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human-in-the-loop section for agentchat tutorial (#4832)
* human-in-the-loop section for agentchat tutorial
This commit is contained in:
Eric Zhu
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@@ -61,6 +61,7 @@ tutorial/models
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tutorial/messages
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tutorial/agents
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tutorial/teams
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tutorial/human-in-the-loop
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tutorial/selector-group-chat
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tutorial/swarm
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tutorial/termination
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@@ -75,4 +76,3 @@ tutorial/state
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examples/index
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```
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Human-in-the-Loop\n",
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"\n",
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"In the previous section [Teams](./teams.ipynb), we have seen how to create, observe,\n",
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"and control a team of agents.\n",
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"This section will focus on how to interact with the team from your application,\n",
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"and provide human feedback to the team.\n",
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"\n",
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"There are two main ways to interact with the team from your application:\n",
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"\n",
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"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",
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"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"
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]
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{
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"source": [
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"## Providing Feedback During a Run\n",
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"\n",
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"The {py:class}`~autogen_agentchat.agents.UserProxyAgent` is a special built-in agent\n",
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"that acts as a proxy for a user to provide feedback to the team.\n",
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"\n",
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"To use the {py:class}`~autogen_agentchat.agents.UserProxyAgent`, you can create an instance of it\n",
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"and include it in the team before running the team.\n",
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"The team will decide when to call the {py:class}`~autogen_agentchat.agents.UserProxyAgent`\n",
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"to ask for feedback from the user.\n",
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"\n",
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"The following diagram illustrates how you can use \n",
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"{py:class}`~autogen_agentchat.agents.UserProxyAgent`\n",
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"to get feedback from the user during a team's run:\n",
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"\n",
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"\n",
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"\n",
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"The bold arrows indicates the flow of control during a team's run:\n",
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"when the team calls the {py:class}`~autogen_agentchat.agents.UserProxyAgent`,\n",
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"it transfers the control to the application/user, and waits for the feedback;\n",
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"once the feedback is provided, the control is transferred back to the team\n",
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"and the team continues its execution.\n",
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"\n",
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"```{note}\n",
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"When {py:class}`~autogen_agentchat.agents.UserProxyAgent` is called during a run,\n",
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"it blocks the execution of the team until the user provides feedback or errors out.\n",
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||||
"This will hold up the team's progress and put the team in an unstable state\n",
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||||
"that cannot be saved or resumed.\n",
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||||
"```\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",
|
||||
"\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
|
||||
}
|
||||
Reference in New Issue
Block a user