v0.1.0-beta prepare

docs/en/README.md

@@ -14,7 +14,7 @@ Using Python code [SpheroBoltGPT](https://github.com/ghost-in-moss/GhostOS/tree/
 an intelligent robot with a [SpheroBolt](https://sphero.com/products/sphero-bolt) as its body is defined.
 If you have a SpheroBolt, running `ghostos web ghostos.demo.sphero.bolt_gpt` can start this robot.
 
-![SpheroBoltGPT](assets/ask_sphero_spin_gif.gif)
+![SpheroBoltGPT](../assets/ask_sphero_spin_gif.gif)
 
 The demo initially implements the following features:
 
@@ -178,7 +178,7 @@ Therefore, a Meta-Agent can develop other Agents just like a normal programming
 Ideally, the Meta-Agent can write code, write its own tools, define memories and chain of thoughts with data structures,
 and develop other Agents for itself.
 
-![meta-agent-cycle](assets/meta-agent-cycle.png)
+![meta-agent-cycle](../assets/meta-agent-cycle.png)
 
 Furthermore, most complex tasks with rigorous steps can be described using tree or graph data structures.
 Constructing a nested graph or tree using methods like JSON is very difficult,

docs/zh-cn/README.md

@@ -13,7 +13,7 @@
 
 如果你有 SpheroBolt, 运行 `ghostos web ghostos.demo.sphero.bolt_gpt` 可以启动这个机器人:
 
-![SpheroBoltGPT](assets/ask_sphero_spin_gif.gif)
+![SpheroBoltGPT](../assets/ask_sphero_spin_gif.gif)
 
 Demo 中初步实现的功能:
 
@@ -157,7 +157,7 @@ AI Agent 本身也是使用代码实现的. 所以大模型驱动的 Meta-Agent
 理想情况下, 大模型驱动的 Meta-Agent 可以通过编写代码, 编写自己的工具, 用数据结构定义的记忆和思维链, 乃至于生成其它的
 Agent.
 
-![meta-agent-cycle](assets/meta-agent-cycle.png)
+![meta-agent-cycle](../assets/meta-agent-cycle.png)
 
 进一步, 大多数有严谨步骤的复杂任务, 都可以用树或者图的数据结构描述.
 用 json 之类的方式构建一个结构嵌套的图或者树非常困难, 而用编程语言是最高效的.

ghostos/app/configs/streamlit_app.yml

@@ -1,6 +1,6 @@
 # from class: ghostos.prototypes.streamlitapp.resources:AppConf
 bool_options:
-  DEBUG_MODE: true
-  HELP_MODE: true
+  DEBUG_MODE: false
+  HELP_MODE: false
 domain: ghostos
 lang: zh

ghostos/prototypes/streamlitapp/pages/chat_with_ghost.py

@@ -380,7 +380,7 @@ def render_receiver(receiver: Receiver, debug: bool):
 
 def render_receive_buffer(buffer: ReceiverBuffer, debug: bool):
     while buffer is not None:
-        st.logger.get_logger("ghostos").info("receive buffer head: %s", buffer.head())
+        st.logger.get_logger("ghostos").debug("receive buffer head: %s", buffer.head())
         if MessageType.is_text(buffer.head()):
             with st.empty():
                 contents = chunks_to_st_stream(buffer.chunks())

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "ghostos"
-version = "0.0.1-dev5"
+version = "0.1.0-beta"
 description = "A framework offers an operating system simulator with a Python Code Interface for AI Agents"
 authors = ["zhuming <thirdgerb@gmail.com>", "Nile Zhou <nilezhou123@gmail.com>"]
 license = "MIT"