[Docs] add request params (#5207)

* [BugFix] rollback  max_tokens and min_tokens when continue to infer

* [BugFix] rollback  max_tokens and min_tokens when continue to infer

* [fix] add more logger info:  max_tokens

* [Docs] add request params

---------

Co-authored-by: liqinrui <liqinrui@baidu.com>
This commit is contained in:
LiqinruiG
2025-11-26 15:04:22 +08:00
committed by GitHub
parent cead6b26fa
commit df427ba06d
2 changed files with 159 additions and 0 deletions

View File

@@ -130,6 +130,17 @@ user: Optional[str] = None
metadata: Optional[dict] = None
# Additional metadata, used for passing custom information (such as request ID, debug markers, etc.).
n: Optional[int] = 1
# Number of candidate outputs to generate (i.e., return multiple independent text completions). Default 1 (return only one result).
seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
# Random seed for controlling deterministic generation (same seed + input yields identical results).
# Must be in range `[0, 922337203685477580]`. Default None means no fixed seed.
stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
# Stop generation conditions - can be a single string or list of strings.
# Generation terminates when any stop string is produced (default empty list means disabled).
```
### Additional Parameters Added by FastDeploy
@@ -160,6 +171,11 @@ bad_words_token_ids: Optional[List[int]] = None
repetition_penalty: Optional[float] = None
# Repetition penalty coefficient, reducing the probability of repeating already generated tokens (`>1.0` suppresses repetition, `<1.0` encourages repetition, default None means disabled).
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
# Stop generation token IDs - list of token IDs that trigger early termination when generated.
# Typically used alongside `stop` for complementary stopping conditions (default empty list means disabled).
```
The following extra parameters are supported:
@@ -202,6 +218,19 @@ temp_scaled_logprobs: Optional[bool] = False
top_p_normalized_logprobs: Optional[bool] = False
# Whether to perform top-p normalization when calculating logprobs (default is False, indicating that top-p normalization is not performed).
include_draft_logprobs: Optional[bool] = False
# Whether to return log probabilities during draft stages (e.g., pre-generation or intermediate steps)
# for debugging or analysis of the generation process (default False means not returned).
logits_processors_args: Optional[Dict] = None
# Additional arguments for logits processors, enabling customization of generation logic
# (e.g., dynamically adjusting probability distributions).
mm_hashes: Optional[list] = None
# Hash values for multimodal (e.g., image/audio) inputs, used for verification or tracking.
# Default None indicates no multimodal input or hash validation required.
```
### Differences in Return Fields
@@ -351,6 +380,39 @@ max_tokens: Optional[int] = None
presence_penalty: Optional[float] = None
# Presence penalty coefficient, reducing the probability of generating new topics (unseen topics) (`>1.0` suppresses new topics, `<1.0` encourages new topics).
echo: Optional[bool] = False
# Whether to include the input prompt in the generated output (default: `False`, i.e., exclude the prompt).
n: Optional[int] = 1
# Number of candidate outputs to generate (i.e., return multiple independent text completions). Default 1 (return only one result).
seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
# Random seed for controlling deterministic generation (same seed + input yields identical results).
# Must be in range `[0, 922337203685477580]`. Default None means no fixed seed.
stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
# Stop generation conditions - can be a single string or list of strings.
# Generation terminates when any stop string is produced (default empty list means disabled).
stream: Optional[bool] = False
# Whether to enable streaming output (return results token by token), default `False` (returns complete results at once).
stream_options: Optional[StreamOptions] = None
# Additional configurations for streaming output (such as chunk size, timeout, etc.), refer to the specific definition of `StreamOptions`.
temperature: Optional[float] = None
# Temperature coefficient, controlling generation randomness (`0.0` for deterministic generation, `>1.0` for more randomness, default `None` uses model default).
top_p: Optional[float] = None
# Nucleus sampling threshold, only retaining tokens whose cumulative probability exceeds `top_p` (default `None` disables).
response_format: Optional[AnyResponseFormat] = None
# Specifies the output format (such as JSON, XML, etc.), requires passing a predefined format configuration object.
user: Optional[str] = None
# User identifier, used for tracking or distinguishing requests from different users (default `None` does not pass).
```
### Additional Parameters Added by FastDeploy
@@ -379,6 +441,10 @@ bad_words: Optional[List[str]] = None
bad_words_token_ids: Optional[List[int]] = None
# List of forbidden token ids that the model should avoid generating (default None means no restriction).
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
# Stop generation token IDs - list of token IDs that trigger early termination when generated.
# Typically used alongside `stop` for complementary stopping conditions (default empty list means disabled).
repetition_penalty: Optional[float] = None
# Repetition penalty coefficient, reducing the probability of repeating already generated tokens (`>1.0` suppresses repetition, `<1.0` encourages repetition, default None means disabled).
```
@@ -402,6 +468,25 @@ return_token_ids: Optional[bool] = None
prompt_token_ids: Optional[List[int]] = None
# Directly passes the token ID list of the prompt, skipping the text encoding step (default None means using text input).
temp_scaled_logprobs: Optional[bool] = False
# Whether to divide the logits by the temperature coefficient when calculating logprobs (default is False, meaning the logits are not divided by the temperature coefficient).
top_p_normalized_logprobs: Optional[bool] = False
# Whether to perform top-p normalization when calculating logprobs (default is False, indicating that top-p normalization is not performed).
include_draft_logprobs: Optional[bool] = False
# Whether to return log probabilities during draft stages (e.g., pre-generation or intermediate steps)
# for debugging or analysis of the generation process (default False means not returned).
logits_processors_args: Optional[Dict] = None
# Additional arguments for logits processors, enabling customization of generation logic
# (e.g., dynamically adjusting probability distributions).
mm_hashes: Optional[list] = None
# Hash values for multimodal (e.g., image/audio) inputs, used for verification or tracking.
# Default None indicates no multimodal input or hash validation required.
```
### Overview of Return Parameters

View File

@@ -130,6 +130,15 @@ user: Optional[str] = None
metadata: Optional[dict] = None
# 附加元数据,用于传递自定义信息(如请求 ID、调试标记等
n: Optional[int] = 1
# 生成结果的候选数量(即返回多少个独立生成的文本),默认 1仅返回一个结果
seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
# 随机种子,用于控制生成过程的确定性(相同种子和输入会得到相同结果)。范围需在 `[0, 922337203685477580]` 之间,默认 None 表示不固定种子。
stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
# 停止生成的条件,可以是单个字符串或字符串列表。当模型生成任一停止字符串时,生成过程会提前终止(默认空列表表示不启用)。
```
### FastDeploy 增加额外参数
@@ -160,6 +169,10 @@ bad_words_token_ids: Optional[List[int]] = None
repetition_penalty: Optional[float] = None
# 重复惩罚系数,降低已生成 token 的重复概率(>1.0 抑制重复,<1.0 鼓励重复,默认 None 表示禁用)。
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
# 停止生成的 token ID 列表,当模型生成任一指定 token 时,生成过程会提前终止(默认空列表表示不启用)。通常与 `stop` 参数互补使用。
```
其他参数的支持如下:
```python
@@ -201,6 +214,16 @@ temp_scaled_logprobs: Optional[bool] = False
top_p_normalized_logprobs: Optional[bool] = False
# 计算logprob时是否进行 top_p 归一化(默认 False 表示不进行top_p归一化
include_draft_logprobs: Optional[bool] = False
# 是否在预生成或中间步骤返回对数概率log probabilities用于调试或分析生成过程默认 False 表示不返回)。
logits_processors_args: Optional[Dict] = None
# 传递给 logits 处理器logits processors的额外参数用于自定义生成过程中的逻辑如动态调整概率分布
mm_hashes: Optional[list] = None
# 多模态multimodal输入的哈希值列表用于验证或跟踪输入内容如图像、音频等。默认 None 表示无多模态输入或无需哈希验证。
```
### 返回字段差异
@@ -350,6 +373,37 @@ max_tokens: Optional[int] = None
presence_penalty: Optional[float] = None
# 存在惩罚系数,降低新主题(未出现过的话题)的生成概率(`>1.0` 抑制新话题,`<1.0` 鼓励新话题)。
echo: Optional[bool] = False
# 是否将输入的 prompt 包含在输出中(默认 False即不输出 prompt
n: Optional[int] = 1
# 生成结果的候选数量(即返回多少个独立生成的文本),默认 1仅返回一个结果
seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
# 随机种子,用于控制生成过程的确定性(相同种子和输入会得到相同结果)。范围需在 `[0, 922337203685477580]` 之间,默认 None 表示不固定种子。
stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
# 停止生成的条件,可以是单个字符串或字符串列表。当模型生成任一停止字符串时,生成过程会提前终止(默认空列表表示不启用)。
stream: Optional[bool] = False
# 是否启用流式输出(逐 token 返回结果),默认 `False`(一次性返回完整结果)。
stream_options: Optional[StreamOptions] = None
# 流式输出的额外配置(如分块大小、超时等),需参考 `StreamOptions` 的具体定义。
temperature: Optional[float] = None
# 温度系数,控制生成随机性(`0.0` 确定性生成,`>1.0` 更随机,默认 `None` 使用模型默认值)。
top_p: Optional[float] = None
# 核采样nucleus sampling阈值只保留概率累计超过 `top_p` 的 token默认 `None` 禁用)。
response_format: Optional[AnyResponseFormat] = None
# 指定输出格式(如 JSON、XML 等),需传入预定义的格式配置对象。
user: Optional[str] = None
# 用户标识符,用于跟踪或区分不同用户的请求(默认 `None` 不传递)。
```
### FastDeploy 增加额外参数
@@ -375,6 +429,12 @@ include_stop_str_in_output: Optional[bool] = False
bad_words: Optional[List[str]] = None
# 禁止生成的词汇列表(例如敏感词),模型会避免输出这些词(默认 None 表示不限制)。
bad_words_token_ids: Optional[List[int]] = None
# 禁止生成的token id列表模型会避免输出这些词默认 None 表示不限制)。
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
# 停止生成的 token ID 列表,当模型生成任一指定 token 时,生成过程会提前终止(默认空列表表示不启用)。通常与 `stop` 参数互补使用。
repetition_penalty: Optional[float] = None
# 重复惩罚系数,降低已生成 token 的重复概率(>1.0 抑制重复,<1.0 鼓励重复,默认 None 表示禁用)。
```
@@ -398,6 +458,20 @@ return_token_ids: Optional[bool] = None
prompt_token_ids: Optional[List[int]] = None
# 直接传入 prompt 的 token ID 列表,跳过文本编码步骤(默认 None 表示使用文本输入)。
temp_scaled_logprobs: Optional[bool] = False
# 计算logprob时是否对logits除以温度系数默认 False 表示不除以温度系数)。
top_p_normalized_logprobs: Optional[bool] = False
# 计算logprob时是否进行 top_p 归一化(默认 False 表示不进行top_p归一化
include_draft_logprobs: Optional[bool] = False
# 是否在预生成或中间步骤返回对数概率log probabilities用于调试或分析生成过程默认 False 表示不返回)。
logits_processors_args: Optional[Dict] = None
# 传递给 logits 处理器logits processors的额外参数用于自定义生成过程中的逻辑如动态调整概率分布
mm_hashes: Optional[list] = None
# 多模态multimodal输入的哈希值列表用于验证或跟踪输入内容如图像、音频等。默认 None 表示无多模态输入或无需哈希验证。
```
### 返回参数总览