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Fix/typos (#2308)

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This commit is contained in:
Ricky
2024-01-31 11:58:07 +08:00
committed by GitHub
parent 9e37702d24
commit 2660fbaa20
58 changed files with 312 additions and 312 deletions
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26
api/core/tools/docs/zh_Hans/advanced_scale_out.md
View File

@@ -125,7 +125,7 @@ from openai import OpenAI
class DallE3Tool(BuiltinTool):
def _invoke(self,
user_id: str,
tool_paramters: Dict[str, Any],
tool_parameters: Dict[str, Any],
) -> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
"""
invoke tools
@@ -135,7 +135,7 @@ class DallE3Tool(BuiltinTool):
)
# prompt
prompt = tool_paramters.get('prompt', '')
prompt = tool_parameters.get('prompt', '')
if not prompt:
return self.create_text_message('Please input prompt')
@@ -163,7 +163,7 @@ class DallE3Tool(BuiltinTool):
```python
from core.tools.tool.builtin_tool import BuiltinTool
from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParamter
from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
from core.tools.errors import ToolProviderCredentialValidationError
from typing import Any, Dict, List, Union
@@ -171,20 +171,20 @@ from httpx import post
from base64 import b64decode
class VectorizerTool(BuiltinTool):
def _invoke(self, user_id: str, tool_paramters: Dict[str, Any]) \
def _invoke(self, user_id: str, tool_parameters: Dict[str, Any]) \
-> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
"""
工具调用，图片变量名需要从这里传递进来，从而我们就可以从变量池中获取到图片
"""
def get_runtime_parameters(self) -> List[ToolParamter]:
def get_runtime_parameters(self) -> List[ToolParameter]:
"""
重写工具参数列表，我们可以根据当前变量池里的实际情况来动态生成参数列表，从而LLM可以根据参数列表来生成表单
"""
def is_tool_avaliable(self) -> bool:
def is_tool_available(self) -> bool:
"""
当前工具是否可用，如果当前变量池中没有图片，那么我们就不需要展示这个工具，这里返回False即可
"""
@@ -194,7 +194,7 @@ class VectorizerTool(BuiltinTool):
```python
from core.tools.tool.builtin_tool import BuiltinTool
from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParamter
from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
from core.tools.errors import ToolProviderCredentialValidationError
from typing import Any, Dict, List, Union
@@ -202,7 +202,7 @@ from httpx import post
from base64 import b64decode
class VectorizerTool(BuiltinTool):
def _invoke(self, user_id: str, tool_paramters: Dict[str, Any]) \
def _invoke(self, user_id: str, tool_parameters: Dict[str, Any]) \
-> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
"""
invoke tools
@@ -214,7 +214,7 @@ class VectorizerTool(BuiltinTool):
raise ToolProviderCredentialValidationError('Please input api key name and value')
# 获取image_id，image_id的定义可以在get_runtime_parameters中找到
image_id = tool_paramters.get('image_id', '')
image_id = tool_parameters.get('image_id', '')
if not image_id:
return self.create_text_message('Please input image id')
@@ -241,24 +241,24 @@ class VectorizerTool(BuiltinTool):
meta={'mime_type': 'image/svg+xml'})
]
def get_runtime_parameters(self) -> List[ToolParamter]:
def get_runtime_parameters(self) -> List[ToolParameter]:
"""
override the runtime parameters
"""
# 这里，我们重写了工具参数列表，定义了image_id，并设置了它的选项列表为当前变量池中的所有图片，这里的配置与yaml中的配置是一致的
return [
ToolParamter.get_simple_instance(
ToolParameter.get_simple_instance(
name='image_id',
llm_description=f'the image id that you want to vectorize, \
and the image id should be specified in \
{[i.name for i in self.list_default_image_variables()]}',
type=ToolParamter.ToolParameterType.SELECT,
type=ToolParameter.ToolParameterType.SELECT,
required=True,
options=[i.name for i in self.list_default_image_variables()]
)
]
def is_tool_avaliable(self) -> bool:
def is_tool_available(self) -> bool:
# 只有当变量池中有图片时，LLM才需要使用这个工具
return len(self.list_default_image_variables()) > 0
```

10
api/core/tools/docs/zh_Hans/tool_scale_out.md
View File

@@ -146,13 +146,13 @@ from typing import Any, Dict, List, Union
class GoogleSearchTool(BuiltinTool):
def _invoke(self,
user_id: str,
tool_paramters: Dict[str, Any],
tool_parameters: Dict[str, Any],
) -> Union[ToolInvokeMessage, List[ToolInvokeMessage]]:
"""
invoke tools
"""
query = tool_paramters['query']
result_type = tool_paramters['result_type']
query = tool_parameters['query']
result_type = tool_parameters['result_type']
api_key = self.runtime.credentials['serpapi_api_key']
# TODO: search with serpapi
result = SerpAPI(api_key).run(query, result_type=result_type)
@@ -163,7 +163,7 @@ class GoogleSearchTool(BuiltinTool):
```
### 参数
工具的整体逻辑都在`_invoke`方法中，这个方法接收两个参数：`user_id`和`tool_paramters`，分别表示用户ID和工具参数
工具的整体逻辑都在`_invoke`方法中，这个方法接收两个参数：`user_id`和`tool_parameters`，分别表示用户ID和工具参数
### 返回数据
在工具返回时，你可以选择返回一个消息或者多个消息，这里我们返回一个消息，使用`create_text_message`和`create_link_message`可以创建一个文本消息或者一个链接消息。
@@ -195,7 +195,7 @@ class GoogleProvider(BuiltinToolProviderController):
}
).invoke(
user_id='',
tool_paramters={
tool_parameters={
"query": "test",
"result_type": "link"
},