Nebula (Symbl.ai)

本指南将介绍如何开始使用 Nebula - Symbl.ai 的聊天模型。

集成详情

请访问 API 参考 获取详细文档。

模型功能：待办

设置

凭证

要开始使用，请请求一个 Nebula API 密钥，并将 NEBULA_API_KEY 环境变量设置为你的密钥：

import getpass
import os

os.environ["NEBULA_API_KEY"] = getpass.getpass()

安装

集成设置在 langchain-community 包中。

实例化

from langchain_community.chat_models.symblai_nebula import ChatNebula
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage

API Reference:ChatNebula | AIMessage | HumanMessage | SystemMessage

chat = ChatNebula(max_tokens=1024, temperature=0.5)

调用

messages = [
    SystemMessage(
        content="You are a helpful assistant that answers general knowledge questions."
    ),
    HumanMessage(content="What is the capital of France?"),
]
chat.invoke(messages)

AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])

异步

await chat.ainvoke(messages)

AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])

流式传输

for chunk in chat.stream(messages):
    print(chunk.content, end="", flush=True)

 The capital of France is Paris.

批处理

chat.batch([messages])

[AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])]

链式调用（

from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_template("Tell me a joke about {topic}")
chain = prompt | chat

API Reference:ChatPromptTemplate

chain.invoke({"topic": "cows"})

AIMessage(content=[{'role': 'human', 'text': 'Tell me a joke about cows'}, {'role': 'assistant', 'text': "Sure, here's a joke about cows:\n\nWhy did the cow cross the road?\n\nTo get to the udder side!"}])

API 参考

更多详情，请查看 API 参考。

Related

• Chat model conceptual guide
• Chat model how-to guides