SelectorGroupChat implementa un equipo donde los participantes se turnan para transmitir mensajes a todos los demás miembros. Un modelo generativo (por ejemplo, un LLM) selecciona al siguiente participante basado en el contexto compartido, permitiendo así una colaboración dinámica y consciente del contexto.
Características clave:
Selección del hablante basada en modelo.
Roles y descripciones de participantes configurables.
Prevención opcional de turnos consecutivos del mismo hablante.
Personalización del mensaje de selección.
Función personalizada de selección para reemplazar la selección basada en modelo por defecto.
¿Cómo Funciona?
SelectorGroupChat es un chat grupal similar a RoundRobinGroupChat, pero con un mecanismo de selección del siguiente hablante basado en un modelo. Cuando el equipo recibe una tarea mediante los métodos run() o run_stream(), se ejecutan los siguientes pasos:
El equipo analiza el contexto actual de la conversación, incluyendo el historial y los atributos de name (nombre) y description (descripción) de los participantes, para determinar quién será el siguiente hablante utilizando un modelo generativo. Por defecto, el equipo no seleccionará al mismo participante de manera consecutiva, salvo que sea el único agente disponible. Esto se puede cambiar configurando allow_repeated_speaker=True. También puedes proporcionar una función personalizada para reemplazar la selección por defecto.
El equipo solicita al agente seleccionado que proporcione una respuesta, la cual se transmite posteriormente a todos los demás participantes.
Se verifica la condición de terminación para determinar si la conversación debe finalizar. En caso contrario, el proceso se repite desde el paso 1.
Cuando la conversación termina, el equipo retorna un TaskResult que contiene el historial completo de la conversación generada durante la tarea.
Una vez que el equipo finaliza la tarea, el contexto de la conversación se mantiene dentro del equipo y todos los participantes, permitiendo que la siguiente tarea pueda continuar desde este contexto. Para reiniciar completamente el contexto de conversación, utiliza el método reset().
En esta sección mostraremos cómo utilizar SelectorGroupChat con un ejemplo sencillo relacionado con una tarea de búsqueda web y análisis de datos.
Ejemplo: Búsqueda/Análisis Web
from typing import Sequence
from saptiva_agents.agents import AssistantAgent, UserProxyAgent
from saptiva_agents.conditions import MaxMessageTermination, TextMentionTermination
from saptiva_agents.messages import BaseAgentEvent, BaseChatMessage
from saptiva_agents.teams import SelectorGroupChat
from saptiva_agents.ui import Console
from saptiva_agents.base import SaptivaAIChatCompletionClient
Agentes
Este sistema utiliza tres agentes especializados:
Agente de planificación: Coordinador estratégico que descompone tareas complejas en subtareas manejables.
Agente de búsqueda web: Especialista en recuperación de información que utiliza la herramienta search_web_tool.
Agente analista de datos: Especialista en cálculos equipado con la herramienta percentage_change_tool.
Las herramientas search_web_tool y percentage_change_tool son herramientas externas que los agentes pueden utilizar para realizar sus tareas.
# Nota: Este ejemplo utiliza herramientas simuladas en lugar de APIs reales, únicamente para fines demostrativos.
def search_web_tool(query: str) -> str:
if "2006-2007" in query:
return """Here are the total points scored by Miami Heat players in the 2006-2007 season:
Udonis Haslem: 844 points
Dwayne Wade: 1397 points
James Posey: 550 points
...
"""
elif "2007-2008" in query:
return "The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214."
elif "2008-2009" in query:
return "The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398."
return "No data found."
def percentage_change_tool(start: float, end: float) -> float:
return ((end - start) / start) * 100
Creemos ahora los agentes especializados utilizando la clase AssistantAgent. Es importante tener en cuenta que los atributos name y description de los agentes son utilizados por el modelo para determinar quién será el siguiente hablante, por lo cual se recomienda proporcionar nombres y descripciones significativas.
model_client = SaptivaAIChatCompletionClient(model="llama3.3:70b")
planning_agent = AssistantAgent(
"PlanningAgent",
description="Un agente para planificar tareas; debe ser el primero en intervenir ante una tarea nueva.",
model_client=model_client,
system_message="""
Eres un agente planificador.
Tu tarea es descomponer tareas complejas en subtareas manejables.
Tus miembros del equipo son:
WebSearchAgent: Busca información
DataAnalystAgent: Realiza cálculos
Solo planificas y delegas tareas, no las ejecutas tú mismo.
Al asignar tareas, utiliza este formato:
1. <agente> : <tarea>
Tras completar todas las tareas, resume los resultados y finaliza con "TERMINATE".
""",
)
web_search_agent = AssistantAgent(
"WebSearchAgent",
description="Un agente para buscar información en la web.",
tools=[search_web_tool],
model_client=model_client,
system_message="""
Eres un agente de búsqueda web.
Tu única herramienta es search_tool - úsala para encontrar información.
Realiza solo una búsqueda a la vez.
Cuando obtengas resultados, nunca realices cálculos con ellos.
""",
)
data_analyst_agent = AssistantAgent(
"DataAnalystAgent",
description="Un agente para realizar cálculos.",
model_client=model_client,
tools=[percentage_change_tool],
system_message="""
Eres un analista de datos.
Dadas las tareas asignadas, analiza los datos y proporciona resultados usando las herramientas provistas.
Si no has visto los datos, solicítalos.
""",
)
Nota:
Por defecto, AssistantAgent devuelve la salida de la herramienta como respuesta. Si tu herramienta no retorna una cadena en lenguaje natural correctamente formada, podrías añadir un paso de reflexión configurando reflect_on_tool_use=True al crear el agente. Esto permite al agente reflexionar sobre la salida de la herramienta y dar una respuesta en lenguaje natural.
Flujo de Trabajo
La tarea es recibida por SelectorGroupChat, que selecciona al agente más apropiado (normalmente el agente planificador) para manejar la tarea inicial.
El agente planificador analiza la tarea, la divide en subtareas y asigna cada una al agente más apropiado usando el formato: <agente> : <tarea>.
Según el contexto de la conversación, el administrador de SelectorGroupChat selecciona dinámicamente al siguiente agente para manejar la subtarea asignada.
El agente de búsqueda web realiza búsquedas una a una, guardando resultados en el historial compartido.
El analista de datos procesa la información usando herramientas de cálculo cuando se selecciona.
El proceso continúa hasta que:
El agente planificador determina que las subtareas están completas y envía "TERMINATE".
Se cumple una condición alternativa de terminación (por ejemplo, un número máximo de mensajes).
Cuando definas tus agentes, asegúrate de incluir descripciones claras, pues estas se usan para decidir el siguiente agente en hablar.
Condiciones de Terminación
Utilizaremos dos condiciones de terminación:
TextMentionTermination: finaliza la conversación cuando el agente planificador envía "TERMINATE".
MaxMessageTermination: limita la conversación a 25 mensajes para evitar bucles infinitos.
SelectorGroupChat usa un modelo para seleccionar al próximo agente basado en el contexto conversacional. Utilizaremos un mensaje de selección personalizado para ajustarnos al flujo de trabajo.
select_prompt = """Selecciona un agente para realizar la tarea.
{roles}
Contexto actual de la conversación:
{history}
Lee la conversación anterior, luego selecciona un agente de {participants} para realizar la siguiente tarea.
Asegúrate de que el agente planificador haya asignado tareas antes de que otros agentes comiencen.
Selecciona únicamente un agente.
"""
Consejo
Intente no sobrecargar el modelo con demasiadas instrucciones en el selector.
¿Qué es demasiado? Depende de las capacidades del modelo que esté utilizando.
Por lo general, si escribe varias condiciones para cada agente, es una señal de que debería considerar usar una función de selección personalizada o dividir la tarea en tareas más pequeñas y secuenciales que sean gestionadas por agentes o equipos separados.
Ejecutando el Equipo
Creamos el equipo con los agentes, condiciones de terminación y mensaje personalizado:
team = SelectorGroupChat(
[planning_agent, web_search_agent, data_analyst_agent],
model_client=model_client,
termination_condition=termination,
selector_prompt=selector_prompt,
allow_repeated_speaker=True, # Permitir turnos consecutivos del mismo agente.
)
Ahora podemos ejecutar el equipo con una tarea relacionada con la búsqueda y análisis de datos sobre un jugador de la NBA.
task = "Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?"
# Utilice `asyncio.run(...)` cuando lo ejecute en un script
await Console(team.run_stream(task=task))
---------- user ----------
Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?
---------- PlanningAgent ----------
To complete this task, we need to perform the following subtasks:
1. Find out which Miami Heat player had the highest points in the 2006-2007 season.
2. Gather data on this player's total rebounds for the 2007-2008 season.
3. Gather data on this player's total rebounds for the 2008-2009 season.
4. Calculate the percentage change in the player's total rebounds between the 2007-2008 and 2008-2009 seasons.
I'll assign these tasks accordingly:
1. WebSearchAgent: Search for the Miami Heat player with the highest points in the 2006-2007 NBA season.
2. WebSearchAgent: Find the total rebounds for this player in the 2007-2008 NBA season.
3. WebSearchAgent: Find the total rebounds for this player in the 2008-2009 NBA season.
4. DataAnalystAgent: Calculate the percentage change in total rebounds from the 2007-2008 season to the 2008-2009 season for this player.
---------- WebSearchAgent ----------
[FunctionCall(id='call_89tUNHaAM0kKQYPJLleGUKK7', arguments='{"query":"Miami Heat player highest points 2006-2007 season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', name='search_web_tool', call_id='call_89tUNHaAM0kKQYPJLleGUKK7', is_error=False)]
---------- WebSearchAgent ----------
Here are the total points scored by Miami Heat players in the 2006-2007 season:
Udonis Haslem: 844 points
Dwayne Wade: 1397 points
James Posey: 550 points
...
---------- WebSearchAgent ----------
The Miami Heat player with the highest points in the 2006-2007 season was Dwyane Wade, with 1,397 points.
Next, I will search for Dwyane Wade's total rebounds for the 2007-2008 season.
---------- WebSearchAgent ----------
[FunctionCall(id='call_RC55TkSjG3JXRuVOTPrcE1RL', arguments='{"query":"Dwyane Wade total rebounds 2007-2008 season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', name='search_web_tool', call_id='call_RC55TkSjG3JXRuVOTPrcE1RL', is_error=False)]
---------- WebSearchAgent ----------
The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.
---------- WebSearchAgent ----------
[FunctionCall(id='call_pBXoABrErDow0rZjw3tjOZol', arguments='{"query":"Dwyane Wade total rebounds 2008-2009 season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', name='search_web_tool', call_id='call_pBXoABrErDow0rZjw3tjOZol', is_error=False)]
---------- WebSearchAgent ----------
The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.
---------- DataAnalystAgent ----------
[FunctionCall(id='call_qMxxXtcJsiK8KFSSCx3zm0is', arguments='{"start":214,"end":398}', name='percentage_change_tool')]
---------- DataAnalystAgent ----------
[FunctionExecutionResult(content='85.98130841121495', name='percentage_change_tool', call_id='call_qMxxXtcJsiK8KFSSCx3zm0is', is_error=False)]
---------- DataAnalystAgent ----------
85.98130841121495
---------- PlanningAgent ----------
The player with the highest points for the Miami Heat in the 2006-2007 NBA season was Dwyane Wade, who scored 1,397 points. The percentage change in Dwyane Wade's total rebounds from 214 in the 2007-2008 season to 398 in the 2008-2009 season is approximately 85.98%.
TERMINATE
TaskResult(messages=[TextMessage(source='user', models_usage=None, metadata={}, content='Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?', type='TextMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=161, completion_tokens=220), metadata={}, content="To complete this task, we need to perform the following subtasks:\n\n1. Find out which Miami Heat player had the highest points in the 2006-2007 season.\n2. Gather data on this player's total rebounds for the 2007-2008 season.\n3. Gather data on this player's total rebounds for the 2008-2009 season.\n4. Calculate the percentage change in the player's total rebounds between the 2007-2008 and 2008-2009 seasons.\n\nI'll assign these tasks accordingly:\n\n1. WebSearchAgent: Search for the Miami Heat player with the highest points in the 2006-2007 NBA season.\n2. WebSearchAgent: Find the total rebounds for this player in the 2007-2008 NBA season.\n3. WebSearchAgent: Find the total rebounds for this player in the 2008-2009 NBA season.\n4. DataAnalystAgent: Calculate the percentage change in total rebounds from the 2007-2008 season to the 2008-2009 season for this player.", type='TextMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=368, completion_tokens=27), metadata={}, content=[FunctionCall(id='call_89tUNHaAM0kKQYPJLleGUKK7', arguments='{"query":"Miami Heat player highest points 2006-2007 season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, metadata={}, content=[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', name='search_web_tool', call_id='call_89tUNHaAM0kKQYPJLleGUKK7', is_error=False)], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, metadata={}, content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', type='ToolCallSummaryMessage'), ThoughtEvent(source='WebSearchAgent', models_usage=None, metadata={}, content="The Miami Heat player with the highest points in the 2006-2007 season was Dwyane Wade, with 1,397 points.\n\nNext, I will search for Dwyane Wade's total rebounds for the 2007-2008 season.", type='ThoughtEvent'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=460, completion_tokens=83), metadata={}, content=[FunctionCall(id='call_RC55TkSjG3JXRuVOTPrcE1RL', arguments='{"query":"Dwyane Wade total rebounds 2007-2008 season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, metadata={}, content=[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', name='search_web_tool', call_id='call_RC55TkSjG3JXRuVOTPrcE1RL', is_error=False)], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, metadata={}, content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', type='ToolCallSummaryMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=585, completion_tokens=28), metadata={}, content=[FunctionCall(id='call_pBXoABrErDow0rZjw3tjOZol', arguments='{"query":"Dwyane Wade total rebounds 2008-2009 season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, metadata={}, content=[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', name='search_web_tool', call_id='call_pBXoABrErDow0rZjw3tjOZol', is_error=False)], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, metadata={}, content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', type='ToolCallSummaryMessage'), ToolCallRequestEvent(source='DataAnalystAgent', models_usage=RequestUsage(prompt_tokens=496, completion_tokens=21), metadata={}, content=[FunctionCall(id='call_qMxxXtcJsiK8KFSSCx3zm0is', arguments='{"start":214,"end":398}', name='percentage_change_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='DataAnalystAgent', models_usage=None, metadata={}, content=[FunctionExecutionResult(content='85.98130841121495', name='percentage_change_tool', call_id='call_qMxxXtcJsiK8KFSSCx3zm0is', is_error=False)], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='DataAnalystAgent', models_usage=None, metadata={}, content='85.98130841121495', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=528, completion_tokens=80), metadata={}, content="The player with the highest points for the Miami Heat in the 2006-2007 NBA season was Dwyane Wade, who scored 1,397 points. The percentage change in Dwyane Wade's total rebounds from 214 in the 2007-2008 season to 398 in the 2008-2009 season is approximately 85.98%.\n\nTERMINATE", type='TextMessage')], stop_reason="Text 'TERMINATE' mentioned")
Como podemos ver, después de que el Agente de Búsqueda Web realiza las búsquedas necesarias y el Agente Analista de Datos completa los cálculos requeridos, descubrimos que ¡Dwyane Wade fue el jugador de los Miami Heat con más puntos en la temporada 2006-2007 y que el cambio porcentual en sus rebotes totales entre las temporadas 2007-2008 y 2008-2009 es del 85.98%!
Función Personalizada para Selección
En ocasiones, queremos un mejor control sobre el proceso de selección. Para lograrlo, podemos definir el argumento selector_func con una función personalizada que reemplace la selección predeterminada basada en el modelo. Esto nos permite implementar lógicas más complejas de selección y transiciones basadas en el estado.
Por ejemplo, podríamos querer que el Agente de Planificación hable inmediatamente después de cualquier agente especializado para verificar el progreso.
Nota
Retornar None desde la función personalizada del selector utilizará la selección basada en modelo predeterminada.
def selector_func(messages: Sequence[BaseAgentEvent | BaseChatMessage]) -> str | None:
# Si el último mensaje no es del agente planificador, selecciona al agente planificador
if messages[-1].source != planning_agent.name:
return planning_agent.name
# De lo contrario, usa la selección predeterminada del modelo
return None
# Reiniciamos el equipo anterior y ejecutamos nuevamente el chat con la función personalizada del selector.
await team.reset()
team = SelectorGroupChat(
[planning_agent, web_search_agent, data_analyst_agent],
model_client=model_client,
termination_condition=termination,
selector_prompt=selector_prompt,
allow_repeated_speaker=True,
selector_func=selector_func,
)
await Console(team.run_stream(task=task))
---------- user ----------
Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?
---------- PlanningAgent ----------
To answer this question, we need to follow these steps:
1. Identify the Miami Heat player with the highest points in the 2006-2007 season.
2. Retrieve the total rebounds of that player for the 2007-2008 and 2008-2009 seasons.
3. Calculate the percentage change in his total rebounds between the two seasons.
Let's delegate these tasks:
1. WebSearchAgent: Find the Miami Heat player with the highest points in the 2006-2007 NBA season.
2. WebSearchAgent: Retrieve the total rebounds for the identified player during the 2007-2008 NBA season.
3. WebSearchAgent: Retrieve the total rebounds for the identified player during the 2008-2009 NBA season.
4. DataAnalystAgent: Calculate the percentage change in total rebounds between the 2007-2008 and 2008-2009 seasons for the player found.
---------- WebSearchAgent ----------
[FunctionCall(id='call_Pz82ndNLSV4cH0Sg6g7ArP4L', arguments='{"query":"Miami Heat player highest points 2006-2007 season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', call_id='call_Pz82ndNLSV4cH0Sg6g7ArP4L')]
---------- WebSearchAgent ----------
Here are the total points scored by Miami Heat players in the 2006-2007 season:
Udonis Haslem: 844 points
Dwayne Wade: 1397 points
James Posey: 550 points
...
---------- PlanningAgent ----------
Great! Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season. Now, let's continue with the next tasks:
2. WebSearchAgent: Retrieve the total rebounds for Dwyane Wade during the 2007-2008 NBA season.
3. WebSearchAgent: Retrieve the total rebounds for Dwyane Wade during the 2008-2009 NBA season.
---------- WebSearchAgent ----------
[FunctionCall(id='call_3qv9so2DXFZIHtzqDIfXoFID', arguments='{"query": "Dwyane Wade total rebounds 2007-2008 season"}', name='search_web_tool'), FunctionCall(id='call_Vh7zzzWUeiUAvaYjP0If0k1k', arguments='{"query": "Dwyane Wade total rebounds 2008-2009 season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', call_id='call_3qv9so2DXFZIHtzqDIfXoFID'), FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', call_id='call_Vh7zzzWUeiUAvaYjP0If0k1k')]
---------- WebSearchAgent ----------
The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.
The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.
---------- PlanningAgent ----------
Now let's calculate the percentage change in total rebounds between the 2007-2008 and 2008-2009 seasons for Dwyane Wade.
4. DataAnalystAgent: Calculate the percentage change in total rebounds for Dwyane Wade between the 2007-2008 and 2008-2009 seasons.
---------- DataAnalystAgent ----------
[FunctionCall(id='call_FXnPSr6JVGfAWs3StIizbt2V', arguments='{"start":214,"end":398}', name='percentage_change_tool')]
---------- DataAnalystAgent ----------
[FunctionExecutionResult(content='85.98130841121495', call_id='call_FXnPSr6JVGfAWs3StIizbt2V')]
---------- DataAnalystAgent ----------
85.98130841121495
---------- PlanningAgent ----------
Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring a total of 1397 points. The percentage change in his total rebounds from the 2007-2008 season (214 rebounds) to the 2008-2009 season (398 rebounds) is approximately 86.0%.
TERMINATE
TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?', type='TextMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=161, completion_tokens=192), content="To answer this question, we need to follow these steps: \n\n1. Identify the Miami Heat player with the highest points in the 2006-2007 season.\n2. Retrieve the total rebounds of that player for the 2007-2008 and 2008-2009 seasons.\n3. Calculate the percentage change in his total rebounds between the two seasons.\n\nLet's delegate these tasks:\n\n1. WebSearchAgent: Find the Miami Heat player with the highest points in the 2006-2007 NBA season.\n2. WebSearchAgent: Retrieve the total rebounds for the identified player during the 2007-2008 NBA season.\n3. WebSearchAgent: Retrieve the total rebounds for the identified player during the 2008-2009 NBA season.\n4. DataAnalystAgent: Calculate the percentage change in total rebounds between the 2007-2008 and 2008-2009 seasons for the player found.", type='TextMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=340, completion_tokens=27), content=[FunctionCall(id='call_Pz82ndNLSV4cH0Sg6g7ArP4L', arguments='{"query":"Miami Heat player highest points 2006-2007 season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, content=[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', call_id='call_Pz82ndNLSV4cH0Sg6g7ArP4L')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=420, completion_tokens=87), content="Great! Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season. Now, let's continue with the next tasks:\n\n2. WebSearchAgent: Retrieve the total rebounds for Dwyane Wade during the 2007-2008 NBA season.\n3. WebSearchAgent: Retrieve the total rebounds for Dwyane Wade during the 2008-2009 NBA season.", type='TextMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=525, completion_tokens=71), content=[FunctionCall(id='call_3qv9so2DXFZIHtzqDIfXoFID', arguments='{"query": "Dwyane Wade total rebounds 2007-2008 season"}', name='search_web_tool'), FunctionCall(id='call_Vh7zzzWUeiUAvaYjP0If0k1k', arguments='{"query": "Dwyane Wade total rebounds 2008-2009 season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, content=[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', call_id='call_3qv9so2DXFZIHtzqDIfXoFID'), FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', call_id='call_Vh7zzzWUeiUAvaYjP0If0k1k')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.\nThe number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=569, completion_tokens=68), content="Now let's calculate the percentage change in total rebounds between the 2007-2008 and 2008-2009 seasons for Dwyane Wade.\n\n4. DataAnalystAgent: Calculate the percentage change in total rebounds for Dwyane Wade between the 2007-2008 and 2008-2009 seasons.", type='TextMessage'), ToolCallRequestEvent(source='DataAnalystAgent', models_usage=RequestUsage(prompt_tokens=627, completion_tokens=21), content=[FunctionCall(id='call_FXnPSr6JVGfAWs3StIizbt2V', arguments='{"start":214,"end":398}', name='percentage_change_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='DataAnalystAgent', models_usage=None, content=[FunctionExecutionResult(content='85.98130841121495', call_id='call_FXnPSr6JVGfAWs3StIizbt2V')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='DataAnalystAgent', models_usage=None, content='85.98130841121495', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=659, completion_tokens=76), content='Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring a total of 1397 points. The percentage change in his total rebounds from the 2007-2008 season (214 rebounds) to the 2008-2009 season (398 rebounds) is approximately 86.0%.\n\nTERMINATE', type='TextMessage')], stop_reason="Text 'TERMINATE' mentioned")
Del registro de la conversación podemos observar que el Agente de Planificación siempre habla inmediatamente después de los agentes especializados.
Consejo:
Cada agente participante realiza solo un paso (ejecutar herramientas, generar respuestas, etc.) en cada turno. Si deseas que un AssistantAgent repita hasta dejar de retornar un ToolCallSummaryMessage al completar todas las herramientas necesarias, verifica el último mensaje y devuelve el agente si es un ToolCallSummaryMessage.
Retroalimentación del Usuario
Podemos agregar UserProxyAgent al equipo para proporcionar retroalimentación del usuario durante la ejecución. Ver Human-in-the-Loop para más detalles sobre UserProxyAgent.
Para utilizar el UserProxyAgent en el ejemplo de búsqueda web, simplemente lo añadimos al equipo y actualizamos la función del selector para verificar siempre la retroalimentación del usuario después de que hable el agente planificador. Si el usuario responde con "APPROVE", la conversación continúa; de lo contrario, el agente planificador vuelve a intentarlo hasta que el usuario apruebe.
user_proxy_agent = UserProxyAgent("UserProxyAgent", description="Un proxy del usuario para aprobar o desaprobar tareas.")
def selector_func_with_user_proxy(messages: Sequence[BaseAgentEvent | BaseChatMessage]) -> str | None:
if messages[-1].source != planning_agent.name and messages[-1].source != user_proxy_agent.name:
# El agente planificador debería intervenir primero en una nueva tarea o revisar progreso.
return planning_agent.name
if messages[-1].source == planning_agent.name:
if messages[-2].source == user_proxy_agent.name and "APPROVE" in messages[-1].content.upper(): # type: ignore
# El usuario ha aprobado el plan, procedemos al siguiente agente.
return None
# Usa el proxy del usuario para obtener aprobación para continuar.
return user_proxy_agent.name
if messages[-1].source == user_proxy_agent.name:
# Si el usuario no aprueba, regresar al agente planificador.
if "APPROVE" not in messages[-1].content.upper(): # type: ignore
return planning_agent.name
return None
# Reiniciamos los agentes previos y ejecutamos nuevamente el chat con el proxy del usuario y la función del selector.
await team.reset()
team = SelectorGroupChat(
[planning_agent, web_search_agent, data_analyst_agent, user_proxy_agent],
model_client=model_client,
termination_condition=termination,
selector_prompt=selector_prompt,
selector_func=selector_func_with_user_proxy,
allow_repeated_speaker=True,
)
await Console(team.run_stream(task=task))
---------- user ----------
Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?
---------- PlanningAgent ----------
To address the user's query, we will need to perform the following tasks:
1. Identify the Miami Heat player with the highest points in the 2006-2007 season.
2. Find the total rebounds for that player in the 2007-2008 season.
3. Find the total rebounds for that player in the 2008-2009 season.
4. Calculate the percentage change in the total rebounds between the 2007-2008 and 2008-2009 seasons.
Let's assign these tasks:
1. **WebSearchAgent**: Identify the Miami Heat player with the highest points in the 2006-2007 season.
(Task 2 and 3 depend on the result of Task 1. We'll proceed with Tasks 2 and 3 once Task 1 is complete.)
---------- UserProxyAgent ----------
approve
---------- WebSearchAgent ----------
[FunctionCall(id='call_0prr3fUnG5CtisUG7QeygW0w', arguments='{"query":"Miami Heat highest points scorer 2006-2007 NBA season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', call_id='call_0prr3fUnG5CtisUG7QeygW0w')]
---------- WebSearchAgent ----------
Here are the total points scored by Miami Heat players in the 2006-2007 season:
Udonis Haslem: 844 points
Dwayne Wade: 1397 points
James Posey: 550 points
...
---------- PlanningAgent ----------
Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring 1397 points.
Next, we need to find Dwyane Wade's total rebounds for the 2007-2008 and 2008-2009 seasons:
2. **WebSearchAgent**: Find Dwyane Wade's total rebounds for the 2007-2008 season.
3. **WebSearchAgent**: Find Dwyane Wade's total rebounds for the 2008-2009 season.
---------- UserProxyAgent ----------
approve
---------- WebSearchAgent ----------
[FunctionCall(id='call_fBZe80NaBfruOVGwRWbhXyRm', arguments='{"query": "Dwyane Wade total rebounds 2007-2008 NBA season"}', name='search_web_tool'), FunctionCall(id='call_cURYibna4fGxySiL7IYt0c3s', arguments='{"query": "Dwyane Wade total rebounds 2008-2009 NBA season"}', name='search_web_tool')]
---------- WebSearchAgent ----------
[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', call_id='call_fBZe80NaBfruOVGwRWbhXyRm'), FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', call_id='call_cURYibna4fGxySiL7IYt0c3s')]
---------- WebSearchAgent ----------
The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.
The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.
---------- PlanningAgent ----------
Now that we have Dwyane Wade's total rebounds for both seasons, we can calculate the percentage change:
4. **DataAnalystAgent**: Calculate the percentage change in Dwyane Wade's total rebounds from the 2007-2008 season (214 rebounds) to the 2008-2009 season (398 rebounds).
---------- UserProxyAgent ----------
approve
---------- DataAnalystAgent ----------
[FunctionCall(id='call_z3uog7t2x0z1Suzl5hACF9hY', arguments='{"start":214,"end":398}', name='percentage_change_tool')]
---------- DataAnalystAgent ----------
[FunctionExecutionResult(content='85.98130841121495', call_id='call_z3uog7t2x0z1Suzl5hACF9hY')]
---------- DataAnalystAgent ----------
85.98130841121495
---------- PlanningAgent ----------
Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring 1397 points. His total rebounds increased from 214 in the 2007-2008 season to 398 in the 2008-2009 season, which is a percentage change of approximately 85.98%.
TERMINATE
TaskResult(messages=[TextMessage(source='user', models_usage=None, content='Who was the Miami Heat player with the highest points in the 2006-2007 season, and what was the percentage change in his total rebounds between the 2007-2008 and 2008-2009 seasons?', type='TextMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=161, completion_tokens=166), content="To address the user's query, we will need to perform the following tasks:\n\n1. Identify the Miami Heat player with the highest points in the 2006-2007 season.\n2. Find the total rebounds for that player in the 2007-2008 season.\n3. Find the total rebounds for that player in the 2008-2009 season.\n4. Calculate the percentage change in the total rebounds between the 2007-2008 and 2008-2009 seasons.\n\nLet's assign these tasks:\n\n1. **WebSearchAgent**: Identify the Miami Heat player with the highest points in the 2006-2007 season.\n \n(Task 2 and 3 depend on the result of Task 1. We'll proceed with Tasks 2 and 3 once Task 1 is complete.)", type='TextMessage'), UserInputRequestedEvent(source='UserProxyAgent', models_usage=None, request_id='2a433f88-f886-4b39-a078-ea1acdcb2f9d', content='', type='UserInputRequestedEvent'), TextMessage(source='UserProxyAgent', models_usage=None, content='approve', type='TextMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=323, completion_tokens=28), content=[FunctionCall(id='call_0prr3fUnG5CtisUG7QeygW0w', arguments='{"query":"Miami Heat highest points scorer 2006-2007 NBA season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, content=[FunctionExecutionResult(content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', call_id='call_0prr3fUnG5CtisUG7QeygW0w')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, content='Here are the total points scored by Miami Heat players in the 2006-2007 season:\n Udonis Haslem: 844 points\n Dwayne Wade: 1397 points\n James Posey: 550 points\n ...\n ', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=403, completion_tokens=112), content="Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring 1397 points.\n\nNext, we need to find Dwyane Wade's total rebounds for the 2007-2008 and 2008-2009 seasons:\n\n2. **WebSearchAgent**: Find Dwyane Wade's total rebounds for the 2007-2008 season.\n3. **WebSearchAgent**: Find Dwyane Wade's total rebounds for the 2008-2009 season.", type='TextMessage'), UserInputRequestedEvent(source='UserProxyAgent', models_usage=None, request_id='23dd4570-2391-41e9-aeea-86598499792c', content='', type='UserInputRequestedEvent'), TextMessage(source='UserProxyAgent', models_usage=None, content='approve', type='TextMessage'), ToolCallRequestEvent(source='WebSearchAgent', models_usage=RequestUsage(prompt_tokens=543, completion_tokens=73), content=[FunctionCall(id='call_fBZe80NaBfruOVGwRWbhXyRm', arguments='{"query": "Dwyane Wade total rebounds 2007-2008 NBA season"}', name='search_web_tool'), FunctionCall(id='call_cURYibna4fGxySiL7IYt0c3s', arguments='{"query": "Dwyane Wade total rebounds 2008-2009 NBA season"}', name='search_web_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='WebSearchAgent', models_usage=None, content=[FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.', call_id='call_fBZe80NaBfruOVGwRWbhXyRm'), FunctionExecutionResult(content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', call_id='call_cURYibna4fGxySiL7IYt0c3s')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='WebSearchAgent', models_usage=None, content='The number of total rebounds for Dwayne Wade in the Miami Heat season 2007-2008 is 214.\nThe number of total rebounds for Dwayne Wade in the Miami Heat season 2008-2009 is 398.', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=586, completion_tokens=70), content="Now that we have Dwyane Wade's total rebounds for both seasons, we can calculate the percentage change:\n\n4. **DataAnalystAgent**: Calculate the percentage change in Dwyane Wade's total rebounds from the 2007-2008 season (214 rebounds) to the 2008-2009 season (398 rebounds).", type='TextMessage'), UserInputRequestedEvent(source='UserProxyAgent', models_usage=None, request_id='e849d193-4ab3-4558-8560-7dbc062a0aee', content='', type='UserInputRequestedEvent'), TextMessage(source='UserProxyAgent', models_usage=None, content='approve', type='TextMessage'), ToolCallRequestEvent(source='DataAnalystAgent', models_usage=RequestUsage(prompt_tokens=655, completion_tokens=21), content=[FunctionCall(id='call_z3uog7t2x0z1Suzl5hACF9hY', arguments='{"start":214,"end":398}', name='percentage_change_tool')], type='ToolCallRequestEvent'), ToolCallExecutionEvent(source='DataAnalystAgent', models_usage=None, content=[FunctionExecutionResult(content='85.98130841121495', call_id='call_z3uog7t2x0z1Suzl5hACF9hY')], type='ToolCallExecutionEvent'), ToolCallSummaryMessage(source='DataAnalystAgent', models_usage=None, content='85.98130841121495', type='ToolCallSummaryMessage'), TextMessage(source='PlanningAgent', models_usage=RequestUsage(prompt_tokens=687, completion_tokens=74), content='Dwyane Wade was the Miami Heat player with the highest points in the 2006-2007 season, scoring 1397 points. His total rebounds increased from 214 in the 2007-2008 season to 398 in the 2008-2009 season, which is a percentage change of approximately 85.98%.\n\nTERMINATE', type='TextMessage')], stop_reason="Text 'TERMINATE' mentioned")
Ahora, la retroalimentación del usuario está incorporada al flujo de conversación, y el usuario puede aprobar o rechazar las decisiones del agente planificador.
