Initial commit

This commit is contained in:
William FH
2024-12-19 17:11:43 -08:00
committed by William Fu-Hinthorn
commit b70e447d38
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# These are available in the oauth section of your Slack App
SLACK_SIGNING_SECRET=
SLACK_BOT_TOKEN=xoxb-...
# SLACK_BOT_USER_ID= (optional)
# This is the LangGraph platform instance you're connecting to
LANGGRAPH_URL=
LANGGRAPH_ASSISTANT_ID=
LANGGRAPH_API_KEY=
# Populate this AFTER you deploy for the first time
DEPLOYMENT_URL=
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# Python-generated files
__pycache__/
*.py[oc]
build/
dist/
wheels/
*.egg-info
.env
# Virtual environments
.venv
.ipynb_checkpoints/
.python_version
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MIT License
Copyright (c) 2024 LangChain
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
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# Messaging Event Servers
## Quick start
### Prereqs
- LangGraph platform deployment
- [Modal account](https://modal.com/apps/) (if you want to deploy to Modal)
### Setup
1. Install `uv` (optional) and install dependencies
```shell
curl -LsSf https://astral.sh/uv/install.sh | sh
uv sync --dev
```
2. Create a Slack app https://api.slack.com/apps/ . Ensure you give it permissions to receive events and to read/write messages.
3. Copy the SLACK_SIGNING_SECRET and SLACK_BOT_TOKEN to your .env file. These are found in the oauth section of your Slack App.
```shell
# .dotenv
SLACK_SIGNING_SECRET=
SLACK_BOT_TOKEN=xoxb-...
```
4. Copy your LangGraph deployment's URL and assistant ID (or graph name) to the `.env` file, along with a LangGraph/LangSmith API key (they're the same).
```shell
# .dotenv
LANGGRAPH_URL=
LANGGRAPH_ASSISTANT_ID=
LANGGRAPH_API_KEY=
```
5. Deploy. Replace "slack-handler" with your desired app name.
```shell
DEPLOY_MODAL=true uv run modal deploy src/langgraph_slack/server.py::modal_app --name slack-handler
```
If successful, you should see something like this in your terminal:
```shell
✓ Created objects.
├── 🔨 Created mount /Users/foo/path/to/slack-server/src/langgraph_slack/server.py
├── 🔨 Created mount PythonPackage:langgraph_slack
└── 🔨 Created web function fastapi_app => https://youraccount--yourdeploymentname-fastapi-app.modal.run
✓ App deployed in 1.101s! 🎉
View Deployment: https://modal.com/apps/youraccount/main/deployed/yourdeploymentname
```
6. Copy the deployment URL from the printout in your terminal. Add that to your `.env` file.
```
# Get the following when you run modal deploy
DEPLOYMENT_URL=
```
7. Redeploy with the updated deployment URL.
8. Install your app to your Slack workspace.
Chat with the bot. The bot responds if you `@mention` it within a channel of which it is a member. You can also DM the bot. You needn't use `@mention`'s in the bot's DMs. It's clear who you are speaking to.
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[project]
name = "langgraph-slack-server"
version = "0.0.1"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"fastapi>=0.115.6",
"langgraph-sdk>=0.1.48",
"modal>=0.68.42",
"python-dotenv>=1.0.1",
"slack-bolt>=1.22.0",
"uvicorn>=0.34.0",
]
[project.optional-dependencies]
dev = [
"ruff>=0.8.4",
]
[tool.setuptools.packages.find]
where = ["src"]
include = ["langgraph_slack*"]
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import logging
import dotenv
dotenv.load_dotenv()
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)s %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
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import uvicorn
uvicorn.run("langgraph_slack.server:app", host="0.0.0.0", port=8080)
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from os import environ
import logging
LOGGER = logging.getLogger(__name__)
if DEPLOY_MODAL := environ.get("DEPLOY_MODAL"):
DEPLOY_MODAL = DEPLOY_MODAL.lower() == "true"
BOT_USER_ID = environ.get("SLACK_BOT_USER_ID")
BOT_TOKEN = environ.get("SLACK_BOT_TOKEN")
if DEPLOY_MODAL:
if not environ.get("SLACK_BOT_TOKEN"):
environ["SLACK_BOT_TOKEN"] = "fake-token"
BOT_USER_ID = BOT_USER_ID or "fake-user-id"
else:
assert isinstance(BOT_TOKEN, str)
# APP_TOKEN = environ["SLACK_APP_TOKEN"]
LANGGRAPH_URL = environ["LANGGRAPH_URL"]
ASSISTANT_ID = environ["LANGGRAPH_ASSISTANT_ID"]
DEPLOYMENT_URL = environ.get("DEPLOYMENT_URL")
if not DEPLOYMENT_URL:
LOGGER.warning("DEPLOYMENT_URL not set")
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import asyncio
import logging
import re
import uuid
from typing import Awaitable, Callable, TypedDict
from contextlib import asynccontextmanager
from fastapi import FastAPI, Request
from langgraph_sdk import get_client
from slack_bolt.adapter.fastapi.async_handler import AsyncSlackRequestHandler
from slack_bolt.async_app import AsyncApp
from langgraph_slack import config
LOGGER = logging.getLogger(__name__)
LANGGRAPH_CLIENT = get_client(url=config.LANGGRAPH_URL)
@asynccontextmanager
async def lifespan(app: FastAPI):
LOGGER.info("App is starting up. Creating background worker...")
loop = asyncio.get_running_loop()
loop.create_task(worker())
yield
LOGGER.info("App is shutting down. Stopping background worker...")
TASK_QUEUE.put_nowait(None)
APP = FastAPI(lifespan=lifespan)
APP_HANDLER = AsyncSlackRequestHandler(AsyncApp(logger=LOGGER))
if not config.BOT_USER_ID or config.BOT_USER_ID == "fake-user-id":
config.BOT_USER_ID = asyncio.run(APP_HANDLER.app.client.auth_test())["user_id"]
USER_ID_PATTERN = re.compile(rf"<@{config.BOT_USER_ID}>")
TASK_QUEUE: asyncio.Queue = asyncio.Queue()
class SlackMessageData(TypedDict):
user: str
type: str
subtype: str | None
ts: str
thread_ts: str | None
client_msg_id: str
text: str
team: str
parent_user_id: str
blocks: list[dict]
channel: str
event_ts: str
channel_type: str
async def worker():
LOGGER.info("Background worker started.")
while True:
try:
# Wait until a task is available
task = await TASK_QUEUE.get()
if not task:
# This pattern can let you send a sentinel to stop the worker gracefully
LOGGER.info("Worker received sentinel, exiting.")
break
LOGGER.info(f"Worker got a new task: {task}")
await _process_task(task)
except Exception as exc:
LOGGER.exception(f"Error in worker: {exc}")
finally:
TASK_QUEUE.task_done()
async def _process_task(task: dict):
"""
The actual logic for handling a single queued task.
We separate this so we can keep 'worker()' logic simple.
"""
event = task["event"]
event_type = task["type"]
if event_type == "slack_message":
thread_id = _get_thread_id(
event.get("thread_ts") or event["ts"], event["channel"]
)
channel_id = event["channel"]
webhook = f"{config.DEPLOYMENT_URL}/callbacks/{thread_id}"
LOGGER.info(
f"[{channel_id}].[{thread_id}] sending message to LangGraph: "
f"with webhook {webhook}: {event['text']}"
)
result = await LANGGRAPH_CLIENT.runs.create(
thread_id=thread_id,
assistant_id=config.ASSISTANT_ID,
input={
"messages": [
{
"role": "user",
"content": _replace_mention(event),
}
]
},
metadata={
"event": "slack",
"slack_event_type": "message",
"bot_user_id": config.BOT_USER_ID,
"channel": channel_id,
"thread_ts": event.get("thread_ts"),
"event_ts": event["ts"],
"channel_type": event.get("channel_type"),
},
multitask_strategy="interrupt",
if_not_exists="create",
webhook=webhook,
)
LOGGER.info(f"LangGraph run: {result}")
elif event_type == "callback":
LOGGER.info(f"Processing LangGraph callback: {event['thread_id']}")
state_values = event["values"]
response_message = state_values["messages"][-1]
thread_ts = event["metadata"]["thread_ts"] or event["metadata"]["event_ts"]
channel_id = event["metadata"]["channel"]
await APP_HANDLER.app.client.chat_postMessage(
channel=channel_id,
thread_ts=thread_ts,
text=_clean_markdown(_get_text(response_message["content"])),
metadata={
"event_type": "webhook",
"event_payload": {"thread_id": event["thread_id"]},
},
)
LOGGER.info(
f"[{channel_id}].[{thread_ts}] sent message to Slack for callback {event['thread_id']}"
)
else:
raise ValueError(f"Unknown event type: {event_type}")
async def handle_message(event: SlackMessageData, say: Callable, ack: Callable):
"""Instead of awaiting the LangGraph call immediately,
we just enqueue a task for the background worker.
"""
LOGGER.info("Enqueuing handle_message task...")
nouser = not event.get("user")
userisbot = event.get("bot_id") == config.BOT_USER_ID
ismention = _is_mention(event)
isdm = _is_dm(event)
if nouser or userisbot or not (ismention or isdm):
LOGGER.info("Message not from bot or not a mention, ignoring")
return
TASK_QUEUE.put_nowait({"type": "slack_message", "event": event})
await ack()
async def just_ack(ack: Callable[..., Awaitable], event):
LOGGER.info(f"Acknowledging {event.get('type')} event")
await ack()
APP_HANDLER.app.event("message")(ack=just_ack, lazy=[handle_message])
APP_HANDLER.app.event("app_mention")(
ack=just_ack,
lazy=[], # We handle mentions above
)
@APP.post("/events/slack")
async def slack_endpoint(req: Request):
return await APP_HANDLER.handle(req)
def _get_text(content: str | list[dict]):
if isinstance(content, str):
return content
else:
return "".join([block["text"] for block in content if block["type"] == "text"])
def _clean_markdown(text: str) -> str:
text = re.sub(r"^```[^\n]*\n", "```\n", text, flags=re.MULTILINE)
text = re.sub(r"\[([^\]]+)\]\(([^)]+)\)", r"<\2|\1>", text)
text = re.sub(r"\*\*([^*]+)\*\*", r"*\1*", text)
text = re.sub(r"(?<!\*)\*([^*]+)\*(?!\*)", r"_\1_", text)
text = re.sub(r"_([^_]+)_", r"_\1_", text)
text = re.sub(r"^\s*[-*]\s", "", text, flags=re.MULTILINE)
return text
@APP.post("/callbacks/{thread_id}")
async def webhook_callback(req: Request):
body = await req.json()
LOGGER.info(
f"Received webhook callback for {req.path_params['thread_id']}/{body['thread_id']}"
)
TASK_QUEUE.put_nowait({"type": "callback", "event": body})
return {"status": "success"}
# Helper functions
def _is_mention(event: SlackMessageData):
matches = re.search(USER_ID_PATTERN, event["text"])
return bool(matches)
def _replace_mention(event: SlackMessageData):
return re.sub(USER_ID_PATTERN, "assistant", event["text"])
def _get_thread_id(thread_ts: str, channel: str) -> str:
return str(uuid.uuid5(uuid.NAMESPACE_DNS, f"SLACK:{thread_ts}-{channel}"))
def _is_dm(event: SlackMessageData):
if channel_type := event.get("channel_type"):
return channel_type == "im"
return False
if config.DEPLOY_MODAL:
import modal
modal_app = modal.App()
image = modal.Image.debian_slim().pip_install_from_pyproject(
pyproject_toml="pyproject.toml"
)
@modal_app.function(
image=image,
keep_warm=1,
allow_concurrent_inputs=30,
secrets=[
modal.Secret.from_dotenv(),
modal.Secret.from_local_environ(["DEPLOY_MODAL"]),
],
)
@modal.asgi_app()
def fastapi_app():
return APP
if __name__ == "__main__":
import uvicorn
uvicorn.run("langgraph_slack.server:APP", host="0.0.0.0", port=8080)
Generated
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version = 1
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