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Gmail 工具包

这将帮助您开始使用GMail 工具包。该工具包与GMail API交互,以读取消息、草拟和发送消息等。有关GmailToolkit所有功能和配置的详细文档,请访问API参考

设置

要使用此工具包,您需要设置您的凭据,这些凭据在Gmail API 文档中有解释。一旦您下载了credentials.json文件,您就可以开始使用 Gmail API。

安装

这个工具包位于langchain-google-community包中。我们需要gmail额外功能:

%pip install -qU langchain-google-community\[gmail\]

如果你想从单个工具的运行中获取自动追踪,你也可以通过取消注释以下内容来设置你的 LangSmith API 密钥:

# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")

实例化

默认情况下,工具包会读取本地的credentials.json文件。你也可以手动提供一个Credentials对象。

from langchain_google_community import GmailToolkit

toolkit = GmailToolkit()
API Reference:GmailToolkit

自定义认证

在幕后,使用以下方法创建了一个googleapi资源。你可以手动构建一个googleapi资源以获得更多的认证控制。

from langchain_google_community.gmail.utils import (
build_resource_service,
get_gmail_credentials,
)

# Can review scopes here https://developers.google.com/gmail/api/auth/scopes
# For instance, readonly scope is 'https://www.googleapis.com/auth/gmail.readonly'
credentials = get_gmail_credentials(
token_file="token.json",
scopes=["https://mail.google.com/"],
client_secrets_file="credentials.json",
)
api_resource = build_resource_service(credentials=credentials)
toolkit = GmailToolkit(api_resource=api_resource)

工具

查看可用工具:

tools = toolkit.get_tools()
tools
[GmailCreateDraft(api_resource=<googleapiclient.discovery.Resource object at 0x1094509d0>),
GmailSendMessage(api_resource=<googleapiclient.discovery.Resource object at 0x1094509d0>),
GmailSearch(api_resource=<googleapiclient.discovery.Resource object at 0x1094509d0>),
GmailGetMessage(api_resource=<googleapiclient.discovery.Resource object at 0x1094509d0>),
GmailGetThread(api_resource=<googleapiclient.discovery.Resource object at 0x1094509d0>)]

在代理中使用

下面我们展示如何将工具包集成到agent中。

我们将需要一个LLM或聊天模型:

pip install -qU langchain-openai
import getpass
import os

if not os.environ.get("OPENAI_API_KEY"):
os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter API key for OpenAI: ")

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")
from langgraph.prebuilt import create_react_agent

agent_executor = create_react_agent(llm, tools)
API Reference:create_react_agent
example_query = "Draft an email to fake@fake.com thanking them for coffee."

events = agent_executor.stream(
{"messages": [("user", example_query)]},
stream_mode="values",
)
for event in events:
event["messages"][-1].pretty_print()
================================ Human Message =================================

Draft an email to fake@fake.com thanking them for coffee.
================================== Ai Message ==================================
Tool Calls:
create_gmail_draft (call_slGkYKZKA6h3Mf1CraUBzs6M)
Call ID: call_slGkYKZKA6h3Mf1CraUBzs6M
Args:
message: Dear Fake,

I wanted to take a moment to thank you for the coffee yesterday. It was a pleasure catching up with you. Let's do it again soon!

Best regards,
[Your Name]
to: ['fake@fake.com']
subject: Thank You for the Coffee
================================= Tool Message =================================
Name: create_gmail_draft

Draft created. Draft Id: r-7233782721440261513
================================== Ai Message ==================================

I have drafted an email to fake@fake.com thanking them for the coffee. You can review and send it from your email draft with the subject "Thank You for the Coffee".

API参考

有关所有GmailToolkit功能和配置的详细文档,请访问API参考


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