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| from __future__ import annotations | |
| import dataclasses | |
| from dataclasses import dataclass, fields, replace | |
| from typing import Any, Literal | |
| from openai._types import Body, Headers, Query | |
| from openai.types.shared import Reasoning | |
| from pydantic import BaseModel | |
| class ModelSettings: | |
| """Settings to use when calling an LLM. | |
| This class holds optional model configuration parameters (e.g. temperature, | |
| top_p, penalties, truncation, etc.). | |
| Not all models/providers support all of these parameters, so please check the API documentation | |
| for the specific model and provider you are using. | |
| """ | |
| temperature: float | None = None | |
| """The temperature to use when calling the model.""" | |
| top_p: float | None = None | |
| """The top_p to use when calling the model.""" | |
| frequency_penalty: float | None = None | |
| """The frequency penalty to use when calling the model.""" | |
| presence_penalty: float | None = None | |
| """The presence penalty to use when calling the model.""" | |
| tool_choice: Literal["auto", "required", "none"] | str | None = None | |
| """The tool choice to use when calling the model.""" | |
| parallel_tool_calls: bool | None = None | |
| """Whether to use parallel tool calls when calling the model. | |
| Defaults to False if not provided.""" | |
| truncation: Literal["auto", "disabled"] | None = None | |
| """The truncation strategy to use when calling the model.""" | |
| max_tokens: int | None = None | |
| """The maximum number of output tokens to generate.""" | |
| reasoning: Reasoning | None = None | |
| """Configuration options for | |
| [reasoning models](https://platform.openai.com/docs/guides/reasoning). | |
| """ | |
| metadata: dict[str, str] | None = None | |
| """Metadata to include with the model response call.""" | |
| store: bool | None = None | |
| """Whether to store the generated model response for later retrieval. | |
| Defaults to True if not provided.""" | |
| include_usage: bool | None = None | |
| """Whether to include usage chunk. | |
| Defaults to True if not provided.""" | |
| extra_query: Query | None = None | |
| """Additional query fields to provide with the request. | |
| Defaults to None if not provided.""" | |
| extra_body: Body | None = None | |
| """Additional body fields to provide with the request. | |
| Defaults to None if not provided.""" | |
| extra_headers: Headers | None = None | |
| """Additional headers to provide with the request. | |
| Defaults to None if not provided.""" | |
| extra_args: dict[str, Any] | None = None | |
| """Arbitrary keyword arguments to pass to the model API call. | |
| These will be passed directly to the underlying model provider's API. | |
| Use with caution as not all models support all parameters.""" | |
| def resolve(self, override: ModelSettings | None) -> ModelSettings: | |
| """Produce a new ModelSettings by overlaying any non-None values from the | |
| override on top of this instance.""" | |
| if override is None: | |
| return self | |
| changes = { | |
| field.name: getattr(override, field.name) | |
| for field in fields(self) | |
| if getattr(override, field.name) is not None | |
| } | |
| # Handle extra_args merging specially - merge dictionaries instead of replacing | |
| if self.extra_args is not None or override.extra_args is not None: | |
| merged_args = {} | |
| if self.extra_args: | |
| merged_args.update(self.extra_args) | |
| if override.extra_args: | |
| merged_args.update(override.extra_args) | |
| changes["extra_args"] = merged_args if merged_args else None | |
| return replace(self, **changes) | |
| def to_json_dict(self) -> dict[str, Any]: | |
| dataclass_dict = dataclasses.asdict(self) | |
| json_dict: dict[str, Any] = {} | |
| for field_name, value in dataclass_dict.items(): | |
| if isinstance(value, BaseModel): | |
| json_dict[field_name] = value.model_dump(mode="json") | |
| else: | |
| json_dict[field_name] = value | |
| return json_dict | |