Agently

Using Tools is the new feature in Agently v3.1.

You can register your function as tools to agent instance or to global tool manager.

You can also use default tools plugins in /plugins/tool/ dir or create more tool package plugins. Go to/plugins/tool/ to see how simple it is to create your own tool package plugins.

Then you can let agent instance plan whether or not to use tools and in what order to use those toolsYou can also use .must call() alias to tell agent instance to generate a dict type result to help you calling a tool.

[Visit this document to see demonstration of the new feature](https://github.com/Maplemx/Agently/blob/main/playground/using_tools_to_enhance_your_agent.ipynb)

-------------------------

你可以把自己编写的函数作为工具注册给Agent实例，或者注册到全局的工具管理器(toolmanager)上。

你也可以使用框架在 /plugins/tool/ 文件夹中内置的工具集(tool package)插件，或者根据这些插件文件的格式，创建自己的工具集插件。访问 /plugins/tool/ 文件夹你就会发现创建自己的工具集插件是一件多么简单的事情。

然后，向Agent实例以,register tool()注册工具，或是通过,use all public tools()等指令告知Agent启用全部或者某些工具，你就可以让Agent实例自行决定是否在处理请求时使用工具了。

当然，你也可以通过.must call()指令让Agent实例生成一个字典类型的结果，帮助你来调用某个指定的工具。

[访问这个文档查看使用新能力的案例演示](https://github.com/Maplemx/Agently/blob/main/playground/using_tools_to_enhance_your_agent.ipynb)

New Feature:
**You can use Gemini Pro now!**

How to use:

python
(
agent_factory
.set_settings("model.Google.auth.api_key", "<Your-Google-API-Key-Here>")
.set_settings("current_model", "Google")
.set_settings("proxy", "http://127.0.0.1:7890") # You can set proxy if needed
)

New Feature:
Agent Component - Search!

How to use:

python
agent\
.set_role("As a preschool teacher, I'm here to turn complex and hard-to-understand knowledge into stories that little ones can understand. Even though it's a story, it's essential to ensure the accuracy and truthfulness of the information.")\
.toggle_component("Search", True)\
.instruct("If the search results or extra information contain a lot of content, try to organize it into multiple structured story segments as much as possible.")\
.input("Why the sky is blue?")\
.start()


Other Important Updates:

- Core Update: Support modify prefix stage call orders, you can modify it by editing config.ini file in plugins/agent_component dir.

新能力：
Agent组件 - 搜索

如何使用：

python
agent\
.set_role("你是一个幼儿教师，你需要将晦涩难懂的专业知识理解之后转化成小孩子能听懂的故事讲给用户听，注意，虽然是讲故事，但是要保证专业知识的准确真实")\
.toggle_component("Search", True)\
.instruct("如果搜索结果中包含较多内容，请尽可能将这些内容有条理系统地转化成多段故事")\
.input("天为什么是蓝色的")\
.start()


其他重要更新：

- 框架核心升级： 支持在prefix阶段设置组件的执行顺序，你可以通过修改plugins/agent_component文件夹里的config.ini文件来调整顺序

**Full Changelog**: https://github.com/Maplemx/Agently/compare/v3.0.3...v3.0.4

**Introducing Agently 3.0 - An AI Agent Native Development Framework**

Agently is a development framework that helps developers build AI agent native application really fast.

You can use and build AI agent in your code in an extremely simple way.

You can create an AI agent instance then interact with it like calling a function in very few codes.

In AI agent native application, we put an AI agent instance into our code, then we ask it to execute / to solve the problem with natural language or natural-language-like expressions.

"Ask-Get Response" takes place of traditional "Define Problem - Programme - Code to Make It Happen".

[Visit this link](https://github.com/Maplemx/Agently/blob/main/docs/guidebook/introduction.ipynb), it is a colab document, you can run code demos online and see how easy develop using agent can be done.

Also, Agently 3.0 re-design the plugins mechanism that brings better support for plugin developers to participate plugin development contribution.

[Click here](https://github.com/Maplemx/Agently/tree/main/src/plugins) to read plugin code in framework as examples to see how easy to develop plugins especially agent component plugins.

If you like our work, please star [our project](https://github.com/Maplemx/Agently).

v2.0.5-python
Bug Fixed:
1. Fixed when try to fix JSON format in workflow, process sometimes report Error: can not find Type 'customize'; https://github.com/Maplemx/Agently/issues/23
2. Fixed a bug when request XunFei Spark model, the result is None; https://github.com/Maplemx/Agently/issues/20

>
> We will soon publish the brand new Agently v2.1(Python) agent framework with a completely new architectural design and refactoring.

v2.0.4-python
新功能：
1. 支持`百度文心模型库`和`讯飞星火大模型`；
2. 提供了一个非常易用的[一键启动shell脚本](https://github.com/Maplemx/Agently/tree/main/demo/python/quick_launch_sh_cn) ，用于启动Agent DEMO，你可以参看blueprint目录了解如何使用它启动自己的Agent蓝图；
3. 提供了一个能够分析用户意图并给出更恰当回答的Agent蓝图：[SmartOne](https://github.com/Maplemx/Agently/blob/main/demo/python/quick_launch_sh_cn/examples/blueprints/smart_one.py)；
4. 在Session上新增了async_start()方法，以更方便您在async环境中编写协程；

New Features:
1. Support Baidu WenXin model workshop and XunFei Spark model;
2. [One-Command Shell Demo Starter](https://github.com/Maplemx/Agently/tree/main/demo/python/quick_launch_sh_cn) that super easy to use and you can run your own agent blueprint by it;
3. Agent Blueprint Example: [SmartOne](https://github.com/Maplemx/Agently/blob/main/demo/python/quick_launch_sh_cn/examples/blueprints/smart_one.py);
4. new method Session.async_start() to help you coding with asyncio coroutine;

变更：
1. 调整了work node中request节点的请求过程事件表达格式，以<阶段:事件>来进行命名；
2. 调整了request节点的文件结构，让编写不同模型的请求支持更加简单；
3. 移除了"register_response_handler"节点，新增“[register_response_suffix"](https://github.com/Maplemx/Agently/commit/d2c6fbc1c709f21c6c840801d8b7a6c94314f5a1)”节点，用于在最终向应用开发层抛出`delta`和`done`事件数据之前，对数据进行处理；
4. 完善了requirements.txt文件。

Update:
1. Change event expression in request work node, use <Stage:Event> to make event clearly to be understand;
2. Change file organize structure of llm request to make it easier to add more llm request support;
3. remove work node "register_response_handler" and add a new work node "[register_response_suffix](https://github.com/Maplemx/Agently/commit/d2c6fbc1c709f21c6c840801d8b7a6c94314f5a1)"
4. Update requirements.txt.

**Full Changelog**: https://github.com/Maplemx/Agently/compare/v2.0.1-python...v2.0.4-python

v2.0.1-python
Agently is now available in Python!

☄️ Only a few lines of code brings you an LLM agent worker in code to help you correct JSON string format error, generate API request parameters from natural languages, etc.

🎭 Easy ways to manage agent role settings, switch models, control status and context.

🧩 Arrange your agents' own Workflow and modify your own Work Nodes' working logic by code. Test your own chain of thoughts to make your agent smarter.

👥 Share your own designed agent through Blueprint to community.

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☄️ 几行代码开箱即用，在你的代码里就可以拥有一个agent帮你改错误的数据格式，生成接口调用数据

🎭 轻松便捷的Agent设定管理方法，轻松切换模型，管理人物设定、状态数值和上下文

🧩 通过工作节点（work node）和工作流(workflow)来编排你的Agent行为，让它通过思维链或是其他方式变得更聪明

👥 通过蓝图的方式进行分享，让别人能够快速用上你设计的独特Agent