langfuse.api
1# This file was auto-generated by Fern from our API Definition. 2 3from .resources import ( 4 AccessDeniedError, 5 BaseEvent, 6 BasePrompt, 7 BaseScore, 8 BooleanScore, 9 CategoricalScore, 10 ChatMessage, 11 ChatPrompt, 12 Comment, 13 CommentObjectType, 14 ConfigCategory, 15 CreateChatPromptRequest, 16 CreateCommentRequest, 17 CreateCommentResponse, 18 CreateDatasetItemRequest, 19 CreateDatasetRequest, 20 CreateDatasetRunItemRequest, 21 CreateEventBody, 22 CreateEventEvent, 23 CreateGenerationBody, 24 CreateGenerationEvent, 25 CreateModelRequest, 26 CreateObservationEvent, 27 CreatePromptRequest, 28 CreatePromptRequest_Chat, 29 CreatePromptRequest_Text, 30 CreateScoreConfigRequest, 31 CreateScoreRequest, 32 CreateScoreResponse, 33 CreateScoreValue, 34 CreateSpanBody, 35 CreateSpanEvent, 36 CreateTextPromptRequest, 37 DailyMetrics, 38 DailyMetricsDetails, 39 Dataset, 40 DatasetItem, 41 DatasetRun, 42 DatasetRunItem, 43 DatasetRunWithItems, 44 DatasetStatus, 45 Error, 46 GetCommentsResponse, 47 GetMediaResponse, 48 GetMediaUploadUrlRequest, 49 GetMediaUploadUrlResponse, 50 GetScoresResponse, 51 GetScoresResponseData, 52 GetScoresResponseDataBoolean, 53 GetScoresResponseDataCategorical, 54 GetScoresResponseDataNumeric, 55 GetScoresResponseData_Boolean, 56 GetScoresResponseData_Categorical, 57 GetScoresResponseData_Numeric, 58 GetScoresResponseTraceData, 59 HealthResponse, 60 IngestionError, 61 IngestionEvent, 62 IngestionEvent_EventCreate, 63 IngestionEvent_GenerationCreate, 64 IngestionEvent_GenerationUpdate, 65 IngestionEvent_ObservationCreate, 66 IngestionEvent_ObservationUpdate, 67 IngestionEvent_ScoreCreate, 68 IngestionEvent_SdkLog, 69 IngestionEvent_SpanCreate, 70 IngestionEvent_SpanUpdate, 71 IngestionEvent_TraceCreate, 72 IngestionResponse, 73 IngestionSuccess, 74 IngestionUsage, 75 MapValue, 76 MediaContentType, 77 MethodNotAllowedError, 78 Model, 79 ModelUsageUnit, 80 NotFoundError, 81 NumericScore, 82 Observation, 83 ObservationBody, 84 ObservationLevel, 85 ObservationType, 86 Observations, 87 ObservationsView, 88 ObservationsViews, 89 OpenAiUsage, 90 OptionalObservationBody, 91 PaginatedDatasetItems, 92 PaginatedDatasetRuns, 93 PaginatedDatasets, 94 PaginatedModels, 95 PaginatedSessions, 96 PatchMediaBody, 97 Project, 98 Projects, 99 Prompt, 100 PromptMeta, 101 PromptMetaListResponse, 102 Prompt_Chat, 103 Prompt_Text, 104 Score, 105 ScoreBody, 106 ScoreConfig, 107 ScoreConfigs, 108 ScoreDataType, 109 ScoreEvent, 110 ScoreSource, 111 Score_Boolean, 112 Score_Categorical, 113 Score_Numeric, 114 SdkLogBody, 115 SdkLogEvent, 116 ServiceUnavailableError, 117 Session, 118 SessionWithTraces, 119 Sort, 120 TextPrompt, 121 Trace, 122 TraceBody, 123 TraceEvent, 124 TraceWithDetails, 125 TraceWithFullDetails, 126 Traces, 127 UnauthorizedError, 128 UpdateEventBody, 129 UpdateGenerationBody, 130 UpdateGenerationEvent, 131 UpdateObservationEvent, 132 UpdateSpanBody, 133 UpdateSpanEvent, 134 Usage, 135 UsageByModel, 136 comments, 137 commons, 138 dataset_items, 139 dataset_run_items, 140 datasets, 141 health, 142 ingestion, 143 media, 144 metrics, 145 models, 146 observations, 147 projects, 148 prompts, 149 score, 150 score_configs, 151 sessions, 152 trace, 153 utils, 154) 155 156__all__ = [ 157 "AccessDeniedError", 158 "BaseEvent", 159 "BasePrompt", 160 "BaseScore", 161 "BooleanScore", 162 "CategoricalScore", 163 "ChatMessage", 164 "ChatPrompt", 165 "Comment", 166 "CommentObjectType", 167 "ConfigCategory", 168 "CreateChatPromptRequest", 169 "CreateCommentRequest", 170 "CreateCommentResponse", 171 "CreateDatasetItemRequest", 172 "CreateDatasetRequest", 173 "CreateDatasetRunItemRequest", 174 "CreateEventBody", 175 "CreateEventEvent", 176 "CreateGenerationBody", 177 "CreateGenerationEvent", 178 "CreateModelRequest", 179 "CreateObservationEvent", 180 "CreatePromptRequest", 181 "CreatePromptRequest_Chat", 182 "CreatePromptRequest_Text", 183 "CreateScoreConfigRequest", 184 "CreateScoreRequest", 185 "CreateScoreResponse", 186 "CreateScoreValue", 187 "CreateSpanBody", 188 "CreateSpanEvent", 189 "CreateTextPromptRequest", 190 "DailyMetrics", 191 "DailyMetricsDetails", 192 "Dataset", 193 "DatasetItem", 194 "DatasetRun", 195 "DatasetRunItem", 196 "DatasetRunWithItems", 197 "DatasetStatus", 198 "Error", 199 "GetCommentsResponse", 200 "GetMediaResponse", 201 "GetMediaUploadUrlRequest", 202 "GetMediaUploadUrlResponse", 203 "GetScoresResponse", 204 "GetScoresResponseData", 205 "GetScoresResponseDataBoolean", 206 "GetScoresResponseDataCategorical", 207 "GetScoresResponseDataNumeric", 208 "GetScoresResponseData_Boolean", 209 "GetScoresResponseData_Categorical", 210 "GetScoresResponseData_Numeric", 211 "GetScoresResponseTraceData", 212 "HealthResponse", 213 "IngestionError", 214 "IngestionEvent", 215 "IngestionEvent_EventCreate", 216 "IngestionEvent_GenerationCreate", 217 "IngestionEvent_GenerationUpdate", 218 "IngestionEvent_ObservationCreate", 219 "IngestionEvent_ObservationUpdate", 220 "IngestionEvent_ScoreCreate", 221 "IngestionEvent_SdkLog", 222 "IngestionEvent_SpanCreate", 223 "IngestionEvent_SpanUpdate", 224 "IngestionEvent_TraceCreate", 225 "IngestionResponse", 226 "IngestionSuccess", 227 "IngestionUsage", 228 "MapValue", 229 "MediaContentType", 230 "MethodNotAllowedError", 231 "Model", 232 "ModelUsageUnit", 233 "NotFoundError", 234 "NumericScore", 235 "Observation", 236 "ObservationBody", 237 "ObservationLevel", 238 "ObservationType", 239 "Observations", 240 "ObservationsView", 241 "ObservationsViews", 242 "OpenAiUsage", 243 "OptionalObservationBody", 244 "PaginatedDatasetItems", 245 "PaginatedDatasetRuns", 246 "PaginatedDatasets", 247 "PaginatedModels", 248 "PaginatedSessions", 249 "PatchMediaBody", 250 "Project", 251 "Projects", 252 "Prompt", 253 "PromptMeta", 254 "PromptMetaListResponse", 255 "Prompt_Chat", 256 "Prompt_Text", 257 "Score", 258 "ScoreBody", 259 "ScoreConfig", 260 "ScoreConfigs", 261 "ScoreDataType", 262 "ScoreEvent", 263 "ScoreSource", 264 "Score_Boolean", 265 "Score_Categorical", 266 "Score_Numeric", 267 "SdkLogBody", 268 "SdkLogEvent", 269 "ServiceUnavailableError", 270 "Session", 271 "SessionWithTraces", 272 "Sort", 273 "TextPrompt", 274 "Trace", 275 "TraceBody", 276 "TraceEvent", 277 "TraceWithDetails", 278 "TraceWithFullDetails", 279 "Traces", 280 "UnauthorizedError", 281 "UpdateEventBody", 282 "UpdateGenerationBody", 283 "UpdateGenerationEvent", 284 "UpdateObservationEvent", 285 "UpdateSpanBody", 286 "UpdateSpanEvent", 287 "Usage", 288 "UsageByModel", 289 "comments", 290 "commons", 291 "dataset_items", 292 "dataset_run_items", 293 "datasets", 294 "health", 295 "ingestion", 296 "media", 297 "metrics", 298 "models", 299 "observations", 300 "projects", 301 "prompts", 302 "score", 303 "score_configs", 304 "sessions", 305 "trace", 306 "utils", 307]
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.
Inherited Members
- langfuse.api.core.api_error.ApiError
- status_code
- body
- builtins.BaseException
- with_traceback
- add_note
- args
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 33 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), 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}
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 33 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 34 35 return deep_union_pydantic_dicts( 36 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 37 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 31 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 32 33 return deep_union_pydantic_dicts( 34 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 35 ) 36 37 class Config: 38 frozen = True 39 smart_union = True 40 extra = pydantic_v1.Extra.allow 41 json_encoders = {dt.datetime: serialize_datetime}
25 def json(self, **kwargs: typing.Any) -> str: 26 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 31 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 32 33 return deep_union_pydantic_dicts( 34 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 35 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
12class BaseScore(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 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 28 """ 29 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 30 """ 31 32 queue_id: typing.Optional[str] = pydantic_v1.Field(alias="queueId", default=None) 33 """ 34 Reference an annotation queue on a score. Populated if the score was initially created in an annotation queue. 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}
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.
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.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 29 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 30 31 return deep_union_pydantic_dicts( 32 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 33 ) 34 35 class Config: 36 frozen = True 37 smart_union = True 38 allow_population_by_field_name = True 39 populate_by_name = True 40 extra = pydantic_v1.Extra.allow 41 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 29 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 30 31 return deep_union_pydantic_dicts( 32 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 33 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 29 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 30 31 return deep_union_pydantic_dicts( 32 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 33 ) 34 35 class Config: 36 frozen = True 37 smart_union = True 38 allow_population_by_field_name = True 39 populate_by_name = True 40 extra = pydantic_v1.Extra.allow 41 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 29 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 30 31 return deep_union_pydantic_dicts( 32 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 33 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 17 return super().json(**kwargs_with_defaults) 18 19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 ) 26 27 class Config: 28 frozen = True 29 smart_union = True 30 extra = pydantic_v1.Extra.allow 31 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 17 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()
.
19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
13class ChatPrompt(BasePrompt): 14 prompt: typing.List[ChatMessage] 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 return super().json(**kwargs_with_defaults) 19 20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 ) 27 28 class Config: 29 frozen = True 30 smart_union = True 31 allow_population_by_field_name = True 32 populate_by_name = True 33 extra = pydantic_v1.Extra.allow 34 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 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()
.
20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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()
Inherited Members
- enum.Enum
- name
- value
- builtins.str
- encode
- replace
- split
- rsplit
- join
- capitalize
- casefold
- title
- center
- count
- expandtabs
- find
- partition
- index
- ljust
- lower
- lstrip
- rfind
- rindex
- rjust
- rstrip
- rpartition
- splitlines
- strip
- swapcase
- translate
- upper
- startswith
- endswith
- removeprefix
- removesuffix
- isascii
- islower
- isupper
- istitle
- isspace
- isdecimal
- isdigit
- isnumeric
- isalpha
- isalnum
- isidentifier
- isprintable
- zfill
- format
- format_map
- maketrans
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 17 return super().json(**kwargs_with_defaults) 18 19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 ) 26 27 class Config: 28 frozen = True 29 smart_union = True 30 extra = pydantic_v1.Extra.allow 31 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 17 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()
.
19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
12class CreateChatPromptRequest(pydantic_v1.BaseModel): 13 name: str 14 prompt: typing.List[ChatMessage] 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 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 32 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 36 ) 37 38 class Config: 39 frozen = True 40 smart_union = True 41 extra = pydantic_v1.Extra.allow 42 json_encoders = {dt.datetime: serialize_datetime}
26 def json(self, **kwargs: typing.Any) -> str: 27 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 32 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 33 34 return deep_union_pydantic_dicts( 35 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 36 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 500 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.
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.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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(alias="expectedOutput", default=None) 16 metadata: typing.Optional[typing.Any] = None 17 source_trace_id: typing.Optional[str] = pydantic_v1.Field(alias="sourceTraceId", default=None) 18 source_observation_id: typing.Optional[str] = pydantic_v1.Field(alias="sourceObservationId", default=None) 19 id: typing.Optional[str] = pydantic_v1.Field(default=None) 20 """ 21 Dataset items are upserted on their id. Id needs to be unique (project-level) and cannot be reused across datasets. 22 """ 23 24 status: typing.Optional[DatasetStatus] = pydantic_v1.Field(default=None) 25 """ 26 Defaults to ACTIVE for newly created items 27 """ 28 29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 35 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), 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}
Dataset items are upserted on their id. Id needs to be unique (project-level) and cannot be reused across datasets.
29 def json(self, **kwargs: typing.Any) -> str: 30 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 35 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 36 37 return deep_union_pydantic_dicts( 38 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 39 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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 = {"by_alias": True, "exclude_unset": True, **kwargs} 18 return super().json(**kwargs_with_defaults) 19 20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 ) 27 28 class Config: 29 frozen = True 30 smart_union = True 31 extra = pydantic_v1.Extra.allow 32 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 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()
.
20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
11class CreateDatasetRunItemRequest(pydantic_v1.BaseModel): 12 run_name: str = pydantic_v1.Field(alias="runName") 13 run_description: typing.Optional[str] = pydantic_v1.Field(alias="runDescription", default=None) 14 """ 15 Description of the run. If run exists, description will be updated. 16 """ 17 18 metadata: typing.Optional[typing.Any] = pydantic_v1.Field(default=None) 19 """ 20 Metadata of the dataset run, updates run if run already exists 21 """ 22 23 dataset_item_id: str = pydantic_v1.Field(alias="datasetItemId") 24 observation_id: typing.Optional[str] = pydantic_v1.Field(alias="observationId", default=None) 25 trace_id: typing.Optional[str] = pydantic_v1.Field(alias="traceId", default=None) 26 """ 27 traceId should always be provided. For compatibility with older SDK versions it can also be inferred from the provided observationId. 28 """ 29 30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 36 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), 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}
traceId should always be provided. For compatibility with older SDK versions it can also be inferred from the provided observationId.
30 def json(self, **kwargs: typing.Any) -> str: 31 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 36 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 37 38 return deep_union_pydantic_dicts( 39 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 40 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
12class CreateEventBody(OptionalObservationBody): 13 id: typing.Optional[str] = None 14 15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 17 return super().json(**kwargs_with_defaults) 18 19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 ) 26 27 class Config: 28 frozen = True 29 smart_union = True 30 allow_population_by_field_name = True 31 populate_by_name = True 32 extra = pydantic_v1.Extra.allow 33 json_encoders = {dt.datetime: serialize_datetime}
15 def json(self, **kwargs: typing.Any) -> str: 16 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 17 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()
.
19 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 20 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 21 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 22 23 return deep_union_pydantic_dicts( 24 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 25 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
13class CreateEventEvent(BaseEvent): 14 body: CreateEventBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 return super().json(**kwargs_with_defaults) 19 20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 ) 27 28 class Config: 29 frozen = True 30 smart_union = True 31 allow_population_by_field_name = True 32 populate_by_name = True 33 extra = pydantic_v1.Extra.allow 34 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 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()
.
20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
14class CreateGenerationBody(CreateSpanBody): 15 completion_start_time: typing.Optional[dt.datetime] = pydantic_v1.Field(alias="completionStartTime", default=None) 16 model: typing.Optional[str] = None 17 model_parameters: typing.Optional[typing.Dict[str, MapValue]] = pydantic_v1.Field( 18 alias="modelParameters", default=None 19 ) 20 usage: typing.Optional[IngestionUsage] = None 21 prompt_name: typing.Optional[str] = pydantic_v1.Field(alias="promptName", default=None) 22 prompt_version: typing.Optional[int] = pydantic_v1.Field(alias="promptVersion", default=None) 23 24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 30 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 31 32 return deep_union_pydantic_dicts( 33 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 34 ) 35 36 class Config: 37 frozen = True 38 smart_union = True 39 allow_population_by_field_name = True 40 populate_by_name = True 41 extra = pydantic_v1.Extra.allow 42 json_encoders = {dt.datetime: serialize_datetime}
24 def json(self, **kwargs: typing.Any) -> str: 25 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 30 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 31 32 return deep_union_pydantic_dicts( 33 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 34 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
13class CreateGenerationEvent(BaseEvent): 14 body: CreateGenerationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 return super().json(**kwargs_with_defaults) 19 20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 ) 27 28 class Config: 29 frozen = True 30 smart_union = True 31 allow_population_by_field_name = True 32 populate_by_name = True 33 extra = pydantic_v1.Extra.allow 34 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 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()
.
20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 )
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: ModelUsageUnit = pydantic_v1.Field() 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.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
13class CreateObservationEvent(BaseEvent): 14 body: ObservationBody 15 16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 return super().json(**kwargs_with_defaults) 19 20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 ) 27 28 class Config: 29 frozen = True 30 smart_union = True 31 allow_population_by_field_name = True 32 populate_by_name = True 33 extra = pydantic_v1.Extra.allow 34 json_encoders = {dt.datetime: serialize_datetime}
16 def json(self, **kwargs: typing.Any) -> str: 17 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 18 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()
.
20 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 21 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 22 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 23 24 return deep_union_pydantic_dicts( 25 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 26 )
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[ChatMessage] 17 config: typing.Optional[typing.Any] = None 18 labels: typing.Optional[typing.List[str]] = None 19 tags: typing.Optional[typing.List[str]] = None 20 type: typing.Literal["chat"] = "chat" 21 22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 28 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 29 30 return deep_union_pydantic_dicts( 31 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 32 ) 33 34 class Config: 35 frozen = True 36 smart_union = True 37 extra = pydantic_v1.Extra.allow 38 json_encoders = {dt.datetime: serialize_datetime}
22 def json(self, **kwargs: typing.Any) -> str: 23 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 28 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 29 30 return deep_union_pydantic_dicts( 31 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 32 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
41class CreatePromptRequest_Text(pydantic_v1.BaseModel): 42 name: str 43 prompt: str 44 config: typing.Optional[typing.Any] = None 45 labels: typing.Optional[typing.List[str]] = None 46 tags: typing.Optional[typing.List[str]] = None 47 type: typing.Literal["text"] = "text" 48 49 def json(self, **kwargs: typing.Any) -> str: 50 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 51 return super().json(**kwargs_with_defaults) 52 53 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 54 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 55 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 59 ) 60 61 class Config: 62 frozen = True 63 smart_union = True 64 extra = pydantic_v1.Extra.allow 65 json_encoders = {dt.datetime: serialize_datetime}
49 def json(self, **kwargs: typing.Any) -> str: 50 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 51 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()
.
53 def dict(self, **kwargs: typing.Any) -> typing.Dict[str, typing.Any]: 54 kwargs_with_defaults_exclude_unset: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 55 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 56 57 return deep_union_pydantic_dicts( 58 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 59 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
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(default=None) 17 """ 18 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 19 """ 20 21 min_value: typing.Optional[float] = pydantic_v1.Field(alias="minValue", default=None) 22 """ 23 Configure a minimum value for numerical scores. If not set, the minimum value defaults to -∞ 24 """ 25 26 max_value: typing.Optional[float] = pydantic_v1.Field(alias="maxValue", default=None) 27 """ 28 Configure a maximum value for numerical scores. If not set, the maximum value defaults to +∞ 29 """ 30 31 description: typing.Optional[str] = pydantic_v1.Field(default=None) 32 """ 33 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 34 """ 35 36 def json(self, **kwargs: typing.Any) -> str: 37 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 42 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), 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}
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
36 def json(self, **kwargs: typing.Any) -> str: 37 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 42 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 43 44 return deep_union_pydantic_dicts( 45 super().dict(**kwargs_with_defaults_exclude_unset), super().dict(**kwargs_with_defaults_exclude_none) 46 )
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
Inherited Members
- pydantic.v1.main.BaseModel
- BaseModel
- parse_obj
- parse_raw
- parse_file
- from_orm
- construct
- copy
- schema
- schema_json
- validate
- update_forward_refs
13class CreateScoreRequest(pydantic_v1.BaseModel): 14 """ 15 Examples 16 -------- 17 from finto 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: str = pydantic_v1.Field(alias="traceId") 28 name: str 29 value: CreateScoreValue = pydantic_v1.Field() 30 """ 31 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) 32 """ 33 34 observation_id: typing.Optional[str] = pydantic_v1.Field(alias="observationId", default=None) 35 comment: typing.Optional[str] = None 36 data_type: typing.Optional[ScoreDataType] = pydantic_v1.Field(alias="dataType", default=None) 37 """ 38 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. 39 """ 40 41 config_id: typing.Optional[str] = pydantic_v1.Field(alias="configId", default=None) 42 """ 43 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. 44 """ 45 46 def json(self, **kwargs: typing.Any) -> str: 47 kwargs_with_defaults: typing.Any = {"by_alias": True, "exclude_unset": True, **kwargs} 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 = {"by_alias": True, "exclude_unset": True, **kwargs} 52 kwargs_with_defaults_exclude_none: typing.Any = {"by_alias": True, "exclude_none": True, **kwargs} 53 54 return deep_union_pydantic_dicts( 55 super().dict(**kwargs_with_defaults_exclude_unset), 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}
Examples
from finto import CreateScoreRequest
CreateScoreRequest( name="novelty", value=0.9, trace_id="cdef-1234-5678-90ab", )