| from typing import Literal, Optional, List, Dict, Any, Union | |
| import time | |
| import shortuuid | |
| from pydantic import BaseModel, Field | |
| class ErrorResponse(BaseModel): | |
| object: str = "error" | |
| message: str | |
| code: int | |
| class ModelPermission(BaseModel): | |
| id: str = Field(default_factory=lambda: f"modelperm-{shortuuid.random()}") | |
| object: str = "model_permission" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| allow_create_engine: bool = False | |
| allow_sampling: bool = True | |
| allow_logprobs: bool = True | |
| allow_search_indices: bool = True | |
| allow_view: bool = True | |
| allow_fine_tuning: bool = False | |
| organization: str = "*" | |
| group: Optional[str] = None | |
| is_blocking: str = False | |
| class ModelCard(BaseModel): | |
| id: str | |
| object: str = "model" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| owned_by: str = "fastchat" | |
| root: Optional[str] = None | |
| parent: Optional[str] = None | |
| permission: List[ModelPermission] = [] | |
| class ModelList(BaseModel): | |
| object: str = "list" | |
| data: List[ModelCard] = [] | |
| class UsageInfo(BaseModel): | |
| prompt_tokens: int = 0 | |
| total_tokens: int = 0 | |
| completion_tokens: Optional[int] = 0 | |
| class LogProbs(BaseModel): | |
| text_offset: List[int] = Field(default_factory=list) | |
| token_logprobs: List[Optional[float]] = Field(default_factory=list) | |
| tokens: List[str] = Field(default_factory=list) | |
| top_logprobs: List[Optional[Dict[str, float]]] = Field(default_factory=list) | |
| class ChatCompletionRequest(BaseModel): | |
| model: str | |
| messages: Union[ | |
| str, | |
| List[Dict[str, str]], | |
| List[Dict[str, Union[str, List[Dict[str, Union[str, Dict[str, str]]]]]]], | |
| ] | |
| temperature: Optional[float] = 0.7 | |
| top_p: Optional[float] = 1.0 | |
| top_k: Optional[int] = -1 | |
| n: Optional[int] = 1 | |
| max_tokens: Optional[int] = None | |
| stop: Optional[Union[str, List[str]]] = None | |
| stream: Optional[bool] = False | |
| presence_penalty: Optional[float] = 0.0 | |
| frequency_penalty: Optional[float] = 0.0 | |
| user: Optional[str] = None | |
| class ChatMessage(BaseModel): | |
| role: str | |
| content: str | |
| class ChatCompletionResponseChoice(BaseModel): | |
| index: int | |
| message: ChatMessage | |
| finish_reason: Optional[Literal["stop", "length"]] = None | |
| class ChatCompletionResponse(BaseModel): | |
| id: str = Field(default_factory=lambda: f"chatcmpl-{shortuuid.random()}") | |
| object: str = "chat.completion" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| model: str | |
| choices: List[ChatCompletionResponseChoice] | |
| usage: UsageInfo | |
| class DeltaMessage(BaseModel): | |
| role: Optional[str] = None | |
| content: Optional[str] = None | |
| class ChatCompletionResponseStreamChoice(BaseModel): | |
| index: int | |
| delta: DeltaMessage | |
| finish_reason: Optional[Literal["stop", "length"]] = None | |
| class ChatCompletionStreamResponse(BaseModel): | |
| id: str = Field(default_factory=lambda: f"chatcmpl-{shortuuid.random()}") | |
| object: str = "chat.completion.chunk" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| model: str | |
| choices: List[ChatCompletionResponseStreamChoice] | |
| class TokenCheckRequestItem(BaseModel): | |
| model: str | |
| prompt: str | |
| max_tokens: int | |
| class TokenCheckRequest(BaseModel): | |
| prompts: List[TokenCheckRequestItem] | |
| class TokenCheckResponseItem(BaseModel): | |
| fits: bool | |
| tokenCount: int | |
| contextLength: int | |
| class TokenCheckResponse(BaseModel): | |
| prompts: List[TokenCheckResponseItem] | |
| class EmbeddingsRequest(BaseModel): | |
| model: Optional[str] = None | |
| engine: Optional[str] = None | |
| input: Union[str, List[Any]] | |
| user: Optional[str] = None | |
| encoding_format: Optional[str] = None | |
| class EmbeddingsResponse(BaseModel): | |
| object: str = "list" | |
| data: List[Dict[str, Any]] | |
| model: str | |
| usage: UsageInfo | |
| class CompletionRequest(BaseModel): | |
| model: str | |
| prompt: Union[str, List[Any]] | |
| suffix: Optional[str] = None | |
| temperature: Optional[float] = 0.7 | |
| n: Optional[int] = 1 | |
| max_tokens: Optional[int] = 16 | |
| stop: Optional[Union[str, List[str]]] = None | |
| stream: Optional[bool] = False | |
| top_p: Optional[float] = 1.0 | |
| top_k: Optional[int] = -1 | |
| logprobs: Optional[int] = None | |
| echo: Optional[bool] = False | |
| presence_penalty: Optional[float] = 0.0 | |
| frequency_penalty: Optional[float] = 0.0 | |
| user: Optional[str] = None | |
| use_beam_search: Optional[bool] = False | |
| best_of: Optional[int] = None | |
| class CompletionResponseChoice(BaseModel): | |
| index: int | |
| text: str | |
| logprobs: Optional[LogProbs] = None | |
| finish_reason: Optional[Literal["stop", "length"]] = None | |
| class CompletionResponse(BaseModel): | |
| id: str = Field(default_factory=lambda: f"cmpl-{shortuuid.random()}") | |
| object: str = "text_completion" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| model: str | |
| choices: List[CompletionResponseChoice] | |
| usage: UsageInfo | |
| class CompletionResponseStreamChoice(BaseModel): | |
| index: int | |
| text: str | |
| logprobs: Optional[LogProbs] = None | |
| finish_reason: Optional[Literal["stop", "length"]] = None | |
| class CompletionStreamResponse(BaseModel): | |
| id: str = Field(default_factory=lambda: f"cmpl-{shortuuid.random()}") | |
| object: str = "text_completion" | |
| created: int = Field(default_factory=lambda: int(time.time())) | |
| model: str | |
| choices: List[CompletionResponseStreamChoice] | |