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Email Assistant with LangChain

Build an AI email assistant that searches your inbox, drafts replies, and manages email workflows — using LangChain.

emailautomationproductivityassistant

Working Code

LangChain
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
@tool
def search_emails(query: str, limit: int = 5) -> str:
"""Search the inbox for emails matching a query."""
results = email_client.search(query, max_results=limit)
return "\n\n".join(
f"From: {e.sender}\nSubject: {e.subject}\nDate: {e.date}\nPreview: {e.body[:200]}"
for e in results
)
@tool
def draft_email(to: str, subject: str, body: str) -> str:
"""Create an email draft."""
draft_id = email_client.create_draft(to=to, subject=subject, body=body)
return f"Draft created (ID: {draft_id}). Review before sending."
model = ChatOpenAI(model="gpt-4o")
model_with_tools = model.bind_tools([search_emails, draft_email])
response = model_with_tools.invoke([
("system", "You are an email assistant. Search emails to find context, then help draft professional replies. Always create drafts — never send directly."),
("user", "Find the latest email from the marketing team and draft a reply confirming the deadline"),
])

Step by Step

1

Install dependencies

Install LangChain and the required tools for this use case.

2

Define your tools

Create the domain-specific tool functions your agent will use to interact with external services.

3

Create the agent and run

Initialize the LangChain agent with your tools, set the system prompt, and execute a query.

Ready to build with LangChain?

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