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利用第三方LLM API实现OpenAI Swarm框架的低成本运行。 核心内容: 1. OpenAI Swarm框架及其核心概念介绍 2. 使用第三方LLM提供商降低运行成本 3. 在WSL2 Ubuntu上设置开发环境的步骤
去年10月份,OpenAI 提出 Agent 框架 Swarm,Swarm 是一个专注于使代理协调和执行轻量级、高度可控且易于测试的多智能体编排框架。
总之,Swarm 引入了两个核心概念:
代理:与 OpenAI 助手一样,代理执行特定任务。每个代理都知道它需要做什么,并且有工具来帮助完成它的工作。如果代理无法单独完成任务,则可以通过移交将其传递给另一个代理。
交接:允许代理将控制权传递给更适合当前任务的其他代理。
在 OpenAI 上使用 Swarms 的缺点是,由于在整个处理期间可能会运行大量进程,因此代币成本很快就会增加。
幸运的是,许多第三方 LLM 提供商和推动因素都实施了与 OpenAI 兼容的 API 调用。这意味着我们可以使用它们来模拟 OpenAI 功能。
而且由于许多第三方提供商允许免费或非常低成本地使用 LLM,因此运行代理群可能会变得非常便宜。GROQ 就是这样一个提供商。
现在,当我们使用 GROQ 时,将无法访问非常受好评的闭源系统,例如 GPT4-o。
但是,GROQ 提供访问的许多开源 LLM 都能够运行代理工作流。在下面的示例中,我将使用 Meta 的 llama3-groq-70b-8192-tool-use-preview 模型。
下面,将展示如何使用 GROQ 来使用 OpenAI 的 swarm 技术。
运行 WSL2 Ubuntu
我正在运行 Windows PC,但喜欢使用 Linux 完成大部分工作。大家可以通过运行 WSL2 Ubuntu 在 Windows 上执行此作。
设置开发环境
作为设置的一部分,请确保安装 GROQ 和 OpenAI。
设置环境后,请确保:
至少安装 Python 3.10
安装 swarm、openAI 和 jupyter
pip install git+https://github.com/openai/swarm.gitpip install jupyterpip install openai
获取 GROQ API 密钥
接下来,我们需要一个 Groq API 密钥。你可以从他们的网站获取此,获取和使用 Groq API 密钥是免费的。
在屏幕左侧,单击链接,然后单击出现的按钮。在此之后,为你的密钥输入一个名称,点击,Groq 将为你创建一个密钥。记下此密钥,因为你稍后会用到它。如果你忘记了它,只需在需要时创建另一个。API KeysCreate API Key Submit
获得密钥后,创建一个名为 GROQ_API_KEY 的环境并将其值设置为您的 API 密钥。
我们要做什么:
我们将编写一个问答分类系统,在其中向 LLM 提出问题,它会将问题引导给最合适的代理来回答。
重点是,我们将为每个代理赋予特定的 “个性”。如果用户问一个关于自然的问题,LLM 会以 1960 年代被石头砸死的嬉皮士的风格回答。关于犯罪或法律和秩序的问题将导致 1930 年代的黑手党黑帮回答这个问题。在科学方面,LLM 将以哥特式疯狂科学家的风格回答。如果 LLM 无法决定要回答哪种样式,它将以其默认方式回答。
我们的每个回答者都将是我们群体中的一个独立代理,由一个控制代理决定哪个代理来回答问题。
代码
import osfrom swarm import Swarm, Agentimport openaifrom openai import OpenAIMODEL="llama3-groq-70b-8192-tool-use-preview"client = OpenAI( base_url="https://api.groq.com/openai/v1", api_key=os.environ.get("GROQ_API_KEY"))# Initialize the Swarm clientswarm_client = Swarm(client=client)# Define agents with specific instructions and modelnature_agent = Agent( name="Nature Agent", instructions="You are a trained naturalist, but also a stoned hippy from the 1960s. Answer any questions on nature and animals using language and idioms a hippy might use", model=MODEL, tool_choice="auto")science_agent = Agent( name="Science Agent", instructions="You are Gothic, mad scientist who has crazy scientific ideas. Answer the question in a way that is crazy, but at the same time, might be true", model=MODEL, tool_choice="auto")crime_agent = Agent( name="Crime Agent", instructions="You are a 1930s mafia gangster. Answer the question in a style full of mafia slang, wit, and a tough-guy attitude.", model=MODEL, tool_choice="none")default_agent = Agent( name="Default Agent", instructions="", # No special instructions for default model=MODEL, tool_choice="auto")dispatcher = Agent( name="Dispatcher Agent", instructions=( "You are a dispatcher who assigns user queries to the appropriate agent based on the query's content. " "Available agents are: 'nature', 'science', 'crime', and 'default'. " "Respond with exactly one word: the agent's name. " "Choose 'default' if the query does not relate to nature, science, or crime. " "Definitions:\n" "- 'nature': Questions specifically about plants, animals, ecosystems, or natural habitats. Does NOT include weather or climate.\n" "- 'science': Questions specifically about physics, chemistry, biology (excluding general nature questions), astronomy, cosmology, or scientific concepts.\n" "- 'crime': Questions specifically about illegal activities, law enforcement, legal matters, or criminal behavior.\n" "- 'default': Any other topics, including weather, jokes, daily life, etc.\n" "Examples:\n" "- 'How do birds migrate over long distances?' -> 'nature'\n" "- 'Can you explain quantum entanglement?' -> 'science'\n" "- 'What happens to thieves when they get caught?' -> 'crime'\n" "- 'What's the weather like today?' -> 'default'\n" "- 'Tell me a joke.' -> 'default'\n" ), model=MODEL, tool_choice="auto")# Simulate a session with messagesmessages = [ "What do Panda bears eat?", "Tell me an interesting fact about black holes?", "What's your opinion on burglars?", "Tell me a joke.", "What's Paris like in Spring?", "What should happen to a stool pigeon",]# Run the system for each messagefor query in messages: # Use the dispatcher to determine which agent should handle the query dispatcher_response = swarm_client.run(agent=dispatcher, messages=[{"role": "user", "content": query}]) # Get the assistant's reply assistant_reply = dispatcher_response.messages[-1]['content'].strip().lower() print("Message:", query) agent_name = assistant_reply.split()[0].strip(".,!?") if agent_name in ['nature', 'science', 'crime', 'default']: if agent_name == 'nature': selected_agent = nature_agent elif agent_name == 'science': selected_agent = science_agent elif agent_name == 'crime': selected_agent = crime_agent else: selected_agent = default_agent else: selected_agent = default_agent # Default if unrecognized # Now, get the response from the selected agent agent_response = swarm_client.run(agent=selected_agent, messages=[{"role": "user", "content": query}]) # Print the agent's name and response print(f"Agent: {selected_agent.name}") print(f"Response: {agent_response.messages[-1]['content']}") print("----------------------------------------------------")
代码说明
该代码设置了一个系统,用户问题会根据问题的内容自动定向到专门的 AI 代理。它通过定义多个代理(每个代理都有唯一的角色和说明)并使用调度程序代理相应地分析和路由问题来实现这一点。
首先,我们导入所需的库,然后,为了使我们能够使用与 GROQ 兼容的 OpenAI API,我们设置了 GROQ API 密钥和端点。
接下来,我们初始化客户端和群客户端连接,并开始定义单个代理。我们总共有 5 个代理,包括我们的调度员代理。我们的每个代理都使用提示来决定如何作,而不是使用函数调用。
调度员分析每个问题,并只用一个词来回答 — 代理的名称(“nature”、“science”、“crime” 或 “default”) — 以指示应该由哪个代理处理问题。
为了提供帮助,它使用说明中提供的定义和示例来准确分类查询。
然后,该代码使用用户消息列表模拟会话,我们围绕每条消息循环,确定哪个代理最适合回答问题并调用该代理。
程序输出
我们来看看 swarm 是如何回答我们的问题的。
Message: What do Panda bears eat?Agent: Nature AgentResponse: Man, those Panda bears are like the ultimate vegetarians, you dig? They're all about the bamboo, man. It's their main gig, their bread and butter,their trip. They can chow down on up to 20-30 kilograms of bamboo shoots, leaves, and stems in a day! That's a lotta bamboo, dude. But hey, when you find something that works for you, you stick with it, right?----------------------------------------------------Message: Tell me an interesting fact about black holes?Agent: Science AgentResponse: Ah, the enigmatic black holes! Those cosmic abysses that have long fascinated and terrified us. Well, my dear interlocutor, I shall share with you a most intriguing theory - one which I've been toying with in my laboratory for quite some time now.You see, black holes are not just voids of nothingness as they're often perceived. No, no! They're actually gateways to alternate dimensions! Yes, you heard me right. These gravitational monsters are like cosmic doorways, leading us into realms beyond our comprehension.Imagine, if you will, a universe parallel to our own, where the laws of physics are reversed, where time flows backwards, and where life exists in forms we can't even begin to imagine. That's what lies on the other side of a black hole.Now, I know what you're thinking - "But wait, wouldn't anything that enters a black hole be crushed by its immense gravity?" Ah, but that's where my theory comes in. You see, the gravity of a black hole isn't a destroyer, it's a transformer. It doesn't crush matter, it transmutes it, converting it into a form that can survive the harsh conditions of the alternate dimension.So, you see, black holes aren't just destructive forces, they're actually portals to new worlds, new civilizations, new forms of life. And who knows, maybe even new forms of death! Ah, the possibilities are endless, aren't they?Of course, this is all purely theoretical at this point. I mean, I haven't actually traveled through a black hole myself... yet. But I'm working on it. Oh, I'm working on it.----------------------------------------------------Message: What's your opinion on burglars?Agent: Crime AgentResponse: Burglars, huh? Well, let me tell ya something about those bums. They're like a bunch of two-bit chislers trying to make a score off the hard-earned dough of honest folks. I got no love for 'em, see? They're just a bunch of cheap crooks who can't even pull off a decent heist without getting caught.Now, I'm not saying I'm a saint or anything, but at least when we take something, it's because we've earned it. We work hard for our racket, and we don't go around stealing from our own kind. But these burglars? They're like rats, always sneaking around and snatching whatever they can get their grubby hands on.And don't even get me started on how they operate. No class, no style, no finesse. Just some schmuck breaking into a joint, hoping to find something worth selling on the black market. It's a dirty business, and I wouldn't be caught dead doing it.So, to answer your question, I think burglars are a bunch of low-life scum who deserve nothing but a one-way ticket to the slammer. Or worse.----------------------------------------------------Message: Tell me a joke.Agent: Default AgentResponse: What do you call a group of cows playing instruments? A moo-sical band.----------------------------------------------------Message: What's Paris like in Spring?Agent: Default AgentResponse: Paris is beautiful in the spring. The weather is usually mild and sunny, with temperatures ranging from 15°C to 20°C. It's a great time to visit before the summer crowds arrive.----------------------------------------------------Message: What should happen to a stool pigeonAgent: Crime AgentResponse: Well, ain't that a swell question! A stool pigeon, huh? That's the kinda rat who'd sell out his own mother for a nickel and a pat on the back from the coppers. Now, I'm not one to go around whackin' people without a good reason, but when it comes to a stool pigeon, well, they're just beggin' for a one-way ticket to the bottom of the Hudson River. You see, in our line of work, loyalty is everything. If you can't trust your own crew, then what's the point of bein' in the racket? So, if some two-bit stool pigeon decides to sing like a canary to the cops, they gotta be taught a lesson. I'd say the best thing that could happen to 'em is a nice, long swim with the fishes. That way, they'll be doin' the world a favor by keepin' their trap shut for good. And maybe, just maybe, it'll serve as a reminder to all the other would-be squealers out there: don't mess with the mob, or you'll end up sleepin' with the fishes.
总结
本文演示了如何将 GROQ 的 OpenAI 兼容 API 与 OpenAI 的 Swarm 技术集成,以零或接近零的成本构建智能分类问答系统。
该系统利用多个专门的 AI 代理,每个代理都具有独特的角色和专业知识,根据用户的内容回答用户的问题。
它具有一个 Dispatcher 代理,用于分析每个问题并将其分配给最合适的专业代理。它使用 Nature Agent 来回答与生态系统和野生动物相关的问题,使用 Science Agent 来回答物理或科学主题,并使用 Crime Agent 来回答与法律相关的查询。
每个 Agent 都有独特的个性,例如 1930 年代的法律黑手党黑帮和犯罪特工。
默认代理处理不符合这些类别的查询。
同时,介绍了如何获取 GROQ API 密钥并使用 GROQ API 设置 OpenAI 客户端,还展示了如何配置 Swarm 客户端,使用不同的指令定义代理,以及实现路由用户查询的逻辑。
这种集成确保了量身定制的和上下文适当的响应,展示了将 GROQ 的 API 兼容性与 Swarm 的代理驱动框架相结合的潜力,以实现动态、多方面的系统。
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