biondizzle/vllm
1
0
Fork 0
Code Issues Pull Requests Actions 2 Packages Projects Releases Wiki Activity

Migrate docs from Sphinx to MkDocs (#18145)

Browse Source 
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-05-23 11:09:53 +02:00
committed by GitHub
parent d0bc2f810b
commit a1fe24d961
218 changed files with 4126 additions and 6790 deletions
Download Patch File Download Diff File Expand all files Collapse all files

64
vllm/entrypoints/openai/protocol.py
View File

@@ -251,7 +251,7 @@ class ChatCompletionRequest(OpenAIBaseModel):
parallel_tool_calls: Optional[bool] = False
user: Optional[str] = None
# doc: begin-chat-completion-sampling-params
# --8<-- [start:chat-completion-sampling-params]
best_of: Optional[int] = None
use_beam_search: bool = False
top_k: Optional[int] = None
@@ -266,9 +266,9 @@ class ChatCompletionRequest(OpenAIBaseModel):
spaces_between_special_tokens: bool = True
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=1)]] = None
prompt_logprobs: Optional[int] = None
# doc: end-chat-completion-sampling-params
# --8<-- [end:chat-completion-sampling-params]
# doc: begin-chat-completion-extra-params
# --8<-- [start:chat-completion-extra-params]
echo: bool = Field(
default=False,
description=(
@@ -407,7 +407,7 @@ class ChatCompletionRequest(OpenAIBaseModel):
default=None,
description="KVTransfer parameters used for disaggregated serving.")
# doc: end-chat-completion-extra-params
# --8<-- [end:chat-completion-extra-params]
# Default sampling parameters for chat completion requests
_DEFAULT_SAMPLING_PARAMS: dict = {
@@ -764,7 +764,7 @@ class CompletionRequest(OpenAIBaseModel):
top_p: Optional[float] = None
user: Optional[str] = None
# doc: begin-completion-sampling-params
# --8<-- [start:completion-sampling-params]
use_beam_search: bool = False
top_k: Optional[int] = None
min_p: Optional[float] = None
@@ -779,9 +779,9 @@ class CompletionRequest(OpenAIBaseModel):
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=1)]] = None
allowed_token_ids: Optional[list[int]] = None
prompt_logprobs: Optional[int] = None
# doc: end-completion-sampling-params
# --8<-- [end:completion-sampling-params]
# doc: begin-completion-extra-params
# --8<-- [start:completion-extra-params]
add_special_tokens: bool = Field(
default=True,
description=(
@@ -858,7 +858,7 @@ class CompletionRequest(OpenAIBaseModel):
default=None,
description="KVTransfer parameters used for disaggregated serving.")
# doc: end-completion-extra-params
# --8<-- [end:completion-extra-params]
# Default sampling parameters for completion requests
_DEFAULT_SAMPLING_PARAMS: dict = {
@@ -1045,11 +1045,11 @@ class EmbeddingCompletionRequest(OpenAIBaseModel):
user: Optional[str] = None
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None
# doc: begin-embedding-pooling-params
# --8<-- [start:embedding-pooling-params]
additional_data: Optional[Any] = None
# doc: end-embedding-pooling-params
# --8<-- [end:embedding-pooling-params]
# doc: begin-embedding-extra-params
# --8<-- [start:embedding-extra-params]
add_special_tokens: bool = Field(
default=True,
description=(
@@ -1064,7 +1064,7 @@ class EmbeddingCompletionRequest(OpenAIBaseModel):
"if the served model does not use priority scheduling."),
)
# doc: end-embedding-extra-params
# --8<-- [end:embedding-extra-params]
def to_pooling_params(self):
return PoolingParams(dimensions=self.dimensions,
@@ -1080,11 +1080,11 @@ class EmbeddingChatRequest(OpenAIBaseModel):
user: Optional[str] = None
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None
# doc: begin-chat-embedding-pooling-params
# --8<-- [start:chat-embedding-pooling-params]
additional_data: Optional[Any] = None
# doc: end-chat-embedding-pooling-params
# --8<-- [end:chat-embedding-pooling-params]
# doc: begin-chat-embedding-extra-params
# --8<-- [start:chat-embedding-extra-params]
add_special_tokens: bool = Field(
default=False,
description=(
@@ -1118,7 +1118,7 @@ class EmbeddingChatRequest(OpenAIBaseModel):
"default: 0). Any priority other than 0 will raise an error "
"if the served model does not use priority scheduling."),
)
# doc: end-chat-embedding-extra-params
# --8<-- [end:chat-embedding-extra-params]
@model_validator(mode="before")
@classmethod
@@ -1147,11 +1147,11 @@ class ScoreRequest(OpenAIBaseModel):
text_2: Union[list[str], str]
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None
# doc: begin-score-pooling-params
# --8<-- [start:score-pooling-params]
additional_data: Optional[Any] = None
# doc: end-score-pooling-params
# --8<-- [end:score-pooling-params]
# doc: begin-score-extra-params
# --8<-- [start:score-extra-params]
priority: int = Field(
default=0,
description=(
@@ -1160,7 +1160,7 @@ class ScoreRequest(OpenAIBaseModel):
"if the served model does not use priority scheduling."),
)
# doc: end-score-extra-params
# --8<-- [end:score-extra-params]
def to_pooling_params(self):
return PoolingParams(additional_data=self.additional_data)
@@ -1173,11 +1173,11 @@ class RerankRequest(OpenAIBaseModel):
top_n: int = Field(default_factory=lambda: 0)
truncate_prompt_tokens: Optional[Annotated[int, Field(ge=-1)]] = None
# doc: begin-rerank-pooling-params
# --8<-- [start:rerank-pooling-params]
additional_data: Optional[Any] = None
# doc: end-rerank-pooling-params
# --8<-- [end:rerank-pooling-params]
# doc: begin-rerank-extra-params
# --8<-- [start:rerank-extra-params]
priority: int = Field(
default=0,
description=(
@@ -1186,7 +1186,7 @@ class RerankRequest(OpenAIBaseModel):
"if the served model does not use priority scheduling."),
)
# doc: end-rerank-extra-params
# --8<-- [end:rerank-extra-params]
def to_pooling_params(self):
return PoolingParams(additional_data=self.additional_data)
@@ -1321,11 +1321,11 @@ class ClassificationRequest(OpenAIBaseModel):
truncate_prompt_tokens: Optional[int] = None
user: Optional[str] = None
# doc: begin-classification-pooling-params
# --8<-- [start:classification-pooling-params]
additional_data: Optional[Any] = None
# doc: end-classification-pooling-params
# --8<-- [end:classification-pooling-params]
# doc: begin-classification-extra-params
# --8<-- [start:classification-extra-params]
priority: int = Field(
default=0,
description=(
@@ -1334,7 +1334,7 @@ class ClassificationRequest(OpenAIBaseModel):
"if the served model does not use priority scheduling."),
)
# doc: end-classification-extra-params
# --8<-- [end:classification-extra-params]
def to_pooling_params(self):
return PoolingParams(additional_data=self.additional_data)
@@ -1698,7 +1698,7 @@ class TranscriptionRequest(OpenAIBaseModel):
timestamps incurs additional latency.
"""
# doc: begin-transcription-extra-params
# --8<-- [start:transcription-extra-params]
stream: Optional[bool] = False
"""Custom field not present in the original OpenAI definition. When set,
it will enable output to be streamed in a similar fashion as the Chat
@@ -1707,9 +1707,9 @@ class TranscriptionRequest(OpenAIBaseModel):
# Flattened stream option to simplify form data.
stream_include_usage: Optional[bool] = False
stream_continuous_usage_stats: Optional[bool] = False
# doc: end-transcription-extra-params
# --8<-- [end:transcription-extra-params]
# doc: begin-transcription-sampling-params
# --8<-- [start:transcription-sampling-params]
temperature: float = Field(default=0.0)
"""The sampling temperature, between 0 and 1.
@@ -1743,7 +1743,7 @@ class TranscriptionRequest(OpenAIBaseModel):
presence_penalty: Optional[float] = 0.0
"""The presence penalty to use for sampling."""
# doc: end-transcription-sampling-params
# --8<-- [end:transcription-sampling-params]
# Default sampling parameters for transcription requests.
_DEFAULT_SAMPLING_PARAMS: dict = {