# coding: utf-8
"""
Arize REST API
API specification for the backend data server. The API is hosted globally at https://api.arize.com/v2 or in your own environment.
The version of the OpenAPI document: 2.0.0
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
from __future__ import annotations
import pprint
import re # noqa: F401
import json
from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StrictInt, StrictStr
from typing import Any, ClassVar, Dict, List, Optional, Union
from arize._generated.api_client.models.response_format import ResponseFormat
from arize._generated.api_client.models.tool_config import ToolConfig
from typing import Optional, Set
from typing_extensions import Self
[docs]
class InvocationParams(BaseModel):
"""
Parameters for the LLM invocation
""" # noqa: E501
temperature: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Sampling temperature (higher = more random)")
max_tokens: Optional[StrictInt] = Field(default=None, description="Maximum number of tokens to generate")
max_completion_tokens: Optional[StrictInt] = Field(default=None, description="Maximum number of completion tokens to generate")
top_p: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Nucleus sampling parameter")
frequency_penalty: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Frequency penalty (-2.0 to 2.0)")
presence_penalty: Optional[Union[StrictFloat, StrictInt]] = Field(default=None, description="Presence penalty (-2.0 to 2.0)")
stop: Optional[List[StrictStr]] = Field(default=None, description="Stop sequences")
response_format: Optional[ResponseFormat] = Field(default=None, description="Response format configuration. Optional. When omitted, no structured output constraint is applied (the provider's default plain-text behavior is used).")
tool_config: Optional[ToolConfig] = Field(default=None, description="Tool configuration for the LLM invocation. Optional. When omitted, no tools are made available to the model.")
__properties: ClassVar[List[str]] = ["temperature", "max_tokens", "max_completion_tokens", "top_p", "frequency_penalty", "presence_penalty", "stop", "response_format", "tool_config"]
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
protected_namespaces=(),
)
[docs]
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.model_dump(by_alias=True))
[docs]
def to_json(self) -> str:
"""Returns the JSON representation of the model using alias"""
# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
return json.dumps(self.to_dict())
[docs]
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of InvocationParams from a JSON string"""
return cls.from_dict(json.loads(json_str))
[docs]
def to_dict(self) -> Dict[str, Any]:
"""Return the dictionary representation of the model using alias.
This has the following differences from calling pydantic's
`self.model_dump(by_alias=True)`:
* `None` is only added to the output dict for nullable fields that
were set at model initialization. Other fields with value `None`
are ignored.
"""
excluded_fields: Set[str] = set([
])
_dict = self.model_dump(
by_alias=True,
exclude=excluded_fields,
exclude_none=True,
)
# override the default output from pydantic by calling `to_dict()` of response_format
if self.response_format:
_dict['response_format'] = self.response_format.to_dict()
# override the default output from pydantic by calling `to_dict()` of tool_config
if self.tool_config:
_dict['tool_config'] = self.tool_config.to_dict()
return _dict
[docs]
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of InvocationParams from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
# raise errors for additional fields in the input
for _key in obj.keys():
if _key not in cls.__properties:
raise ValueError("Error due to additional fields (not defined in InvocationParams) in the input: " + _key)
_obj = cls.model_validate({
"temperature": obj.get("temperature"),
"max_tokens": obj.get("max_tokens"),
"max_completion_tokens": obj.get("max_completion_tokens"),
"top_p": obj.get("top_p"),
"frequency_penalty": obj.get("frequency_penalty"),
"presence_penalty": obj.get("presence_penalty"),
"stop": obj.get("stop"),
"response_format": ResponseFormat.from_dict(obj["response_format"]) if obj.get("response_format") is not None else None,
"tool_config": ToolConfig.from_dict(obj["tool_config"]) if obj.get("tool_config") is not None else None
})
return _obj
