mirror of
https://gitee.com/dify_ai/dify.git
synced 2024-12-02 11:18:19 +08:00
Add model parameter translation (#8509)
Co-authored-by: swingchen01 <swings@126.com> Co-authored-by: 陈长君 <chenchangjun@shuwen.com>
This commit is contained in:
AAEE86
GitHub
parent
740fad06c1
commit
c9f1e18df1
@ -472,12 +472,13 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.TEMPERATURE.value,
|
||||
use_template=DefaultParameterName.TEMPERATURE.value,
|
||||
label=I18nObject(en_US="Temperature"),
|
||||
label=I18nObject(en_US="Temperature", zh_Hans="温度"),
|
||||
type=ParameterType.FLOAT,
|
||||
help=I18nObject(
|
||||
en_US="The temperature of the model. "
|
||||
"Increasing the temperature will make the model answer "
|
||||
"more creatively. (Default: 0.8)"
|
||||
"more creatively. (Default: 0.8)",
|
||||
zh_Hans="模型的温度。增加温度将使模型的回答更具创造性。（默认值：0.8）",
|
||||
),
|
||||
default=0.1,
|
||||
min=0,
|
||||
@ -486,12 +487,13 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.TOP_P.value,
|
||||
use_template=DefaultParameterName.TOP_P.value,
|
||||
label=I18nObject(en_US="Top P"),
|
||||
label=I18nObject(en_US="Top P", zh_Hans="Top P"),
|
||||
type=ParameterType.FLOAT,
|
||||
help=I18nObject(
|
||||
en_US="Works together with top-k. A higher value (e.g., 0.95) will lead to "
|
||||
"more diverse text, while a lower value (e.g., 0.5) will generate more "
|
||||
"focused and conservative text. (Default: 0.9)"
|
||||
"focused and conservative text. (Default: 0.9)",
|
||||
zh_Hans="与top-k一起工作。较高的值（例如，0.95）会导致生成更多样化的文本，而较低的值（例如，0.5）会生成更专注和保守的文本。（默认值：0.9）",
|
||||
),
|
||||
default=0.9,
|
||||
min=0,
|
||||
@ -499,12 +501,13 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name="top_k",
|
||||
label=I18nObject(en_US="Top K"),
|
||||
label=I18nObject(en_US="Top K", zh_Hans="Top K"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Reduces the probability of generating nonsense. "
|
||||
"A higher value (e.g. 100) will give more diverse answers, "
|
||||
"while a lower value (e.g. 10) will be more conservative. (Default: 40)"
|
||||
"while a lower value (e.g. 10) will be more conservative. (Default: 40)",
|
||||
zh_Hans="减少生成无意义内容的可能性。较高的值（例如100）将提供更多样化的答案，而较低的值（例如10）将更为保守。（默认值：40）",
|
||||
),
|
||||
min=1,
|
||||
max=100,
|
||||
@ -516,7 +519,8 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
help=I18nObject(
|
||||
en_US="Sets how strongly to penalize repetitions. "
|
||||
"A higher value (e.g., 1.5) will penalize repetitions more strongly, "
|
||||
"while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)"
|
||||
"while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)",
|
||||
zh_Hans="设置对重复内容的惩罚强度。一个较高的值（例如，1.5）会更强地惩罚重复内容，而一个较低的值（例如，0.9）则会相对宽容。（默认值：1.1）",
|
||||
),
|
||||
min=-2,
|
||||
max=2,
|
||||
@ -524,11 +528,12 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
ParameterRule(
|
||||
name="num_predict",
|
||||
use_template="max_tokens",
|
||||
label=I18nObject(en_US="Num Predict"),
|
||||
label=I18nObject(en_US="Num Predict", zh_Hans="最大令牌数预测"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Maximum number of tokens to predict when generating text. "
|
||||
"(Default: 128, -1 = infinite generation, -2 = fill context)"
|
||||
"(Default: 128, -1 = infinite generation, -2 = fill context)",
|
||||
zh_Hans="生成文本时预测的最大令牌数。（默认值：128，-1 = 无限生成，-2 = 填充上下文）",
|
||||
),
|
||||
default=(512 if int(credentials.get("max_tokens", 4096)) >= 768 else 128),
|
||||
min=-2,
|
||||
@ -536,121 +541,137 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name="mirostat",
|
||||
label=I18nObject(en_US="Mirostat sampling"),
|
||||
label=I18nObject(en_US="Mirostat sampling", zh_Hans="Mirostat 采样"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Enable Mirostat sampling for controlling perplexity. "
|
||||
"(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)"
|
||||
"(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)",
|
||||
zh_Hans="启用 Mirostat 采样以控制困惑度。"
|
||||
"（默认值：0，0 = 禁用，1 = Mirostat，2 = Mirostat 2.0）",
|
||||
),
|
||||
min=0,
|
||||
max=2,
|
||||
),
|
||||
ParameterRule(
|
||||
name="mirostat_eta",
|
||||
label=I18nObject(en_US="Mirostat Eta"),
|
||||
label=I18nObject(en_US="Mirostat Eta", zh_Hans="学习率"),
|
||||
type=ParameterType.FLOAT,
|
||||
help=I18nObject(
|
||||
en_US="Influences how quickly the algorithm responds to feedback from "
|
||||
"the generated text. A lower learning rate will result in slower adjustments, "
|
||||
"while a higher learning rate will make the algorithm more responsive. "
|
||||
"(Default: 0.1)"
|
||||
"(Default: 0.1)",
|
||||
zh_Hans="影响算法对生成文本反馈响应的速度。较低的学习率会导致调整速度变慢，而较高的学习率会使得算法更加灵敏。（默认值：0.1）",
|
||||
),
|
||||
precision=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="mirostat_tau",
|
||||
label=I18nObject(en_US="Mirostat Tau"),
|
||||
label=I18nObject(en_US="Mirostat Tau", zh_Hans="文本连贯度"),
|
||||
type=ParameterType.FLOAT,
|
||||
help=I18nObject(
|
||||
en_US="Controls the balance between coherence and diversity of the output. "
|
||||
"A lower value will result in more focused and coherent text. (Default: 5.0)"
|
||||
"A lower value will result in more focused and coherent text. (Default: 5.0)",
|
||||
zh_Hans="控制输出的连贯性和多样性之间的平衡。较低的值会导致更专注和连贯的文本。（默认值：5.0）",
|
||||
),
|
||||
precision=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="num_ctx",
|
||||
label=I18nObject(en_US="Size of context window"),
|
||||
label=I18nObject(en_US="Size of context window", zh_Hans="上下文窗口大小"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Sets the size of the context window used to generate the next token. (Default: 2048)"
|
||||
en_US="Sets the size of the context window used to generate the next token. (Default: 2048)",
|
||||
zh_Hans="设置用于生成下一个标记的上下文窗口大小。（默认值：2048）",
|
||||
),
|
||||
default=2048,
|
||||
min=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="num_gpu",
|
||||
label=I18nObject(en_US="GPU Layers"),
|
||||
label=I18nObject(en_US="GPU Layers", zh_Hans="GPU 层数"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="The number of layers to offload to the GPU(s). "
|
||||
"On macOS it defaults to 1 to enable metal support, 0 to disable."
|
||||
"As long as a model fits into one gpu it stays in one. "
|
||||
"It does not set the number of GPU(s). "
|
||||
"It does not set the number of GPU(s). ",
|
||||
zh_Hans="加载到 GPU 的层数。在 macOS 上，默认为 1 以启用 Metal 支持，设置为 0 则禁用。"
|
||||
"只要模型适合一个 GPU，它就保留在其中。它不设置 GPU 的数量。",
|
||||
),
|
||||
min=-1,
|
||||
default=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="num_thread",
|
||||
label=I18nObject(en_US="Num Thread"),
|
||||
label=I18nObject(en_US="Num Thread", zh_Hans="线程数"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Sets the number of threads to use during computation. "
|
||||
"By default, Ollama will detect this for optimal performance. "
|
||||
"It is recommended to set this value to the number of physical CPU cores "
|
||||
"your system has (as opposed to the logical number of cores)."
|
||||
"your system has (as opposed to the logical number of cores).",
|
||||
zh_Hans="设置计算过程中使用的线程数。默认情况下，Ollama会检测以获得最佳性能。建议将此值设置为系统拥有的物理CPU核心数（而不是逻辑核心数）。",
|
||||
),
|
||||
min=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="repeat_last_n",
|
||||
label=I18nObject(en_US="Repeat last N"),
|
||||
label=I18nObject(en_US="Repeat last N", zh_Hans="回溯内容"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Sets how far back for the model to look back to prevent repetition. "
|
||||
"(Default: 64, 0 = disabled, -1 = num_ctx)"
|
||||
"(Default: 64, 0 = disabled, -1 = num_ctx)",
|
||||
zh_Hans="设置模型回溯多远的内容以防止重复。（默认值：64，0 = 禁用，-1 = num_ctx）",
|
||||
),
|
||||
min=-1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="tfs_z",
|
||||
label=I18nObject(en_US="TFS Z"),
|
||||
label=I18nObject(en_US="TFS Z", zh_Hans="减少标记影响"),
|
||||
type=ParameterType.FLOAT,
|
||||
help=I18nObject(
|
||||
en_US="Tail free sampling is used to reduce the impact of less probable tokens "
|
||||
"from the output. A higher value (e.g., 2.0) will reduce the impact more, "
|
||||
"while a value of 1.0 disables this setting. (default: 1)"
|
||||
"while a value of 1.0 disables this setting. (default: 1)",
|
||||
zh_Hans="用于减少输出中不太可能的标记的影响。较高的值（例如，2.0）会更多地减少这种影响，而1.0的值则会禁用此设置。（默认值：1）",
|
||||
),
|
||||
precision=1,
|
||||
),
|
||||
ParameterRule(
|
||||
name="seed",
|
||||
label=I18nObject(en_US="Seed"),
|
||||
label=I18nObject(en_US="Seed", zh_Hans="随机数种子"),
|
||||
type=ParameterType.INT,
|
||||
help=I18nObject(
|
||||
en_US="Sets the random number seed to use for generation. Setting this to "
|
||||
"a specific number will make the model generate the same text for "
|
||||
"the same prompt. (Default: 0)"
|
||||
"the same prompt. (Default: 0)",
|
||||
zh_Hans="设置用于生成的随机数种子。将此设置为特定数字将使模型对相同的提示生成相同的文本。（默认值：0）",
|
||||
),
|
||||
),
|
||||
ParameterRule(
|
||||
name="keep_alive",
|
||||
label=I18nObject(en_US="Keep Alive"),
|
||||
label=I18nObject(en_US="Keep Alive", zh_Hans="模型存活时间"),
|
||||
type=ParameterType.STRING,
|
||||
help=I18nObject(
|
||||
en_US="Sets how long the model is kept in memory after generating a response. "
|
||||
"This must be a duration string with a unit (e.g., '10m' for 10 minutes or '24h' for 24 hours)."
|
||||
" A negative number keeps the model loaded indefinitely, and '0' unloads the model"
|
||||
" immediately after generating a response."
|
||||
" Valid time units are 's','m','h'. (Default: 5m)"
|
||||
" Valid time units are 's','m','h'. (Default: 5m)",
|
||||
zh_Hans="设置模型在生成响应后在内存中保留的时间。"
|
||||
"这必须是一个带有单位的持续时间字符串（例如，'10m' 表示10分钟，'24h' 表示24小时）。"
|
||||
"负数表示无限期地保留模型，'0'表示在生成响应后立即卸载模型。"
|
||||
"有效的时间单位有 's'（秒）、'm'（分钟）、'h'（小时）。（默认值：5m）",
|
||||
),
|
||||
),
|
||||
ParameterRule(
|
||||
name="format",
|
||||
label=I18nObject(en_US="Format"),
|
||||
label=I18nObject(en_US="Format", zh_Hans="返回格式"),
|
||||
type=ParameterType.STRING,
|
||||
help=I18nObject(
|
||||
en_US="the format to return a response in. Currently the only accepted value is json."
|
||||
en_US="the format to return a response in. Currently the only accepted value is json.",
|
||||
zh_Hans="返回响应的格式。目前唯一接受的值是json。",
|
||||
),
|
||||
options=["json"],
|
||||
),
|
||||
|
||||
@ -205,7 +205,13 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
||||
parameter_rules=[
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.TEMPERATURE.value,
|
||||
label=I18nObject(en_US="Temperature"),
|
||||
label=I18nObject(en_US="Temperature", zh_Hans="温度"),
|
||||
help=I18nObject(
|
||||
en_US="Kernel sampling threshold. Used to determine the randomness of the results."
|
||||
"The higher the value, the stronger the randomness."
|
||||
"The higher the possibility of getting different answers to the same question.",
|
||||
zh_Hans="核采样阈值。用于决定结果随机性，取值越高随机性越强即相同的问题得到的不同答案的可能性越高。",
|
||||
),
|
||||
type=ParameterType.FLOAT,
|
||||
default=float(credentials.get("temperature", 0.7)),
|
||||
min=0,
|
||||
@ -214,7 +220,13 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.TOP_P.value,
|
||||
label=I18nObject(en_US="Top P"),
|
||||
label=I18nObject(en_US="Top P", zh_Hans="Top P"),
|
||||
help=I18nObject(
|
||||
en_US="The probability threshold of the nucleus sampling method during the generation process."
|
||||
"The larger the value is, the higher the randomness of generation will be."
|
||||
"The smaller the value is, the higher the certainty of generation will be.",
|
||||
zh_Hans="生成过程中核采样方法概率阈值。取值越大，生成的随机性越高；取值越小，生成的确定性越高。",
|
||||
),
|
||||
type=ParameterType.FLOAT,
|
||||
default=float(credentials.get("top_p", 1)),
|
||||
min=0,
|
||||
@ -223,7 +235,12 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.FREQUENCY_PENALTY.value,
|
||||
label=I18nObject(en_US="Frequency Penalty"),
|
||||
label=I18nObject(en_US="Frequency Penalty", zh_Hans="频率惩罚"),
|
||||
help=I18nObject(
|
||||
en_US="For controlling the repetition rate of words used by the model."
|
||||
"Increasing this can reduce the repetition of the same words in the model's output.",
|
||||
zh_Hans="用于控制模型已使用字词的重复率。 提高此项可以降低模型在输出中重复相同字词的重复度。",
|
||||
),
|
||||
type=ParameterType.FLOAT,
|
||||
default=float(credentials.get("frequency_penalty", 0)),
|
||||
min=-2,
|
||||
@ -231,7 +248,12 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.PRESENCE_PENALTY.value,
|
||||
label=I18nObject(en_US="Presence Penalty"),
|
||||
label=I18nObject(en_US="Presence Penalty", zh_Hans="存在惩罚"),
|
||||
help=I18nObject(
|
||||
en_US="Used to control the repetition rate when generating models."
|
||||
"Increasing this can reduce the repetition rate of model generation.",
|
||||
zh_Hans="用于控制模型生成时的重复度。提高此项可以降低模型生成的重复度。",
|
||||
),
|
||||
type=ParameterType.FLOAT,
|
||||
default=float(credentials.get("presence_penalty", 0)),
|
||||
min=-2,
|
||||
@ -239,7 +261,10 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
||||
),
|
||||
ParameterRule(
|
||||
name=DefaultParameterName.MAX_TOKENS.value,
|
||||
label=I18nObject(en_US="Max Tokens"),
|
||||
label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"),
|
||||
help=I18nObject(
|
||||
en_US="Maximum length of tokens for the model response.", zh_Hans="模型回答的tokens的最大长度。"
|
||||
),
|
||||
type=ParameterType.INT,
|
||||
default=512,
|
||||
min=1,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user