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param_model.py
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import time
from pydantic import BaseModel, Field
from typing import List, Dict, Optional, Literal, Union, Any
class ModelCard(BaseModel):
id: str
object: str = "model"
created: int = Field(default_factory=lambda: int(time.time()))
owned_by: str = "owner"
root: Optional[str] = None
parent: Optional[str] = None
permission: Optional[list] = None
class ModelList(BaseModel):
object: str = "list"
data: List[ModelCard] = []
class FunctionCallResponse(BaseModel):
name: Optional[str] = None
arguments: Optional[str] = None
class ChatMessage(BaseModel):
role: Literal["user", "assistant", "system", "function"]
content: str = None
name: Optional[str] = None
function_call: Optional[FunctionCallResponse] = None
class DeltaMessage(BaseModel):
role: Optional[Literal["user", "assistant", "system"]] = None
content: Optional[str] = None
function_call: Optional[FunctionCallResponse] = None
class ChatCompletionRequest(BaseModel):
model: str
messages: List[ChatMessage]
temperature: Optional[float] = None
top_p: Optional[float] = None
max_tokens: Optional[int] = None
stream: Optional[bool] = False
functions: Optional[Union[dict, List[dict]]] = None
# Additional parameters
repetition_penalty: Optional[float] = None
class TouristSceneRequest(BaseModel):
messages: List[ChatMessage]
class ChatCompletionResponseChoice(BaseModel):
index: int
message: ChatMessage
finish_reason: Literal["stop", "length", "function_call"]
class ChatCompletionResponseStreamChoice(BaseModel):
index: int
delta: DeltaMessage
finish_reason: Optional[Literal["stop", "length", "function_call"]]
class UsageInfo(BaseModel):
prompt_tokens: int = 0
total_tokens: int = 0
completion_tokens: Optional[int] = 0
class ChatCompletionResponse(BaseModel):
model: str
object: Literal["chat.completion", "chat.completion.chunk"]
choices: List[Union[ChatCompletionResponseChoice, ChatCompletionResponseStreamChoice]]
created: Optional[int] = Field(default_factory=lambda: int(time.time()))
usage: Optional[UsageInfo] = None
class EmbeddingRequest(BaseModel):
input: List[str]
model: str
class CompletionUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class EmbeddingResponse(BaseModel):
data: list
model: str
object: str
usage: CompletionUsage
class CopyWritingPayload(BaseModel):
model: str = "chatglm3-6b__baseline"
prompt: str
class CommentPayload(BaseModel):
text: str
image: List[str] = None
class GenderPayload(BaseModel):
name: str
class BaseResponse(BaseModel):
object: Literal["list", "dict", "str"]
data: Any
class TransPayload(BaseModel):
content: str
to: Literal["en", "ja", "zh-tw"]
class EmbeddingPayload(BaseModel):
input: Union[List[str], str]
model: str
class Embedding(BaseModel):
embedding: List[float]
index: int
object: Literal["embedding"]
class CreateEmbeddingResponse(BaseModel):
data: List[Embedding]
model: str
object: Literal["list"]
usage: CompletionUsage