ChatCerebras 餐厅

此笔记本提供了 Cerebras 聊天模型的快速入门概述。有关所有 ChatCerebras 功能和配置的详细文档，请参阅 API 参考。

在 Cerebras，我们开发了世界上最大、最快的 AI 处理器，即晶圆级引擎-3 （WSE-3）。由 WSE-3 提供支持的 Cerebras CS-3 系统代表了一类新型 AI 超级计算机，它以无与伦比的性能和可扩展性为生成式 AI 训练和推理设定了标准。

使用 Cerebras 作为您的推理提供商，您可以：

实现前所未有的 AI 推理工作负载速度
以高吞吐量进行商业化构建
使用我们的无缝集群技术轻松扩展您的 AI 工作负载

我们的 CS-3 系统可以快速轻松地进行集群化，以创建世界上最大的 AI 超级计算机，从而轻松放置和运行最大的模型。领先的公司、研究机构和政府已经在使用 Cerebras 解决方案来开发专有模型并训练流行的开源模型。

想体验 Cerebras 的强大功能吗？查看我们的网站以获取更多资源，并探索通过 Cerebras Cloud 或本地部署访问我们技术的选项！

有关 Cerebras Cloud 的更多信息，请访问 cloud.cerebras.ai。我们的 API 参考可在 inference-docs.cerebras.ai 上找到。

概述

集成详细信息

类	包	本地化	序列化	JS 支持	软件包下载	最新包装
ChatCerebras	langchain-cerebras	❌	beta	❌

模型特点

工具调用	结构化输出	JSON 模式	图像输入	音频输入	视频输入	令牌级流式处理	本机异步	Token 使用情况	日志
✅	✅	✅	❌	❌	❌	✅	✅	✅	❌

设置

pip install langchain-cerebras

凭据

从 cloud.cerebras.ai 获取 API 密钥并将其添加到您的环境变量中：

export CEREBRAS_API_KEY="your-api-key-here"

import getpass
import os

if "CEREBRAS_API_KEY" not in os.environ:
    os.environ["CEREBRAS_API_KEY"] = getpass.getpass("Enter your Cerebras API key: ")

Enter your Cerebras API key:  ········

要启用模型调用的自动跟踪，请设置您的 LangSmith API 密钥：

# os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
# os.environ["LANGSMITH_TRACING"] = "true"

安装

LangChain Cerebras 集成位于langchain-cerebras包：

%pip install -qU langchain-cerebras

实例

现在我们可以实例化我们的 Model 对象并生成聊天补全：

from langchain_cerebras import ChatCerebras

llm = ChatCerebras(
    model="llama-3.3-70b",
    # other params...
)

API 参考：ChatCerebras

调用

messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg

AIMessage(content='Je adore le programmation.', response_metadata={'token_usage': {'completion_tokens': 7, 'prompt_tokens': 35, 'total_tokens': 42}, 'model_name': 'llama3-8b-8192', 'system_fingerprint': 'fp_be27ec77ff', 'finish_reason': 'stop'}, id='run-e5d66faf-019c-4ac6-9265-71093b13202d-0', usage_metadata={'input_tokens': 35, 'output_tokens': 7, 'total_tokens': 42})

链接

我们可以用 prompt 模板链接我们的模型，如下所示：

from langchain_cerebras import ChatCerebras
from langchain_core.prompts import ChatPromptTemplate

llm = ChatCerebras(
    model="llama-3.3-70b",
    # other params...
)

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

chain = prompt | llm
chain.invoke(
    {
        "input_language": "English",
        "output_language": "German",
        "input": "I love programming.",
    }
)

API 参考：ChatCerebras | 聊天提示模板

AIMessage(content='Ich liebe Programmieren!\n\n(Literally: I love programming!)', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 30, 'total_tokens': 44}, 'model_name': 'llama3-8b-8192', 'system_fingerprint': 'fp_be27ec77ff', 'finish_reason': 'stop'}, id='run-e1d2ebb8-76d1-471b-9368-3b68d431f16a-0', usage_metadata={'input_tokens': 30, 'output_tokens': 14, 'total_tokens': 44})

流

from langchain_cerebras import ChatCerebras
from langchain_core.prompts import ChatPromptTemplate

llm = ChatCerebras(
    model="llama-3.3-70b",
    # other params...
)

system = "You are an expert on animals who must answer questions in a manner that a 5 year old can understand."
human = "I want to learn more about this animal: {animal}"
prompt = ChatPromptTemplate.from_messages([("system", system), ("human", human)])

chain = prompt | llm

for chunk in chain.stream({"animal": "Lion"}):
    print(chunk.content, end="", flush=True)

API 参考：ChatCerebras | 聊天提示模板

OH BOY! Let me tell you all about LIONS!

Lions are the kings of the jungle! They're really big and have beautiful, fluffy manes around their necks. The mane is like a big, golden crown!

Lions live in groups called prides. A pride is like a big family, and the lionesses (that's what we call the female lions) take care of the babies. The lionesses are like the mommies, and they teach the babies how to hunt and play.

Lions are very good at hunting. They work together to catch their food, like zebras and antelopes. They're super fast and can run really, really fast!

But lions are also very sleepy. They like to take long naps in the sun, and they can sleep for up to 20 hours a day! Can you imagine sleeping that much?

Lions are also very loud. They roar really loudly to talk to each other. It's like they're saying, "ROAR! I'm the king of the jungle!"

And guess what? Lions are very social. They like to play and cuddle with each other. They're like big, furry teddy bears!

So, that's lions! Aren't they just the coolest?

异步

from langchain_cerebras import ChatCerebras
from langchain_core.prompts import ChatPromptTemplate

llm = ChatCerebras(
    model="llama-3.3-70b",
    # other params...
)

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "human",
            "Let's play a game of opposites. What's the opposite of {topic}? Just give me the answer with no extra input.",
        )
    ]
)
chain = prompt | llm
await chain.ainvoke({"topic": "fire"})

API 参考：ChatCerebras | 聊天提示模板

AIMessage(content='Ice', response_metadata={'token_usage': {'completion_tokens': 2, 'prompt_tokens': 36, 'total_tokens': 38}, 'model_name': 'llama3-8b-8192', 'system_fingerprint': 'fp_be27ec77ff', 'finish_reason': 'stop'}, id='run-7434bdde-1bec-44cf-827b-8d978071dfe8-0', usage_metadata={'input_tokens': 36, 'output_tokens': 2, 'total_tokens': 38})

异步流式处理

from langchain_cerebras import ChatCerebras
from langchain_core.prompts import ChatPromptTemplate

llm = ChatCerebras(
    model="llama-3.3-70b",
    # other params...
)

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "human",
            "Write a long convoluted story about {subject}. I want {num_paragraphs} paragraphs.",
        )
    ]
)
chain = prompt | llm

async for chunk in chain.astream({"num_paragraphs": 3, "subject": "blackholes"}):
    print(chunk.content, end="", flush=True)

API 参考：ChatCerebras | 聊天提示模板

In the distant reaches of the cosmos, there existed a peculiar phenomenon known as the "Eclipse of Eternity," a swirling vortex of darkness that had been shrouded in mystery for eons. It was said that this blackhole, born from the cataclysmic collision of two ancient stars, had been slowly devouring the fabric of space-time itself, warping the very essence of reality. As the celestial bodies of the galaxy danced around it, they began to notice a strange, almost imperceptible distortion in the fabric of space, as if the blackhole's gravitational pull was exerting an influence on the very course of events itself.

As the centuries passed, astronomers from across the galaxy became increasingly fascinated by the Eclipse of Eternity, pouring over ancient texts and scouring the cosmos for any hint of its secrets. One such scholar, a brilliant and reclusive astrophysicist named Dr. Elara Vex, became obsessed with unraveling the mysteries of the blackhole. She spent years pouring over ancient texts, deciphering cryptic messages and hidden codes that hinted at the existence of a long-lost civilization that had once thrived in the heart of the blackhole itself. According to legend, this ancient civilization had possessed knowledge of the cosmos that was beyond human comprehension, and had used their mastery of the universe to create the Eclipse of Eternity as a gateway to other dimensions.

As Dr. Vex delved deeper into her research, she began to experience strange and vivid dreams, visions that seemed to transport her to the very heart of the blackhole itself. In these dreams, she saw ancient beings, their faces twisted in agony as they were consumed by the void. She saw stars and galaxies, their light warped and distorted by the blackhole's gravitational pull. And she saw the Eclipse of Eternity itself, its swirling vortex of darkness pulsing with an otherworldly energy that seemed to be calling to her. As the dreams grew more vivid and more frequent, Dr. Vex became convinced that she was being drawn into the heart of the blackhole, and that the secrets of the universe lay waiting for her on the other side.

API 参考

有关所有 ChatCerebras 功能和配置的详细文档，请参阅 API 参考：https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#

聊天模型概念指南
聊天模型操作指南

概述

集成详细信息

模型特点

设置

凭据

安装

实例

调用

链接

流

异步

异步流式处理

API 参考

相关