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，您需要设置在 Gmail API 文档 中解释的凭据。下载 credentials.json 文件后，您可以开始使用 Gmail API。

安装

该工具包位于 langchain-google-community 包中。我们需要 gmail 附加功能：

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

如果您想从单个工具的运行中获取自动跟踪，您还可以通过取消注释下面的内容来设置您的 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，工具包会读取本地的 credentials.json 文件。您也可以手动提供一个 Credentials 对象。

from langchain_google_community import GmailToolkit

toolkit = GmailToolkit()

自定义身份验证

在后台，使用以下方法创建一个 googleapi 资源。 您可以手动构建一个 googleapi 资源以获得更多的身份验证控制。

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
• Gmail搜索
• 获取Gmail消息
• 获取Gmail线程

在代理中使用

下面我们展示如何将工具包整合到一个代理中。

我们需要一个大型语言模型或聊天模型：

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)

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。

相关

• 工具概念指南
• 工具 使用指南