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Fix typos

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2025-04-26 14:09:40 +08:00
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33 changed files with 37 additions and 37 deletions
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2
CONTRIBUTING.md
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@@ -70,4 +70,4 @@ def connect_to_next_port(self, minimum: int) -> int:
```
#### Contributing to article & examples
If you have used the agentUniverse project and are satisfied with it, we welcome you to share your case studies in the project community or on any media platform. We will periodically hold community events to commend, encourage, and promote outstanding cases and developers.
If you have used the agentUniverse project and are satisfied with it, we welcome you to share your case studies in the project community or on any media platform. We will periodically hold community events to comment, encourage, and promote outstanding cases and developers.

2
README.md
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@@ -43,7 +43,7 @@ The LLM model integration can be accomplished with simple configuration, current
|<img src="https://github.com/user-attachments/assets/fe265f24-4ea6-4ff2-9b50-58ab6706a5f5" height="25">|BaiChuan|baichuan2-turbo、baichuan2-13b-chat-v1、…|
|<img src="https://github.com/user-attachments/assets/41ffe268-392f-4ab9-b42d-e30dbd70d66b" height="25">|Doubao|Doubao-pro-128k、Doubao-pro-32k、Doubao-lite-128k、…|
For example, to use deepseek model, you can simply set DEEPSEEK_API_KEY value in the custom_key.toml file, and set the llm_model name in the agent configuration file to 'default_deepseek_llm' and you're all set. For more infomation about llm configuration, please refer to [switch-the-llm](https://github.com/agentuniverse-ai/agentUniverse/blob/master/docs/guidebook/en/Get_Start/2.Run_Your_First_Tutorial_Example.md#switch-the-llm).
For example, to use deepseek model, you can simply set DEEPSEEK_API_KEY value in the custom_key.toml file, and set the llm_model name in the agent configuration file to 'default_deepseek_llm' and you're all set. For more information about llm configuration, please refer to [switch-the-llm](https://github.com/agentuniverse-ai/agentUniverse/blob/master/docs/guidebook/en/Get_Start/2.Run_Your_First_Tutorial_Example.md#switch-the-llm).
****************************************

4
README_PYPI.md
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@@ -1,9 +1,9 @@
# agentUniverse
## Overview
agentUniverse is a framework for developing applications powered by multi-agent base on large language model. It provides all the essential components for building a single agent, and a multi-agent collaboration mechanism which serves as a pattern factory that allowing developers to buid and customize multi-agent collaboration patterns. With this framework, developers can easily construct multi-agent applications, and share the pattern practices from different technical and business fields.
agentUniverse is a framework for developing applications powered by multi-agent base on large language model. It provides all the essential components for building a single agent, and a multi-agent collaboration mechanism which serves as a pattern factory that allowing developers to build and customize multi-agent collaboration patterns. With this framework, developers can easily construct multi-agent applications, and share the pattern practices from different technical and business fields.
The framework will come with serveral pre-install multi-agent collaboration patterns which have been proven effective in real business scenarios, and will continue to be enriched in the future. Patterns that are currently about to be released include:
The framework will come with several pre-install multi-agent collaboration patterns which have been proven effective in real business scenarios, and will continue to be enriched in the future. Patterns that are currently about to be released include:
- PEER pattern：
This pattern utilizes four distinct agent roles: Plan, Execute, Express, and Review, to achieve a multi-step breakdown and sequential execution of a complex task. It also performs autonomous iteration based on evaluative feedback which enhancing performance in reasoning and analytical tasks.

4
agentuniverse/agent/template/contextual_iteration_agent_template.py
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@@ -66,7 +66,7 @@ class ContextualIterationAgentTemplate(AgentTemplate):
})
agent_input['chat_history'] = json.dumps(conversation_history, ensure_ascii=False)
# build interation chain
# build iteration chain
continue_prompt: Prompt = super(AgentTemplate, self).process_prompt(
agent_input, prompt_version=self.continue_prompt_version)
continue_chain = continue_prompt.as_langchain() | llm.as_langchain_runnable(
@@ -138,7 +138,7 @@ class ContextualIterationAgentTemplate(AgentTemplate):
agent_input['chat_history'] = json.dumps(conversation_history,
ensure_ascii=False)
# build interation chain
# build iteration chain
continue_prompt: Prompt = super(AgentTemplate, self).process_prompt(
agent_input, prompt_version=self.continue_prompt_version)
continue_chain = continue_prompt.as_langchain() | llm.as_langchain_runnable(

2
agentuniverse/agent_serve/service_instance.py
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@@ -15,7 +15,7 @@ class ServiceInstance(object):
def __init__(self, service_code: str):
"""Initialize a service instance. Raise an ServiceNotFoundError when
service code can't be found by servie manager.
service code can't be found by service manager.
Args:
service_code (`str`):

4
agentuniverse_product/service/util/knowledge_util.py
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@@ -21,7 +21,7 @@ from agentuniverse_product.service.model.knowledge_dto import KnowledgeDTO
def assemble_knowledge_product_config_data(knowledge_dto: KnowledgeDTO) -> Dict:
"""Asemble the knowledge product configuration data.
"""Assemble the knowledge product configuration data.
Args:
knowledge_dto (KnowledgeDTO): The knowledge DTO.
@@ -43,7 +43,7 @@ def assemble_knowledge_product_config_data(knowledge_dto: KnowledgeDTO) -> Dict:
def assemble_knowledge_config(knowledge_dto: KnowledgeDTO) -> Dict:
"""Asemble the knowledge configuration data.
"""Assemble the knowledge configuration data.
Args:
knowledge_dto (KnowledgeDTO): The knowledge DTO object containing the knowledge parameters.

4
au_dir_structure_updater.py
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@@ -190,11 +190,11 @@ def migrate_files(source_root, target_root):
},
{
'source': 'app/bootstrap/product_application.py',
'target': 'boostrap/platform'
'target': 'bootstrap/platform'
},
{
'source': 'app/boostrap/product_application.py',
'target': 'boostrap/platform'
'target': 'bootstrap/platform'
},
{
'source': 'app/bootstrap/server_application.py',

2
docs/guidebook/en/Examples/Translation_Assistant.md
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@@ -45,7 +45,7 @@ The [configuration file](../../../../examples/sample_apps/traslation_agent_app/i
[Translation Of Short Text](../../../../examples/sample_apps/traslation_agent_app/intelligence/test/translation_data/long_text_result.txt)
### Demonstration Results
We can see that using agentUniverse maintains consistency with the results of the orginal translation_agent project, which hasa been successfully replicated.
We can see that using agentUniverse maintains consistency with the results of the original translation_agent project, which hasa been successfully replicated.
agentUniverse Results:
![](../../_picture/long_translation_au.png)

2
docs/guidebook/en/How-to/Guide to Visual Agentic Workflow Platform/Product_Platform_Advancement_Guide.md
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@@ -62,7 +62,7 @@ The operational process is illustrated in the figure below:
## Custom Knowledge Insertion Feature
### Create Custom Knowledge
On the product homepage, naviagte to the Knowledge tab, and click the 'Add Knowledge' button located to the right to create a custom knowledge base.
On the product homepage, navigate to the Knowledge tab, and click the 'Add Knowledge' button located to the right to create a custom knowledge base.
agentUniverse will automatically generate the corresponding knowledge and storage YAML files locally, thereby assisting users in completing their development tasks.

2
docs/guidebook/en/In-Depth_Guides/Components/Tools/Integrated_Tools.md
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@@ -183,7 +183,7 @@ metadata:
```
Parameter Description:
method: the method of the request, such as GET, POST, PUT, etc.
headers: the HTTP headers neccessary for sending the request.
headers: the HTTP headers necessary for sending the request.
json_parse: indicates whether the input parameters should be serialized as JSON and sent in the request body (True for POST requests) or not (False for GET requests, where parameters are typically sent as a query string).
response_content_type: the output format for the HTTP request result. If set to 'json', the result will be returned in JSON format; if set to 'text', it will be returned as plain text.
This tool can be used directly without requiring any keys.

2
docs/guidebook/en/In-Depth_Guides/Tech_Capabilities/Log_And_Monitor/Logging_Utils.md
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@@ -1,6 +1,6 @@
# Logging Utils
The log component of agentUniverse is implemented based on loguru, offering a well-packaged global log component and customizable log components. This tutorial will first introduce the usage of the log configuration file within agentUniverse, then sequentially explain the utilization of the global log component and customizable log components, and finally describe how to intergrate with external log service components.
The log component of agentUniverse is implemented based on loguru, offering a well-packaged global log component and customizable log components. This tutorial will first introduce the usage of the log configuration file within agentUniverse, then sequentially explain the utilization of the global log component and customizable log components, and finally describe how to integrate with external log service components.
## Log Configuration

2
docs/guidebook/en/In-Depth_Guides/Tech_Capabilities/Service/gRPC.md
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@@ -10,7 +10,7 @@ max_workers = 10
server_port = 50051
```
- **activate**: The gRPC server will only start when this value is set to `true`.
- **max_workers**: TThe maximum number of threads in the gRPC server thread pool, with a default of 10.
- **max_workers**: The maximum number of threads in the gRPC server thread pool, with a default of 10.
- **server_port**: The service port of the gRPC server, with a default of 50051.
And then，proceed to start the gRPC server:

2
docs/guidebook/en/In-Depth_Guides/Tech_Capabilities/Storage/SQLDB_WRAPPER.md
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@@ -11,7 +11,7 @@ agentUniverse automatically registers SQLDBWrapper configuration files by scanni
default = ['default_scan_path']
sqldb_wrapper = ['sqldb_wrapper_scan_path']
```
By default, AgentUniverse scans all paths under either `default` or `sqldb_wrapper`sections in the configurtion, with paths under `sqldb_wrapper` having a higher priority than those under `default`.
By default, AgentUniverse scans all paths under either `default` or `sqldb_wrapper`sections in the configuration, with paths under `sqldb_wrapper` having a higher priority than those under `default`.
### Step Two: Configuration File

2
docs/guidebook/en/In-Depth_Guides/Tutorials/Agent/Agent_Create_And_Use.md
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@@ -13,7 +13,7 @@ We will provide detailed descriptions of each component within the configuration
### Setting the basic information of the agent.
**`info` - basic information of the agent**
* `name`: the name of the agent
* `description`: a description of the agent's purpose or funtion
* `description`: a description of the agent's purpose or function
### Setting the global configurations for the agent.
**`profile` - Agent global settings.**

2
docs/guidebook/zh/In-Depth_Guides/原理介绍/知识/Store.md
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@@ -54,7 +54,7 @@ class Store(ComponentBase):
```
- `_new_client`和`_new_async_client`用于创建数据库链接，在组件注册阶段会被添加到[post_fork](../../技术组件/服务化/Web_Server.md)执行列表中，保证创建的数据库连接在Gunicorn模式下的子进程中是独立的。
- `query`函数是知识组件在查询时调用的函数，负责根据传入的Query实例在store中查找相关的内容并以document的形式返回
- `Store`的还包括对`Docuemnt`类型数据的增删改查，作为知识存储的管理接口。
- `Store`的还包括对`Document`类型数据的增删改查，作为知识存储的管理接口。
在编写完对应代码后，可以参考下面的yaml将你的Store注册为aU组件：
```yaml

2
examples/sample_apps/basic_sop_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/data_agent_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/difizen_app/config/custom_key.toml.sample
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@@ -67,7 +67,7 @@ GOOGLE_PROXY=''
#Google search
SERPER_API_KEY=''
#bing seacrh
#bing search
BING_SUBSCRIPTION_KEY=''
#search.io api

2
examples/sample_apps/discussion_group_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/multimodal_app/config/custom_key.toml.sample
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@@ -45,7 +45,7 @@ example_key = 'AnExampleKey'
#Google search
#SERPER_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'
#
# You could sign up for a free account at https://www.searchapi.io/

2
examples/sample_apps/openai_protocol_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/peer_agent_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/rag_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/react_agent_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/traslation_agent_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_apps/workflow_agent_app/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/sample_standard_app/config/custom_key.toml.sample
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@@ -67,7 +67,7 @@ GOOGLE_PROXY=''
#Google search
SERPER_API_KEY=''
#bing seacrh
#bing search
BING_SUBSCRIPTION_KEY=''
#search.io api

2
examples/startup_app/demo_startup_app_with_agent_templates/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/startup_app/demo_startup_app_with_multi_agents/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/startup_app/demo_startup_app_with_single_agent/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/startup_app/demo_startup_app_with_single_agent_and_actions/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
examples/startup_app/demo_startup_app_with_single_agent_and_memory/config/custom_key.toml.sample
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@@ -42,5 +42,5 @@ example_key = 'AnExampleKey'
##search api
#SEARCHAPI_API_KEY='xxxxxx'
#
##bing seacrh
##bing search
#BING_SUBSCRIPTION_KEY='xxxxxx'

2
tests/test_agentuniverse/unit/agent/config.toml
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@@ -31,5 +31,5 @@ gunicorn_config_path = './gunicorn_config.toml'
#custom_key_path = './custom_key.toml'
[DB]
# A mysql db uri used to save web request task status. Status will be saved in sqllite if the uri is empty all not exist.
# A mysql db uri used to save web request task status. Status will be saved in sqlite if the uri is empty all not exist.
system_db_uri = ''