Slack Bot with Memory

# pip install slack-bolt openai maximem-synap
import os
import uuid
import asyncio
from slack_bolt.async_app import AsyncApp
from slack_bolt.adapter.socket_mode.aiohttp import AsyncSocketModeHandler
from openai import AsyncOpenAI
from maximem_synap import MaximemSynapSDK

app = AsyncApp(token=os.environ["SLACK_BOT_TOKEN"])
sdk = MaximemSynapSDK(api_key=...)
openai = AsyncOpenAI()

# One conversation_id per Slack channel — channel-level threading
_channel_convs: dict[str, str] = {}

def conv_for(channel_id: str) -> str:
    return _channel_convs.setdefault(channel_id, str(uuid.uuid4()))

@app.event("app_mention")
async def on_mention(event, say):
    text = event["text"]
    slack_user_id = event["user"]            # e.g., "U01ABC"
    team_id = event["team"]                  # e.g., "T01XYZ" — Slack workspace
    channel_id = event["channel"]

    # Map Slack identifiers to Synap scopes:
    #   customer_id ← team_id      (one Slack workspace = one customer)
    #   user_id     ← slack_user_id
    #   conversation_id ← per-channel UUID
    conversation_id = conv_for(channel_id)

    # Register the incoming user turn on the conversation thread so
    # `conversation.context.fetch` has a real thread to scope against.
    await sdk.conversation.record_message(
        conversation_id=conversation_id,
        user_id=slack_user_id,
        customer_id=team_id,
        role="user",
        content=text,
    )

    ctx = await sdk.conversation.context.fetch(
        conversation_id=conversation_id,
        search_query=[text],
        max_results=6,
    )

    memory_block = "\n".join(f"- {f.content}" for f in ctx.facts[:5])
    prefs_block = "\n".join(f"- {p.content}" for p in ctx.preferences[:3])

    completion = await openai.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": (
                "You are a helpful Slack bot.\n"
                f"Known facts:\n{memory_block or '(none)'}\n"
                f"User preferences:\n{prefs_block or '(none)'}"
            )},
            {"role": "user", "content": text},
        ],
    )
    reply = completion.choices[0].message.content

    await say(text=reply, thread_ts=event.get("ts"))

    # Record the assistant turn on the same conversation thread.
    await sdk.conversation.record_message(
        conversation_id=conversation_id,
        user_id=slack_user_id,
        customer_id=team_id,
        role="assistant",
        content=reply,
    )

    # Fire-and-forget ingestion so it doesn't add latency to the response
    asyncio.create_task(sdk.memories.create(
        document=f"<@{slack_user_id}>: {text}\nBot: {reply}",
        document_type="ai-chat-conversation",
        user_id=slack_user_id,
        customer_id=team_id,
        metadata={
            "conversation_id": conversation_id,
            "channel": channel_id,
            "source": "slack",
        },
    ))

async def main():
    await sdk.initialize()
    handler = AsyncSocketModeHandler(app, os.environ["SLACK_APP_TOKEN"])
    await handler.start_async()

asyncio.run(main())