Source code for arize._generated.api_client.models.llm_message

# 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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from arize._generated.api_client.models.message_role import MessageRole
from arize._generated.api_client.models.tool_call import ToolCall
from typing import Optional, Set
from typing_extensions import Self

[docs] class LLMMessage(BaseModel): """ A message in the prompt template """ # noqa: E501 role: MessageRole content: Optional[StrictStr] = Field(default=None, description="The content of the message") tool_call_id: Optional[StrictStr] = Field(default=None, description="The ID of the tool call this message is responding to") tool_calls: Optional[List[ToolCall]] = Field(default=None, description="Tool calls generated by the model") __properties: ClassVar[List[str]] = ["role", "content", "tool_call_id", "tool_calls"] 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 LLMMessage 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 each item in tool_calls (list) _items = [] if self.tool_calls: for _item_tool_calls in self.tool_calls: if _item_tool_calls: _items.append(_item_tool_calls.to_dict()) _dict['tool_calls'] = _items # set to None if content (nullable) is None # and model_fields_set contains the field if self.content is None and "content" in self.model_fields_set: _dict['content'] = None return _dict
[docs] @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of LLMMessage 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 LLMMessage) in the input: " + _key) _obj = cls.model_validate({ "role": obj.get("role"), "content": obj.get("content"), "tool_call_id": obj.get("tool_call_id"), "tool_calls": [ToolCall.from_dict(_item) for _item in obj["tool_calls"]] if obj.get("tool_calls") is not None else None }) return _obj