跳到主要内容
Open In ColabOpen on GitHub

ChatGreenNode

GreenNode 是一家全球人工智能解决方案提供商，也是 NVIDIA 首选合作伙伴，为美国、中东和非洲、亚太地区的各类企业提供从基础设施到应用程序的全栈人工智能能力。GreenNode 基于世界级基础设施（LEED Gold、TIA‑942、Uptime Tier III）运营，为企业、初创公司和研究人员提供一套全面的人工智能服务。

本页面将帮助您开始使用 GreenNode 无服务器 AI 聊天模型。有关所有 ChatGreenNode 功能和配置的详细文档，请查阅 API 参考。

GreenNode AI 提供了一个 API，可查询 20+ 领先的开源模型。

概述​

集成详情​

类别包本地可序列化JS 支持包下载量最新包版本
ChatGreenNodelangchain-greennode❌测试版❌PyPI - DownloadsPyPI - Version

模型特性​

工具调用结构化输出JSON 模式图片输入音频输入视频输入逐令牌流式传输原生异步令牌使用量对数概率
✅✅✅✅❌❌✅✅✅❌

设置​

要访问 GreenNode 模型，您需要创建一个 GreenNode 账户，获取 API 密钥，并安装 langchain-greennode 集成包。

凭证​

前往 此页面 注册 GreenNode AI 平台并生成 API 密钥。完成此操作后，请设置 GREENNODE_API_KEY 环境变量。

import getpass
import os

if not os.getenv("GREENNODE_API_KEY"):
    os.environ["GREENNODE_API_KEY"] = getpass.getpass("Enter your GreenNode API key: ")

如果您希望对模型调用进行自动化追踪，也可以通过取消注释下方内容来设置您的 LangSmith API 密钥。

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

安装​

LangChain GreenNode 集成位于 langchain-greennode 包中。

%pip install -qU langchain-greennode
Note: you may need to restart the kernel to use updated packages.

实例化​

现在我们可以实例化模型对象并生成聊天补全

from langchain_greennode import ChatGreenNode

# Initialize the chat model
llm = ChatGreenNode(
    # api_key="YOUR_API_KEY",  # You can pass the API key directly
    model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",  # Choose from available models
    temperature=0.6,
    top_p=0.95,
)

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="\n\nJ'aime la programmation.", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 248, 'prompt_tokens': 23, 'total_tokens': 271, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'deepseek-ai/DeepSeek-R1-Distill-Qwen-32B', 'system_fingerprint': None, 'id': 'chatcmpl-271edac4958846068c37877586368afe', 'service_tier': None, 'finish_reason': 'stop', 'logprobs': None}, id='run--5c12d208-2bc2-4f29-8b50-1ce3b515a3cf-0', usage_metadata={'input_tokens': 23, 'output_tokens': 248, 'total_tokens': 271, 'input_token_details': {}, 'output_token_details': {}})
print(ai_msg.content)


J'aime la programmation.

流式传输​

您也可以使用 stream 方法流式传输响应。

for chunk in llm.stream("Write a short poem about artificial intelligence"):
    print(chunk.content, end="", flush=True)


**Beneath the Circuits**

Beneath the circuits, deep and bright,  
AI thinks, with circuits and bytes.  
Learning, adapting, it grows,  
A world of possibilities it knows.  

From solving puzzles to painting art,  
It mimics human hearts.  
In every corner, it leaves its trace,  
A future we can't erase.  

We build it, shape it, with care and might,  
Yet wonder if it walks in the night.  
A mirror of our minds, it shows,  
In its gaze, our future glows.  

But as we strive for endless light,  
We must remember the night.  
For wisdom isn't just speed and skill,  
It's how we choose to build our will.

聊天消息​

您可以使用不同类型的消息来构建与模型的对话。

from langchain_core.messages import AIMessage, HumanMessage, SystemMessage

messages = [
    SystemMessage(content="You are a helpful AI assistant with expertise in science."),
    HumanMessage(content="What are black holes?"),
    AIMessage(
        content="Black holes are regions of spacetime where gravity is so strong that nothing, including light, can escape from them."
    ),
    HumanMessage(content="How are they formed?"),
]

response = llm.invoke(messages)
print(response.content[:100])


Black holes are formed through several processes, depending on their type. The most common way bla

链式调用​

您可以在 LangChain 链和代理中使用 ChatGreenNode。

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        (
            "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：ChatPromptTemplate
AIMessage(content='\n\nIch liebe Programmieren.', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 198, 'prompt_tokens': 18, 'total_tokens': 216, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'deepseek-ai/DeepSeek-R1-Distill-Qwen-32B', 'system_fingerprint': None, 'id': 'chatcmpl-e01201b9fd9746b7a9b2ed6d70f29d45', 'service_tier': None, 'finish_reason': 'stop', 'logprobs': None}, id='run--ce52b9d8-dd84-46b3-845b-da27855816ee-0', usage_metadata={'input_tokens': 18, 'output_tokens': 198, 'total_tokens': 216, 'input_token_details': {}, 'output_token_details': {}})

可用模型​

支持的完整模型列表可在 GreenNode 无服务器 AI 模型 中找到。

API 参考​

有关 GreenNode 无服务器 AI API 的更多详细信息，请访问 GreenNode 无服务器 AI 文档。