModel): 12 formatted: typing.Optional[str] = None 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class ScimUser(pydantic_v1.BaseModel): 15 schemas: typing.List[str] 16 id: str 17 user_name: str = pydantic_v1.Field(alias="userName") 18 name: ScimName 19 emails: typing.List[ScimEmail] 20 meta: UserMeta 21 22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 return super().json(**kwargs_with_defaults) 29 30 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 31 kwargs_with_defaults_exclude_unset: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 kwargs_with_defaults_exclude_none: typing.Any = { 37 "by_alias": True, 38 "exclude_none": True, 39 **kwargs, 40 } 41 42 return deep_union_pydantic_dicts( 43 super().dict(**kwargs_with_defaults_exclude_unset), 44 super().dict(**kwargs_with_defaults_exclude_none), 45 ) 46 47 class Config: 48 frozen = True 49 smart_union = True 50 allow_population_by_field_name = True 51 populate_by_name = True 52 extra = pydantic_v1.Extra.allow 53 json_encoders = {dt.datetime: serialize_datetime}
22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
30 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 31 kwargs_with_defaults_exclude_unset: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 kwargs_with_defaults_exclude_none: typing.Any = { 37 "by_alias": True, 38 "exclude_none": True, 39 **kwargs, 40 } 41 42 return deep_union_pydantic_dicts( 43 super().dict(**kwargs_with_defaults_exclude_unset), 44 super().dict(**kwargs_with_defaults_exclude_none), 45 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class ScimUsersListResponse(pydantic_v1.BaseModel): 13 schemas: typing.List[str] 14 total_results: int = pydantic_v1.Field(alias="totalResults") 15 start_index: int = pydantic_v1.Field(alias="startIndex") 16 items_per_page: int = pydantic_v1.Field(alias="itemsPerPage") 17 resources: typing.List[ScimUser] = pydantic_v1.Field(alias="Resources") 18 19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults) 26 27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 ) 43 44 class Config: 45 frozen = True 46 smart_union = True 47 allow_population_by_field_name = True 48 populate_by_name = True 49 extra = pydantic_v1.Extra.allow 50 json_encoders = {dt.datetime: serialize_datetime}
19 def json(self, **kwargs: typing.Any) -> str: 20 kwargs_with_defaults: typing.Any = { 21 "by_alias": True, 22 "exclude_unset": True, 23 **kwargs, 24 } 25 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
27 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 28 kwargs_with_defaults_exclude_unset: typing.Any = { 29 "by_alias": True, 30 "exclude_unset": True, 31 **kwargs, 32 } 33 kwargs_with_defaults_exclude_none: typing.Any = { 34 "by_alias": True, 35 "exclude_none": True, 36 **kwargs, 37 } 38 39 return deep_union_pydantic_dicts( 40 super().dict(**kwargs_with_defaults_exclude_unset), 41 super().dict(**kwargs_with_defaults_exclude_none), 42 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ScoreBody(pydantic_v1.BaseModel): 14 """ 15 Examples 16 -------- 17 from langfuse import ScoreBody 18 19 ScoreBody( 20 name="novelty", 21 value=0.9, 22 trace_id="cdef-1234-5678-90ab", 23 ) 24 """ 25 26 id: typing.Optional[str] = None 27 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 28 session_id: typing.Optional[str] = pydantic_v1.Field( 29 alias="sessionId", default=None 30 ) 31 observation_id: typing.Optional[str] = pydantic_v1.Field( 32 alias="observationId", default=None 33 ) 34 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 35 alias="datasetRunId", default=None 36 ) 37 name: str 38 environment: typing.Optional[str] = None 39 value: CreateScoreValue = pydantic_v1.Field() 40 """ 41 The value of the score. Must be passed as string for categorical scores, and numeric for boolean and numeric scores. Boolean score values must equal either 1 or 0 (true or false) 42 """ 43 44 comment: typing.Optional[str] = None 45 metadata: typing.Optional[typing.Any] = None 46 data_type: typing.Optional[ScoreDataType] = pydantic_v1.Field( 47 alias="dataType", default=None 48 ) 49 """ 50 When set, must match the score value's type. If not set, will be inferred from the score value or config 51 """ 52 53 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 54 """ 55 Reference a score config on a score. When set, the score name must equal the config name and scores must comply with the config's range and data type. For categorical scores, the value must map to a config category. Numeric scores might be constrained by the score config's max and min values 56 """ 57 58 def json(self, **kwargs: typing.Any) -> str: 59 kwargs_with_defaults: typing.Any = { 60 "by_alias": True, 61 "exclude_unset": True, 62 **kwargs, 63 } 64 return super().json(**kwargs_with_defaults) 65 66 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 67 kwargs_with_defaults_exclude_unset: typing.Any = { 68 "by_alias": True, 69 "exclude_unset": True, 70 **kwargs, 71 } 72 kwargs_with_defaults_exclude_none: typing.Any = { 73 "by_alias": True, 74 "exclude_none": True, 75 **kwargs, 76 } 77 78 return deep_union_pydantic_dicts( 79 super().dict(**kwargs_with_defaults_exclude_unset), 80 super().dict(**kwargs_with_defaults_exclude_none), 81 ) 82 83 class Config: 84 frozen = True 85 smart_union = True 86 allow_population_by_field_name = True 87 populate_by_name = True 88 extra = pydantic_v1.Extra.allow 89 json_encoders = {dt.datetime: serialize_datetime}
Examples
from langfuse import ScoreBody
ScoreBody( name="novelty", value=0.9, trace_id="cdef-1234-5678-90ab", )
The value of the score. Must be passed as string for categorical scores, and numeric for boolean and numeric scores. Boolean score values must equal either 1 or 0 (true or false)
When set, must match the score value's type. If not set, will be inferred from the score value or config
Reference a score config on a score. When set, the score name must equal the config name and scores must comply with the config's range and data type. For categorical scores, the value must map to a config category. Numeric scores might be constrained by the score config's max and min values
58 def json(self, **kwargs: typing.Any) -> str: 59 kwargs_with_defaults: typing.Any = { 60 "by_alias": True, 61 "exclude_unset": True, 62 **kwargs, 63 } 64 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
66 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 67 kwargs_with_defaults_exclude_unset: typing.Any = { 68 "by_alias": True, 69 "exclude_unset": True, 70 **kwargs, 71 } 72 kwargs_with_defaults_exclude_none: typing.Any = { 73 "by_alias": True, 74 "exclude_none": True, 75 **kwargs, 76 } 77 78 return deep_union_pydantic_dicts( 79 super().dict(**kwargs_with_defaults_exclude_unset), 80 super().dict(**kwargs_with_defaults_exclude_none), 81 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ScoreConfig(pydantic_v1.BaseModel): 14 """ 15 Configuration for a score 16 """ 17 18 id: str 19 name: str 20 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 21 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 22 project_id: str = pydantic_v1.Field(alias="projectId") 23 data_type: ScoreDataType = pydantic_v1.Field(alias="dataType") 24 is_archived: bool = pydantic_v1.Field(alias="isArchived") 25 """ 26 Whether the score config is archived. Defaults to false 27 """ 28 29 min_value: typing.Optional[float] = pydantic_v1.Field( 30 alias="minValue", default=None 31 ) 32 """ 33 Sets minimum value for numerical scores. If not set, the minimum value defaults to -∞ 34 """ 35 36 max_value: typing.Optional[float] = pydantic_v1.Field( 37 alias="maxValue", default=None 38 ) 39 """ 40 Sets maximum value for numerical scores. If not set, the maximum value defaults to +∞ 41 """ 42 43 categories: typing.Optional[typing.List[ConfigCategory]] = pydantic_v1.Field( 44 default=None 45 ) 46 """ 47 Configures custom categories for categorical scores 48 """ 49 50 description: typing.Optional[str] = None 51 52 def json(self, **kwargs: typing.Any) -> str: 53 kwargs_with_defaults: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 return super().json(**kwargs_with_defaults) 59 60 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 61 kwargs_with_defaults_exclude_unset: typing.Any = { 62 "by_alias": True, 63 "exclude_unset": True, 64 **kwargs, 65 } 66 kwargs_with_defaults_exclude_none: typing.Any = { 67 "by_alias": True, 68 "exclude_none": True, 69 **kwargs, 70 } 71 72 return deep_union_pydantic_dicts( 73 super().dict(**kwargs_with_defaults_exclude_unset), 74 super().dict(**kwargs_with_defaults_exclude_none), 75 ) 76 77 class Config: 78 frozen = True 79 smart_union = True 80 allow_population_by_field_name = True 81 populate_by_name = True 82 extra = pydantic_v1.Extra.allow 83 json_encoders = {dt.datetime: serialize_datetime}
Configuration for a score
Sets minimum value for numerical scores. If not set, the minimum value defaults to -∞
Sets maximum value for numerical scores. If not set, the maximum value defaults to +∞
52 def json(self, **kwargs: typing.Any) -> str: 53 kwargs_with_defaults: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
60 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 61 kwargs_with_defaults_exclude_unset: typing.Any = { 62 "by_alias": True, 63 "exclude_unset": True, 64 **kwargs, 65 } 66 kwargs_with_defaults_exclude_none: typing.Any = { 67 "by_alias": True, 68 "exclude_none": True, 69 **kwargs, 70 } 71 72 return deep_union_pydantic_dicts( 73 super().dict(**kwargs_with_defaults_exclude_unset), 74 super().dict(**kwargs_with_defaults_exclude_none), 75 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class ScoreConfigs(pydantic_v1.BaseModel): 14 data: typing.List[ScoreConfig] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class ScoreDataType(str, enum.Enum): 11 NUMERIC = "NUMERIC" 12 BOOLEAN = "BOOLEAN" 13 CATEGORICAL = "CATEGORICAL" 14 15 def visit( 16 self, 17 numeric: typing.Callable[[], T_Result], 18 boolean: typing.Callable[[], T_Result], 19 categorical: typing.Callable[[], T_Result], 20 ) -> T_Result: 21 if self is ScoreDataType.NUMERIC: 22 return numeric() 23 if self is ScoreDataType.BOOLEAN: 24 return boolean() 25 if self is ScoreDataType.CATEGORICAL: 26 return categorical()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
15 def visit( 16 self, 17 numeric: typing.Callable[[], T_Result], 18 boolean: typing.Callable[[], T_Result], 19 categorical: typing.Callable[[], T_Result], 20 ) -> T_Result: 21 if self is ScoreDataType.NUMERIC: 22 return numeric() 23 if self is ScoreDataType.BOOLEAN: 24 return boolean() 25 if self is ScoreDataType.CATEGORICAL: 26 return categorical()
13class ScoreEvent(BaseEvent): 14 body: ScoreBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
10class ScoreSource(str, enum.Enum): 11 ANNOTATION = "ANNOTATION" 12 API = "API" 13 EVAL = "EVAL" 14 15 def visit( 16 self, 17 annotation: typing.Callable[[], T_Result], 18 api: typing.Callable[[], T_Result], 19 eval: typing.Callable[[], T_Result], 20 ) -> T_Result: 21 if self is ScoreSource.ANNOTATION: 22 return annotation() 23 if self is ScoreSource.API: 24 return api() 25 if self is ScoreSource.EVAL: 26 return eval()
str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str
Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.
15 def visit( 16 self, 17 annotation: typing.Callable[[], T_Result], 18 api: typing.Callable[[], T_Result], 19 eval: typing.Callable[[], T_Result], 20 ) -> T_Result: 21 if self is ScoreSource.ANNOTATION: 22 return annotation() 23 if self is ScoreSource.API: 24 return api() 25 if self is ScoreSource.EVAL: 26 return eval()
131class ScoreV1_Boolean(pydantic_v1.BaseModel): 132 value: float 133 string_value: str = pydantic_v1.Field(alias="stringValue") 134 id: str 135 trace_id: str = pydantic_v1.Field(alias="traceId") 136 name: str 137 source: ScoreSource 138 observation_id: typing.Optional[str] = pydantic_v1.Field( 139 alias="observationId", default=None 140 ) 141 timestamp: dt.datetime 142 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 143 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 144 author_user_id: typing.Optional[str] = pydantic_v1.Field( 145 alias="authorUserId", default=None 146 ) 147 comment: typing.Optional[str] = None 148 metadata: typing.Optional[typing.Any] = None 149 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 150 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 151 environment: typing.Optional[str] = None 152 data_type: typing.Literal["BOOLEAN"] = pydantic_v1.Field( 153 alias="dataType", default="BOOLEAN" 154 ) 155 156 def json(self, **kwargs: typing.Any) -> str: 157 kwargs_with_defaults: typing.Any = { 158 "by_alias": True, 159 "exclude_unset": True, 160 **kwargs, 161 } 162 return super().json(**kwargs_with_defaults) 163 164 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 165 kwargs_with_defaults_exclude_unset: typing.Any = { 166 "by_alias": True, 167 "exclude_unset": True, 168 **kwargs, 169 } 170 kwargs_with_defaults_exclude_none: typing.Any = { 171 "by_alias": True, 172 "exclude_none": True, 173 **kwargs, 174 } 175 176 return deep_union_pydantic_dicts( 177 super().dict(**kwargs_with_defaults_exclude_unset), 178 super().dict(**kwargs_with_defaults_exclude_none), 179 ) 180 181 class Config: 182 frozen = True 183 smart_union = True 184 allow_population_by_field_name = True 185 populate_by_name = True 186 extra = pydantic_v1.Extra.allow 187 json_encoders = {dt.datetime: serialize_datetime}
156 def json(self, **kwargs: typing.Any) -> str: 157 kwargs_with_defaults: typing.Any = { 158 "by_alias": True, 159 "exclude_unset": True, 160 **kwargs, 161 } 162 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
164 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 165 kwargs_with_defaults_exclude_unset: typing.Any = { 166 "by_alias": True, 167 "exclude_unset": True, 168 **kwargs, 169 } 170 kwargs_with_defaults_exclude_none: typing.Any = { 171 "by_alias": True, 172 "exclude_none": True, 173 **kwargs, 174 } 175 176 return deep_union_pydantic_dicts( 177 super().dict(**kwargs_with_defaults_exclude_unset), 178 super().dict(**kwargs_with_defaults_exclude_none), 179 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
72class ScoreV1_Categorical(pydantic_v1.BaseModel): 73 value: typing.Optional[float] = None 74 string_value: str = pydantic_v1.Field(alias="stringValue") 75 id: str 76 trace_id: str = pydantic_v1.Field(alias="traceId") 77 name: str 78 source: ScoreSource 79 observation_id: typing.Optional[str] = pydantic_v1.Field( 80 alias="observationId", default=None 81 ) 82 timestamp: dt.datetime 83 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 84 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 85 author_user_id: typing.Optional[str] = pydantic_v1.Field( 86 alias="authorUserId", default=None 87 ) 88 comment: typing.Optional[str] = None 89 metadata: typing.Optional[typing.Any] = None 90 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 91 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 92 environment: typing.Optional[str] = None 93 data_type: typing.Literal["CATEGORICAL"] = pydantic_v1.Field( 94 alias="dataType", default="CATEGORICAL" 95 ) 96 97 def json(self, **kwargs: typing.Any) -> str: 98 kwargs_with_defaults: typing.Any = { 99 "by_alias": True, 100 "exclude_unset": True, 101 **kwargs, 102 } 103 return super().json(**kwargs_with_defaults) 104 105 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 106 kwargs_with_defaults_exclude_unset: typing.Any = { 107 "by_alias": True, 108 "exclude_unset": True, 109 **kwargs, 110 } 111 kwargs_with_defaults_exclude_none: typing.Any = { 112 "by_alias": True, 113 "exclude_none": True, 114 **kwargs, 115 } 116 117 return deep_union_pydantic_dicts( 118 super().dict(**kwargs_with_defaults_exclude_unset), 119 super().dict(**kwargs_with_defaults_exclude_none), 120 ) 121 122 class Config: 123 frozen = True 124 smart_union = True 125 allow_population_by_field_name = True 126 populate_by_name = True 127 extra = pydantic_v1.Extra.allow 128 json_encoders = {dt.datetime: serialize_datetime}
97 def json(self, **kwargs: typing.Any) -> str: 98 kwargs_with_defaults: typing.Any = { 99 "by_alias": True, 100 "exclude_unset": True, 101 **kwargs, 102 } 103 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
105 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 106 kwargs_with_defaults_exclude_unset: typing.Any = { 107 "by_alias": True, 108 "exclude_unset": True, 109 **kwargs, 110 } 111 kwargs_with_defaults_exclude_none: typing.Any = { 112 "by_alias": True, 113 "exclude_none": True, 114 **kwargs, 115 } 116 117 return deep_union_pydantic_dicts( 118 super().dict(**kwargs_with_defaults_exclude_unset), 119 super().dict(**kwargs_with_defaults_exclude_none), 120 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class ScoreV1_Numeric(pydantic_v1.BaseModel): 15 value: float 16 id: str 17 trace_id: str = pydantic_v1.Field(alias="traceId") 18 name: str 19 source: ScoreSource 20 observation_id: typing.Optional[str] = pydantic_v1.Field( 21 alias="observationId", default=None 22 ) 23 timestamp: dt.datetime 24 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 25 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 26 author_user_id: typing.Optional[str] = pydantic_v1.Field( 27 alias="authorUserId", default=None 28 ) 29 comment: typing.Optional[str] = None 30 metadata: typing.Optional[typing.Any] = None 31 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 32 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 33 environment: typing.Optional[str] = None 34 data_type: typing.Literal["NUMERIC"] = pydantic_v1.Field( 35 alias="dataType", default="NUMERIC" 36 ) 37 38 def json(self, **kwargs: typing.Any) -> str: 39 kwargs_with_defaults: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 return super().json(**kwargs_with_defaults) 45 46 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 47 kwargs_with_defaults_exclude_unset: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 kwargs_with_defaults_exclude_none: typing.Any = { 53 "by_alias": True, 54 "exclude_none": True, 55 **kwargs, 56 } 57 58 return deep_union_pydantic_dicts( 59 super().dict(**kwargs_with_defaults_exclude_unset), 60 super().dict(**kwargs_with_defaults_exclude_none), 61 ) 62 63 class Config: 64 frozen = True 65 smart_union = True 66 allow_population_by_field_name = True 67 populate_by_name = True 68 extra = pydantic_v1.Extra.allow 69 json_encoders = {dt.datetime: serialize_datetime}
38 def json(self, **kwargs: typing.Any) -> str: 39 kwargs_with_defaults: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
46 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 47 kwargs_with_defaults_exclude_unset: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 kwargs_with_defaults_exclude_none: typing.Any = { 53 "by_alias": True, 54 "exclude_none": True, 55 **kwargs, 56 } 57 58 return deep_union_pydantic_dicts( 59 super().dict(**kwargs_with_defaults_exclude_unset), 60 super().dict(**kwargs_with_defaults_exclude_none), 61 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
143class Score_Boolean(pydantic_v1.BaseModel): 144 value: float 145 string_value: str = pydantic_v1.Field(alias="stringValue") 146 id: str 147 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 148 session_id: typing.Optional[str] = pydantic_v1.Field( 149 alias="sessionId", default=None 150 ) 151 observation_id: typing.Optional[str] = pydantic_v1.Field( 152 alias="observationId", default=None 153 ) 154 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 155 alias="datasetRunId", default=None 156 ) 157 name: str 158 source: ScoreSource 159 timestamp: dt.datetime 160 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 161 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 162 author_user_id: typing.Optional[str] = pydantic_v1.Field( 163 alias="authorUserId", default=None 164 ) 165 comment: typing.Optional[str] = None 166 metadata: typing.Optional[typing.Any] = None 167 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 168 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 169 environment: typing.Optional[str] = None 170 data_type: typing.Literal["BOOLEAN"] = pydantic_v1.Field( 171 alias="dataType", default="BOOLEAN" 172 ) 173 174 def json(self, **kwargs: typing.Any) -> str: 175 kwargs_with_defaults: typing.Any = { 176 "by_alias": True, 177 "exclude_unset": True, 178 **kwargs, 179 } 180 return super().json(**kwargs_with_defaults) 181 182 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 183 kwargs_with_defaults_exclude_unset: typing.Any = { 184 "by_alias": True, 185 "exclude_unset": True, 186 **kwargs, 187 } 188 kwargs_with_defaults_exclude_none: typing.Any = { 189 "by_alias": True, 190 "exclude_none": True, 191 **kwargs, 192 } 193 194 return deep_union_pydantic_dicts( 195 super().dict(**kwargs_with_defaults_exclude_unset), 196 super().dict(**kwargs_with_defaults_exclude_none), 197 ) 198 199 class Config: 200 frozen = True 201 smart_union = True 202 allow_population_by_field_name = True 203 populate_by_name = True 204 extra = pydantic_v1.Extra.allow 205 json_encoders = {dt.datetime: serialize_datetime}
174 def json(self, **kwargs: typing.Any) -> str: 175 kwargs_with_defaults: typing.Any = { 176 "by_alias": True, 177 "exclude_unset": True, 178 **kwargs, 179 } 180 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
182 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 183 kwargs_with_defaults_exclude_unset: typing.Any = { 184 "by_alias": True, 185 "exclude_unset": True, 186 **kwargs, 187 } 188 kwargs_with_defaults_exclude_none: typing.Any = { 189 "by_alias": True, 190 "exclude_none": True, 191 **kwargs, 192 } 193 194 return deep_union_pydantic_dicts( 195 super().dict(**kwargs_with_defaults_exclude_unset), 196 super().dict(**kwargs_with_defaults_exclude_none), 197 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
78class Score_Categorical(pydantic_v1.BaseModel): 79 value: typing.Optional[float] = None 80 string_value: str = pydantic_v1.Field(alias="stringValue") 81 id: str 82 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 83 session_id: typing.Optional[str] = pydantic_v1.Field( 84 alias="sessionId", default=None 85 ) 86 observation_id: typing.Optional[str] = pydantic_v1.Field( 87 alias="observationId", default=None 88 ) 89 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 90 alias="datasetRunId", default=None 91 ) 92 name: str 93 source: ScoreSource 94 timestamp: dt.datetime 95 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 96 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 97 author_user_id: typing.Optional[str] = pydantic_v1.Field( 98 alias="authorUserId", default=None 99 ) 100 comment: typing.Optional[str] = None 101 metadata: typing.Optional[typing.Any] = None 102 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 103 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 104 environment: typing.Optional[str] = None 105 data_type: typing.Literal["CATEGORICAL"] = pydantic_v1.Field( 106 alias="dataType", default="CATEGORICAL" 107 ) 108 109 def json(self, **kwargs: typing.Any) -> str: 110 kwargs_with_defaults: typing.Any = { 111 "by_alias": True, 112 "exclude_unset": True, 113 **kwargs, 114 } 115 return super().json(**kwargs_with_defaults) 116 117 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 118 kwargs_with_defaults_exclude_unset: typing.Any = { 119 "by_alias": True, 120 "exclude_unset": True, 121 **kwargs, 122 } 123 kwargs_with_defaults_exclude_none: typing.Any = { 124 "by_alias": True, 125 "exclude_none": True, 126 **kwargs, 127 } 128 129 return deep_union_pydantic_dicts( 130 super().dict(**kwargs_with_defaults_exclude_unset), 131 super().dict(**kwargs_with_defaults_exclude_none), 132 ) 133 134 class Config: 135 frozen = True 136 smart_union = True 137 allow_population_by_field_name = True 138 populate_by_name = True 139 extra = pydantic_v1.Extra.allow 140 json_encoders = {dt.datetime: serialize_datetime}
109 def json(self, **kwargs: typing.Any) -> str: 110 kwargs_with_defaults: typing.Any = { 111 "by_alias": True, 112 "exclude_unset": True, 113 **kwargs, 114 } 115 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
117 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 118 kwargs_with_defaults_exclude_unset: typing.Any = { 119 "by_alias": True, 120 "exclude_unset": True, 121 **kwargs, 122 } 123 kwargs_with_defaults_exclude_none: typing.Any = { 124 "by_alias": True, 125 "exclude_none": True, 126 **kwargs, 127 } 128 129 return deep_union_pydantic_dicts( 130 super().dict(**kwargs_with_defaults_exclude_unset), 131 super().dict(**kwargs_with_defaults_exclude_none), 132 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class Score_Numeric(pydantic_v1.BaseModel): 15 value: float 16 id: str 17 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 18 session_id: typing.Optional[str] = pydantic_v1.Field( 19 alias="sessionId", default=None 20 ) 21 observation_id: typing.Optional[str] = pydantic_v1.Field( 22 alias="observationId", default=None 23 ) 24 dataset_run_id: typing.Optional[str] = pydantic_v1.Field( 25 alias="datasetRunId", default=None 26 ) 27 name: str 28 source: ScoreSource 29 timestamp: dt.datetime 30 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 31 updated_at: dt.datetime = pydantic_v1.Field(alias="updatedAt") 32 author_user_id: typing.Optional[str] = pydantic_v1.Field( 33 alias="authorUserId", default=None 34 ) 35 comment: typing.Optional[str] = None 36 metadata: typing.Optional[typing.Any] = None 37 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 38 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 39 environment: typing.Optional[str] = None 40 data_type: typing.Literal["NUMERIC"] = pydantic_v1.Field( 41 alias="dataType", default="NUMERIC" 42 ) 43 44 def json(self, **kwargs: typing.Any) -> str: 45 kwargs_with_defaults: typing.Any = { 46 "by_alias": True, 47 "exclude_unset": True, 48 **kwargs, 49 } 50 return super().json(**kwargs_with_defaults) 51 52 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 53 kwargs_with_defaults_exclude_unset: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 kwargs_with_defaults_exclude_none: typing.Any = { 59 "by_alias": True, 60 "exclude_none": True, 61 **kwargs, 62 } 63 64 return deep_union_pydantic_dicts( 65 super().dict(**kwargs_with_defaults_exclude_unset), 66 super().dict(**kwargs_with_defaults_exclude_none), 67 ) 68 69 class Config: 70 frozen = True 71 smart_union = True 72 allow_population_by_field_name = True 73 populate_by_name = True 74 extra = pydantic_v1.Extra.allow 75 json_encoders = {dt.datetime: serialize_datetime}
44 def json(self, **kwargs: typing.Any) -> str: 45 kwargs_with_defaults: typing.Any = { 46 "by_alias": True, 47 "exclude_unset": True, 48 **kwargs, 49 } 50 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
52 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 53 kwargs_with_defaults_exclude_unset: typing.Any = { 54 "by_alias": True, 55 "exclude_unset": True, 56 **kwargs, 57 } 58 kwargs_with_defaults_exclude_none: typing.Any = { 59 "by_alias": True, 60 "exclude_none": True, 61 **kwargs, 62 } 63 64 return deep_union_pydantic_dicts( 65 super().dict(**kwargs_with_defaults_exclude_unset), 66 super().dict(**kwargs_with_defaults_exclude_none), 67 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class SdkLogBody(pydantic_v1.BaseModel): 12 log: typing.Any 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class SdkLogEvent(BaseEvent): 14 body: SdkLogBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
16class ServiceProviderConfig(pydantic_v1.BaseModel): 17 schemas: typing.List[str] 18 documentation_uri: str = pydantic_v1.Field(alias="documentationUri") 19 patch: ScimFeatureSupport 20 bulk: BulkConfig 21 filter: FilterConfig 22 change_password: ScimFeatureSupport = pydantic_v1.Field(alias="changePassword") 23 sort: ScimFeatureSupport 24 etag: ScimFeatureSupport 25 authentication_schemes: typing.List[AuthenticationScheme] = pydantic_v1.Field( 26 alias="authenticationSchemes" 27 ) 28 meta: ResourceMeta 29 30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 return super().json(**kwargs_with_defaults) 37 38 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 39 kwargs_with_defaults_exclude_unset: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 kwargs_with_defaults_exclude_none: typing.Any = { 45 "by_alias": True, 46 "exclude_none": True, 47 **kwargs, 48 } 49 50 return deep_union_pydantic_dicts( 51 super().dict(**kwargs_with_defaults_exclude_unset), 52 super().dict(**kwargs_with_defaults_exclude_none), 53 ) 54 55 class Config: 56 frozen = True 57 smart_union = True 58 allow_population_by_field_name = True 59 populate_by_name = True 60 extra = pydantic_v1.Extra.allow 61 json_encoders = {dt.datetime: serialize_datetime}
30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = { 32 "by_alias": True, 33 "exclude_unset": True, 34 **kwargs, 35 } 36 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
38 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 39 kwargs_with_defaults_exclude_unset: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 kwargs_with_defaults_exclude_none: typing.Any = { 45 "by_alias": True, 46 "exclude_none": True, 47 **kwargs, 48 } 49 50 return deep_union_pydantic_dicts( 51 super().dict(**kwargs_with_defaults_exclude_unset), 52 super().dict(**kwargs_with_defaults_exclude_none), 53 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class Session(pydantic_v1.BaseModel): 12 id: str 13 created_at: dt.datetime = pydantic_v1.Field(alias="createdAt") 14 project_id: str = pydantic_v1.Field(alias="projectId") 15 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 16 """ 17 The environment from which this session originated. 18 """ 19 20 def json(self, **kwargs: typing.Any) -> str: 21 kwargs_with_defaults: typing.Any = { 22 "by_alias": True, 23 "exclude_unset": True, 24 **kwargs, 25 } 26 return super().json(**kwargs_with_defaults) 27 28 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 29 kwargs_with_defaults_exclude_unset: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 kwargs_with_defaults_exclude_none: typing.Any = { 35 "by_alias": True, 36 "exclude_none": True, 37 **kwargs, 38 } 39 40 return deep_union_pydantic_dicts( 41 super().dict(**kwargs_with_defaults_exclude_unset), 42 super().dict(**kwargs_with_defaults_exclude_none), 43 ) 44 45 class Config: 46 frozen = True 47 smart_union = True 48 allow_population_by_field_name = True 49 populate_by_name = True 50 extra = pydantic_v1.Extra.allow 51 json_encoders = {dt.datetime: serialize_datetime}
20 def json(self, **kwargs: typing.Any) -> str: 21 kwargs_with_defaults: typing.Any = { 22 "by_alias": True, 23 "exclude_unset": True, 24 **kwargs, 25 } 26 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
28 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 29 kwargs_with_defaults_exclude_unset: typing.Any = { 30 "by_alias": True, 31 "exclude_unset": True, 32 **kwargs, 33 } 34 kwargs_with_defaults_exclude_none: typing.Any = { 35 "by_alias": True, 36 "exclude_none": True, 37 **kwargs, 38 } 39 40 return deep_union_pydantic_dicts( 41 super().dict(**kwargs_with_defaults_exclude_unset), 42 super().dict(**kwargs_with_defaults_exclude_none), 43 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class SessionWithTraces(Session): 14 traces: typing.List[Trace] 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class Sort(pydantic_v1.BaseModel): 12 id: str 13 14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults) 21 22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 ) 38 39 class Config: 40 frozen = True 41 smart_union = True 42 extra = pydantic_v1.Extra.allow 43 json_encoders = {dt.datetime: serialize_datetime}
14 def json(self, **kwargs: typing.Any) -> str: 15 kwargs_with_defaults: typing.Any = { 16 "by_alias": True, 17 "exclude_unset": True, 18 **kwargs, 19 } 20 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
22 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 23 kwargs_with_defaults_exclude_unset: typing.Any = { 24 "by_alias": True, 25 "exclude_unset": True, 26 **kwargs, 27 } 28 kwargs_with_defaults_exclude_none: typing.Any = { 29 "by_alias": True, 30 "exclude_none": True, 31 **kwargs, 32 } 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), 36 super().dict(**kwargs_with_defaults_exclude_none), 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class TextPrompt(BasePrompt): 13 prompt: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class Trace(pydantic_v1.BaseModel): 12 id: str = pydantic_v1.Field() 13 """ 14 The unique identifier of a trace 15 """ 16 17 timestamp: dt.datetime = pydantic_v1.Field() 18 """ 19 The timestamp when the trace was created 20 """ 21 22 name: typing.Optional[str] = pydantic_v1.Field(default=None) 23 """ 24 The name of the trace 25 """ 26 27 input: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 28 """ 29 The input data of the trace. Can be any JSON. 30 """ 31 32 output: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 33 """ 34 The output data of the trace. Can be any JSON. 35 """ 36 37 session_id: typing.Optional[str] = pydantic_v1.Field( 38 alias="sessionId", default=None 39 ) 40 """ 41 The session identifier associated with the trace 42 """ 43 44 release: typing.Optional[str] = pydantic_v1.Field(default=None) 45 """ 46 The release version of the application when the trace was created 47 """ 48 49 version: typing.Optional[str] = pydantic_v1.Field(default=None) 50 """ 51 The version of the trace 52 """ 53 54 user_id: typing.Optional[str] = pydantic_v1.Field(alias="userId", default=None) 55 """ 56 The user identifier associated with the trace 57 """ 58 59 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 60 """ 61 The metadata associated with the trace. Can be any JSON. 62 """ 63 64 tags: typing.Optional[typing.List[str]] = pydantic_v1.Field(default=None) 65 """ 66 The tags associated with the trace. Can be an array of strings or null. 67 """ 68 69 public: typing.Optional[bool] = pydantic_v1.Field(default=None) 70 """ 71 Public traces are accessible via url without login 72 """ 73 74 environment: typing.Optional[str] = pydantic_v1.Field(default=None) 75 """ 76 The environment from which this trace originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'. 77 """ 78 79 def json(self, **kwargs: typing.Any) -> str: 80 kwargs_with_defaults: typing.Any = { 81 "by_alias": True, 82 "exclude_unset": True, 83 **kwargs, 84 } 85 return super().json(**kwargs_with_defaults) 86 87 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 88 kwargs_with_defaults_exclude_unset: typing.Any = { 89 "by_alias": True, 90 "exclude_unset": True, 91 **kwargs, 92 } 93 kwargs_with_defaults_exclude_none: typing.Any = { 94 "by_alias": True, 95 "exclude_none": True, 96 **kwargs, 97 } 98 99 return deep_union_pydantic_dicts( 100 super().dict(**kwargs_with_defaults_exclude_unset), 101 super().dict(**kwargs_with_defaults_exclude_none), 102 ) 103 104 class Config: 105 frozen = True 106 smart_union = True 107 allow_population_by_field_name = True 108 populate_by_name = True 109 extra = pydantic_v1.Extra.allow 110 json_encoders = {dt.datetime: serialize_datetime}
The environment from which this trace originated. Can be any lowercase alphanumeric string with hyphens and underscores that does not start with 'langfuse'.
79 def json(self, **kwargs: typing.Any) -> str: 80 kwargs_with_defaults: typing.Any = { 81 "by_alias": True, 82 "exclude_unset": True, 83 **kwargs, 84 } 85 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
87 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 88 kwargs_with_defaults_exclude_unset: typing.Any = { 89 "by_alias": True, 90 "exclude_unset": True, 91 **kwargs, 92 } 93 kwargs_with_defaults_exclude_none: typing.Any = { 94 "by_alias": True, 95 "exclude_none": True, 96 **kwargs, 97 } 98 99 return deep_union_pydantic_dicts( 100 super().dict(**kwargs_with_defaults_exclude_unset), 101 super().dict(**kwargs_with_defaults_exclude_none), 102 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class TraceBody(pydantic_v1.BaseModel): 12 id: typing.Optional[str] = None 13 timestamp: typing.Optional[dt.datetime] = None 14 name: typing.Optional[str] = None 15 user_id: typing.Optional[str] = pydantic_v1.Field(alias="userId", default=None) 16 input: typing.Optional[typing.Any] = None 17 output: typing.Optional[typing.Any] = None 18 session_id: typing.Optional[str] = pydantic_v1.Field( 19 alias="sessionId", default=None 20 ) 21 release: typing.Optional[str] = None 22 version: typing.Optional[str] = None 23 metadata: typing.Optional[typing.Any] = None 24 tags: typing.Optional[typing.List[str]] = None 25 environment: typing.Optional[str] = None 26 public: typing.Optional[bool] = pydantic_v1.Field(default=None) 27 """ 28 Make trace publicly accessible via url 29 """ 30 31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults) 38 39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 ) 55 56 class Config: 57 frozen = True 58 smart_union = True 59 allow_population_by_field_name = True 60 populate_by_name = True 61 extra = pydantic_v1.Extra.allow 62 json_encoders = {dt.datetime: serialize_datetime}
31 def json(self, **kwargs: typing.Any) -> str: 32 kwargs_with_defaults: typing.Any = { 33 "by_alias": True, 34 "exclude_unset": True, 35 **kwargs, 36 } 37 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
39 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 40 kwargs_with_defaults_exclude_unset: typing.Any = { 41 "by_alias": True, 42 "exclude_unset": True, 43 **kwargs, 44 } 45 kwargs_with_defaults_exclude_none: typing.Any = { 46 "by_alias": True, 47 "exclude_none": True, 48 **kwargs, 49 } 50 51 return deep_union_pydantic_dicts( 52 super().dict(**kwargs_with_defaults_exclude_unset), 53 super().dict(**kwargs_with_defaults_exclude_none), 54 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class TraceEvent(BaseEvent): 14 body: TraceBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class TraceWithDetails(Trace): 13 html_path: str = pydantic_v1.Field(alias="htmlPath") 14 """ 15 Path of trace in Langfuse UI 16 """ 17 18 latency: float = pydantic_v1.Field() 19 """ 20 Latency of trace in seconds 21 """ 22 23 total_cost: float = pydantic_v1.Field(alias="totalCost") 24 """ 25 Cost of trace in USD 26 """ 27 28 observations: typing.List[str] = pydantic_v1.Field() 29 """ 30 List of observation ids 31 """ 32 33 scores: typing.List[str] = pydantic_v1.Field() 34 """ 35 List of score ids 36 """ 37 38 def json(self, **kwargs: typing.Any) -> str: 39 kwargs_with_defaults: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 return super().json(**kwargs_with_defaults) 45 46 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 47 kwargs_with_defaults_exclude_unset: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 kwargs_with_defaults_exclude_none: typing.Any = { 53 "by_alias": True, 54 "exclude_none": True, 55 **kwargs, 56 } 57 58 return deep_union_pydantic_dicts( 59 super().dict(**kwargs_with_defaults_exclude_unset), 60 super().dict(**kwargs_with_defaults_exclude_none), 61 ) 62 63 class Config: 64 frozen = True 65 smart_union = True 66 allow_population_by_field_name = True 67 populate_by_name = True 68 extra = pydantic_v1.Extra.allow 69 json_encoders = {dt.datetime: serialize_datetime}
38 def json(self, **kwargs: typing.Any) -> str: 39 kwargs_with_defaults: typing.Any = { 40 "by_alias": True, 41 "exclude_unset": True, 42 **kwargs, 43 } 44 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
46 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 47 kwargs_with_defaults_exclude_unset: typing.Any = { 48 "by_alias": True, 49 "exclude_unset": True, 50 **kwargs, 51 } 52 kwargs_with_defaults_exclude_none: typing.Any = { 53 "by_alias": True, 54 "exclude_none": True, 55 **kwargs, 56 } 57 58 return deep_union_pydantic_dicts( 59 super().dict(**kwargs_with_defaults_exclude_unset), 60 super().dict(**kwargs_with_defaults_exclude_none), 61 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class TraceWithFullDetails(Trace): 15 html_path: str = pydantic_v1.Field(alias="htmlPath") 16 """ 17 Path of trace in Langfuse UI 18 """ 19 20 latency: float = pydantic_v1.Field() 21 """ 22 Latency of trace in seconds 23 """ 24 25 total_cost: float = pydantic_v1.Field(alias="totalCost") 26 """ 27 Cost of trace in USD 28 """ 29 30 observations: typing.List[ObservationsView] = pydantic_v1.Field() 31 """ 32 List of observations 33 """ 34 35 scores: typing.List[ScoreV1] = pydantic_v1.Field() 36 """ 37 List of scores 38 """ 39 40 def json(self, **kwargs: typing.Any) -> str: 41 kwargs_with_defaults: typing.Any = { 42 "by_alias": True, 43 "exclude_unset": True, 44 **kwargs, 45 } 46 return super().json(**kwargs_with_defaults) 47 48 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 49 kwargs_with_defaults_exclude_unset: typing.Any = { 50 "by_alias": True, 51 "exclude_unset": True, 52 **kwargs, 53 } 54 kwargs_with_defaults_exclude_none: typing.Any = { 55 "by_alias": True, 56 "exclude_none": True, 57 **kwargs, 58 } 59 60 return deep_union_pydantic_dicts( 61 super().dict(**kwargs_with_defaults_exclude_unset), 62 super().dict(**kwargs_with_defaults_exclude_none), 63 ) 64 65 class Config: 66 frozen = True 67 smart_union = True 68 allow_population_by_field_name = True 69 populate_by_name = True 70 extra = pydantic_v1.Extra.allow 71 json_encoders = {dt.datetime: serialize_datetime}
40 def json(self, **kwargs: typing.Any) -> str: 41 kwargs_with_defaults: typing.Any = { 42 "by_alias": True, 43 "exclude_unset": True, 44 **kwargs, 45 } 46 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
48 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 49 kwargs_with_defaults_exclude_unset: typing.Any = { 50 "by_alias": True, 51 "exclude_unset": True, 52 **kwargs, 53 } 54 kwargs_with_defaults_exclude_none: typing.Any = { 55 "by_alias": True, 56 "exclude_none": True, 57 **kwargs, 58 } 59 60 return deep_union_pydantic_dicts( 61 super().dict(**kwargs_with_defaults_exclude_unset), 62 super().dict(**kwargs_with_defaults_exclude_none), 63 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class Traces(pydantic_v1.BaseModel): 14 data: typing.List[TraceWithDetails] 15 meta: MetaResponse 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class UpdateAnnotationQueueItemRequest(pydantic_v1.BaseModel): 13 status: typing.Optional[AnnotationQueueStatus] = None 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 extra = pydantic_v1.Extra.allow 44 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class UpdateEventBody(OptionalObservationBody): 13 id: str 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults) 22 23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 ) 39 40 class Config: 41 frozen = True 42 smart_union = True 43 allow_population_by_field_name = True 44 populate_by_name = True 45 extra = pydantic_v1.Extra.allow 46 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = { 17 "by_alias": True, 18 "exclude_unset": True, 19 **kwargs, 20 } 21 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
23 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 24 kwargs_with_defaults_exclude_unset: typing.Any = { 25 "by_alias": True, 26 "exclude_unset": True, 27 **kwargs, 28 } 29 kwargs_with_defaults_exclude_none: typing.Any = { 30 "by_alias": True, 31 "exclude_none": True, 32 **kwargs, 33 } 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 37 super().dict(**kwargs_with_defaults_exclude_none), 38 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
15class UpdateGenerationBody(UpdateSpanBody): 16 completion_start_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 17 alias="completionStartTime", default=None 18 ) 19 model: typing.Optional[str] = None 20 model_parameters: typing.Optional[typing.Dict[str, MapValue]] = pydantic_v1.Field( 21 alias="modelParameters", default=None 22 ) 23 usage: typing.Optional[IngestionUsage] = None 24 prompt_name: typing.Optional[str] = pydantic_v1.Field( 25 alias="promptName", default=None 26 ) 27 usage_details: typing.Optional[UsageDetails] = pydantic_v1.Field( 28 alias="usageDetails", default=None 29 ) 30 cost_details: typing.Optional[typing.Dict[str, float]] = pydantic_v1.Field( 31 alias="costDetails", default=None 32 ) 33 prompt_version: typing.Optional[int] = pydantic_v1.Field( 34 alias="promptVersion", default=None 35 ) 36 37 def json(self, **kwargs: typing.Any) -> str: 38 kwargs_with_defaults: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 return super().json(**kwargs_with_defaults) 44 45 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 46 kwargs_with_defaults_exclude_unset: typing.Any = { 47 "by_alias": True, 48 "exclude_unset": True, 49 **kwargs, 50 } 51 kwargs_with_defaults_exclude_none: typing.Any = { 52 "by_alias": True, 53 "exclude_none": True, 54 **kwargs, 55 } 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), 59 super().dict(**kwargs_with_defaults_exclude_none), 60 ) 61 62 class Config: 63 frozen = True 64 smart_union = True 65 allow_population_by_field_name = True 66 populate_by_name = True 67 extra = pydantic_v1.Extra.allow 68 json_encoders = {dt.datetime: serialize_datetime}
37 def json(self, **kwargs: typing.Any) -> str: 38 kwargs_with_defaults: typing.Any = { 39 "by_alias": True, 40 "exclude_unset": True, 41 **kwargs, 42 } 43 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
45 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 46 kwargs_with_defaults_exclude_unset: typing.Any = { 47 "by_alias": True, 48 "exclude_unset": True, 49 **kwargs, 50 } 51 kwargs_with_defaults_exclude_none: typing.Any = { 52 "by_alias": True, 53 "exclude_none": True, 54 **kwargs, 55 } 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), 59 super().dict(**kwargs_with_defaults_exclude_none), 60 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class UpdateGenerationEvent(BaseEvent): 14 body: UpdateGenerationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class UpdateObservationEvent(BaseEvent): 14 body: ObservationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class UpdateSpanBody(UpdateEventBody): 13 end_time: typing.Optional[dt.datetime] = pydantic_v1.Field( 14 alias="endTime", default=None 15 ) 16 17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults) 24 25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 ) 41 42 class Config: 43 frozen = True 44 smart_union = True 45 allow_population_by_field_name = True 46 populate_by_name = True 47 extra = pydantic_v1.Extra.allow 48 json_encoders = {dt.datetime: serialize_datetime}
17 def json(self, **kwargs: typing.Any) -> str: 18 kwargs_with_defaults: typing.Any = { 19 "by_alias": True, 20 "exclude_unset": True, 21 **kwargs, 22 } 23 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
25 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 26 kwargs_with_defaults_exclude_unset: typing.Any = { 27 "by_alias": True, 28 "exclude_unset": True, 29 **kwargs, 30 } 31 kwargs_with_defaults_exclude_none: typing.Any = { 32 "by_alias": True, 33 "exclude_none": True, 34 **kwargs, 35 } 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 39 super().dict(**kwargs_with_defaults_exclude_none), 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
13class UpdateSpanEvent(BaseEvent): 14 body: UpdateSpanBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults) 23 24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 ) 40 41 class Config: 42 frozen = True 43 smart_union = True 44 allow_population_by_field_name = True 45 populate_by_name = True 46 extra = pydantic_v1.Extra.allow 47 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = { 18 "by_alias": True, 19 "exclude_unset": True, 20 **kwargs, 21 } 22 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
24 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 25 kwargs_with_defaults_exclude_unset: typing.Any = { 26 "by_alias": True, 27 "exclude_unset": True, 28 **kwargs, 29 } 30 kwargs_with_defaults_exclude_none: typing.Any = { 31 "by_alias": True, 32 "exclude_none": True, 33 **kwargs, 34 } 35 36 return deep_union_pydantic_dicts( 37 super().dict(**kwargs_with_defaults_exclude_unset), 38 super().dict(**kwargs_with_defaults_exclude_none), 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class UpsertLlmConnectionRequest(pydantic_v1.BaseModel): 13 """ 14 Request to create or update an LLM connection (upsert) 15 """ 16 17 provider: str = pydantic_v1.Field() 18 """ 19 Provider name (e.g., 'openai', 'my-gateway'). Must be unique in project, used for upserting. 20 """ 21 22 adapter: LlmAdapter = pydantic_v1.Field() 23 """ 24 The adapter used to interface with the LLM 25 """ 26 27 secret_key: str = pydantic_v1.Field(alias="secretKey") 28 """ 29 Secret key for the LLM API. 30 """ 31 32 base_url: typing.Optional[str] = pydantic_v1.Field(alias="baseURL", default=None) 33 """ 34 Custom base URL for the LLM API 35 """ 36 37 custom_models: typing.Optional[typing.List[str]] = pydantic_v1.Field( 38 alias="customModels", default=None 39 ) 40 """ 41 List of custom model names 42 """ 43 44 with_default_models: typing.Optional[bool] = pydantic_v1.Field( 45 alias="withDefaultModels", default=None 46 ) 47 """ 48 Whether to include default models. Default is true. 49 """ 50 51 extra_headers: typing.Optional[typing.Dict[str, str]] = pydantic_v1.Field( 52 alias="extraHeaders", default=None 53 ) 54 """ 55 Extra headers to send with requests 56 """ 57 58 def json(self, **kwargs: typing.Any) -> str: 59 kwargs_with_defaults: typing.Any = { 60 "by_alias": True, 61 "exclude_unset": True, 62 **kwargs, 63 } 64 return super().json(**kwargs_with_defaults) 65 66 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 67 kwargs_with_defaults_exclude_unset: typing.Any = { 68 "by_alias": True, 69 "exclude_unset": True, 70 **kwargs, 71 } 72 kwargs_with_defaults_exclude_none: typing.Any = { 73 "by_alias": True, 74 "exclude_none": True, 75 **kwargs, 76 } 77 78 return deep_union_pydantic_dicts( 79 super().dict(**kwargs_with_defaults_exclude_unset), 80 super().dict(**kwargs_with_defaults_exclude_none), 81 ) 82 83 class Config: 84 frozen = True 85 smart_union = True 86 allow_population_by_field_name = True 87 populate_by_name = True 88 extra = pydantic_v1.Extra.allow 89 json_encoders = {dt.datetime: serialize_datetime}
Request to create or update an LLM connection (upsert)
Provider name (e.g., 'openai', 'my-gateway'). Must be unique in project, used for upserting.
58 def json(self, **kwargs: typing.Any) -> str: 59 kwargs_with_defaults: typing.Any = { 60 "by_alias": True, 61 "exclude_unset": True, 62 **kwargs, 63 } 64 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
66 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 67 kwargs_with_defaults_exclude_unset: typing.Any = { 68 "by_alias": True, 69 "exclude_unset": True, 70 **kwargs, 71 } 72 kwargs_with_defaults_exclude_none: typing.Any = { 73 "by_alias": True, 74 "exclude_none": True, 75 **kwargs, 76 } 77 78 return deep_union_pydantic_dicts( 79 super().dict(**kwargs_with_defaults_exclude_unset), 80 super().dict(**kwargs_with_defaults_exclude_none), 81 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
12class Usage(pydantic_v1.BaseModel): 13 """ 14 (Deprecated. Use usageDetails and costDetails instead.) Standard interface for usage and cost 15 """ 16 17 input: typing.Optional[int] = pydantic_v1.Field(default=None) 18 """ 19 Number of input units (e.g. tokens) 20 """ 21 22 output: typing.Optional[int] = pydantic_v1.Field(default=None) 23 """ 24 Number of output units (e.g. tokens) 25 """ 26 27 total: typing.Optional[int] = pydantic_v1.Field(default=None) 28 """ 29 Defaults to input+output if not set 30 """ 31 32 unit: typing.Optional[ModelUsageUnit] = None 33 input_cost: typing.Optional[float] = pydantic_v1.Field( 34 alias="inputCost", default=None 35 ) 36 """ 37 USD input cost 38 """ 39 40 output_cost: typing.Optional[float] = pydantic_v1.Field( 41 alias="outputCost", default=None 42 ) 43 """ 44 USD output cost 45 """ 46 47 total_cost: typing.Optional[float] = pydantic_v1.Field( 48 alias="totalCost", default=None 49 ) 50 """ 51 USD total cost, defaults to input+output 52 """ 53 54 def json(self, **kwargs: typing.Any) -> str: 55 kwargs_with_defaults: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 return super().json(**kwargs_with_defaults) 61 62 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 63 kwargs_with_defaults_exclude_unset: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 kwargs_with_defaults_exclude_none: typing.Any = { 69 "by_alias": True, 70 "exclude_none": True, 71 **kwargs, 72 } 73 74 return deep_union_pydantic_dicts( 75 super().dict(**kwargs_with_defaults_exclude_unset), 76 super().dict(**kwargs_with_defaults_exclude_none), 77 ) 78 79 class Config: 80 frozen = True 81 smart_union = True 82 allow_population_by_field_name = True 83 populate_by_name = True 84 extra = pydantic_v1.Extra.allow 85 json_encoders = {dt.datetime: serialize_datetime}
(Deprecated. Use usageDetails and costDetails instead.) Standard interface for usage and cost
54 def json(self, **kwargs: typing.Any) -> str: 55 kwargs_with_defaults: typing.Any = { 56 "by_alias": True, 57 "exclude_unset": True, 58 **kwargs, 59 } 60 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
62 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 63 kwargs_with_defaults_exclude_unset: typing.Any = { 64 "by_alias": True, 65 "exclude_unset": True, 66 **kwargs, 67 } 68 kwargs_with_defaults_exclude_none: typing.Any = { 69 "by_alias": True, 70 "exclude_none": True, 71 **kwargs, 72 } 73 74 return deep_union_pydantic_dicts( 75 super().dict(**kwargs_with_defaults_exclude_unset), 76 super().dict(**kwargs_with_defaults_exclude_none), 77 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
11class UserMeta(pydantic_v1.BaseModel): 12 resource_type: str = pydantic_v1.Field(alias="resourceType") 13 created: typing.Optional[str] = None 14 last_modified: typing.Optional[str] = pydantic_v1.Field( 15 alias="lastModified", default=None 16 ) 17 18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults) 25 26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 ) 42 43 class Config: 44 frozen = True 45 smart_union = True 46 allow_population_by_field_name = True 47 populate_by_name = True 48 extra = pydantic_v1.Extra.allow 49 json_encoders = {dt.datetime: serialize_datetime}
18 def json(self, **kwargs: typing.Any) -> str: 19 kwargs_with_defaults: typing.Any = { 20 "by_alias": True, 21 "exclude_unset": True, 22 **kwargs, 23 } 24 return super().json(**kwargs_with_defaults)
Generate a JSON representation of the model, include
and exclude
arguments as per dict()
.
encoder
is an optional function to supply as default
to json.dumps(), other arguments as per json.dumps()
.
26 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 27 kwargs_with_defaults_exclude_unset: typing.Any = { 28 "by_alias": True, 29 "exclude_unset": True, 30 **kwargs, 31 } 32 kwargs_with_defaults_exclude_none: typing.Any = { 33 "by_alias": True, 34 "exclude_none": True, 35 **kwargs, 36 } 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 40 super().dict(**kwargs_with_defaults_exclude_none), 41 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.