Merge pull request #20 from alipay/dev

feat: release version 0.0.5

CHANGELOG.md

@@ -19,10 +19,23 @@ Deprecated - Soon to be deprecated features.
 Removed - Features removed in this version.
 Fixed - Any bug fixes.
 Security - Patches and security improvements.
+Note - Additional remarks regarding the version.
 
 ***************************************************
 
 # Version Update History
+## [0.0.5] - 2024-05-08
+### Added
+- The LLM component supports streaming calls.
+- The Knowledge component has an added update definition.
+
+### Fixed
+- Fixed potential concurrency safety issues in the peer planner.
+- Fixed the issue in version 0.0.4 of the PyPI package where the packaging method forced users to enter an AK upon startup.
+
+### Note 
+- Some code optimizations and documentation updates.
+
 ## [0.0.4] - 2024-04-26
 ### Added
 - Add version management capability to the prompt.
@@ -32,6 +45,9 @@ Security - Patches and security improvements.
   * Due to compatibility issues of Gunicorn with Windows systems, automatically identify the kernel version to select the web startup method.
   * Specified YAML reading as UTF-8 encoding method.
 
+### Note
+- [2024-05-08] Please be aware that the PyPI package version 0.0.4 includes the sample_standard_app example project by default. This will reference additional components from sample_standard_app at startup and require users to input an AK. If you are not using the corresponding components, you can bypass this restriction by using a mock AK. This issue has been fixed in version 0.0.5.
+
 ## [0.0.3] - 2024-04-19
 ### Init
 - The official release version of AgentUniverse has been initialized. Enjoy using it!

CHANGELOG_zh.md

@@ -19,10 +19,23 @@ Deprecated - 即将废弃的功能。
 Removed - 现版本中移除的功能。
 Fixed - 任何错误修复。
 Security - 补丁与安全改进。
+Note - 对于版本的额外说明。
 
 ***************************************************
 
 # 版本更新记录
+## [0.0.5] - 2024-05-08
+### Added
+- LLM组件支持流式调用
+- 知识组件添加update定义
+
+### Fixed
+- 修复peer planner中可能存在的并发安全性隐患
+- 修复0.0.4版本中pypi package打包方式导致启动强制要求用户填写AK问题
+
+### Note 
+- 追加部分代码优化与文档更新
+
 ## [0.0.4] - 2024-04-26
 ### Added
 - 新增prompt版本管理能力
@@ -31,6 +44,8 @@ Security - 补丁与安全改进。
 - Windows版本下的兼容问题修复
   * 由于Gunicore对于windows系统的兼容问题，自动识别内核版本自动选择web启动方式
   * yaml读取指定为utf-8 encode方式
+### Note 
+- [2024-05-08] 注意，0.0.4的pypi package版本中默认包含了sample_standard_app示例工程, 这将会在启动时引用sample_standard_app中的额外组件,并要求用户填写AK, 若您没有使用对应组件可以通过mock ak跳过这一限制, 这已经在0.0.5版本中修复。
 
 ## [0.0.3] - 2024-04-19
 ### Init

MANIFEST.in

@@ -0,0 +1,13 @@
+include CHANGELOG.md
+include CHANGELOG_zh.md
+include LICENSE
+include README.md
+include README_zh.md
+include requirements.txt
+include MANIFEST.in
+recursive-exclude docs *
+recursive-exclude sample_standard_app *
+recursive-exclude tests *
+global-exclude __pycache__
+global-exclude *.log
+global-exclude *.pyc

agentuniverse/agent/agent.py

@@ -7,6 +7,7 @@
 # @FileName: agent.py
 """The definition of agent paradigm."""
 from abc import abstractmethod
+from datetime import datetime
 from typing import Optional
 
 from agentuniverse.agent.agent_model import AgentModel
@@ -104,6 +105,7 @@ def pre_parse_input(self, input_object) -> dict:
         planner_input = dict()
         planner_input['chat_history'] = input_object.get_data('chat_history') or ''
         planner_input['background'] = input_object.get_data('background') or ''
+        planner_input['date'] = datetime.now().strftime('%Y-%m-%d')
 
         self.parse_input(input_object, planner_input)
         return planner_input

agentuniverse/agent/default/executing_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:34
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/plan/planner/executing_planner/default_cn_prompt.yaml → agentuniverse/agent/default/executing_agent/default_cn_prompt.yaml

@@ -20,6 +20,8 @@ instruction: |
   背景信息是:
   {background}
   
+  今天的日期是: {date}
+  
   开始!
   我的问题是: {input}
   
@@ -28,4 +30,4 @@ instruction: |
   让我们一步一步来。
 metadata:
   type: 'PROMPT'
-  version: 'executing_planner.default_cn'
+  version: 'default_executing_agent.cn'

agentuniverse/agent/plan/planner/executing_planner/default_en_prompt.yaml → agentuniverse/agent/default/executing_agent/default_en_prompt.yaml

@@ -20,6 +20,8 @@ instruction: |
   Background Information:
   {background}
   
+  Today's date is: {date}
+
   Let's begin!
   My question is: {input}
   
@@ -28,4 +30,4 @@ instruction: |
   Let's take it step by step.
 metadata:
   type: 'PROMPT'
-  version: 'executing_planner.default_en'
+  version: 'default_executing_agent.en'

agentuniverse/agent/default/executing_agent.py → agentuniverse/agent/default/executing_agent/executing_agent.py

@@ -37,6 +37,7 @@ def parse_input(self, input_object: InputObject, planner_input: dict) -> dict:
         """
         planner_input['input'] = input_object.get_data('input')
         planner_input['framework'] = input_object.get_data('planning_result').get_data('framework')
+        self.agent_model.profile.setdefault('prompt_version', 'default_executing_agent.cn')
         return planner_input
 
     def parse_result(self, planner_result: dict) -> dict:

agentuniverse/agent/default/executing_agent.yaml → agentuniverse/agent/default/executing_agent/executing_agent.yaml

@@ -2,7 +2,6 @@ info:
   name: 'ExecutingAgent'
   description: 'executing agent'
 profile:
-  prompt_version:
   llm_model:
     name: 'default_openai_llm'
     model_name: 'gpt-3.5-turbo'
@@ -15,5 +14,5 @@ memory:
 action:
 metadata:
   type: 'AGENT'
-  module: 'agentuniverse.agent.default.executing_agent'
+  module: 'agentuniverse.agent.default.executing_agent.executing_agent'
   class: 'ExecutingAgent'

agentuniverse/agent/default/expressing_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:35
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/plan/planner/expressing_planner/default_cn_prompt.yaml → agentuniverse/agent/default/expressing_agent/default_cn_prompt.yaml

@@ -15,11 +15,13 @@ instruction: |
   背景信息是:
   {background}
   
+  今天的日期是: {date}
+
   开始!
   必须使用中文回答用户提出的问题。
   需要回答的问题是: {input}
   --------------------------------------------------------------
   请根据规则要求做出回答。
 metadata:
   type: 'PROMPT'
-  version: 'expressing_planner.default_cn'
+  version: 'default_expressing_agent.cn'

agentuniverse/agent/plan/planner/expressing_planner/default_en_prompt.yaml → agentuniverse/agent/default/expressing_agent/default_en_prompt.yaml

@@ -15,11 +15,13 @@ instruction: |
   Background information:
   {background}
   
+  Today's date is: {date}
+
   Let's begin!
   You must answer user questions in English.
   The question that needs answering is: {input}
   --------------------------------------------------------------
   Please provide your response according to to these rules.
 metadata:
   type: 'PROMPT'
-  version: 'expressing_planner.default_en'
+  version: 'default_expressing_agent.en'

agentuniverse/agent/default/expressing_agent.py → agentuniverse/agent/default/expressing_agent/expressing_agent.py

@@ -31,6 +31,7 @@ def parse_input(self, input_object: InputObject, planner_input: dict) -> dict:
         """
         planner_input['input'] = input_object.get_data('input')
         planner_input['background'] = self.build_background(input_object)
+        self.agent_model.profile.setdefault('prompt_version', 'default_expressing_agent.cn')
         return planner_input
 
     def parse_result(self, planner_result: dict) -> dict:

agentuniverse/agent/default/expressing_agent.yaml → agentuniverse/agent/default/expressing_agent/expressing_agent.yaml

@@ -2,7 +2,6 @@ info:
   name: 'ExpressingAgent'
   description: 'expressing agent'
 profile:
-  prompt_version:
   llm_model:
     name: 'default_openai_llm'
     model_name: 'gpt-3.5-turbo'
@@ -14,5 +13,5 @@ memory:
   name: ''
 metadata:
   type: 'AGENT'
-  module: 'agentuniverse.agent.default.expressing_agent'
+  module: 'agentuniverse.agent.default.expressing_agent.expressing_agent'
   class: 'ExpressingAgent'

agentuniverse/agent/default/peer_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:35
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/default/peer_agent.yaml → agentuniverse/agent/default/peer_agent/peer_agent.yaml

@@ -12,5 +12,5 @@ plan:
     reviewing: 'ReviewingAgent'
 metadata:
   type: 'AGENT'
-  module: 'agentuniverse.agent.default.peer_agent'
+  module: 'agentuniverse.agent.default.peer_agent.peer_agent'
   class: 'PeerAgent'

agentuniverse/agent/default/planning_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:36
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/plan/planner/planning_planner/default_cn_prompt.yaml → agentuniverse/agent/default/planning_agent/default_cn_prompt.yaml

@@ -22,9 +22,11 @@ instruction: |
   背景信息是:
   {background}
   
+  今天的日期是: {date}
+
   开始!
   必须使用中文回答用户提出的问题。
   需要回答的问题是: {input}
 metadata:
   type: 'PROMPT'
-  version: 'planning_planner.default_cn'
+  version: 'default_planning_agent.cn'

agentuniverse/agent/plan/planner/planning_planner/default_en_prompt.yaml → agentuniverse/agent/default/planning_agent/default_en_prompt.yaml

@@ -22,9 +22,11 @@ instruction: |
   Background information is.
   {background}
   
+  Today's date is: {date}
+  
   Start!
   You must answer user questions in English.
   The question that needs to be answered is: {input}
 metadata:
   type: 'PROMPT'
-  version: 'planning_planner.default_en'
+  version: 'default_planning_agent.en'

agentuniverse/agent/default/planning_agent.py → agentuniverse/agent/default/planning_agent/planning_agent.py

@@ -32,6 +32,7 @@ def parse_input(self, input_object: InputObject, planner_input: dict) -> dict:
         """
         planner_input['input'] = input_object.get_data('input')
         planner_input['expert_framework'] = input_object.get_data('expert_framework')
+        self.agent_model.profile.setdefault('prompt_version', 'default_planning_agent.cn')
         return planner_input
 
     def parse_result(self, planner_result: dict) -> dict:

agentuniverse/agent/default/planning_agent.yaml → agentuniverse/agent/default/planning_agent/planning_agent.yaml

@@ -2,7 +2,6 @@ info:
   name: 'PlanningAgent'
   description: 'planning agent'
 profile:
-  prompt_version:
   llm_model:
     name: 'default_openai_llm'
     model_name: 'gpt-3.5-turbo'
@@ -14,5 +13,5 @@ memory:
   name: ''
 metadata:
   type: 'AGENT'
-  module: 'agentuniverse.agent.default.planning_agent'
+  module: 'agentuniverse.agent.default.planning_agent.planning_agent'
   class: 'PlanningAgent'

agentuniverse/agent/default/rag_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:35
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/plan/planner/rag_planner/default_cn_prompt.yaml → agentuniverse/agent/default/rag_agent/default_cn_prompt.yaml

@@ -16,9 +16,11 @@ instruction: |
   背景信息是:
   {background}
 
+  今天的日期是: {date}
+
   开始!
 
   需要回答的问题是: {input}
 metadata:
   type: 'PROMPT'
-  version: 'rag_planner.default_cn'
+  version: 'default_rag_agent.cn'

agentuniverse/agent/plan/planner/rag_planner/default_en_prompt.yaml → agentuniverse/agent/default/rag_agent/default_en_prompt.yaml

@@ -16,9 +16,11 @@ instruction: |
   Background information:
   {background}
   
+  Today's date is: {date}
+
   Let's get started!
   
   The question that needs to be answered is: {input}
 metadata:
   type: 'PROMPT'
-  version: 'rag_planner.default_en'
+  version: 'default_rag_agent.en'

agentuniverse/agent/default/rag_agent.py → agentuniverse/agent/default/rag_agent/rag_agent.py

@@ -31,6 +31,7 @@ def parse_input(self, input_object: InputObject, planner_input: dict) -> dict:
         """
         input = input_object.get_data('input')
         planner_input['input'] = input
+        self.agent_model.profile.setdefault('prompt_version', 'default_rag_agent.cn')
         return planner_input
 
     def parse_result(self, planner_result: dict) -> dict:

agentuniverse/agent/default/rag_agent.yaml → agentuniverse/agent/default/rag_agent/rag_agent.yaml

@@ -2,7 +2,6 @@ info:
   name: 'rag_agent'
   description: 'rag agent'
 profile:
-  prompt_version:
   llm_model:
     name: 'default_openai_llm'
     model_name: 'gpt-4'
@@ -11,5 +10,5 @@ plan:
     name: 'rag_planner'
 metadata:
   type: 'AGENT'
-  module: 'agentuniverse.agent.default.rag_agent'
+  module: 'agentuniverse.agent.default.rag_agent.rag_agent'
   class: 'RagAgent'

agentuniverse/agent/default/reviewing_agent/__init__.py

@@ -0,0 +1,7 @@
+# !/usr/bin/env python3
+# -*- coding:utf-8 -*-
+
+# @Time    : 2024/5/7 14:44
+# @Author  : wangchongshi
+# @Email   : [email protected]
+# @FileName: __init__.py.py

agentuniverse/agent/plan/planner/reviewing_planner/default_cn_prompt.yaml → agentuniverse/agent/default/reviewing_agent/default_cn_prompt.yaml

@@ -19,10 +19,12 @@ instruction: |
   背景信息是:
   {background}
   
+  今天的日期是: {date}
+
   开始!
   必须使用中文回答用户提出的问题。
   指定的问题是: {input}
   给出的答案是: {expressing_result}
 metadata:
   type: 'PROMPT'
-  version: 'reviewing_planner.default_cn'
+  version: 'default_reviewing_agent.cn'

agentuniverse/agent/plan/planner/reviewing_planner/default_en_prompt.yaml → agentuniverse/agent/default/reviewing_agent/default_en_prompt.yaml

@@ -19,10 +19,12 @@ instruction: |
   Background information:
   {background}
   
+  Today's date is: {date}
+
   Let's begin!
   You must answer user questions in English.
   The specified question is: {input}
   The provided answer is: {expressing_result}
 metadata:
   type: 'PROMPT'
-  version: 'reviewing_planner.default_en'
+  version: 'default_reviewing_agent.en'