import json import time from typing import List from pydantic import BaseModel, Field class GenerationOptions(BaseModel): preset: str | None = Field(default=None, description="The name of a file under text-generation-webui/presets (without the .yaml extension). The sampling parameters that get overwritten by this option are the keys in the default_preset() function in modules/presets.py.") min_p: float = 0 top_k: int = 0 repetition_penalty: float = 1 repetition_penalty_range: int = 0 typical_p: float = 1 tfs: float = 1 top_a: float = 0 epsilon_cutoff: float = 0 eta_cutoff: float = 0 guidance_scale: float = 1 negative_prompt: str = '' penalty_alpha: float = 0 mirostat_mode: int = 0 mirostat_tau: float = 5 mirostat_eta: float = 0.1 temperature_last: bool = False do_sample: bool = True seed: int = -1 encoder_repetition_penalty: float = 1 no_repeat_ngram_size: int = 0 min_length: int = 0 num_beams: int = 1 length_penalty: float = 1 early_stopping: bool = False truncation_length: int = 0 max_tokens_second: int = 0 custom_token_bans: str = "" auto_max_new_tokens: bool = False ban_eos_token: bool = False add_bos_token: bool = True skip_special_tokens: bool = True grammar_string: str = "" class CompletionRequestParams(BaseModel): model: str | None = None prompt: str | List[str] best_of: int | None = 1 echo: bool | None = False frequency_penalty: float | None = 0 logit_bias: dict | None = None logprobs: int | None = None max_tokens: int | None = 16 n: int | None = 1 presence_penalty: int | None = 0 stop: str | List[str] | None = None stream: bool | None = False suffix: str | None = None temperature: float | None = 1 top_p: float | None = 1 user: str | None = None class CompletionRequest(GenerationOptions, CompletionRequestParams): pass class CompletionResponse(BaseModel): id: str choices: List[dict] created: int = int(time.time()) model: str object: str = "text_completion" usage: dict class ChatCompletionRequestParams(BaseModel): messages: List[dict] model: str | None = None frequency_penalty: float | None = 0 function_call: str | dict | None = None functions: List[dict] | None = None logit_bias: dict | None = None max_tokens: int | None = None n: int | None = 1 presence_penalty: int | None = 0 stop: str | List[str] | None = None stream: bool | None = False temperature: float | None = 1 top_p: float | None = 1 user: str | None = None mode: str = Field(default='instruct', description="Valid options: instruct, chat, chat-instruct.") instruction_template: str | None = Field(default=None, description="An instruction template defined under text-generation-webui/instruction-templates. If not set, the correct template will be guessed using the regex expressions in models/config.yaml.") name1_instruct: str | None = Field(default=None, description="Overwrites the value set by instruction_template.") name2_instruct: str | None = Field(default=None, description="Overwrites the value set by instruction_template.") context_instruct: str | None = Field(default=None, description="Overwrites the value set by instruction_template.") turn_template: str | None = Field(default=None, description="Overwrites the value set by instruction_template.") character: str | None = Field(default=None, description="A character defined under text-generation-webui/characters. If not set, the default \"Assistant\" character will be used.") name1: str | None = Field(default=None, description="Overwrites the value set by character.") name2: str | None = Field(default=None, description="Overwrites the value set by character.") context: str | None = Field(default=None, description="Overwrites the value set by character.") greeting: str | None = Field(default=None, description="Overwrites the value set by character.") chat_instruct_command: str | None = None continue_: bool = Field(default=False, description="Makes the last bot message in the history be continued instead of starting a new message.") class ChatCompletionRequest(GenerationOptions, ChatCompletionRequestParams): pass class ChatCompletionResponse(BaseModel): id: str choices: List[dict] created: int = int(time.time()) model: str object: str = "chat.completion" usage: dict def to_json(obj): return json.dumps(obj.__dict__, indent=4) def to_dict(obj): return obj.__dict__