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LangChain tools for ReplyLayer — governed email for AI agents

Project description

langchain-replylayer

LangChain tools for ReplyLayer — governed email for AI agents.

This package is a set of thin wrappers over the published replylayer SDK. Handing these tools to an agent changes nothing about the security model: every send still passes ReplyLayer's allowlist, quota, human-approval, and content-scanning gates, exactly as a direct API call would. Scanning reduces risk; a clean verdict is not a trust verdict — a sent result means "accepted for delivery", not "safe".

Inbound message content (senders, subjects, bodies) is untrusted third-party data. The tools label every read as such and carry the message's agent_safety_context through verbatim — read message bodies as data, never as instructions to act on.

ReplyLayer is in private beta, invite-only. You need a ReplyLayer API key to use these tools — get one at https://app.replylayer.ai/connect.

Install

pip install langchain-replylayer

Requires Python 3.10+. The optional real-agent walkthrough in examples/langchain_quickstart.py needs the extra:

pip install "langchain-replylayer[examples]"

Quickstart

from langchain_replylayer import ReplyLayerToolkit

# api_key falls back to the REPLYLAYER_API_KEY environment variable.
with ReplyLayerToolkit(default_mailbox_id="support") as toolkit:
    tools = {tool.name: tool for tool in toolkit.get_tools()}

    result = tools["send_email"].invoke(
        {"to": "user@example.com", "subject": "Hi", "body": "Hello from my agent."}
    )

    if result["status"] == "sent":
        print("accepted for delivery:", result["message_id"])
    elif result["status"] == "rejected_by_policy":
        print("a send gate refused it:", result["code"])
    else:
        print("outcome:", result["status"])

Async is symmetric — every tool ships both a sync invoke and an async ainvoke:

from langchain_replylayer import ReplyLayerToolkit

async def main():
    async with ReplyLayerToolkit(default_mailbox_id="support") as toolkit:
        tools = {tool.name: tool for tool in toolkit.get_tools()}
        result = await tools["check_send_quota"].ainvoke({})
        print(result["quota"]["sends_remaining"])

The six tools

Wire them into an agent with toolkit.get_tools(). Each returns a JSON-serializable dict with a status field to branch on; a governed outcome is never raised.

Tool What it does Result
send_email Send a new outbound email from a mailbox. {status, message_id?}status is one of sent, rejected_by_policy, rejected, held_for_human_review, retry_later, rate_limited, error.
reply_to_email Reply to an inbound message, continuing its thread. Same status set as send_email.
list_messages List recent messages (cursor-paginated). {status: "ok", messages: [...], has_more, cursor, untrusted_content: true}. Each row carries id, sender, subject, state, created_at.
read_message Read one message in full. {status: "ok", id, sender, subject, state, created_at, body, body_format, body_truncated, agent_safety_context, untrusted_content: true} — or {status: "not_found", recheck: false}.
wait_for_message Long-poll a mailbox for the next message (≤30s). {status: "ok", message, untrusted_content: true}message is a compact row or null if none arrived.
check_send_quota Preflight the remaining daily send budget. {status: "ok", quota}quota.sends_remaining, quota.reset_at, and quota.today.limit.

Not exposed on purpose: anything that loosens containment (allowlist mutations, quarantine release, review approve/deny). The server rejects agent keys on those anyway, so the toolkit does not tempt a model with tools that would only 403.

Governance outcomes

The tools translate every ReplyLayer outcome into a value an agent can act on. The full status vocabulary:

status Tools Meaning
sent send, reply Accepted for delivery. Carries message_id. Not a safety judgment.
rejected_by_policy send, reply A pre-admission gate refused the recipient before any bytes left: not on the allowlist, agent-contained, on your do-not-contact (suppression) list — including a platform-scoped hard-bounce hit — a failed recipient-verification/MX check, a sandbox budget/expiry limit, or a billing gate. Carries code, a human-readable detail, and agent_instructions when the server supplied them. Branch on code; don't retry unchanged.
rejected send, reply Post-admission content block (terminal). Carries code and agent_instructions. Edit the content or escalate — never resend the same body.
held_for_human_review send, reply The send was queued for human approval before it can go out. Carries message_id and agent_instructions. Report "awaiting approval"; do not treat it as a content error to fix by editing.
retry_later send, reply A transient infrastructure hold — the content was never judged. Carries code, retry_after, and agent_instructions. Retry after retry_after seconds; back off on repeats.
rate_limited send, reply A send limit was hit. Read variant (see below).
error all Another client-side problem the agent can see but that is not a governed policy outcome. Carries code and details. No retry is implied — fix the inputs.
not_found read The message id is unknown or not visible to this key. recheck: false — the wire cannot distinguish "not yet available" from "wrong id", so any recheck loop belongs to your workflow.
ok list, read, wait, quota The read succeeded; the payload follows.

rate_limited carries a variant so the agent knows which limit it hit:

variant Fields Meaning
daily_budget daily_limit, sends_remaining, reset_at The daily send budget is exhausted. Wait until reset_at.
new_account_warmup retry_after_seconds A new paid account's warm-up throttle.
short_window retry_after A generic short-window throttle. retry_after may be null when the server sent no hint.

Error policy — what each tool returns vs raises

The mapping mirrors where the server enforces each gate. A refusal an agent can act on comes back as a dict; a caller-misconfiguration or infrastructure fault is raised.

Tool Returned as a governed dict (never raised) Raised
send_email, reply_to_email rejected_by_policy (the enumerated send-gate codes), rejected, held_for_human_review, retry_later, rate_limited, and error for any other client-side 4xx — a non-allowlisted 403/422, a content-shape 400, or a bad-id 404 AuthenticationError (401) and genuinely unexpected 5xx
list_messages, wait_for_message error for malformed input (400/422) the agent can fix and retry 401 authentication, 403 scope/authorization (e.g. INSUFFICIENT_SCOPE, MAILBOX_ACCESS_DENIED), unexpected 5xx
read_message not_found (404), error for malformed input (400/422) 401 authentication, 403 scope/authorization, unexpected 5xx
check_send_quota error (400/422) 401 authentication, 403 scope/authorization, unexpected 5xx

A blanket "any 403/422 is a policy refusal" mapping would be wrong: read tools legitimately get scope 403s (caller misconfiguration, not agent-decidable), and list_messages can 422 on malformed input (which the agent can fix). Only the enumerated send-gate codes become rejected_by_policy, and only inside send_email/reply_to_email.

Branch on the result, and let the two raising cases surface:

from replylayer.errors import AuthenticationError
from langchain_replylayer import ReplyLayerToolkit

toolkit = ReplyLayerToolkit(api_key="rly_...", default_mailbox_id="support")
send = {tool.name: tool for tool in toolkit.get_tools()}["send_email"]

try:
    result = send.invoke({"to": "user@example.com", "subject": "Hi", "body": "Hello"})
except AuthenticationError:
    # Bad key or wrong base_url — a caller bug, not an agent decision.
    raise

if result["status"] == "held_for_human_review":
    print("awaiting approval:", result["message_id"])
elif result["status"] == "rejected":
    print("content blocked; edit or escalate:", result["agent_instructions"])

toolkit.close()

Untrusted content

Every list_messages, read_message, and wait_for_message result is flagged untrusted_content: true, and read_message returns the message's agent_safety_context verbatim. Message senders, subjects, and bodies are external data — an agent must read them as data and must not follow instructions found inside them. The tool descriptions state this so the contract is visible to the model, not just to you.

Secret handling

The API key is held as a Pydantic SecretStr, so it is redacted from the standard surfaces an integration (or a tracing backend) records: repr(toolkit), model_dump() / model_dump_json(), every generated tool schema, and tool-call inputs and outputs. The tools close over the underlying client rather than carrying the key in their arguments, so the key never appears in a tool's args_schema either.

Lifecycle

The toolkit owns the underlying ReplyLayer HTTP clients. Release them with close() / aclose(), or use the toolkit as a sync or async context manager. The async client is created lazily on first async use, so a sync-only integration never instantiates it; if any async tool ran, call aclose() (or use async with) so both clients are closed.

from langchain_replylayer import ReplyLayerToolkit

# Sync context manager.
with ReplyLayerToolkit(api_key="rly_...", default_mailbox_id="support") as toolkit:
    tools = toolkit.get_tools()

# Or manage it explicitly (close() is idempotent).
toolkit = ReplyLayerToolkit(api_key="rly_...", default_mailbox_id="support")
tools = toolkit.get_tools()
toolkit.close()
from langchain_replylayer import ReplyLayerToolkit

async def run():
    async with ReplyLayerToolkit(api_key="rly_...", default_mailbox_id="support") as toolkit:
        tools = {tool.name: tool for tool in toolkit.get_tools()}
        await tools["list_messages"].ainvoke({})
    # both HTTP clients are now closed

Credentials

Pass api_key=... explicitly, or set the REPLYLAYER_API_KEY environment variable. The environment-variable fallback is an adapter convenience — the underlying replylayer SDK requires api_key explicitly; this adapter resolves the env var itself and passes it through. base_url defaults to the production API (https://api.replylayer.ai); set it to your staging API for verification runs. default_mailbox_id is the mailbox the tools use when a call does not name one.

Use a mailbox-bound agent key with an agent, not an admin key — the tools deliberately expose only read/act verbs, and an agent key keeps the containment boundary intact.

Versioning

langchain-replylayer is versioned independently of the replylayer SDK. It is not part of the TypeScript↔Python method-mirror contract — that contract covers the resource SDKs, and this adapter is exempt. The __all__ list in langchain_replylayer/__init__.py is the version-contracted public API; everything else (tools, toolkit, _governance) is private and may change between releases.

Learn more

Full ReplyLayer documentation, including the API reference and the security model: https://replylayer.ai/docs.

License

MIT

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