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sglang/python/sglang/srt/openai_api/protocol.py

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Python

# Copyright 2023-2024 SGLang 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.
# ==============================================================================
"""Pydantic models for OpenAI API protocol"""
import time
from typing import Dict, List, Optional, Union
from pydantic import BaseModel, Field
from typing_extensions import Literal
class ModelCard(BaseModel):
"""Model cards."""
id: str
object: str = "model"
created: int = Field(default_factory=lambda: int(time.time()))
owned_by: str = "sglang"
root: Optional[str] = None
class ModelList(BaseModel):
"""Model list consists of model cards."""
object: str = "list"
data: List[ModelCard] = Field(default_factory=list)
class ErrorResponse(BaseModel):
object: str = "error"
message: str
type: str
param: Optional[str] = None
code: int
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 TopLogprob(BaseModel):
token: str
bytes: List[int]
logprob: float
class ChatCompletionTokenLogprob(BaseModel):
token: str
bytes: List[int]
logprob: float
top_logprobs: List[TopLogprob]
class ChoiceLogprobs(BaseModel):
# build for v1/chat/completions response
content: List[ChatCompletionTokenLogprob]
class UsageInfo(BaseModel):
prompt_tokens: int = 0
total_tokens: int = 0
completion_tokens: Optional[int] = 0
# only used to return cached tokens when --enable-cache-report is set
prompt_tokens_details: Optional[Dict[str, int]] = None
class StreamOptions(BaseModel):
include_usage: Optional[bool] = False
class JsonSchemaResponseFormat(BaseModel):
name: str
description: Optional[str] = None
# use alias to workaround pydantic conflict
schema_: Optional[Dict[str, object]] = Field(alias="schema", default=None)
strict: Optional[bool] = False
class FileRequest(BaseModel):
# https://platform.openai.com/docs/api-reference/files/create
file: bytes # The File object (not file name) to be uploaded
purpose: str = (
"batch" # The intended purpose of the uploaded file, default is "batch"
)
class FileResponse(BaseModel):
id: str
object: str = "file"
bytes: int
created_at: int
filename: str
purpose: str
class FileDeleteResponse(BaseModel):
id: str
object: str = "file"
deleted: bool
class BatchRequest(BaseModel):
input_file_id: (
str # The ID of an uploaded file that contains requests for the new batch
)
endpoint: str # The endpoint to be used for all requests in the batch
completion_window: str # The time frame within which the batch should be processed
metadata: Optional[dict] = None # Optional custom metadata for the batch
class BatchResponse(BaseModel):
id: str
object: str = "batch"
endpoint: str
errors: Optional[dict] = None
input_file_id: str
completion_window: str
status: str = "validating"
output_file_id: Optional[str] = None
error_file_id: Optional[str] = None
created_at: int
in_progress_at: Optional[int] = None
expires_at: Optional[int] = None
finalizing_at: Optional[int] = None
completed_at: Optional[int] = None
failed_at: Optional[int] = None
expired_at: Optional[int] = None
cancelling_at: Optional[int] = None
cancelled_at: Optional[int] = None
request_counts: Optional[dict] = None
metadata: Optional[dict] = None
class CompletionRequest(BaseModel):
# Ordered by official OpenAI API documentation
# https://platform.openai.com/docs/api-reference/completions/create
model: str
prompt: Union[List[int], List[List[int]], str, List[str]]
best_of: Optional[int] = None
echo: bool = False
frequency_penalty: float = 0.0
logit_bias: Optional[Dict[str, float]] = None
logprobs: Optional[int] = None
max_tokens: int = 16
n: int = 1
presence_penalty: float = 0.0
seed: Optional[int] = None
stop: Optional[Union[str, List[str]]] = None
stream: bool = False
stream_options: Optional[StreamOptions] = None
suffix: Optional[str] = None
temperature: float = 1.0
top_p: float = 1.0
user: Optional[str] = None
# Extra parameters for SRT backend only and will be ignored by OpenAI models.
json_schema: Optional[str] = None
regex: Optional[str] = None
min_tokens: int = 0
repetition_penalty: float = 1.0
stop_token_ids: Optional[List[int]] = None
no_stop_trim: bool = False
ignore_eos: bool = False
skip_special_tokens: bool = True
class CompletionResponseChoice(BaseModel):
index: int
text: str
logprobs: Optional[LogProbs] = None
finish_reason: Optional[str] = None
matched_stop: Union[None, int, str] = None
class CompletionResponse(BaseModel):
id: str
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[str] = None
matched_stop: Union[None, int, str] = None
class CompletionStreamResponse(BaseModel):
id: str
object: str = "text_completion"
created: int = Field(default_factory=lambda: int(time.time()))
model: str
choices: List[CompletionResponseStreamChoice]
usage: Optional[UsageInfo] = None
class ChatCompletionMessageContentTextPart(BaseModel):
type: Literal["text"]
text: str
class ChatCompletionMessageContentImageURL(BaseModel):
url: str
detail: Optional[Literal["auto", "low", "high"]] = "auto"
class ChatCompletionMessageContentImagePart(BaseModel):
type: Literal["image_url"]
image_url: ChatCompletionMessageContentImageURL
modalities: Optional[Literal["image", "multi-images", "video"]] = "image"
ChatCompletionMessageContentPart = Union[
ChatCompletionMessageContentTextPart, ChatCompletionMessageContentImagePart
]
class ChatCompletionMessageGenericParam(BaseModel):
role: Literal["system", "assistant", "tool"]
content: Union[str, List[ChatCompletionMessageContentTextPart]]
class ChatCompletionMessageUserParam(BaseModel):
role: Literal["user"]
content: Union[str, List[ChatCompletionMessageContentPart]]
ChatCompletionMessageParam = Union[
ChatCompletionMessageGenericParam, ChatCompletionMessageUserParam
]
class ResponseFormat(BaseModel):
type: Literal["text", "json_object", "json_schema"]
json_schema: Optional[JsonSchemaResponseFormat] = None
class ChatCompletionRequest(BaseModel):
# Ordered by official OpenAI API documentation
# https://platform.openai.com/docs/api-reference/chat/create
messages: List[ChatCompletionMessageParam]
model: str
frequency_penalty: float = 0.0
logit_bias: Optional[Dict[str, float]] = None
logprobs: bool = False
top_logprobs: Optional[int] = None
max_tokens: Optional[int] = None
n: int = 1
presence_penalty: float = 0.0
response_format: Optional[ResponseFormat] = None
seed: Optional[int] = None
stop: Optional[Union[str, List[str]]] = None
stream: bool = False
stream_options: Optional[StreamOptions] = None
temperature: float = 0.7
top_p: float = 1.0
user: Optional[str] = None
# Extra parameters for SRT backend only and will be ignored by OpenAI models.
regex: Optional[str] = None
min_tokens: int = 0
repetition_penalty: float = 1.0
stop_token_ids: Optional[List[int]] = None
no_stop_trim: bool = False
ignore_eos: bool = False
skip_special_tokens: bool = True
class ChatMessage(BaseModel):
role: Optional[str] = None
content: Optional[str] = None
class ChatCompletionResponseChoice(BaseModel):
index: int
message: ChatMessage
logprobs: Optional[Union[LogProbs, ChoiceLogprobs]] = None
finish_reason: str
matched_stop: Union[None, int, str] = None
class ChatCompletionResponse(BaseModel):
id: str
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
logprobs: Optional[Union[LogProbs, ChoiceLogprobs]] = None
finish_reason: Optional[str] = None
matched_stop: Union[None, int, str] = None
class ChatCompletionStreamResponse(BaseModel):
id: str
object: str = "chat.completion.chunk"
created: int = Field(default_factory=lambda: int(time.time()))
model: str
choices: List[ChatCompletionResponseStreamChoice]
usage: Optional[UsageInfo] = None
class EmbeddingRequest(BaseModel):
# Ordered by official OpenAI API documentation
# https://platform.openai.com/docs/api-reference/embeddings/create
input: Union[List[int], List[List[int]], str, List[str]]
model: str
encoding_format: str = "float"
dimensions: int = None
user: Optional[str] = None
class EmbeddingObject(BaseModel):
embedding: List[float]
index: int
object: str = "embedding"
class EmbeddingResponse(BaseModel):
data: List[EmbeddingObject]
model: str
object: str = "list"
usage: Optional[UsageInfo] = None