Gmail 工具包

这将帮助您开始使用 Gmail 工具包。此工具包与 Gmail API 交互以读取消息、草拟和发送消息等。有关所有 GmailToolkit 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，如 Gmail API 文档 中所述。下载 credentials.json 文件后，即可开始使用 Gmail API。

安装

此工具包位于 langchain-google-community 包中。我们需要 gmail 扩展

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

如果希望从单个工具的运行中获取自动跟踪，还可以通过取消以下注释来设置您的 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，工具包读取本地 credentials.json 文件。您也可以手动提供 Credentials 对象。

from langchain_google_community import GmailToolkit

toolkit = GmailToolkit()

自定义身份验证

在后台，使用以下方法创建 googleapi 资源。您可以手动构建 googleapi 资源以获得更多身份验证控制。

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>)]

• GmailCreateDraft
• GmailSendMessage
• GmailSearch
• GmailGetMessage
• GmailGetThread

在代理中使用

下面我们展示如何将工具包集成到 代理 中。

我们需要一个 LLM 或聊天模型

OpenAI

pip install -qU langchain-openai

import getpass
import os

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

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(model="gpt-4o-mini")

Anthropic

pip install -qU langchain-anthropic

import getpass
import os

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

from langchain_anthropic import ChatAnthropic

llm = ChatAnthropic(model="claude-3-5-sonnet-20240620")

Azure

pip install -qU langchain-openai

import getpass
import os

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

from langchain_openai import AzureChatOpenAI

llm = AzureChatOpenAI(
    azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
    azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT_NAME"],
    openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"],
)

Google

pip install -qU langchain-google-vertexai

import getpass
import os

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

from langchain_google_vertexai import ChatVertexAI

llm = ChatVertexAI(model="gemini-1.5-flash")

Cohere

pip install -qU langchain-cohere

import getpass
import os

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

from langchain_cohere import ChatCohere

llm = ChatCohere(model="command-r-plus")

NVIDIA

pip install -qU langchain-nvidia-ai-endpoints

import getpass
import os

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

from langchain import ChatNVIDIA

llm = ChatNVIDIA(model="meta/llama3-70b-instruct")

FireworksAI

pip install -qU langchain-fireworks

import getpass
import os

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

from langchain_fireworks import ChatFireworks

llm = ChatFireworks(model="accounts/fireworks/models/llama-v3p1-70b-instruct")

Groq

pip install -qU langchain-groq

import getpass
import os

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

from langchain_groq import ChatGroq

llm = ChatGroq(model="llama3-8b-8192")

MistralAI

pip install -qU langchain-mistralai

import getpass
import os

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

from langchain_mistralai import ChatMistralAI

llm = ChatMistralAI(model="mistral-large-latest")

TogetherAI

pip install -qU langchain-openai

import getpass
import os

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

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://api.together.xyz/v1",
    api_key=os.environ["TOGETHER_API_KEY"],
    model="mistralai/Mixtral-8x7B-Instruct-v0.1",
)

from langgraph.prebuilt import create_react_agent

agent_executor = create_react_agent(llm, tools)

API 参考：create_react_agent

example_query = "Draft an email to [email protected] 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 [email protected] 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: ['[email protected]']
    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 [email protected] 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。

相关

• 工具 概念指南
• 工具 操作指南