feat: add ops trace (#5483)
Co-authored-by: takatost <takatost@gmail.com>
This commit is contained in:
Joe
0
api/core/ops/langfuse_trace/entities/__init__.py
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api/core/ops/langfuse_trace/entities/__init__.py
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280
api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py
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api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py
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from datetime import datetime
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from enum import Enum
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from typing import Any, Optional, Union
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from pydantic import BaseModel, ConfigDict, Field, field_validator
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from pydantic_core.core_schema import ValidationInfo
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from core.ops.utils import replace_text_with_content
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def validate_input_output(v, field_name):
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"""
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Validate input output
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:param v:
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:param field_name:
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:return:
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"""
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if v == {} or v is None:
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return v
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if isinstance(v, str):
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return [
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{
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"role": "assistant" if field_name == "output" else "user",
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"content": v,
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}
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]
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elif isinstance(v, list):
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if len(v) > 0 and isinstance(v[0], dict):
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v = replace_text_with_content(data=v)
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return v
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else:
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return [
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{
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"role": "assistant" if field_name == "output" else "user",
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"content": str(v),
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}
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]
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return v
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class LevelEnum(str, Enum):
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DEBUG = "DEBUG"
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WARNING = "WARNING"
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ERROR = "ERROR"
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DEFAULT = "DEFAULT"
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class LangfuseTrace(BaseModel):
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"""
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Langfuse trace model
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"""
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id: Optional[str] = Field(
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default=None,
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description="The id of the trace can be set, defaults to a random id. Used to link traces to external systems "
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"or when creating a distributed trace. Traces are upserted on id.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Identifier of the trace. Useful for sorting/filtering in the UI.",
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)
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input: Optional[Union[str, dict[str, Any], list, None]] = Field(
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default=None, description="The input of the trace. Can be any JSON object."
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)
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output: Optional[Union[str, dict[str, Any], list, None]] = Field(
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default=None, description="The output of the trace. Can be any JSON object."
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)
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metadata: Optional[dict[str, Any]] = Field(
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default=None,
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description="Additional metadata of the trace. Can be any JSON object. Metadata is merged when being updated "
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"via the API.",
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)
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user_id: Optional[str] = Field(
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default=None,
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description="The id of the user that triggered the execution. Used to provide user-level analytics.",
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)
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session_id: Optional[str] = Field(
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default=None,
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description="Used to group multiple traces into a session in Langfuse. Use your own session/thread identifier.",
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)
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version: Optional[str] = Field(
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default=None,
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description="The version of the trace type. Used to understand how changes to the trace type affect metrics. "
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"Useful in debugging.",
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)
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release: Optional[str] = Field(
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default=None,
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description="The release identifier of the current deployment. Used to understand how changes of different "
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"deployments affect metrics. Useful in debugging.",
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)
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tags: Optional[list[str]] = Field(
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default=None,
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description="Tags are used to categorize or label traces. Traces can be filtered by tags in the UI and GET "
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"API. Tags can also be changed in the UI. Tags are merged and never deleted via the API.",
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)
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public: Optional[bool] = Field(
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default=None,
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description="You can make a trace public to share it via a public link. This allows others to view the trace "
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"without needing to log in or be members of your Langfuse project.",
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)
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@field_validator("input", "output")
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def ensure_dict(cls, v, info: ValidationInfo):
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field_name = info.field_name
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return validate_input_output(v, field_name)
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class LangfuseSpan(BaseModel):
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"""
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Langfuse span model
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"""
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id: Optional[str] = Field(
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default=None,
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description="The id of the span can be set, otherwise a random id is generated. Spans are upserted on id.",
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)
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session_id: Optional[str] = Field(
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default=None,
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description="Used to group multiple spans into a session in Langfuse. Use your own session/thread identifier.",
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)
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trace_id: Optional[str] = Field(
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default=None,
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description="The id of the trace the span belongs to. Used to link spans to traces.",
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)
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user_id: Optional[str] = Field(
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default=None,
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description="The id of the user that triggered the execution. Used to provide user-level analytics.",
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)
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start_time: Optional[datetime | str] = Field(
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default_factory=datetime.now,
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description="The time at which the span started, defaults to the current time.",
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)
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end_time: Optional[datetime | str] = Field(
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default=None,
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description="The time at which the span ended. Automatically set by span.end().",
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)
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name: Optional[str] = Field(
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default=None,
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description="Identifier of the span. Useful for sorting/filtering in the UI.",
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)
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metadata: Optional[dict[str, Any]] = Field(
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default=None,
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description="Additional metadata of the span. Can be any JSON object. Metadata is merged when being updated "
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"via the API.",
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)
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level: Optional[str] = Field(
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default=None,
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description="The level of the span. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering of "
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"traces with elevated error levels and for highlighting in the UI.",
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)
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status_message: Optional[str] = Field(
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default=None,
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description="The status message of the span. Additional field for context of the event. E.g. the error "
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"message of an error event.",
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)
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input: Optional[Union[str, dict[str, Any], list, None]] = Field(
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default=None, description="The input of the span. Can be any JSON object."
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)
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output: Optional[Union[str, dict[str, Any], list, None]] = Field(
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default=None, description="The output of the span. Can be any JSON object."
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)
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version: Optional[str] = Field(
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default=None,
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description="The version of the span type. Used to understand how changes to the span type affect metrics. "
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"Useful in debugging.",
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)
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parent_observation_id: Optional[str] = Field(
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default=None,
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description="The id of the observation the span belongs to. Used to link spans to observations.",
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)
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@field_validator("input", "output")
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def ensure_dict(cls, v, info: ValidationInfo):
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field_name = info.field_name
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return validate_input_output(v, field_name)
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class UnitEnum(str, Enum):
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CHARACTERS = "CHARACTERS"
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TOKENS = "TOKENS"
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SECONDS = "SECONDS"
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MILLISECONDS = "MILLISECONDS"
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IMAGES = "IMAGES"
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class GenerationUsage(BaseModel):
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promptTokens: Optional[int] = None
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completionTokens: Optional[int] = None
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totalTokens: Optional[int] = None
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input: Optional[int] = None
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output: Optional[int] = None
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total: Optional[int] = None
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unit: Optional[UnitEnum] = None
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inputCost: Optional[float] = None
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outputCost: Optional[float] = None
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totalCost: Optional[float] = None
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@field_validator("input", "output")
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def ensure_dict(cls, v, info: ValidationInfo):
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field_name = info.field_name
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return validate_input_output(v, field_name)
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class LangfuseGeneration(BaseModel):
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id: Optional[str] = Field(
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default=None,
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description="The id of the generation can be set, defaults to random id.",
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)
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trace_id: Optional[str] = Field(
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default=None,
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description="The id of the trace the generation belongs to. Used to link generations to traces.",
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)
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parent_observation_id: Optional[str] = Field(
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default=None,
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description="The id of the observation the generation belongs to. Used to link generations to observations.",
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)
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name: Optional[str] = Field(
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default=None,
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description="Identifier of the generation. Useful for sorting/filtering in the UI.",
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)
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start_time: Optional[datetime | str] = Field(
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default_factory=datetime.now,
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description="The time at which the generation started, defaults to the current time.",
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)
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completion_start_time: Optional[datetime | str] = Field(
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default=None,
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description="The time at which the completion started (streaming). Set it to get latency analytics broken "
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"down into time until completion started and completion duration.",
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)
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end_time: Optional[datetime | str] = Field(
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default=None,
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description="The time at which the generation ended. Automatically set by generation.end().",
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)
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model: Optional[str] = Field(
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default=None, description="The name of the model used for the generation."
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)
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model_parameters: Optional[dict[str, Any]] = Field(
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default=None,
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description="The parameters of the model used for the generation; can be any key-value pairs.",
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)
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input: Optional[Any] = Field(
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default=None,
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description="The prompt used for the generation. Can be any string or JSON object.",
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)
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output: Optional[Any] = Field(
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default=None,
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description="The completion generated by the model. Can be any string or JSON object.",
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)
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usage: Optional[GenerationUsage] = Field(
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default=None,
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description="The usage object supports the OpenAi structure with tokens and a more generic version with "
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"detailed costs and units.",
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)
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metadata: Optional[dict[str, Any]] = Field(
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default=None,
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description="Additional metadata of the generation. Can be any JSON object. Metadata is merged when being "
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"updated via the API.",
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)
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level: Optional[LevelEnum] = Field(
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default=None,
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description="The level of the generation. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering "
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"of traces with elevated error levels and for highlighting in the UI.",
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)
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status_message: Optional[str] = Field(
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default=None,
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description="The status message of the generation. Additional field for context of the event. E.g. the error "
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"message of an error event.",
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)
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version: Optional[str] = Field(
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default=None,
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description="The version of the generation type. Used to understand how changes to the span type affect "
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"metrics. Useful in debugging.",
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)
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model_config = ConfigDict(protected_namespaces=())
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@field_validator("input", "output")
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def ensure_dict(cls, v, info: ValidationInfo):
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field_name = info.field_name
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return validate_input_output(v, field_name)
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