Chattice

Async, typed event framework for Google Chat apps — aiogram-quality DX, Google-native semantics.

from chattice import Dispatcher, F, Router
from chattice.events import MessageEvent

router = Router()


@router.message(F.text == "ping")
async def ping(message: MessageEvent) -> str:
    return "pong"  # HTTP response; no outbound credentials, 30 s deadline


dispatcher = Dispatcher()
dispatcher.include_router(router)

What this is

• Google Chat-native. Space, Thread, Message, Command, Action, Card, Dialog, App Home, Workspace Events are first-class typed objects. No Telegram concepts leak into the domain model.
• aiogram ergonomics. Routers, magic filters (F), middleware, dependency injection, FSM — the DX you know, without Telegram semantics.
• Explicit response model. A handler RETURN is the synchronous interaction response (30 s deadline); outbound Bot calls are separate authenticated operations. Contextual message.reply() / thread.send() / space.send() methods are zero-fetch adapters over that same Bot, never a hidden second channel.
• Secure by default. Incoming verification is fail-closed, push endpoints require a verifier, outbound privacy gates (private messages, notifications, preview features) fail closed before any network call.
• Core is small. Core abstracts Google Chat platform primitives and technical boilerplate ONLY. Business scenarios (polls, approvals, tickets) are assembled from the primitives in your application code — never added to core.
• Curated outbound facade. An operation registry is the single source of outbound auth truth; identity-bound resource clients (bot.app.* / bot.user.* for spaces, messages, memberships, reactions, and per-user state) and one executor path make every Google call explicit about who is calling.
• Explicit identity. APP and USER are always chosen by the caller (bot.raw.app() / bot.raw.user()); the framework never switches silently. Direct messages are first-class: bot.user.spaces.get_or_setup_direct_message(...) returns the official Space with its clickable space_uri.
• Diagnosable in production. Structured lifecycle stages (handler_started before invocation), stage-tagged error logs, Pub/Sub delivery identity/age, per-card update serialization, configurable RuntimeDiagnostics thresholds, and CI-verified operation registry against the Google discovery document. DEBUG can include exception text in tracebacks; see the logging guidance.

What this is not

• Not a Telegram framework. No chat_id, no CallbackQuery, no Update hierarchy, no Telegram-style long polling (see the aiogram comparison).
• Not a Google product. Independent open-source project, not endorsed by Google.

Two ways to run

Chattice has two startup models (see the aiogram side-by-side):

# HTTP — Google calls your HTTPS endpoint; the handler RETURN is the
# synchronous response (Dialogs and App Home work here).
app.include_router(create_chat_router(dispatcher, GoogleTokenVerifier(audience=...)))
# python -m uvicorn app:app

# Pub/Sub streaming pull — a persistent subscriber process, visually
# like aiogram's start_polling, but it is NOT Telegram polling.
# No domain/TLS needed; no Dialogs, no App Home — answers go outbound
# through the authenticated Bot.
await dispatcher.run_pubsub(
    subscription, bot=bot, credentials_provider=pull_credentials
)
# python app.py

Capabilities

Install

Python 3.11+ (3.11–3.13 tested). MIT-licensed.

pip install "chattice[fastapi,pubsub,redis]"  # HTTP, streaming pull, Redis

# or pick only what you need:
#   pip install chattice            core
#   pip install "chattice[fastapi]" FastAPI integration
#   pip install "chattice[redis]"   Redis FSM/idempotency storage
#   pip install "chattice[pubsub]"  Pub/Sub streaming pull
#   pip install "chattice[media]"   Media/attachment uploads (Google API client)
#   pip install "chattice[gcs]"     Local Card image publication through GCS
#   pip install "chattice[gemini]"  Experimental Gemini agent bridge

# using uv
uv add "chattice[fastapi,pubsub,redis]"

Quickstart

1. Parse a documented interaction payload:

from chattice.adapters.google_chat import parse_interaction

event = parse_interaction(payload)
result = await dispatcher.feed_update(event)

2. Serve HTTP interactions (FastAPI):

from fastapi import FastAPI
from chattice.integrations.fastapi import create_chat_router
from chattice.transports.http import GoogleTokenVerifier

app = FastAPI()
app.include_router(create_chat_router(dispatcher, GoogleTokenVerifier(audience="...")))

3. Send messages:

from chattice.client import Bot

bot = Bot(credentials=...)
await bot.app.messages.create("spaces/AAA", text="hello")

Inside an interaction handler, configure the same Bot once and use the known Google context without extra fetches:

dispatcher = Dispatcher(bot=bot)


@router.message()
async def reply(message: MessageEvent) -> None:
    await message.reply("hello in this thread")

Docs

Start with Installation, the 5-minute Quickstart, and the Space → Thread → Message mental model. The public API reference, Google mapping, the debugging guide, and aiogram comparison are linked from the docs site. Runnable examples live in examples/.

Status

Pre-1.0 public release (current version 0.3.4) — see CHANGELOG. The documented public surface is the compatibility baseline: patch releases preserve it; pre-1.0 incompatible changes require a minor-version bump and upgrade notes. chattice.experimental has no compatibility promise. bot.raw.app() / bot.raw.user() and raw event payloads follow Google's SDK and wire schema rather than the stable facade promise. Not an official Google product — independent open-source software, not endorsed by Google. MIT License, see LICENSE.