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Nebula (Symbl.ai)

概述​

本笔记本介绍如何开始使用 Nebula - Symbl.ai 的聊天模型。

集成细节​

前往 API 参考 获取详细文档。

模型特性：待办事项​

设置​

凭证​

要开始，请请求 Nebula API 密钥 并设置 NEBULA_API_KEY 环境变量：

import getpass
import os

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

安装​

集成在 langchain-community 包中设置。

实例化​

<!--IMPORTS:[{"imported": "ChatNebula", "source": "langchain_community.chat_models.symblai_nebula", "docs": "https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.symblai_nebula.ChatNebula.html", "title": "Nebula (Symbl.ai)"}, {"imported": "AIMessage", "source": "langchain_core.messages", "docs": "https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.AIMessage.html", "title": "Nebula (Symbl.ai)"}, {"imported": "HumanMessage", "source": "langchain_core.messages", "docs": "https://python.langchain.com/api_reference/core/messages/langchain_core.messages.human.HumanMessage.html", "title": "Nebula (Symbl.ai)"}, {"imported": "SystemMessage", "source": "langchain_core.messages", "docs": "https://python.langchain.com/api_reference/core/messages/langchain_core.messages.system.SystemMessage.html", "title": "Nebula (Symbl.ai)"}]-->
from langchain_community.chat_models.symblai_nebula import ChatNebula
from langchain_core.messages import 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.'}])

流式处理​

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.'}])]

链接​

<!--IMPORTS:[{"imported": "ChatPromptTemplate", "source": "langchain_core.prompts", "docs": "https://python.langchain.com/api_reference/core/prompts/langchain_core.prompts.chat.ChatPromptTemplate.html", "title": "Nebula (Symbl.ai)"}]-->
from langchain_core.prompts import ChatPromptTemplate

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

查看 API 参考 以获取更多详细信息。

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