feat: showcase text generation and thinking steps from suggested prompts by zimeg · Pull Request #37 · slack-samples/bolt-python-assistant-template

zimeg · 2025-12-18T00:09:43Z

Type of change

New feature

Summary

This PR showcases "chunks" in a chat stream. The example is meant to be quick to understand but perhaps not so meaningful. Related: slackapi/python-slack-sdk#1809

Requirements

I have ensured the changes I am contributing align with existing patterns and have tested and linted my code
I've read and agree to the Code of Conduct

jonigl · 2025-12-18T12:13:40Z

listeners/assistant/message.py

+        # The second example shows detailed thinking steps similar to tool calls
+        else:
+            streamer.append(
+                chunks=[
+                    MarkdownTextChunk(
+                        text="Hello.\nI have received the task. ",
+                    ),
+                    MarkdownTextChunk(
+                        text="This task appears manageable.\nThat is good.",
+                    ),
+                    TaskUpdateChunk(
+                        id="001",
+                        title="Understanding the task...",
+                        status="in_progress",
+                        details="- Identifying the goal\n- Identifying constraints",
+                    ),
+                    TaskUpdateChunk(
+                        id="002",
+                        title="Performing acrobatics...",
+                        status="pending",
+                    ),
+                ],
+            )
+            time.sleep(4)
+
+            streamer.append(
+                chunks=[
+                    TaskUpdateChunk(
+                        id="001",
+                        title="Understanding the task...",
+                        status="complete",
+                        details="\n- Pretending this was obvious",
+                        output="We'll continue to ramble now",
+                    ),
+                    TaskUpdateChunk(
+                        id="002",
+                        title="Performing acrobatics...",
+                        status="in_progress",
+                    ),
+                ],
+            )
+            time.sleep(4)


Nice! I've been experimenting with something similar on my own, I like this idea. Featuring what is the agent doing is great like (tools calls or thinking steps)

srtaalej · 2025-12-18T19:46:07Z

listeners/events/app_mentioned.py

        )

-        returned_message = call_llm([{"role": "user", "content": text}])
+        returned_message = call_llm(text)


zimeg · 2026-01-19T06:30:55Z

📸 Demo with current changes!

Timeline with tool calls and LLM call

dice.mov

Plan with mocked data

plan.mov

mwbrooks

✅ Super fun prompts that showcase the timeline and plan display styles alongside the new task and plan blocks. I think this is a good start to inspiring developers to integrate their own tool calls.

🧪 Local testing worked like a charm. I didn't find any issues.

📝 I left a few suggestions. Nothing is blocking, but I'd ask to consider switching the inverse logic (maybe I'm just a little slow in the ol'noodle and need it outlined simpler). Feel free to pump any-or-all to the future.

🚀 Please drop that draft label so we can smash the merge!

agent/tools/dice.py

mwbrooks · 2026-01-19T23:18:14Z

listeners/assistant/message.py

+        # This first example shows a generated text response for the provided prompt
+        if message["text"] != "Wonder a few deep thoughts.":


suggestion: It took me a few re-reads before I noticed the inverted logic (!=).

At first, I kept wondering why "Wonder a few deep thoughts." would be passed directly to the LLM, while the else statement handled the example.

Non-blocker, but could we flip this logic to be == "Wonder a few deep thoughts.": and have the else handle the general LLM response?

mwbrooks · 2026-01-19T23:19:58Z

listeners/assistant/message.py

+            streamer.append(
+                chunks=[
+                    MarkdownTextChunk(
+                        text="Hello.\nI have received the task. ",
+                    ),
+                    MarkdownTextChunk(
+                        text="This task appears manageable.\nThat is good.",
+                    ),
+                    TaskUpdateChunk(
+                        id="001",
+                        title="Understanding the task...",
+                        status="in_progress",
+                        details="- Identifying the goal\n- Identifying constraints",
+                    ),
+                    TaskUpdateChunk(
+                        id="002",
+                        title="Performing acrobatics...",
+                        status="pending",
+                    ),
+                ],
+            )
+            time.sleep(4)


praise: Love this example. It's dead simple and easy to grok. It's ripe to be altered, experimented, and hacked on for folks playing with the sample. 🙌🏻

mwbrooks · 2026-01-19T23:21:10Z

ai/tools/__init__.py

suggestion: I think it's reasonable to rename ai/ to agent/ if we want, but it can also happen in a later PR.

@mwbrooks Awesome callout! Let's make it in this PR as part of 6ab8795 with the addition of tools 🤖

listeners/assistant/message.py

srtaalej · 2026-01-20T19:02:12Z

agent/tools/dice.py

i really like this example 🤩

@srtaalej It makes for fun games! 🎲 ✨

srtaalej

Nice changes and its working for me ⭐ ⭐ ⭐

srtaalej · 2026-01-20T21:08:01Z

agent/llm_caller.py

-    messages.extend(messages_in_thread)
-    response = openai_client.responses.create(
-        model="gpt-4o-mini", input=messages, stream=True
+    streamer: ChatStream,


what do we think about moving the OpenAI client initialization to the module level instead of creating it inside call_llm() 🤔 that way we’re not re-initializing the client on every call
it’s probably fine either way for this dice-rolling use case, but it might be better to model best practices for users ❓

@srtaalej That might be nice to follow up with! At the moment I find the following error perhaps due to import order and the "dotenv" package of the main module though:

openai.OpenAIError: The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable

🗣️ ramble: We might also consider keeping it within a function to avoid global variables, but I do not know the best practices of modules, I admit!

Ah, i was getting the same error when i was working on the app. Ill try to figure out how we fixed it in case we run into it again but good work! ⭐ ⭐ ⭐

Co-authored-by: Michael Brooks <michael@michaelbrooks.ca>

zimeg

@jonigl @srtaalej @mwbrooks Thanks all for taking a look at these changes and the kind encouragement 💌

I made a few changes around code structure to make understanding easier I hope, but we might want to follow up with instructions around development with the CLI too.

Let's merge this after a bit more testing 🧪 ✨

agent/tools/dice.py

zimeg · 2026-01-20T23:23:00Z

ai/tools/__init__.py

@mwbrooks Awesome callout! Let's make it in this PR as part of 6ab8795 with the addition of tools 🤖

zimeg · 2026-01-20T23:23:35Z

agent/tools/dice.py

@srtaalej It makes for fun games! 🎲 ✨

zimeg · 2026-01-20T23:27:16Z

agent/llm_caller.py

-    messages.extend(messages_in_thread)
-    response = openai_client.responses.create(
-        model="gpt-4o-mini", input=messages, stream=True
+    streamer: ChatStream,


@srtaalej That might be nice to follow up with! At the moment I find the following error perhaps due to import order and the "dotenv" package of the main module though:

openai.OpenAIError: The api_key client option must be set either by passing api_key to the client or by setting the OPENAI_API_KEY environment variable

zimeg · 2026-01-20T23:29:26Z

agent/llm_caller.py

-    messages.extend(messages_in_thread)
-    response = openai_client.responses.create(
-        model="gpt-4o-mini", input=messages, stream=True
+    streamer: ChatStream,


🗣️ ramble: We might also consider keeping it within a function to avoid global variables, but I do not know the best practices of modules, I admit!

listeners/assistant/message.py

Co-authored-by: Michael Brooks <michael@michaelbrooks.ca>

zimeg · 2026-01-21T00:56:22Z

@mwbrooks Thanks for that last minute find too! I'll merge this now for upcoming testing and continued iterations 🚢 💨 🫡

zimeg added 2 commits December 17, 2025 15:45

feat: showcase text generation and thinking steps from suggested prompts

242297a

fix: append to details instead of overwrite past arguments

ea6c722

zimeg requested review from mwbrooks and srtaalej December 18, 2025 00:09

zimeg self-assigned this Dec 18, 2025

zimeg added the enhancement New feature or request label Dec 18, 2025

zimeg marked this pull request as draft December 18, 2025 00:09

jonigl reviewed Dec 18, 2025

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srtaalej approved these changes Dec 18, 2025

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feat: roll dice

4a5de84

mwbrooks approved these changes Jan 19, 2026

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srtaalej self-requested a review January 20, 2026 18:59

srtaalej reviewed Jan 20, 2026

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srtaalej approved these changes Jan 20, 2026

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zimeg marked this pull request as ready for review January 20, 2026 19:52

srtaalej reviewed Jan 20, 2026

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zimeg and others added 4 commits January 20, 2026 15:17

docs: improve comments to reason about sections of code

ac2816f

Co-authored-by: Michael Brooks <michael@michaelbrooks.ca>

refactor: move 'ai' features to an 'agent' directory

6ab8795

refactor: reverse the order of expected prompts for longform demo first

e2f6fa2

fix: match verbe tenses of actions and details in steps

7ddcac0

zimeg commented Jan 21, 2026

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mwbrooks reviewed Jan 21, 2026

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listeners/assistant/message.py Outdated Show resolved Hide resolved

docs: correct spellings of shocked wordage in example

d6af288

Co-authored-by: Michael Brooks <michael@michaelbrooks.ca>

zimeg merged commit b387ecf into feat-ai-apps-thinking-steps Jan 21, 2026
2 checks passed

zimeg deleted the zimeg-feat-chunks branch January 21, 2026 00:56

zimeg mentioned this pull request Jan 22, 2026

feat: showcase thinking steps slack-samples/bolt-js-assistant-template#98

Merged

5 tasks

		# This first example shows a generated text response for the provided prompt
		if message["text"] != "Wonder a few deep thoughts.":

Conversation

zimeg commented Dec 18, 2025

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zimeg commented Jan 19, 2026

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zimeg commented Jan 21, 2026

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