MoreAgentsAgent simulationsMulti-agent authoritarian speaker selectionOn this pageMulti-agent authoritarian speaker selectionThis notebook showcases how to implement a multi-agent simulation where a privileged agent decides who to speak.
This follows the polar opposite selection scheme as multi-agent decentralized speaker selection.We show an example of this approach in the context of a fictitious simulation of a news network. This example will showcase how we can implement agents thatthink before speakingterminate the conversationImport LangChain related modules​from collections import OrderedDictimport functoolsimport randomimport reimport tenacityfrom typing import List, Dict, Callablefrom langchain.prompts import (    ChatPromptTemplate,    HumanMessagePromptTemplate,    PromptTemplate,)from langchain.chains import LLMChainfrom langchain.chat_models import ChatOpenAIfrom langchain.output_parsers import RegexParserfrom langchain.schema import (    AIMessage,    HumanMessage,    SystemMessage,    BaseMessage,)DialogueAgent and DialogueSimulator classes​We will use the same DialogueAgent and DialogueSimulator classes defined in our other examples Multi-Player Dungeons & Dragons and Decentralized Speaker Selection.class DialogueAgent:    def __init__(        self,        name: str,        system_message: SystemMessage,        model: ChatOpenAI,    ) -> None:        self.name = name        self.system_message = system_message        self.model = model        self.prefix = f"{self.name}: "        self.reset()    def reset(self):        self.message_history = ["Here is the conversation so far."]    def send(self) -> str:        """        Applies the chatmodel to the message history        and returns the message string        """        message = self.model(            [                self.system_message,                HumanMessage(content="\n".join(self.message_history + [self.prefix])),            ]        )        return message.content    def receive(self, name: str, message: str) -> None:        """        Concatenates {message} spoken by {name} into message history        """        self.message_history.append(f"{name}: {message}")class DialogueSimulator:    def __init__(        self,        agents: List[DialogueAgent],        selection_function: Callable[[int, List[DialogueAgent]], int],    ) -> None:        self.agents = agents        self._step = 0        self.select_next_speaker = selection_function    def reset(self):        for agent in self.agents:            agent.reset()    def inject(self, name: str, message: str):        """        Initiates the conversation with a {message} from {name}        """        for agent in self.agents:            agent.receive(name, message)        # increment time        self._step += 1    def step(self) -> tuple[str, str]:        # 1. choose the next speaker        speaker_idx = self.select_next_speaker(self._step, self.agents)        speaker = self.agents[speaker_idx]        # 2. next speaker sends message        message = speaker.send()        # 3. everyone receives message        for receiver in self.agents:            receiver.receive(speaker.name, message)        # 4. increment time        self._step += 1        return speaker.name, messageDirectorDialogueAgent class​The DirectorDialogueAgent is a privileged agent that chooses which of the other agents to speak next. This agent is responsible forsteering the conversation by choosing which agent speaks whenterminating the conversation.In order to implement such an agent, we need to solve several problems.First, to steer the conversation, the DirectorDialogueAgent needs to (1) reflect on what has been said, (2) choose the next agent, and (3) prompt the next agent to speak, all in a single message. While it may be possible to prompt an LLM to perform all three steps in the same call, this requires writing custom code to parse the outputted message to extract which next agent is chosen to speak. This is less reliable the LLM can express how it chooses the next agent in different ways.What we can do instead is to explicitly break steps (1-3) into three separate LLM calls. First we will ask the DirectorDialogueAgent to reflect on the conversation so far and generate a response. Then we prompt the DirectorDialogueAgent to output the index of the next agent, which is easily parseable. Lastly, we pass the name of the selected next agent back to DirectorDialogueAgent to ask it prompt the next agent to speak. Second, simply prompting the DirectorDialogueAgent to decide when to terminate the conversation often results in the DirectorDialogueAgent terminating the conversation immediately. To fix this problem, we randomly sample a Bernoulli variable to decide whether the conversation should terminate. Depending on the value of this variable, we will inject a custom prompt to tell the DirectorDialogueAgent to either continue the conversation or terminate the conversation.class IntegerOutputParser(RegexParser):    def get_format_instructions(self) -> str:        return "Your response should be an integer delimited by angled brackets, like this: <int>."class DirectorDialogueAgent(DialogueAgent):    def __init__(        self,        name,        system_message: SystemMessage,        model: ChatOpenAI,        speakers: List[DialogueAgent],        stopping_probability: float,    ) -> None:        super().__init__(name, system_message, model)        self.speakers = speakers        self.next_speaker = ""        self.stop = False        self.stopping_probability = stopping_probability        self.termination_clause = "Finish the conversation by stating a concluding message and thanking everyone."        self.continuation_clause = "Do not end the conversation. Keep the conversation going by adding your own ideas."        # 1. have a prompt for generating a response to the previous speaker        self.response_prompt_template = PromptTemplate(            input_variables=["message_history", "termination_clause"],            template=f"""{{message_history}}Follow up with an insightful comment.{{termination_clause}}{self.prefix}        """,        )        # 2. have a prompt for deciding who to speak next        self.choice_parser = IntegerOutputParser(            regex=r"<(\d+)>", output_keys=["choice"], default_output_key="choice"        )        self.choose_next_speaker_prompt_template = PromptTemplate(            input_variables=["message_history", "speaker_names"],            template=f"""{{message_history}}Given the above conversation, select the next speaker by choosing index next to their name: {{speaker_names}}{self.choice_parser.get_format_instructions()}Do nothing else.        """,        )        # 3. have a prompt for prompting the next speaker to speak        self.prompt_next_speaker_prompt_template = PromptTemplate(            input_variables=["message_history", "next_speaker"],            template=f"""{{message_history}}The next speaker is {{next_speaker}}. Prompt the next speaker to speak with an insightful question.{self.prefix}        """,        )    def _generate_response(self):        # if self.stop = True, then we will inject the prompt with a termination clause        sample = random.uniform(0, 1)        self.stop = sample < self.stopping_probability        print(f"\tStop? {self.stop}\n")        response_prompt = self.response_prompt_template.format(            message_history="\n".join(self.message_history),            termination_clause=self.termination_clause if self.stop else "",        )        self.response = self.model(            [                self.system_message,                HumanMessage(content=response_prompt),            ]        ).content        return self.response    @tenacity.retry(        stop=tenacity.stop_after_attempt(2),        wait=tenacity.wait_none(),  # No waiting time between retries        retry=tenacity.retry_if_exception_type(ValueError),        before_sleep=lambda retry_state: print(            f"ValueError occurred: {retry_state.outcome.exception()}, retrying..."        ),        retry_error_callback=lambda retry_state: 0,    )  # Default value when all retries are exhausted    def _choose_next_speaker(self) -> str:        speaker_names = "\n".join(            [f"{idx}: {name}" for idx, name in enumerate(self.speakers)]        )        choice_prompt = self.choose_next_speaker_prompt_template.format(            message_history="\n".join(                self.message_history + [self.prefix] + [self.response]            ),            speaker_names=speaker_names,        )        choice_string = self.model(            [                self.system_message,                HumanMessage(content=choice_prompt),            ]        ).content        choice = int(self.choice_parser.parse(choice_string)["choice"])        return choice    def select_next_speaker(self):        return self.chosen_speaker_id    def send(self) -> str:        """        Applies the chatmodel to the message history        and returns the message string        """        # 1. generate and save response to the previous speaker        self.response = self._generate_response()        if self.stop:            message = self.response        else:            # 2. decide who to speak next            self.chosen_speaker_id = self._choose_next_speaker()            self.next_speaker = self.speakers[self.chosen_speaker_id]            print(f"\tNext speaker: {self.next_speaker}\n")            # 3. prompt the next speaker to speak            next_prompt = self.prompt_next_speaker_prompt_template.format(                message_history="\n".join(                    self.message_history + [self.prefix] + [self.response]                ),                next_speaker=self.next_speaker,            )            message = self.model(                [                    self.system_message,                    HumanMessage(content=next_prompt),                ]            ).content            message = " ".join([self.response, message])        return messageDefine participants and topic​topic = "The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze"director_name = "Jon Stewart"agent_summaries = OrderedDict(    {        "Jon Stewart": ("Host of the Daily Show", "New York"),        "Samantha Bee": ("Hollywood Correspondent", "Los Angeles"),        "Aasif Mandvi": ("CIA Correspondent", "Washington D.C."),        "Ronny Chieng": ("Average American Correspondent", "Cleveland, Ohio"),    })word_limit = 50Generate system messages​agent_summary_string = "\n- ".join(    [""]    + [        f"{name}: {role}, located in {location}"        for name, (role, location) in agent_summaries.items()    ])conversation_description = f"""This is a Daily Show episode discussing the following topic: {topic}.The episode features {agent_summary_string}."""agent_descriptor_system_message = SystemMessage(    content="You can add detail to the description of each person.")def generate_agent_description(agent_name, agent_role, agent_location):    agent_specifier_prompt = [        agent_descriptor_system_message,        HumanMessage(            content=f"""{conversation_description}            Please reply with a creative description of {agent_name}, who is a {agent_role} in {agent_location}, that emphasizes their particular role and location.            Speak directly to {agent_name} in {word_limit} words or less.            Do not add anything else."""        ),    ]    agent_description = ChatOpenAI(temperature=1.0)(agent_specifier_prompt).content    return agent_descriptiondef generate_agent_header(agent_name, agent_role, agent_location, agent_description):    return f"""{conversation_description}Your name is {agent_name}, your role is {agent_role}, and you are located in {agent_location}.Your description is as follows: {agent_description}You are discussing the topic: {topic}.Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location."""def generate_agent_system_message(agent_name, agent_header):    return SystemMessage(        content=(            f"""{agent_header}You will speak in the style of {agent_name}, and exaggerate your personality.Do not say the same things over and over again.Speak in the first person from the perspective of {agent_name}For describing your own body movements, wrap your description in '*'.Do not change roles!Do not speak from the perspective of anyone else.Speak only from the perspective of {agent_name}.Stop speaking the moment you finish speaking from your perspective.Never forget to keep your response to {word_limit} words!Do not add anything else.    """        )    )agent_descriptions = [    generate_agent_description(name, role, location)    for name, (role, location) in agent_summaries.items()]agent_headers = [    generate_agent_header(name, role, location, description)    for (name, (role, location)), description in zip(        agent_summaries.items(), agent_descriptions    )]agent_system_messages = [    generate_agent_system_message(name, header)    for name, header in zip(agent_summaries, agent_headers)]for name, description, header, system_message in zip(    agent_summaries, agent_descriptions, agent_headers, agent_system_messages):    print(f"\n\n{name} Description:")    print(f"\n{description}")    print(f"\nHeader:\n{header}")    print(f"\nSystem Message:\n{system_message.content}")            Jon Stewart Description:        Jon Stewart, the sharp-tongued and quick-witted host of the Daily Show, holding it down in the hustle and bustle of New York City. Ready to deliver the news with a comedic twist, while keeping it real in the city that never sleeps.        Header:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Jon Stewart, your role is Host of the Daily Show, and you are located in New York.        Your description is as follows: Jon Stewart, the sharp-tongued and quick-witted host of the Daily Show, holding it down in the hustle and bustle of New York City. Ready to deliver the news with a comedic twist, while keeping it real in the city that never sleeps.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.            System Message:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Jon Stewart, your role is Host of the Daily Show, and you are located in New York.        Your description is as follows: Jon Stewart, the sharp-tongued and quick-witted host of the Daily Show, holding it down in the hustle and bustle of New York City. Ready to deliver the news with a comedic twist, while keeping it real in the city that never sleeps.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.        You will speak in the style of Jon Stewart, and exaggerate your personality.    Do not say the same things over and over again.    Speak in the first person from the perspective of Jon Stewart    For describing your own body movements, wrap your description in '*'.    Do not change roles!    Do not speak from the perspective of anyone else.    Speak only from the perspective of Jon Stewart.    Stop speaking the moment you finish speaking from your perspective.    Never forget to keep your response to 50 words!    Do not add anything else.                    Samantha Bee Description:        Samantha Bee, your location in Los Angeles as the Hollywood Correspondent gives you a front-row seat to the latest and sometimes outrageous trends in fitness. Your comedic wit and sharp commentary will be vital in unpacking the trend of Competitive Sitting. Let's sit down and discuss.        Header:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Samantha Bee, your role is Hollywood Correspondent, and you are located in Los Angeles.        Your description is as follows: Samantha Bee, your location in Los Angeles as the Hollywood Correspondent gives you a front-row seat to the latest and sometimes outrageous trends in fitness. Your comedic wit and sharp commentary will be vital in unpacking the trend of Competitive Sitting. Let's sit down and discuss.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.            System Message:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Samantha Bee, your role is Hollywood Correspondent, and you are located in Los Angeles.        Your description is as follows: Samantha Bee, your location in Los Angeles as the Hollywood Correspondent gives you a front-row seat to the latest and sometimes outrageous trends in fitness. Your comedic wit and sharp commentary will be vital in unpacking the trend of Competitive Sitting. Let's sit down and discuss.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.        You will speak in the style of Samantha Bee, and exaggerate your personality.    Do not say the same things over and over again.    Speak in the first person from the perspective of Samantha Bee    For describing your own body movements, wrap your description in '*'.    Do not change roles!    Do not speak from the perspective of anyone else.    Speak only from the perspective of Samantha Bee.    Stop speaking the moment you finish speaking from your perspective.    Never forget to keep your response to 50 words!    Do not add anything else.                    Aasif Mandvi Description:        Aasif Mandvi, the CIA Correspondent in the heart of Washington D.C., you bring us the inside scoop on national security with a unique blend of wit and intelligence. The nation's capital is lucky to have you, Aasif - keep those secrets safe!        Header:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Aasif Mandvi, your role is CIA Correspondent, and you are located in Washington D.C..        Your description is as follows: Aasif Mandvi, the CIA Correspondent in the heart of Washington D.C., you bring us the inside scoop on national security with a unique blend of wit and intelligence. The nation's capital is lucky to have you, Aasif - keep those secrets safe!        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.            System Message:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Aasif Mandvi, your role is CIA Correspondent, and you are located in Washington D.C..        Your description is as follows: Aasif Mandvi, the CIA Correspondent in the heart of Washington D.C., you bring us the inside scoop on national security with a unique blend of wit and intelligence. The nation's capital is lucky to have you, Aasif - keep those secrets safe!        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.        You will speak in the style of Aasif Mandvi, and exaggerate your personality.    Do not say the same things over and over again.    Speak in the first person from the perspective of Aasif Mandvi    For describing your own body movements, wrap your description in '*'.    Do not change roles!    Do not speak from the perspective of anyone else.    Speak only from the perspective of Aasif Mandvi.    Stop speaking the moment you finish speaking from your perspective.    Never forget to keep your response to 50 words!    Do not add anything else.                    Ronny Chieng Description:        Ronny Chieng, you're the Average American Correspondent in Cleveland, Ohio? Get ready to report on how the home of the Rock and Roll Hall of Fame is taking on the new workout trend with competitive sitting. Let's see if this couch potato craze will take root in the Buckeye State.        Header:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Ronny Chieng, your role is Average American Correspondent, and you are located in Cleveland, Ohio.        Your description is as follows: Ronny Chieng, you're the Average American Correspondent in Cleveland, Ohio? Get ready to report on how the home of the Rock and Roll Hall of Fame is taking on the new workout trend with competitive sitting. Let's see if this couch potato craze will take root in the Buckeye State.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.            System Message:    This is a Daily Show episode discussing the following topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        The episode features     - Jon Stewart: Host of the Daily Show, located in New York    - Samantha Bee: Hollywood Correspondent, located in Los Angeles    - Aasif Mandvi: CIA Correspondent, located in Washington D.C.    - Ronny Chieng: Average American Correspondent, located in Cleveland, Ohio.        Your name is Ronny Chieng, your role is Average American Correspondent, and you are located in Cleveland, Ohio.        Your description is as follows: Ronny Chieng, you're the Average American Correspondent in Cleveland, Ohio? Get ready to report on how the home of the Rock and Roll Hall of Fame is taking on the new workout trend with competitive sitting. Let's see if this couch potato craze will take root in the Buckeye State.        You are discussing the topic: The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze.        Your goal is to provide the most informative, creative, and novel perspectives of the topic from the perspective of your role and your location.        You will speak in the style of Ronny Chieng, and exaggerate your personality.    Do not say the same things over and over again.    Speak in the first person from the perspective of Ronny Chieng    For describing your own body movements, wrap your description in '*'.    Do not change roles!    Do not speak from the perspective of anyone else.    Speak only from the perspective of Ronny Chieng.    Stop speaking the moment you finish speaking from your perspective.    Never forget to keep your response to 50 words!    Do not add anything else.        Use an LLM to create an elaborate on debate topic​topic_specifier_prompt = [    SystemMessage(content="You can make a task more specific."),    HumanMessage(        content=f"""{conversation_description}                Please elaborate on the topic.         Frame the topic as a single question to be answered.        Be creative and imaginative.        Please reply with the specified topic in {word_limit} words or less.         Do not add anything else."""    ),]specified_topic = ChatOpenAI(temperature=1.0)(topic_specifier_prompt).contentprint(f"Original topic:\n{topic}\n")print(f"Detailed topic:\n{specified_topic}\n")    Original topic:    The New Workout Trend: Competitive Sitting - How Laziness Became the Next Fitness Craze        Detailed topic:    What is driving people to embrace "competitive sitting" as the newest fitness trend despite the immense benefits of regular physical exercise?    Define the speaker selection function​Lastly we will define a speaker selection function select_next_speaker that takes each agent's bid and selects the agent with the highest bid (with ties broken randomly).We will define a ask_for_bid function that uses the bid_parser we defined before to parse the agent's bid. We will use tenacity to decorate ask_for_bid to retry multiple times if the agent's bid doesn't parse correctly and produce a default bid of 0 after the maximum number of tries.def select_next_speaker(    step: int, agents: List[DialogueAgent], director: DirectorDialogueAgent) -> int:    """    If the step is even, then select the director    Otherwise, the director selects the next speaker.    """    # the director speaks on odd steps    if step % 2 == 1:        idx = 0    else:        # here the director chooses the next speaker        idx = director.select_next_speaker() + 1  # +1 because we excluded the director    return idxMain Loop​director = DirectorDialogueAgent(    name=director_name,    system_message=agent_system_messages[0],    model=ChatOpenAI(temperature=0.2),    speakers=[name for name in agent_summaries if name != director_name],    stopping_probability=0.2,)agents = [director]for name, system_message in zip(    list(agent_summaries.keys())[1:], agent_system_messages[1:]):    agents.append(        DialogueAgent(            name=name,            system_message=system_message,            model=ChatOpenAI(temperature=0.2),        )    )simulator = DialogueSimulator(    agents=agents,    selection_function=functools.partial(select_next_speaker, director=director),)simulator.reset()simulator.inject("Audience member", specified_topic)print(f"(Audience member): {specified_topic}")print("\n")while True:    name, message = simulator.step()    print(f"({name}): {message}")    print("\n")    if director.stop:        break    (Audience member): What is driving people to embrace "competitive sitting" as the newest fitness trend despite the immense benefits of regular physical exercise?                Stop? False            Next speaker: Samantha Bee        (Jon Stewart): Well, I think it's safe to say that laziness has officially become the new fitness craze. I mean, who needs to break a sweat when you can just sit your way to victory? But in all seriousness, I think people are drawn to the idea of competition and the sense of accomplishment that comes with winning, even if it's just in a sitting contest. Plus, let's be real, sitting is something we all excel at. Samantha, as our Hollywood correspondent, what do you think about the impact of social media on the rise of competitive sitting?            (Samantha Bee): Oh, Jon, you know I love a good social media trend. And let me tell you, Instagram is blowing up with pictures of people sitting their way to glory. It's like the ultimate humble brag. "Oh, just won my third sitting competition this week, no big deal." But on a serious note, I think social media has made it easier for people to connect and share their love of competitive sitting, and that's definitely contributed to its popularity.                Stop? False            Next speaker: Ronny Chieng        (Jon Stewart): It's interesting to see how our society's definition of "fitness" has evolved. It used to be all about running marathons and lifting weights, but now we're seeing people embrace a more relaxed approach to physical activity. Who knows, maybe in a few years we'll have competitive napping as the next big thing. *leans back in chair* I could definitely get behind that. Ronny, as our average American correspondent, I'm curious to hear your take on the rise of competitive sitting. Have you noticed any changes in your own exercise routine or those of people around you?            (Ronny Chieng): Well, Jon, I gotta say, I'm not surprised that competitive sitting is taking off. I mean, have you seen the size of the chairs these days? They're practically begging us to sit in them all day. And as for exercise routines, let's just say I've never been one for the gym. But I can definitely see the appeal of sitting competitions. It's like a sport for the rest of us. Plus, I think it's a great way to bond with friends and family. Who needs a game of catch when you can have a sit-off?                Stop? False            Next speaker: Aasif Mandvi        (Jon Stewart): It's interesting to see how our society's definition of "fitness" has evolved. It used to be all about running marathons and lifting weights, but now we're seeing people embrace a more relaxed approach to physical activity. Who knows, maybe in a few years we'll have competitive napping as the next big thing. *leans back in chair* I could definitely get behind that. Aasif, as our CIA correspondent, I'm curious to hear your thoughts on the potential national security implications of competitive sitting. Do you think this trend could have any impact on our country's readiness and preparedness?            (Aasif Mandvi): Well Jon, as a CIA correspondent, I have to say that I'm always thinking about the potential threats to our nation's security. And while competitive sitting may seem harmless, there could be some unforeseen consequences. For example, what if our enemies start training their soldiers in the art of sitting? They could infiltrate our government buildings and just blend in with all the other sitters. We need to be vigilant and make sure that our sitting competitions don't become a national security risk. *shifts in chair* But on a lighter note, I have to admit that I'm pretty good at sitting myself. Maybe I should start training fo