Merge branch 'main' into main

README.md

@@ -54,7 +54,7 @@ pip install "pyautogen[blendsearch]"
 
 Find more options in [Installation](https://microsoft.github.io/autogen/docs/Installation).
 <!-- Each of the [`notebook examples`](https://github.com/microsoft/autogen/tree/main/notebook) may require a specific option to be installed. -->
-For [code execution](https://microsoft.github.io/autogen/FAQ#code-execution), we strongly recommend installing the python docker package, and using docker.
+For [code execution](https://microsoft.github.io/autogen/docs/FAQ/#code-execution), we strongly recommend installing the python docker package, and using docker.
 
 For LLM inference configurations, check the [FAQ](https://microsoft.github.io/autogen/docs/FAQ#set-your-api-endpoints).
 

autogen/agentchat/agent.py

@@ -28,7 +28,7 @@ def send(self, message: Union[Dict, str], recipient: "Agent", request_reply: Opt
         """(Abstract method) Send a message to another agent."""
 
     async def a_send(self, message: Union[Dict, str], recipient: "Agent", request_reply: Optional[bool] = None):
-        """(Aabstract async method) Send a message to another agent."""
+        """(Abstract async method) Send a message to another agent."""
 
     def receive(self, message: Union[Dict, str], sender: "Agent", request_reply: Optional[bool] = None):
         """(Abstract method) Receive a message from another agent."""

autogen/code_utils.py

@@ -259,7 +259,7 @@ def execute_code(
 
     timeout = timeout or DEFAULT_TIMEOUT
     original_filename = filename
-    if WIN32 and lang in ["sh", "shell"]:
+    if WIN32 and lang in ["sh", "shell"] and (not use_docker):
         lang = "ps1"
     if filename is None:
         code_hash = md5(code.encode()).hexdigest()

autogen/version.py

@@ -1 +1 @@
-__version__ = "0.1.6"
+__version__ = "0.1.7"

notebook/agentchat_RetrieveChat.ipynb

@@ -19,7 +19,7 @@
     "AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framwork allows tool use and human participance through multi-agent conversation.\n",
     "Please find documentation about this feature [here](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat).\n",
     "\n",
-    "RetrieveChat is a convesational system for retrieve augmented code generation and question answering. In this notebook, we demonstrate how to utilize RetrieveChat to generate code and answer questions based on customized documentations that are not present in the LLM's training dataset. RetrieveChat uses the `RetrieveAssistantAgent` and `RetrieveUserProxyAgent`, which is similar to the usage of `AssistantAgent` and `UserProxyAgent` in other notebooks (e.g., [Automated Task Solving with Code Generation, Execution & Debugging](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_auto_feedback_from_code_execution.ipynb)). Essentially, `RetrieveAssistantAgent` and  `RetrieveUserProxyAgent` implement a different auto-reply mechanism corresponding to the RetrieveChat prompts.\n",
+    "RetrieveChat is a conversational system for retrieve augmented code generation and question answering. In this notebook, we demonstrate how to utilize RetrieveChat to generate code and answer questions based on customized documentations that are not present in the LLM's training dataset. RetrieveChat uses the `RetrieveAssistantAgent` and `RetrieveUserProxyAgent`, which is similar to the usage of `AssistantAgent` and `UserProxyAgent` in other notebooks (e.g., [Automated Task Solving with Code Generation, Execution & Debugging](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_auto_feedback_from_code_execution.ipynb)). Essentially, `RetrieveAssistantAgent` and  `RetrieveUserProxyAgent` implement a different auto-reply mechanism corresponding to the RetrieveChat prompts.\n",
     "\n",
     "## Table of Contents\n",
     "We'll demonstrates six examples of using RetrieveChat for code generation and question answering:\n",

website/docs/Examples/AutoGen-AgentChat.md

@@ -1,6 +1,6 @@
 # AutoGen - Automated Multi Agent Chat
 
-AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framwork allows tool use and human participance via multi-agent conversation.
+AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participance via multi-agent conversation.
 Please find documentation about this feature [here](/docs/Use-Cases/agent_chat).
 
 Links to notebook examples: