Agents & Assistants
If you don't have a paid workspace for development, you can join the Developer Program and provision a sandbox with access to all Slack features for free.
Agents and assistants comprise a new messaging experience for Slack. If you're unfamiliar with using agents and assistants within Slack, you'll want to read the API documentation on the subject. Then come back here to implement them with Bolt!
Configuring your app to support assistants
-
Within App Settings, enable the Agents & Assistants feature.
-
Within the App Settings OAuth & Permissions page, add the following scopes:
- Within the App Settings Event Subscriptions page, subscribe to the following events:
You could implement your own assistants by listening for the assistant_thread_started, assistant_thread_context_changed, and message.im events (see implementation details below). That being said, using the Assistant class will streamline the process. And we already wrote this nice guide for you!
The Assistant class instance
The Assistant class can be used to handle the incoming events expected from a user interacting with an assistant in Slack. A typical flow would look like:
- The user starts a thread. The
Assistantclass handles the incomingassistant_thread_startedevent. - The thread context may change at any point. The Assistant class can handle any incoming
assistant_thread_context_changedevents. The class also provides a default context store to keep track of thread context changes as the user moves through Slack. - The user responds. The Assistant class handles the incoming
message.imevent.
assistant = Assistant()
# This listener is invoked when a human user opened an assistant thread
@assistant.thread_started
def start_assistant_thread(say: Say, set_suggested_prompts: SetSuggestedPrompts):
# Send the first reply to the human who started chat with your app's assistant bot
say(":wave: Hi, how can I help you today?")
# Setting suggested prompts is optional
set_suggested_prompts(
prompts=[
# If the suggested prompt is long, you can use {"title": "short one to display", "message": "full prompt"} instead
"What does SLACK stand for?",
"When Slack was released?",
],
)
# This listener is invoked when the human user sends a reply in the assistant thread
@assistant.user_message
def respond_in_assistant_thread(
payload: dict,
logger: logging.Logger,
context: BoltContext,
set_status: SetStatus,
client: WebClient,
say: Say,
):
try:
# Tell the human user the assistant bot acknowledges the request and is working on it
set_status("is typing...")
# Collect the conversation history with this user
replies_in_thread = client.conversations_replies(
channel=context.channel_id,
ts=context.thread_ts,
oldest=context.thread_ts,
limit=10,
)
messages_in_thread: List[Dict[str, str]] = []
for message in replies_in_thread["messages"]:
role = "user" if message.get("bot_id") is None else "assistant"
messages_in_thread.append({"role": role, "content": message["text"]})
# Pass the latest prompt and chat history to the LLM (call_llm is your own code)
returned_message = call_llm(messages_in_thread)
# Post the result in the assistant thread
say(text=returned_message)
except Exception as e:
logger.exception(f"Failed to respond to an inquiry: {e}")
# Don't forget sending a message telling the error
# Without this, the status 'is typing...' won't be cleared, therefore the end-user is unable to continue the chat
say(f":warning: Sorry, something went wrong during processing your request (error: {e})")
# Enable this assistant middleware in your Bolt app
app.use(assistant)
While the assistant_thread_started and assistant_thread_context_changed events do provide Slack-client thread context information, the message.im event does not. Any subsequent user message events won't contain thread context data. For that reason, Bolt not only provides a way to store thread context — the threadContextStore property — but it also provides an instance that is utilized by default. This implementation relies on storing and retrieving message metadata as the user interacts with the assistant.
If you do provide your own threadContextStore property, it must feature get and save methods.
Refer to the module document to learn the available listener arguments.
Handling a new thread
When the user opens a new thread with your assistant, the assistant_thread_started event will be sent to your app.
When a user opens an assistant thread while in a channel, the channel info is stored as the thread's AssistantThreadContext data. You can grab that info by using the get_thread_context utility, as subsequent user message event payloads won't include the channel info.
Block Kit interactions in the assistant thread
For advanced use cases, Block Kit buttons may be used instead of suggested prompts, as well as the sending of messages with structured metadata to trigger subsequent interactions with the user.
For example, an app can display a button such as "Summarize the referring channel" in the initial reply. When the user clicks the button and submits detailed information (such as the number of messages, days to check, purpose of the summary, etc.), the app can handle that information and post a message that describes the request with structured metadata.
By default, apps can't respond to their own bot messages (Bolt prevents infinite loops by default). However, if you pass ignoring_self_assistant_message_events_enabled=False to the App constructor and add a bot_message listener to your Assistant middleware, your app can continue processing the request as shown below:
app = App(
token=os.environ["SLACK_BOT_TOKEN"],
# This must be set to handle bot message events
ignoring_self_assistant_message_events_enabled=False,
)
assistant = Assistant()
@assistant.thread_started
def start_assistant_thread(say: Say):
say(
text=":wave: Hi, how can I help you today?",
blocks=[
{
"type": "section",
"text": {"type": "mrkdwn", "text": ":wave: Hi, how can I help you today?"},
},
{
"type": "actions",
"elements": [
# You can have multiple buttons here
{
"type": "button",
"action_id": "assistant-generate-random-numbers",
"text": {"type": "plain_text", "text": "Generate random numbers"},
"value": "clicked",
},
],
},
],
)
# This listener is invoked when the above button is clicked
@app.action("assistant-generate-random-numbers")
def configure_random_number_generation(ack: Ack, client: WebClient, body: dict):
ack()
client.views_open(
trigger_id=body["trigger_id"],
view={
"type": "modal",
"callback_id": "configure_assistant_summarize_channel",
"title": {"type": "plain_text", "text": "My Assistant"},
"submit": {"type": "plain_text", "text": "Submit"},
"close": {"type": "plain_text", "text": "Cancel"},
# Relay the assistant thread information to app.view listener
"private_metadata": json.dumps(
{
"channel_id": body["channel"]["id"],
"thread_ts": body["message"]["thread_ts"],
}
),
"blocks": [
{
"type": "input",
"block_id": "num",
"label": {"type": "plain_text", "text": "# of outputs"},
# You can have this kind of predefined input from a user instead of parsing human text
"element": {
"type": "static_select",
"action_id": "input",
"placeholder": {"type": "plain_text", "text": "How many numbers do you need?"},
"options": [
{"text": {"type": "plain_text", "text": "5"}, "value": "5"},
{"text": {"type": "plain_text", "text": "10"}, "value": "10"},
{"text": {"type": "plain_text", "text": "20"}, "value": "20"},
],
"initial_option": {"text": {"type": "plain_text", "text": "5"}, "value": "5"},
},
}
],
},
)
# This listener is invoked when the above modal is submitted
@app.view("configure_assistant_summarize_channel")
def receive_random_number_generation_details(ack: Ack, client: WebClient, payload: dict):
ack()
num = payload["state"]["values"]["num"]["input"]["selected_option"]["value"]
thread = json.loads(payload["private_metadata"])
# Post a bot message with structured input data
# The following assistant.bot_message will continue processing
# If you prefer processing this request within this listener, it also works!
# If you don't need bot_message listener, no need to set ignoring_self_assistant_message_events_enabled=False
client.chat_postMessage(
channel=thread["channel_id"],
thread_ts=thread["thread_ts"],
text=f"OK, you need {num} numbers. I will generate it shortly!",
metadata={
"event_type": "assistant-generate-random-numbers",
"event_payload": {"num": int(num)},
},
)
# This listener is invoked whenever your app's bot user posts a message
@assistant.bot_message
def respond_to_bot_messages(logger: logging.Logger, set_status: SetStatus, say: Say, payload: dict):
try:
if payload.get("metadata", {}).get("event_type") == "assistant-generate-random-numbers":
# Handle the above random-number-generation request
set_status("is generating an array of random numbers...")
time.sleep(1)
nums: Set[str] = set()
num = payload["metadata"]["event_payload"]["num"]
while len(nums) < num:
nums.add(str(random.randint(1, 100)))
say(f"Here you are: {', '.join(nums)}")
else:
# nothing to do for this bot message
# If you want to add more patterns here, be careful not to cause infinite loop messaging
pass
except Exception as e:
logger.exception(f"Failed to respond to an inquiry: {e}")
...
Handling thread context changes
When the user switches channels, the assistant_thread_context_changed event will be sent to your app.
If you use the built-in Assistant middleware without any custom configuration, the updated context data is automatically saved as message metadata of the first reply from the assistant bot.
As long as you use the built-in approach, you don't need to store the context data within a datastore. The downside of this default behavior is the overhead of additional calls to the Slack API. These calls include those to conversations.history, which are used to look up the stored message metadata that contains the thread context (via get_thread_context).
To store context elsewhere, pass a custom AssistantThreadContextStore implementation to the Assistant constructor. We provide FileAssistantThreadContextStore, which is a reference implementation that uses the local file system. Since this reference implementation relies on local files, it's not advised for use in production. For production apps, we recommend creating a class that inherits AssistantThreadContextStore.
from slack_bolt import FileAssistantThreadContextStore
assistant = Assistant(thread_context_store=FileAssistantThreadContextStore())
Handling the user response
When the user messages your assistant, the message.im event will be sent to your app.
Messages sent to the assistant do not contain a subtype and must be deduced based on their shape and any provided message metadata.
There are three utilities that are particularly useful in curating the user experience:
...
# This listener is invoked when the human user posts a reply
@assistant.user_message
def respond_to_user_messages(logger: logging.Logger, set_status: SetStatus, say: Say):
try:
set_status("is typing...")
say("Please use the buttons in the first reply instead :bow:")
except Exception as e:
logger.exception(f"Failed to respond to an inquiry: {e}")
say(f":warning: Sorry, something went wrong during processing your request (error: {e})")
# Enable this assistant middleware in your Bolt app
app.use(assistant)
Full example: Assistant Template
Below is the assistant.py listener file of the Assistant Template repo we've created for you to build off of.
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