From cea80cd1d6181fe1ec1eb341030a199c765065a6 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 01:26:17 +0000
Subject: [PATCH 01/10] Docs update (0cadeb6)

---
 .../tutorial/termination.ipynb                | 29 +++++++++++++++++++
 1 file changed, 29 insertions(+)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ef09378635f9..78278b84bbe1 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -70,6 +70,25 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
+      "\n",
+      "Write a unique, Haiku about the weather in Paris\n","source": [
+    "## MaxMessageTermination \n",
+    "\n",
+    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -138,6 +157,16 @@
     "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,"\n",
+    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
+    "\n",
+    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
+    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
+    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,

From 1458076f206c13a948c12594e08d2d7c092a26ac Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 18:21:13 +0000
Subject: [PATCH 02/10] Revert previous docs update

---
 .../tutorial/termination.ipynb                | 29 -------------------
 1 file changed, 29 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index 78278b84bbe1..ef09378635f9 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -70,25 +70,6 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
-      "\n",
-      "Write a unique, Haiku about the weather in Paris\n","source": [
-    "## MaxMessageTermination \n",
-    "\n",
-    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -157,16 +138,6 @@
     "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,"\n",
-    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
-    "\n",
-    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
-    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
-    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,

From ed01985a1045054a48505c0b2f0b83260f6f31fe Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 20:44:19 +0000
Subject: [PATCH 03/10] Revert previous docs update


From 9c553cd915140f52ccdd862ebaaf962afa4e2e06 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 20:44:25 +0000
Subject: [PATCH 04/10] Docs update (0cadeb6)

---
 .../tutorial/termination.ipynb                | 35 +++++++++++++++++--
 1 file changed, 33 insertions(+), 2 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ef09378635f9..50b2ed748c37 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -37,7 +37,7 @@
     "from autogen_agentchat import EVENT_LOGGER_NAME\n",
     "from autogen_agentchat.agents import CodingAssistantAgent\n",
     "from autogen_agentchat.logging import ConsoleLogHandler\n",
-    "from autogen_agentchat.task import MaxMessageTermination, StopMessageTermination\n",
+    "from autogen_agentchat.task import MaxMessageTermination, TextMentionTermination\n",
     "from autogen_agentchat.teams import RoundRobinGroupChat\n",
     "from autogen_core.components.models import OpenAIChatCompletionClient\n",
     "\n",
@@ -70,6 +70,26 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
+      "\n",
+      "Write a unique, Haiku about the weather in Paris\n",```plaintext
+"source": [
+    "## MaxMessageTermination \n",
+    "\n",
+    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -138,6 +158,17 @@
     "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},"\n",
+    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
+    "\n",
+    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
+    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
+    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -178,7 +209,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
     ")"
    ]
   }

From 2aaffc47fb6d8500b9099c92b4066bd707f09cc6 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 21:16:28 +0000
Subject: [PATCH 05/10] Revert previous docs update

---
 .../tutorial/termination.ipynb                | 35 ++-----------------
 1 file changed, 2 insertions(+), 33 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index 50b2ed748c37..ef09378635f9 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -37,7 +37,7 @@
     "from autogen_agentchat import EVENT_LOGGER_NAME\n",
     "from autogen_agentchat.agents import CodingAssistantAgent\n",
     "from autogen_agentchat.logging import ConsoleLogHandler\n",
-    "from autogen_agentchat.task import MaxMessageTermination, TextMentionTermination\n",
+    "from autogen_agentchat.task import MaxMessageTermination, StopMessageTermination\n",
     "from autogen_agentchat.teams import RoundRobinGroupChat\n",
     "from autogen_core.components.models import OpenAIChatCompletionClient\n",
     "\n",
@@ -70,26 +70,6 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
-      "\n",
-      "Write a unique, Haiku about the weather in Paris\n",```plaintext
-"source": [
-    "## MaxMessageTermination \n",
-    "\n",
-    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -158,17 +138,6 @@
     "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},"\n",
-    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
-    "\n",
-    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
-    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
-    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -209,7 +178,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
     ")"
    ]
   }

From 4605f2e7dd96ea7634ef009b4d347249fb801f94 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 21:16:36 +0000
Subject: [PATCH 06/10] Docs update (0cadeb6)

---
 .../tutorial/agents.ipynb                     | 74 ++++++++++++++++++-
 .../tutorial/termination.ipynb                | 38 +++++++++-
 2 files changed, 105 insertions(+), 7 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
index d367ba29b7e0..fef793897348 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
@@ -64,6 +64,23 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!-- ## CodingAssistantAgent\n",
+    "\n",
+    "Generates responses (text and code) using an LLM upon receipt of a message. It takes a `system_message` argument that defines or sets the tone for how the agent's LLM should respond. \n",
+    "\n",
+    "```python\n",
+    "\n",
+    "writing_assistant_agent = CodingAssistantAgent(\n",
+    "    name=\"writing_assistant_agent\",\n",
+    "    system_message=\"You are a helpful assistant that solve tasks by generating text responses and code.\",\n",
+    "    model_client=model_client,\n",
+    ")\n",")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -141,6 +158,26 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": ["\n",
+    "\n",
+    "get_weather_tool = FunctionTool(get_weather, description=\"Get the weather for a city\")\n",
+    "\n",
+    "tool_use_agent = ToolUseAssistantAgent(\n",
+    "    \"tool_use_agent\",\n",
+    "    system_message=\"You are a helpful assistant that solves tasks by only using your tools.\",\n",
+    "    model_client=model_client,\n",
+    "    registered_tools=[get_weather_tool],\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -220,6 +257,20 @@
     "    print(code_execution_result)"
    ]
   },
+  {"from autogen_agentchat.agents import CodeExecutorAgent\n",
+    "from autogen_ext.code_executors import DockerCommandLineCodeExecutor\n",
+    "\n",
+    "async with DockerCommandLineCodeExecutor(work_dir=\"coding\") as code_executor:  # type: ignore[syntax]\n",
+    "    code_executor_agent = CodeExecutorAgent(\"code_executor\", code_executor=code_executor)\n",
+    "    code_execution_result = await code_executor_agent.on_messages(\n",
+    "        messages=[\n",
+    "            TextMessage(content=\"Here is some code \\n ```python print('Hello world') \\n``` \", source=\"user\"),\n",
+    "        ],\n",
+    "        cancellation_token=CancellationToken(),\n",
+    "    )\n",
+    "    print(code_execution_result)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -254,7 +305,6 @@
     "from autogen_agentchat.base import Response\n",
     "from autogen_agentchat.messages import (\n",
     "    ChatMessage,\n",
-    "    StopMessage,\n",
     "    TextMessage,\n",
     ")\n",
     "\n",
@@ -265,12 +315,12 @@
     "\n",
     "    @property\n",
     "    def produced_message_types(self) -> List[type[ChatMessage]]:\n",
-    "        return [TextMessage, StopMessage]\n",
+    "        return [TextMessage]\n",
     "\n",
     "    async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:\n",
     "        user_input = await asyncio.get_event_loop().run_in_executor(None, input, \"Enter your response: \")\n",
     "        if \"TERMINATE\" in user_input:\n",
-    "            return Response(chat_message=StopMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
+    "            return Response(chat_message=TextMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
     "        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
     "\n",
     "\n",
@@ -285,6 +335,24 @@
     "print(user_proxy_agent_result)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n","        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
+    "\n",
+    "\n",
+    "user_proxy_agent = UserProxyAgent(name=\"user_proxy_agent\")\n",
+    "\n",
+    "user_proxy_agent_result = await user_proxy_agent.on_messages(\n",
+    "    messages=[\n",
+    "        TextMessage(content=\"What is the weather right now in France?\", source=\"user\"),\n",
+    "    ],\n",
+    "    cancellation_token=CancellationToken(),\n",
+    ")\n",
+    "print(user_proxy_agent_result)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ef09378635f9..04bffe2dd7bd 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -37,7 +37,7 @@
     "from autogen_agentchat import EVENT_LOGGER_NAME\n",
     "from autogen_agentchat.agents import CodingAssistantAgent\n",
     "from autogen_agentchat.logging import ConsoleLogHandler\n",
-    "from autogen_agentchat.task import MaxMessageTermination, StopMessageTermination\n",
+    "from autogen_agentchat.task import MaxMessageTermination, TextMentionTermination\n",
     "from autogen_agentchat.teams import RoundRobinGroupChat\n",
     "from autogen_core.components.models import OpenAIChatCompletionClient\n",
     "\n",
@@ -70,6 +70,25 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
+      "\n",
+      "Write a unique, Haiku about the weather in Paris\n","source": [
+    "## MaxMessageTermination \n",
+    "\n",
+    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -127,10 +146,21 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## StopMessageTermination\n",
+    "## TextMentionTermination\n",
+    "\n",
+    "In this scenario, the team terminates the conversation if any agent's message contains a specific text string, such as \"TERMINATE\". This is typically implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to trigger the termination condition based on the presence of the specified text. \n",
     "\n",
-    "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
+    "A common pattern here is to prompt the agent (or some agent participating in the conversation) to emit a specific text string in its response, which can be used to trigger the termination condition. \n",
     "\n",
+    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
+    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
+    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and triggers the termination condition if it does. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},"\n",
     "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
     "\n",
     "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
@@ -178,7 +208,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
     ")"
    ]
   }

From a4301851c23363f50576a422b9fcc3a086c5692b Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 23:34:03 +0000
Subject: [PATCH 07/10] Revert previous docs update

---
 .../tutorial/agents.ipynb                     | 74 +------------------
 .../tutorial/termination.ipynb                | 38 +---------
 2 files changed, 7 insertions(+), 105 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
index fef793897348..d367ba29b7e0 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
@@ -64,23 +64,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<!-- ## CodingAssistantAgent\n",
-    "\n",
-    "Generates responses (text and code) using an LLM upon receipt of a message. It takes a `system_message` argument that defines or sets the tone for how the agent's LLM should respond. \n",
-    "\n",
-    "```python\n",
-    "\n",
-    "writing_assistant_agent = CodingAssistantAgent(\n",
-    "    name=\"writing_assistant_agent\",\n",
-    "    system_message=\"You are a helpful assistant that solve tasks by generating text responses and code.\",\n",
-    "    model_client=model_client,\n",
-    ")\n",")"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -158,26 +141,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": ["\n",
-    "\n",
-    "get_weather_tool = FunctionTool(get_weather, description=\"Get the weather for a city\")\n",
-    "\n",
-    "tool_use_agent = ToolUseAssistantAgent(\n",
-    "    \"tool_use_agent\",\n",
-    "    system_message=\"You are a helpful assistant that solves tasks by only using your tools.\",\n",
-    "    model_client=model_client,\n",
-    "    registered_tools=[get_weather_tool],\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -257,20 +220,6 @@
     "    print(code_execution_result)"
    ]
   },
-  {"from autogen_agentchat.agents import CodeExecutorAgent\n",
-    "from autogen_ext.code_executors import DockerCommandLineCodeExecutor\n",
-    "\n",
-    "async with DockerCommandLineCodeExecutor(work_dir=\"coding\") as code_executor:  # type: ignore[syntax]\n",
-    "    code_executor_agent = CodeExecutorAgent(\"code_executor\", code_executor=code_executor)\n",
-    "    code_execution_result = await code_executor_agent.on_messages(\n",
-    "        messages=[\n",
-    "            TextMessage(content=\"Here is some code \\n ```python print('Hello world') \\n``` \", source=\"user\"),\n",
-    "        ],\n",
-    "        cancellation_token=CancellationToken(),\n",
-    "    )\n",
-    "    print(code_execution_result)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -305,6 +254,7 @@
     "from autogen_agentchat.base import Response\n",
     "from autogen_agentchat.messages import (\n",
     "    ChatMessage,\n",
+    "    StopMessage,\n",
     "    TextMessage,\n",
     ")\n",
     "\n",
@@ -315,12 +265,12 @@
     "\n",
     "    @property\n",
     "    def produced_message_types(self) -> List[type[ChatMessage]]:\n",
-    "        return [TextMessage]\n",
+    "        return [TextMessage, StopMessage]\n",
     "\n",
     "    async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:\n",
     "        user_input = await asyncio.get_event_loop().run_in_executor(None, input, \"Enter your response: \")\n",
     "        if \"TERMINATE\" in user_input:\n",
-    "            return Response(chat_message=TextMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
+    "            return Response(chat_message=StopMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
     "        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
     "\n",
     "\n",
@@ -335,24 +285,6 @@
     "print(user_proxy_agent_result)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Summary\n","        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
-    "\n",
-    "\n",
-    "user_proxy_agent = UserProxyAgent(name=\"user_proxy_agent\")\n",
-    "\n",
-    "user_proxy_agent_result = await user_proxy_agent.on_messages(\n",
-    "    messages=[\n",
-    "        TextMessage(content=\"What is the weather right now in France?\", source=\"user\"),\n",
-    "    ],\n",
-    "    cancellation_token=CancellationToken(),\n",
-    ")\n",
-    "print(user_proxy_agent_result)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index 04bffe2dd7bd..ef09378635f9 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -37,7 +37,7 @@
     "from autogen_agentchat import EVENT_LOGGER_NAME\n",
     "from autogen_agentchat.agents import CodingAssistantAgent\n",
     "from autogen_agentchat.logging import ConsoleLogHandler\n",
-    "from autogen_agentchat.task import MaxMessageTermination, TextMentionTermination\n",
+    "from autogen_agentchat.task import MaxMessageTermination, StopMessageTermination\n",
     "from autogen_agentchat.teams import RoundRobinGroupChat\n",
     "from autogen_core.components.models import OpenAIChatCompletionClient\n",
     "\n",
@@ -70,25 +70,6 @@
     "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
-      "\n",
-      "Write a unique, Haiku about the weather in Paris\n","source": [
-    "## MaxMessageTermination \n",
-    "\n",
-    "The simplest termination condition is the {py:class}`~autogen_agentchat.teams.MaxMessageTermination` condition, which terminates the conversation after a fixed number of messages. \n"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -146,21 +127,10 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## TextMentionTermination\n",
-    "\n",
-    "In this scenario, the team terminates the conversation if any agent's message contains a specific text string, such as \"TERMINATE\". This is typically implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to trigger the termination condition based on the presence of the specified text. \n",
+    "## StopMessageTermination\n",
     "\n",
-    "A common pattern here is to prompt the agent (or some agent participating in the conversation) to emit a specific text string in its response, which can be used to trigger the termination condition. \n",
+    "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
     "\n",
-    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
-    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
-    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and triggers the termination condition if it does. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},"\n",
     "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
     "\n",
     "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
@@ -208,7 +178,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
     ")"
    ]
   }

From 0f1accc442a1fc29964f60ab08a4c40d16a60cd3 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Tue, 19 Nov 2024 23:34:11 +0000
Subject: [PATCH 08/10] Docs update (0cadeb6)

---
 .../tutorial/agents.ipynb                     | 89 ++++++++++++-------
 .../tutorial/termination.ipynb                | 59 +++---------
 2 files changed, 71 insertions(+), 77 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
index d367ba29b7e0..8ceb669c7e80 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
@@ -64,6 +64,23 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<!-- ## CodingAssistantAgent\n",
+    "\n",
+    "Generates responses (text and code) using an LLM upon receipt of a message. It takes a `system_message` argument that defines or sets the tone for how the agent's LLM should respond. \n",
+    "\n",
+    "```python\n",
+    "\n",
+    "writing_assistant_agent = CodingAssistantAgent(\n",
+    "    name=\"writing_assistant_agent\",\n",
+    "    system_message=\"You are a helpful assistant that solve tasks by generating text responses and code.\",\n",
+    "    model_client=model_client,\n",
+    ")\n",")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -141,6 +158,26 @@
     ")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": ["\n",
+    "\n",
+    "get_weather_tool = FunctionTool(get_weather, description=\"Get the weather for a city\")\n",
+    "\n",
+    "tool_use_agent = ToolUseAssistantAgent(\n",
+    "    \"tool_use_agent\",\n",
+    "    system_message=\"You are a helpful assistant that solves tasks by only using your tools.\",\n",
+    "    model_client=model_client,\n",
+    "    registered_tools=[get_weather_tool],\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -220,41 +257,13 @@
     "    print(code_execution_result)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Building Custom Agents\n",
-    "\n",
-    "In many cases, you may have agents with custom behaviors that do not fall into any of the preset agent categories. In such cases, you can build custom agents by subclassing the {py:class}`~autogen_agentchat.agents.BaseChatAgent`   class and implementing the  {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages`  method.\n",
-    "\n",
-    "A common example is an agent that can be part of a team but primarily is driven by human input. Other examples include agents that respond with specific text, tool or function calls. \n",
-    "\n",
-    "In the example below we show how to implement a `UserProxyAgent` - an agent that asks the user to enter some text and then returns that message as a response.  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "source='user_proxy_agent' content='Hello there'\n"
-     ]
-    }
-   ],
-   "source": [
-    "import asyncio\n",
+  {"import asyncio\n",
     "from typing import List, Sequence\n",
     "\n",
     "from autogen_agentchat.agents import BaseChatAgent\n",
     "from autogen_agentchat.base import Response\n",
     "from autogen_agentchat.messages import (\n",
     "    ChatMessage,\n",
-    "    StopMessage,\n",
     "    TextMessage,\n",
     ")\n",
     "\n",
@@ -265,12 +274,12 @@
     "\n",
     "    @property\n",
     "    def produced_message_types(self) -> List[type[ChatMessage]]:\n",
-    "        return [TextMessage, StopMessage]\n",
+    "        return [TextMessage]\n",
     "\n",
     "    async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:\n",
     "        user_input = await asyncio.get_event_loop().run_in_executor(None, input, \"Enter your response: \")\n",
     "        if \"TERMINATE\" in user_input:\n",
-    "            return Response(chat_message=StopMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
+    "            return Response(chat_message=TextMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
     "        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
     "\n",
     "\n",
@@ -285,6 +294,24 @@
     "print(user_proxy_agent_result)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Summary\n","        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
+    "\n",
+    "\n",
+    "user_proxy_agent = UserProxyAgent(name=\"user_proxy_agent\")\n",
+    "\n",
+    "user_proxy_agent_result = await user_proxy_agent.on_messages(\n",
+    "    messages=[\n",
+    "        TextMessage(content=\"What is the weather right now in France?\", source=\"user\"),\n",
+    "    ],\n",
+    "    cancellation_token=CancellationToken(),\n",
+    ")\n",
+    "print(user_proxy_agent_result)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ef09378635f9..ad2200942775 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -83,51 +83,7 @@
       "--------------------------------------------------------------------------- \n",
       "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
       "\n",
-      "Write a unique, Haiku about the weather in Paris\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:29.604935], writing_assistant_agent:\u001b[0m\n",
-      "\n",
-      "Gentle rain whispers,  \n",
-      "Eiffel veiled in mist’s embrace,  \n",
-      "Spring’s soft sigh in France.\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:30.168531], writing_assistant_agent:\u001b[0m\n",
-      "\n",
-      "Gentle rain whispers,  \n",
-      "Eiffel veiled in mist’s embrace,  \n",
-      "Spring’s soft sigh in France.\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:31.213291], writing_assistant_agent:\u001b[0m\n",
-      "\n",
-      "Gentle rain whispers,  \n",
-      "Eiffel veiled in mist’s embrace,  \n",
-      "Spring’s soft sigh in France.\n",
-      "--------------------------------------------------------------------------- \n",
-      "\u001b[91m[2024-10-19T12:19:31.213655], Termination:\u001b[0m\n",
-      "\n",
-      "Maximal number of messages 3 reached, current message count: 3"
-     ]
-    }
-   ],
-   "source": [
-    "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
-    "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=MaxMessageTermination(max_messages=3)\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "We see that the conversation is terminated after the specified number of messages have been sent by the agent."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## StopMessageTermination\n",
+      "Write a unique, Haiku about the weather in Paris\n",    "## StopMessageTermination\n",
     "\n",
     "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
     "\n",
@@ -138,6 +94,17 @@
     "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},"\n",
+    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
+    "\n",
+    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
+    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
+    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -178,7 +145,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
     ")"
    ]
   }

From 4741ea5fc608a469fb6c2cefd5d04b4d3a788271 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Mon, 6 Jan 2025 21:07:19 +0000
Subject: [PATCH 09/10] Revert previous docs update

---
 .../tutorial/agents.ipynb                     | 89 +++++++------------
 .../tutorial/termination.ipynb                | 59 +++++++++---
 2 files changed, 77 insertions(+), 71 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
index 8ceb669c7e80..d367ba29b7e0 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/agents.ipynb
@@ -64,23 +64,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<!-- ## CodingAssistantAgent\n",
-    "\n",
-    "Generates responses (text and code) using an LLM upon receipt of a message. It takes a `system_message` argument that defines or sets the tone for how the agent's LLM should respond. \n",
-    "\n",
-    "```python\n",
-    "\n",
-    "writing_assistant_agent = CodingAssistantAgent(\n",
-    "    name=\"writing_assistant_agent\",\n",
-    "    system_message=\"You are a helpful assistant that solve tasks by generating text responses and code.\",\n",
-    "    model_client=model_client,\n",
-    ")\n",")"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -158,26 +141,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": ["\n",
-    "\n",
-    "get_weather_tool = FunctionTool(get_weather, description=\"Get the weather for a city\")\n",
-    "\n",
-    "tool_use_agent = ToolUseAssistantAgent(\n",
-    "    \"tool_use_agent\",\n",
-    "    system_message=\"You are a helpful assistant that solves tasks by only using your tools.\",\n",
-    "    model_client=model_client,\n",
-    "    registered_tools=[get_weather_tool],\n",
-    ")"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -257,13 +220,41 @@
     "    print(code_execution_result)"
    ]
   },
-  {"import asyncio\n",
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Building Custom Agents\n",
+    "\n",
+    "In many cases, you may have agents with custom behaviors that do not fall into any of the preset agent categories. In such cases, you can build custom agents by subclassing the {py:class}`~autogen_agentchat.agents.BaseChatAgent`   class and implementing the  {py:meth}`~autogen_agentchat.agents.BaseChatAgent.on_messages`  method.\n",
+    "\n",
+    "A common example is an agent that can be part of a team but primarily is driven by human input. Other examples include agents that respond with specific text, tool or function calls. \n",
+    "\n",
+    "In the example below we show how to implement a `UserProxyAgent` - an agent that asks the user to enter some text and then returns that message as a response.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "source='user_proxy_agent' content='Hello there'\n"
+     ]
+    }
+   ],
+   "source": [
+    "import asyncio\n",
     "from typing import List, Sequence\n",
     "\n",
     "from autogen_agentchat.agents import BaseChatAgent\n",
     "from autogen_agentchat.base import Response\n",
     "from autogen_agentchat.messages import (\n",
     "    ChatMessage,\n",
+    "    StopMessage,\n",
     "    TextMessage,\n",
     ")\n",
     "\n",
@@ -274,12 +265,12 @@
     "\n",
     "    @property\n",
     "    def produced_message_types(self) -> List[type[ChatMessage]]:\n",
-    "        return [TextMessage]\n",
+    "        return [TextMessage, StopMessage]\n",
     "\n",
     "    async def on_messages(self, messages: Sequence[ChatMessage], cancellation_token: CancellationToken) -> Response:\n",
     "        user_input = await asyncio.get_event_loop().run_in_executor(None, input, \"Enter your response: \")\n",
     "        if \"TERMINATE\" in user_input:\n",
-    "            return Response(chat_message=TextMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
+    "            return Response(chat_message=StopMessage(content=\"User has terminated the conversation.\", source=self.name))\n",
     "        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
     "\n",
     "\n",
@@ -294,24 +285,6 @@
     "print(user_proxy_agent_result)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Summary\n","        return Response(chat_message=TextMessage(content=user_input, source=self.name))\n",
-    "\n",
-    "\n",
-    "user_proxy_agent = UserProxyAgent(name=\"user_proxy_agent\")\n",
-    "\n",
-    "user_proxy_agent_result = await user_proxy_agent.on_messages(\n",
-    "    messages=[\n",
-    "        TextMessage(content=\"What is the weather right now in France?\", source=\"user\"),\n",
-    "    ],\n",
-    "    cancellation_token=CancellationToken(),\n",
-    ")\n",
-    "print(user_proxy_agent_result)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ad2200942775..ef09378635f9 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -83,21 +83,54 @@
       "--------------------------------------------------------------------------- \n",
       "\u001b[91m[2024-10-19T12:19:28.807176]:\u001b[0m\n",
       "\n",
-      "Write a unique, Haiku about the weather in Paris\n",    "## StopMessageTermination\n",
-    "\n",
-    "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
-    "\n",
-    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
-    "\n",
-    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
-    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
-    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
+      "Write a unique, Haiku about the weather in Paris\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:29.604935], writing_assistant_agent:\u001b[0m\n",
+      "\n",
+      "Gentle rain whispers,  \n",
+      "Eiffel veiled in mist’s embrace,  \n",
+      "Spring’s soft sigh in France.\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:30.168531], writing_assistant_agent:\u001b[0m\n",
+      "\n",
+      "Gentle rain whispers,  \n",
+      "Eiffel veiled in mist’s embrace,  \n",
+      "Spring’s soft sigh in France.\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:31.213291], writing_assistant_agent:\u001b[0m\n",
+      "\n",
+      "Gentle rain whispers,  \n",
+      "Eiffel veiled in mist’s embrace,  \n",
+      "Spring’s soft sigh in France.\n",
+      "--------------------------------------------------------------------------- \n",
+      "\u001b[91m[2024-10-19T12:19:31.213655], Termination:\u001b[0m\n",
+      "\n",
+      "Maximal number of messages 3 reached, current message count: 3"
+     ]
+    }
+   ],
+   "source": [
+    "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
+    "round_robin_team_result = await round_robin_team.run(\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=MaxMessageTermination(max_messages=3)\n",
+    ")"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},"\n",
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We see that the conversation is terminated after the specified number of messages have been sent by the agent."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## StopMessageTermination\n",
+    "\n",
+    "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
+    "\n",
     "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
     "\n",
     "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
@@ -145,7 +178,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
     ")"
    ]
   }

From 1428d390dc02e9fadd18f92ffd568c7fb573b7b2 Mon Sep 17 00:00:00 2001
From: "promptless[bot]" <179508745+promptless[bot]@users.noreply.github.com>
Date: Mon, 6 Jan 2025 21:07:25 +0000
Subject: [PATCH 10/10] Docs update (0cadeb6)

---
 .../tutorial/termination.ipynb                   | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
index ef09378635f9..8c142e4c52a3 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/termination.ipynb
@@ -127,15 +127,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## StopMessageTermination\n",
+    "## TextMentionTermination\n",
     "\n",
-    "In this scenario, the team terminates the conversation if any agent sends a `StopMessage`. So, when does an agent send a `StopMessage`? Typically, this is implemented in the `on_message` method of the agent, where the agent can check the incoming message and decide to send a `StopMessage` based on some condition. \n",
+    "In this scenario, the team terminates the conversation if any agent's message contains a specific text mention, such as \"TERMINATE\". This approach provides more flexible and explicit control over when a chat session should end. \n",
     "\n",
-    "A common pattern here is prompt the agent (or some agent participating in the conversation) to emit a specific text string in it's response, which can be used to trigger the termination condition. \n",
+    "A common pattern here is to prompt the agent (or some agent participating in the conversation) to emit a specific text string in its response, which can be used to trigger the termination condition. \n",
     "\n",
-    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things\n",
-    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed\n",
-    "- in the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and returns a `StopMessage` if it does. "
+    "In fact, if you review the code implementation for the default `CodingAssistantAgent` class provided by AgentChat, you will observe two things:\n",
+    "- The default `system_message` instructs the agent to end their response with the word \"terminate\" if they deem the task to be completed.\n",
+    "- In the `on_message` method, the agent checks if the incoming message contains the text \"terminate\" and triggers a termination if it does."
    ]
   },
   {
@@ -163,7 +163,7 @@
       "--------------------------------------------------------------------------- \n",
       "\u001b[91m[2024-10-19T12:19:31.753265], Termination:\u001b[0m\n",
       "\n",
-      "Stop message received"
+      "Termination condition met"
      ]
     }
    ],
@@ -178,7 +178,7 @@
     "round_robin_team = RoundRobinGroupChat([writing_assistant_agent])\n",
     "\n",
     "round_robin_team_result = await round_robin_team.run(\n",
-    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=StopMessageTermination()\n",
+    "    \"Write a unique, Haiku about the weather in Paris\", termination_condition=TextMentionTermination(\"TERMINATE\")\n",
     ")"
    ]
   }