From b9bd8b0c64dbd6c7ebeff47e5818c64e5a7c2cf4 Mon Sep 17 00:00:00 2001 From: Eric Zhu Date: Fri, 27 Dec 2024 10:20:52 -0800 Subject: [PATCH] human-in-the-loop section for agentchat tutorial (#4832) * human-in-the-loop section for agentchat tutorial --- .../agents/_user_proxy_agent.py | 2 +- .../human-in-the-loop-termination.drawio | 64 +++ .../human-in-the-loop-user-proxy.drawio | 92 ++++ .../user-guide/agentchat-user-guide/index.md | 2 +- .../human-in-the-loop-termination.svg | 3 + .../tutorial/human-in-the-loop-user-proxy.svg | 3 + .../tutorial/human-in-the-loop.ipynb | 439 ++++++++++++++++++ 7 files changed, 603 insertions(+), 2 deletions(-) create mode 100644 python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio create mode 100644 python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg create mode 100644 python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb diff --git a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py index 6b8ab3055..1695be426 100644 --- a/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py +++ b/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_user_proxy_agent.py @@ -48,7 +48,7 @@ class UserProxyAgent(BaseChatAgent): You can run the team again with the user input. This way, the state of the team can be saved and restored when the user responds. - See `Pause for User Input `_ for more information. + See `Human-in-the-loop `_ for more information. Example: Simple usage case:: diff --git a/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio b/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio new file mode 100644 index 000000000..1c4b1564b --- /dev/null +++ b/python/packages/autogen-core/docs/drawio/human-in-the-loop-termination.drawio @@ -0,0 +1,64 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio b/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio new file mode 100644 index 000000000..6b392341e --- /dev/null +++ b/python/packages/autogen-core/docs/drawio/human-in-the-loop-user-proxy.drawio @@ -0,0 +1,92 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md index d5df491a6..bfc6e8859 100644 --- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/index.md @@ -61,6 +61,7 @@ tutorial/models tutorial/messages tutorial/agents tutorial/teams +tutorial/human-in-the-loop tutorial/selector-group-chat tutorial/swarm tutorial/termination @@ -75,4 +76,3 @@ tutorial/state examples/index ``` - diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg new file mode 100644 index 000000000..6bfda4dd0 --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-termination.svg @@ -0,0 +1,3 @@ + + +
Agent 2
Agent 2
Agent 1
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Agent 3
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RoundRobinGroupChat
RoundRobinGroupChat
Application/User
Application/User
Task/Feedback
Task/Feedback
TaskResult
TaskResult
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Condition
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Orchestrator
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Starts / Resumes the Team
Saves the Team's State
Saves the Team's State \ No newline at end of file diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg new file mode 100644 index 000000000..77d9a2372 --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop-user-proxy.svg @@ -0,0 +1,3 @@ + + +
UserProxyAgent
UserProxyAgent
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Agent 1
Agent 3
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TaskResult
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Request for User Input \ No newline at end of file diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb new file mode 100644 index 000000000..7862fecea --- /dev/null +++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/human-in-the-loop.ipynb @@ -0,0 +1,439 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Human-in-the-Loop\n", + "\n", + "In the previous section [Teams](./teams.ipynb), we have seen how to create, observe,\n", + "and control a team of agents.\n", + "This section will focus on how to interact with the team from your application,\n", + "and provide human feedback to the team.\n", + "\n", + "There are two main ways to interact with the team from your application:\n", + "\n", + "1. During a team's run -- execution of {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream`, provide feedback through a {py:class}`~autogen_agentchat.agents.UserProxyAgent`.\n", + "2. Once the run terminates, provide feedback through input to the next call to {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run` or {py:meth}`~autogen_agentchat.teams.BaseGroupChat.run_stream`.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Providing Feedback During a Run\n", + "\n", + "The {py:class}`~autogen_agentchat.agents.UserProxyAgent` is a special built-in agent\n", + "that acts as a proxy for a user to provide feedback to the team.\n", + "\n", + "To use the {py:class}`~autogen_agentchat.agents.UserProxyAgent`, you can create an instance of it\n", + "and include it in the team before running the team.\n", + "The team will decide when to call the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to ask for feedback from the user.\n", + "\n", + "The following diagram illustrates how you can use \n", + "{py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to get feedback from the user during a team's run:\n", + "\n", + "![human-in-the-loop-user-proxy](./human-in-the-loop-user-proxy.svg)\n", + "\n", + "The bold arrows indicates the flow of control during a team's run:\n", + "when the team calls the {py:class}`~autogen_agentchat.agents.UserProxyAgent`,\n", + "it transfers the control to the application/user, and waits for the feedback;\n", + "once the feedback is provided, the control is transferred back to the team\n", + "and the team continues its execution.\n", + "\n", + "```{note}\n", + "When {py:class}`~autogen_agentchat.agents.UserProxyAgent` is called during a run,\n", + "it blocks the execution of the team until the user provides feedback or errors out.\n", + "This will hold up the team's progress and put the team in an unstable state\n", + "that cannot be saved or resumed.\n", + "```\n", + "\n", + "Due to the blocking nature of this approach, it is recommended to use it only for short interactions\n", + "that require immediate feedback from the user, such as asking for approval or disapproval\n", + "with a button click, or an alert requiring immediate attention otherwise failing the task.\n", + "\n", + "Here is an example of how to use the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "in a {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` for a poetry generation task:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a 4-line poem about the ocean.\n", + "---------- assistant ----------\n", + "Waves whisper secrets to the shore’s embrace, \n", + "A dance of blue under the sun's warm grace. \n", + "Endless horizons where dreams take flight, \n", + "The ocean's heart glimmers, a canvas of light. \n", + "TERMINATE\n", + "[Prompt tokens: 46, Completion tokens: 49]\n", + "---------- user_proxy ----------\n", + "APPROVE\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'APPROVE' mentioned\n", + "Total prompt tokens: 46\n", + "Total completion tokens: 49\n", + "Duration: 6.64 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Write a 4-line poem about the ocean.', type='TextMessage'), TextMessage(source='assistant', models_usage=RequestUsage(prompt_tokens=46, completion_tokens=49), content=\"Waves whisper secrets to the shore’s embrace, \\nA dance of blue under the sun's warm grace. \\nEndless horizons where dreams take flight, \\nThe ocean's heart glimmers, a canvas of light. \\nTERMINATE\", type='TextMessage'), TextMessage(source='user_proxy', models_usage=None, content='APPROVE', type='TextMessage')], stop_reason=\"Text 'APPROVE' mentioned\")" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent, UserProxyAgent\n", + "from autogen_agentchat.conditions import TextMentionTermination\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create the agents.\n", + "model_client = OpenAIChatCompletionClient(model=\"gpt-4o-mini\")\n", + "assistant = AssistantAgent(\"assistant\", model_client=model_client)\n", + "user_proxy = UserProxyAgent(\"user_proxy\", input_func=input) # Use input() to get user input from console.\n", + "\n", + "# Create the termination condition which will end the conversation when the user says \"APPROVE\".\n", + "termination = TextMentionTermination(\"APPROVE\")\n", + "\n", + "# Create the team.\n", + "team = RoundRobinGroupChat([assistant, user_proxy], termination_condition=termination)\n", + "\n", + "# Run the conversation and stream to the console.\n", + "stream = team.run_stream(task=\"Write a 4-line poem about the ocean.\")\n", + "# Use asyncio.run(...) when running in a script.\n", + "await Console(stream)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "From the console output, you can see the team solicited feedback from the user\n", + "through `user_proxy` to approve the generated poem.\n", + "\n", + "You can provide your own input function to the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n", + "to customize the feedback process." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Providing Feedback to the Next Run\n", + "\n", + "Often times, an application or a user interacts with the team of agents in an interactive loop:\n", + "the team runs until termination, \n", + "the application or user provides feedback, and the team runs again with the feedback.\n", + "\n", + "This approach is useful in a persisted session\n", + "with asynchronous communication between the team and the application/user:\n", + "Once a team finishes a run, the application saves the state of the team,\n", + "puts it in a persistent storage, and resumes the team when the feedback arrives.\n", + "\n", + "```{note}\n", + "For how to save and load the state of a team, please refer to [Managing State](./state.ipynb).\n", + "This section will focus on the feedback mechanisms.\n", + "```\n", + "\n", + "The following diagram illustrates the flow of control in this approach:\n", + "\n", + "![human-in-the-loop-termination](./human-in-the-loop-termination.svg)\n", + "\n", + "There are two ways to implement this approach:\n", + "\n", + "- Set the maximum number of turns so that the team always stops after the specified number of turns.\n", + "- Use termination conditions such as {py:class}`~autogen_agentchat.conditions.TextMentionTermination` and {py:class}`~autogen_agentchat.conditions.HandoffTermination` to allow the team to decide when to stop and give control back, given the team's internal state.\n", + "\n", + "You can use both methods together to achieve your desired behavior." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Max Turns\n", + "\n", + "This method allows you to pause the team for user input by setting a maximum number of turns. For instance, you can configure the team to stop after the first agent responds by setting `max_turns` to 1. This is particularly useful in scenarios where continuous user engagement is required, such as in a chatbot.\n", + "\n", + "To implement this, set the `max_turns` parameter in the {py:meth}`~autogen_agentchat.teams.RoundRobinGroupChat` constructor.\n", + "\n", + "```python\n", + "team = RoundRobinGroupChat([...], max_turns=1)\n", + "```\n", + "\n", + "Once the team stops, the turn count will be reset. When you resume the team,\n", + "it will start from 0 again. However, the team's internal state will be preserved,\n", + "for example, the {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` will\n", + "resume from the next agent in the list with the same conversation history.\n", + "\n", + "```{note}\n", + "`max_turn` is specific to the team class and is currently only supported by\n", + "{py:class}`~autogen_agentchat.teams.RoundRobinGroupChat`, {py:class}`~autogen_agentchat.teams.SelectorGroupChat`, and {py:class}`~autogen_agentchat.teams.Swarm`.\n", + "When used with termination conditions, the team will stop when either condition is met.\n", + "```\n", + "\n", + "Here is an example of how to use `max_turns` in a {py:class}`~autogen_agentchat.teams.RoundRobinGroupChat` for a poetry generation task\n", + "with a maximum of 1 turn:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "Write a 4-line poem about the ocean.\n", + "---------- assistant ----------\n", + "Endless waves in a dance with the shore, \n", + "Whispers of secrets in tales from the roar, \n", + "Beneath the vast sky, where horizons blend, \n", + "The ocean’s embrace is a timeless friend. \n", + "TERMINATE\n", + "[Prompt tokens: 46, Completion tokens: 48]\n", + "---------- Summary ----------\n", + "Number of messages: 2\n", + "Finish reason: Maximum number of turns 1 reached.\n", + "Total prompt tokens: 46\n", + "Total completion tokens: 48\n", + "Duration: 1.63 seconds\n", + "---------- user ----------\n", + "Can you make it about a person and its relationship with the ocean\n", + "---------- assistant ----------\n", + "She walks along the tide, where dreams intertwine, \n", + "With every crashing wave, her heart feels aligned, \n", + "In the ocean's embrace, her worries dissolve, \n", + "A symphony of solace, where her spirit evolves. \n", + "TERMINATE\n", + "[Prompt tokens: 117, Completion tokens: 49]\n", + "---------- Summary ----------\n", + "Number of messages: 2\n", + "Finish reason: Maximum number of turns 1 reached.\n", + "Total prompt tokens: 117\n", + "Total completion tokens: 49\n", + "Duration: 1.21 seconds\n" + ] + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create the agents.\n", + "model_client = OpenAIChatCompletionClient(model=\"gpt-4o-mini\")\n", + "assistant = AssistantAgent(\"assistant\", model_client=model_client)\n", + "\n", + "# Create the team setting a maximum number of turns to 1.\n", + "team = RoundRobinGroupChat([assistant], max_turns=1)\n", + "\n", + "task = \"Write a 4-line poem about the ocean.\"\n", + "while True:\n", + " # Run the conversation and stream to the console.\n", + " stream = team.run_stream(task=task)\n", + " # Use asyncio.run(...) when running in a script.\n", + " await Console(stream)\n", + " # Get the user response.\n", + " task = input(\"Enter your feedback (type 'exit' to leave): \")\n", + " if task.lower().strip() == \"exit\":\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see that the team stopped immediately after one agent responded." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Using Termination Conditions\n", + "\n", + "We have already seen several examples of termination conditions in the previous sections.\n", + "In this section, we focus on {py:class}`~autogen_agentchat.conditions.HandoffTermination`\n", + "which stops the team when an agent sends a {py:class}`~autogen_agentchat.messages.HandoffMessage` message.\n", + "\n", + "Let's create a team with a single {py:class}`~autogen_agentchat.agents.AssistantAgent` agent\n", + "with a handoff setting, and run the team with a task that requires additional input from the user\n", + "because the agent doesn't have relevant tools to continue processing the task.\n", + "\n", + "```{note}\n", + "The model used with {py:class}`~autogen_agentchat.agents.AssistantAgent` must support tool call\n", + "to use the handoff feature.\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "What is the weather in New York?\n", + "---------- lazy_assistant ----------\n", + "[FunctionCall(id='call_nSjgvWCUYo5ccacBz7yzrPLN', arguments='{}', name='transfer_to_user')]\n", + "[Prompt tokens: 68, Completion tokens: 12]\n", + "---------- lazy_assistant ----------\n", + "[FunctionExecutionResult(content='Transfer to user.', call_id='call_nSjgvWCUYo5ccacBz7yzrPLN')]\n", + "---------- lazy_assistant ----------\n", + "Transfer to user.\n", + "---------- Summary ----------\n", + "Number of messages: 4\n", + "Finish reason: Handoff to user from lazy_assistant detected.\n", + "Total prompt tokens: 68\n", + "Total completion tokens: 12\n", + "Duration: 0.75 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='What is the weather in New York?', type='TextMessage'), ToolCallRequestEvent(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=68, completion_tokens=12), content=[FunctionCall(id='call_nSjgvWCUYo5ccacBz7yzrPLN', arguments='{}', name='transfer_to_user')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='lazy_assistant', models_usage=None, content=[FunctionExecutionResult(content='Transfer to user.', call_id='call_nSjgvWCUYo5ccacBz7yzrPLN')], type='ToolCallExecutionEvent'), HandoffMessage(source='lazy_assistant', models_usage=None, target='user', content='Transfer to user.', type='HandoffMessage')], stop_reason='Handoff to user from lazy_assistant detected.')" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from autogen_agentchat.agents import AssistantAgent\n", + "from autogen_agentchat.base import Handoff\n", + "from autogen_agentchat.conditions import HandoffTermination, TextMentionTermination\n", + "from autogen_agentchat.teams import RoundRobinGroupChat\n", + "from autogen_agentchat.ui import Console\n", + "from autogen_ext.models.openai import OpenAIChatCompletionClient\n", + "\n", + "# Create an OpenAI model client.\n", + "model_client = OpenAIChatCompletionClient(\n", + " model=\"gpt-4o-2024-08-06\",\n", + " # api_key=\"sk-...\", # Optional if you have an OPENAI_API_KEY env variable set.\n", + ")\n", + "\n", + "# Create a lazy assistant agent that always hands off to the user.\n", + "lazy_agent = AssistantAgent(\n", + " \"lazy_assistant\",\n", + " model_client=model_client,\n", + " handoffs=[Handoff(target=\"user\", message=\"Transfer to user.\")],\n", + " system_message=\"Always transfer to user when you don't know the answer. Respond 'TERMINATE' when task is complete.\",\n", + ")\n", + "\n", + "# Define a termination condition that checks for handoff message targetting helper and text \"TERMINATE\".\n", + "handoff_termination = HandoffTermination(target=\"user\")\n", + "text_termination = TextMentionTermination(\"TERMINATE\")\n", + "combined_termination = handoff_termination | text_termination\n", + "\n", + "# Create a single-agent team.\n", + "lazy_agent_team = RoundRobinGroupChat([lazy_agent], termination_condition=combined_termination)\n", + "\n", + "# Run the team and stream to the console.\n", + "task = \"What is the weather in New York?\"\n", + "await Console(lazy_agent_team.run_stream(task=task))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see the team stopped due to the handoff message was detected.\n", + "Let's continue the team by providing the information the agent needs." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "---------- user ----------\n", + "The weather in New York is sunny.\n", + "---------- lazy_assistant ----------\n", + "Great to hear that it's sunny in New York! Is there anything else you'd like to know or discuss?\n", + "[Prompt tokens: 109, Completion tokens: 23]\n", + "---------- lazy_assistant ----------\n", + "TERMINATE\n", + "[Prompt tokens: 138, Completion tokens: 5]\n", + "---------- Summary ----------\n", + "Number of messages: 3\n", + "Finish reason: Text 'TERMINATE' mentioned\n", + "Total prompt tokens: 247\n", + "Total completion tokens: 28\n", + "Duration: 1.44 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "TaskResult(messages=[TextMessage(source='user', models_usage=None, content='The weather in New York is sunny.', type='TextMessage'), TextMessage(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=109, completion_tokens=23), content=\"Great to hear that it's sunny in New York! Is there anything else you'd like to know or discuss?\", type='TextMessage'), TextMessage(source='lazy_assistant', models_usage=RequestUsage(prompt_tokens=138, completion_tokens=5), content='TERMINATE', type='TextMessage')], stop_reason=\"Text 'TERMINATE' mentioned\")" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "await Console(lazy_agent_team.run_stream(task=\"The weather in New York is sunny.\"))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can see the team continued after the user provided the information." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}