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Merge branch 'main' into feat/plugin

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Yeuoly 2024-08-30 18:21:22 +08:00
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11 changed files with 102 additions and 21 deletions
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7
api/commands.py
View File

@ -559,8 +559,9 @@ def add_qdrant_doc_id_index(field: str):
@click.command("create-tenant", help="Create account and tenant.")
@click.option("--email", prompt=True, help="The email address of the tenant account.")
@click.option("--name", prompt=True, help="The workspace name of the tenant account.")
@click.option("--language", prompt=True, help="Account language, default: en-US.")
def create_tenant(email: str, language: Optional[str] = None):
def create_tenant(email: str, language: Optional[str] = None, name: Optional[str] = None):
"""
Create tenant account
"""
@ -580,13 +581,15 @@ def create_tenant(email: str, language: Optional[str] = None):
if language not in languages:
language = "en-US"
name = name.strip()
# generate random password
new_password = secrets.token_urlsafe(16)
# register account
account = RegisterService.register(email=email, name=account_name, password=new_password, language=language)
TenantService.create_owner_tenant_if_not_exist(account)
TenantService.create_owner_tenant_if_not_exist(account, name)
click.echo(
click.style(

1
api/controllers/console/explore/installed_app.py
View File

@ -35,6 +35,7 @@ class InstalledAppsListApi(Resource):
"uninstallable": current_tenant_id == installed_app.app_owner_tenant_id,
}
for installed_app in installed_apps
if installed_app.app is not None
]
installed_apps.sort(
key=lambda app: (

4
api/core/model_runtime/model_providers/openai_api_compatible/llm/llm.py
View File

@ -150,9 +150,9 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
except json.JSONDecodeError as e:
raise CredentialsValidateFailedError('Credentials validation failed: JSON decode error')
if (completion_type is LLMMode.CHAT and json_result['object'] == ''):
if (completion_type is LLMMode.CHAT and json_result.get('object','') == ''):
json_result['object'] = 'chat.completion'
elif (completion_type is LLMMode.COMPLETION and json_result['object'] == ''):
elif (completion_type is LLMMode.COMPLETION and json_result.get('object','') == ''):
json_result['object'] = 'text_completion'
if (completion_type is LLMMode.CHAT

39
api/core/model_runtime/model_providers/zhipuai/llm/glm_4_plus.yaml Normal file
View File

@ -0,0 +1,39 @@
model: glm-4-plus
label:
en_US: glm-4-plus
model_type: llm
features:
- multi-tool-call
- agent-thought
- stream-tool-call
model_properties:
mode: chat
parameter_rules:
- name: temperature
use_template: temperature
default: 0.95
min: 0.0
max: 1.0
help:
zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
- name: top_p
use_template: top_p
default: 0.7
help:
zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
- name: incremental
label:
zh_Hans: 增量返回
en_US: Incremental
type: boolean
help:
zh_Hans: SSE接口调用时，用于控制每次返回内容方式是增量还是全量，不提供此参数时默认为增量返回，true 为增量返回，false 为全量返回。
en_US: When the SSE interface is called, it is used to control whether the content is returned incrementally or in full. If this parameter is not provided, the default is incremental return. true means incremental return, false means full return.
required: false
- name: max_tokens
use_template: max_tokens
default: 1024
min: 1
max: 8192

37
api/core/model_runtime/model_providers/zhipuai/llm/glm_4v_plus.yaml Normal file
View File

@ -0,0 +1,37 @@
model: glm-4v-plus
label:
en_US: glm-4v-plus
model_type: llm
model_properties:
mode: chat
features:
- vision
parameter_rules:
- name: temperature
use_template: temperature
default: 0.95
min: 0.0
max: 1.0
help:
zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
- name: top_p
use_template: top_p
default: 0.7
help:
zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
- name: incremental
label:
zh_Hans: 增量返回
en_US: Incremental
type: boolean
help:
zh_Hans: SSE接口调用时，用于控制每次返回内容方式是增量还是全量，不提供此参数时默认为增量返回，true 为增量返回，false 为全量返回。
en_US: When the SSE interface is called, it is used to control whether the content is returned incrementally or in full. If this parameter is not provided, the default is incremental return. true means incremental return, false means full return.
required: false
- name: max_tokens
use_template: max_tokens
default: 1024
min: 1
max: 8192

9
api/core/model_runtime/model_providers/zhipuai/llm/llm.py
View File

@ -153,7 +153,8 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
:return: full response or stream response chunk generator result
"""
extra_model_kwargs = {}
if stop:
# request to glm-4v-plus with stop words will always response "finish_reason":"network_error"
if stop and model!= 'glm-4v-plus':
extra_model_kwargs['stop'] = stop
client = ZhipuAI(
@ -174,7 +175,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
if copy_prompt_message.role in [PromptMessageRole.USER, PromptMessageRole.SYSTEM, PromptMessageRole.TOOL]:
if isinstance(copy_prompt_message.content, list):
# check if model is 'glm-4v'
if model != 'glm-4v':
if model not in ('glm-4v', 'glm-4v-plus'):
# not support list message
continue
# get image and
@ -207,7 +208,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
else:
new_prompt_messages.append(copy_prompt_message)
if model == 'glm-4v':
if model == 'glm-4v' or model == 'glm-4v-plus':
params = self._construct_glm_4v_parameter(model, new_prompt_messages, model_parameters)
else:
params = {
@ -304,7 +305,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
return params
def _construct_glm_4v_messages(self, prompt_message: Union[str | list[PromptMessageContent]]) -> list[dict]:
def _construct_glm_4v_messages(self, prompt_message: Union[str, list[PromptMessageContent]]) -> list[dict]:
if isinstance(prompt_message, str):
return [{'type': 'text', 'text': prompt_message}]

5
api/services/account_service.py
View File

@ -265,7 +265,7 @@ class TenantService:
return tenant
@staticmethod
def create_owner_tenant_if_not_exist(account: Account):
def create_owner_tenant_if_not_exist(account: Account, name: Optional[str] = None):
"""Create owner tenant if not exist"""
available_ta = (
TenantAccountJoin.query.filter_by(account_id=account.id).order_by(TenantAccountJoin.id.asc()).first()
@ -274,6 +274,9 @@ class TenantService:
if available_ta:
return
if name:
tenant = TenantService.create_tenant(name)
else:
tenant = TenantService.create_tenant(f"{account.name}'s Workspace")
TenantService.create_tenant_member(tenant, account, role="owner")
account.current_tenant = tenant

2
web/app/components/datasets/common/retrieval-param-config/index.tsx
View File

@ -191,7 +191,7 @@ const RetrievalParamConfig: FC<Props> = ({
<div className='truncate'>{option.label}</div>
<Tooltip
popupContent={<div className='w-[200px]'>{option.tips}</div>}
triggerClassName='ml-0.5 w-3.5 h-4.5'
triggerClassName='ml-0.5 w-3.5 h-3.5'
/>
</div>
))

13
web/app/components/header/account-setting/model-provider-page/system-model-selector/index.tsx
View File

@ -148,7 +148,7 @@ const SystemModel: FC<SystemModelSelectorProps> = ({
{t('common.modelProvider.systemReasoningModel.tip')}
</div>
}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4 shrink-0'
/>
</div>
<div>
@ -168,8 +168,7 @@ const SystemModel: FC<SystemModelSelectorProps> = ({
{t('common.modelProvider.embeddingModel.tip')}
</div>
}
needsDelay={false}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4 shrink-0'
/>
</div>
<div>
@ -189,8 +188,7 @@ const SystemModel: FC<SystemModelSelectorProps> = ({
{t('common.modelProvider.rerankModel.tip')}
</div>
}
needsDelay={false}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4 shrink-0'
/>
</div>
<div>
@ -210,8 +208,7 @@ const SystemModel: FC<SystemModelSelectorProps> = ({
{t('common.modelProvider.speechToTextModel.tip')}
</div>
}
needsDelay={false}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4 shrink-0'
/>
</div>
<div>
@ -231,7 +228,7 @@ const SystemModel: FC<SystemModelSelectorProps> = ({
{t('common.modelProvider.ttsModel.tip')}
</div>
}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4 shrink-0'
/>
</div>
<div>

2
web/app/components/tools/edit-custom-collection-modal/config-credentials.tsx
View File

@ -114,7 +114,7 @@ const ConfigCredential: FC<Props> = ({
{t('tools.createTool.authMethod.keyTooltip')}
</div>
}
triggerClassName='ml-0.5'
triggerClassName='ml-0.5 w-4 h-4'
/>
</div>
<input

2
web/i18n/zh-Hans/workflow.ts
View File

@ -80,7 +80,7 @@ const translation = {
},
env: {
envPanelTitle: '环境变量',
envDescription: '环境变量是一种存储敏感信息的方法，如 API 密钥、数据库密码等。它们被存储在工作流程中，而不是代码中，以便在不同环墋中共享。',
envDescription: '环境变量是一种存储敏感信息的方法，如 API 密钥、数据库密码等。它们被存储在工作流程中，而不是代码中，以便在不同环境中共享。',
envPanelButton: '添加环境变量',
modal: {
title: '添加环境变量',