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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/en_US/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 @@ Next, we use Vectorizer.AI to convert the PNG icon generated by DallE3 into a ve
```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]]:
"""
Tool invocation, the image variable name needs to be passed in from here, so that we can get the image from the variable pool
"""
def get_runtime_parameters(self) -> List[ToolParamter]:
def get_runtime_parameters(self) -> List[ToolParameter]:
"""
Override the tool parameter list, we can dynamically generate the parameter list based on the actual situation in the current variable pool, so that the LLM can generate the form based on the parameter list
"""
def is_tool_avaliable(self) -> bool:
def is_tool_available(self) -> bool:
"""
Whether the current tool is available, if there is no image in the current variable pool, then we don't need to display this tool, just return False here
"""
@@ -194,7 +194,7 @@ Next, let's implement these three functions
```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')
# Get image_id, the definition of image_id can be found in get_runtime_parameters
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
"""
# Here, we override the tool parameter list, define the image_id, and set its option list to all images in the current variable pool. The configuration here is consistent with the configuration in yaml.
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:
# Only when there are images in the variable pool, the LLM needs to use this tool
return len(self.list_default_image_variables()) > 0
```

10
api/core/tools/docs/en_US/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):
```
### Parameters
The overall logic of the tool is in the `_invoke` method, this method accepts two parameters: `user_id` and `tool_paramters`, which represent the user ID and tool parameters respectively
The overall logic of the tool is in the `_invoke` method, this method accepts two parameters: `user_id` and `tool_parameters`, which represent the user ID and tool parameters respectively
### Return Data
When the tool returns, you can choose to return one message or multiple messages, here we return one message, using `create_text_message` and `create_link_message` can create a text message or a link message.
@@ -195,7 +195,7 @@ class GoogleProvider(BuiltinToolProviderController):
}
).invoke(
user_id='',
tool_paramters={
tool_parameters={
"query": "test",
"result_type": "link"
},

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"
},