> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sentfrom.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChain

> Give a LangChain agent email tools backed by SentFromAI.

Wrap SentFromAI operations as LangChain tools with the `@tool` decorator, then hand them to an agent.

## Install

```bash theme={null}
pip install langchain langchain-openai langgraph requests
```

## Define the tools

```python theme={null}
import os, requests
from langchain_core.tools import tool

API = "https://api.sentfrom.ai/v1"
H = {"Authorization": f"Bearer {os.environ['SENTFROMAI_API_KEY']}"}

@tool
def create_inbox(local_part: str) -> dict:
    """Create a new email inbox. Returns its id and address."""
    return requests.post(f"{API}/inboxes", headers=H, json={"local_part": local_part}).json()

@tool
def send_email(inbox_id: str, to: str, subject: str, body: str) -> dict:
    """Send an email from an inbox to a recipient."""
    return requests.post(f"{API}/messages", headers=H,
        json={"inbox_id": inbox_id, "to": [to], "subject": subject, "text": body}).json()

@tool
def check_inbox(inbox_id: str) -> list:
    """List the most recent messages in an inbox."""
    return requests.get(f"{API}/messages", headers=H,
        params={"inbox_id": inbox_id, "limit": 10}).json()["messages"]
```

## Run an agent

```python theme={null}
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

agent = create_react_agent(ChatOpenAI(model="gpt-4o"), [create_inbox, send_email, check_inbox])

result = agent.invoke({"messages": [
    ("user", "Create an inbox called concierge and email jane@acme.com a welcome note.")
]})
print(result["messages"][-1].content)
```

The model now calls `create_inbox` then `send_email` on its own. Add `reply` and `check_inbox`
tools to build a full back-and-forth agent.

<Tip>Prefer no glue at all? Connect the [SentFromAI MCP server](/guides/mcp) and skip tool definitions.</Tip>