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# Copyright 2024 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import time
from enum import Enum, unique
from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel, Field
from typing_extensions import Literal
@unique
class Role(str, Enum):
USER = "user"
ASSISTANT = "assistant"
SYSTEM = "system"
FUNCTION = "function"
TOOL = "tool"
@unique
class Finish(str, Enum):
STOP = "stop"
LENGTH = "length"
TOOL = "tool_calls"
class ModelCard(BaseModel):
id: str
object: Literal["model"] = "model"
created: int = Field(default_factory=lambda: int(time.time()))
owned_by: Literal["owner"] = "owner"
class ModelList(BaseModel):
object: Literal["list"] = "list"
data: List[ModelCard] = []
class Function(BaseModel):
name: str
arguments: str
class FunctionDefinition(BaseModel):
name: str
description: str
parameters: Dict[str, Any]
class FunctionAvailable(BaseModel):
type: Literal["function", "code_interpreter"] = "function"
function: Optional[FunctionDefinition] = None
class FunctionCall(BaseModel):
id: str
type: Literal["function"] = "function"
function: Function
class ImageURL(BaseModel):
url: str
class MultimodalInputItem(BaseModel):
type: Literal["text", "image_url"]
text: Optional[str] = None
image_url: Optional[ImageURL] = None
class ChatMessage(BaseModel):
role: Role
content: Optional[Union[str, List[MultimodalInputItem]]] = None
tool_calls: Optional[List[FunctionCall]] = None
class ChatCompletionMessage(BaseModel):
role: Optional[Role] = None
content: Optional[str] = None
tool_calls: Optional[List[FunctionCall]] = None
class ChatCompletionRequest(BaseModel):
model: str
messages: List[ChatMessage]
tools: Optional[List[FunctionAvailable]] = None
do_sample: Optional[bool] = None
temperature: Optional[float] = None
top_p: Optional[float] = None
n: int = 1
max_tokens: Optional[int] = None
stop: Optional[Union[str, List[str]]] = None
stream: bool = False
class ChatCompletionResponseChoice(BaseModel):
index: int
message: ChatCompletionMessage
finish_reason: Finish
class ChatCompletionStreamResponseChoice(BaseModel):
index: int
delta: ChatCompletionMessage
finish_reason: Optional[Finish] = None
class ChatCompletionResponseUsage(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class ChatCompletionResponse(BaseModel):
id: str
object: Literal["chat.completion"] = "chat.completion"
created: int = Field(default_factory=lambda: int(time.time()))
model: str
choices: List[ChatCompletionResponseChoice]
usage: ChatCompletionResponseUsage
class ChatCompletionStreamResponse(BaseModel):
id: str
object: Literal["chat.completion.chunk"] = "chat.completion.chunk"
created: int = Field(default_factory=lambda: int(time.time()))
model: str
choices: List[ChatCompletionStreamResponseChoice]
class ScoreEvaluationRequest(BaseModel):
model: str
messages: List[str]
max_length: Optional[int] = None
class ScoreEvaluationResponse(BaseModel):
id: str
object: Literal["score.evaluation"] = "score.evaluation"
model: str
scores: List[float]
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