feat: showcase text generation and thinking steps from suggested prompts

README.md

@@ -152,7 +152,9 @@ Configures the new Slack Assistant features, providing a dedicated side panel UI
 
 ### `/ai`
 
-The `llm_caller.py` file, which handles OpenAI API integration and message formatting. It includes the `call_llm()` function that sends conversation threads to OpenAI's models.
+The `llm_caller.py` file calls the OpenAI API and streams the generated response into a Slack conversation.
+
+The `tools` directory contains app-specific functions for the LLM to call.
 
 ## App Distribution / OAuth
 

ai/llm_caller.py

@@ -1,27 +1,101 @@
+import json
 import os
-from typing import Dict, List
 
 import openai
-from openai import Stream
-from openai.types.responses import ResponseStreamEvent
+from openai.types.responses import ResponseInputParam
+from slack_sdk.models.messages.chunk import TaskUpdateChunk
+from slack_sdk.web.chat_stream import ChatStream
 
-DEFAULT_SYSTEM_CONTENT = """
-You're an assistant in a Slack workspace.
-Users in the workspace will ask you to help them write something or to think better about a specific topic.
-You'll respond to those questions in a professional way.
-When you include markdown text, convert them to Slack compatible ones.
-When a prompt has Slack's special syntax like <@USER_ID> or <#CHANNEL_ID>, you must keep them as-is in your response.
-"""
+from ai.tools.dice import roll_dice, roll_dice_definition
 
 
 def call_llm(
-    messages_in_thread: List[Dict[str, str]],
-    system_content: str = DEFAULT_SYSTEM_CONTENT,
-) -> Stream[ResponseStreamEvent]:
-    openai_client = openai.OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-    messages = [{"role": "system", "content": system_content}]
-    messages.extend(messages_in_thread)
-    response = openai_client.responses.create(
-        model="gpt-4o-mini", input=messages, stream=True
+    streamer: ChatStream,
+    prompts: ResponseInputParam,
+):
+    """
+    Stream an LLM response to prompts with an example dice rolling function
+
+    https://docs.slack.dev/tools/python-slack-sdk/web#sending-streaming-messages
+    https://platform.openai.com/docs/guides/text
+    https://platform.openai.com/docs/guides/streaming-responses
+    https://platform.openai.com/docs/guides/function-calling
+    """
+    llm = openai.OpenAI(
+        api_key=os.getenv("OPENAI_API_KEY"),
+    )
+    tool_calls = []
+    response = llm.responses.create(
+        model="gpt-4o-mini",
+        input=prompts,
+        tools=[
+            roll_dice_definition,
+        ],
+        stream=True,
     )
-    return response
+    for event in response:
+        # Markdown text from the LLM response is streamed in chat as it arrives
+        if event.type == "response.output_text.delta":
+            streamer.append(markdown_text=f"{event.delta}")
+
+        # Function calls are saved for later computation and a new task is shown
+        if event.type == "response.output_item.done":
+            if event.item.type == "function_call":
+                tool_calls.append(event.item)
+                if event.item.name == "roll_dice":
+                    args = json.loads(event.item.arguments)
+                    streamer.append(
+                        chunks=[
+                            TaskUpdateChunk(
+                                id=f"{event.item.call_id}",
+                                title=f"Rolling a {args['count']}d{args['sides']}...",
+                                status="in_progress",
+                            ),
+                        ],
+                    )
+
+    # Tool calls are performed and tasks are marked as completed in Slack
+    if tool_calls:
+        for call in tool_calls:
+            if call.name == "roll_dice":
+                args = json.loads(call.arguments)
+                prompts.append(
+                    {
+                        "id": call.id,
+                        "call_id": call.call_id,
+                        "type": "function_call",
+                        "name": "roll_dice",
+                        "arguments": call.arguments,
+                    }
+                )
+                result = roll_dice(**args)
+                prompts.append(
+                    {
+                        "type": "function_call_output",
+                        "call_id": call.call_id,
+                        "output": json.dumps(result),
+                    }
+                )
+                if result.get("error") is not None:
+                    streamer.append(
+                        chunks=[
+                            TaskUpdateChunk(
+                                id=f"{call.call_id}",
+                                title=f"{result['error']}",
+                                status="error",
+                            ),
+                        ],
+                    )
+                else:
+                    streamer.append(
+                        chunks=[
+                            TaskUpdateChunk(
+                                id=f"{call.call_id}",
+                                title=f"{result['description']}",
+                                status="complete",
+                            ),
+                        ],
+                    )
+
+        # Complete the LLM response after making tool calls
+        call_llm(streamer, prompts)

ai/tools/dice.py

@@ -0,0 +1,58 @@
+import random
+import time
+
+from openai.types.responses import FunctionToolParam
+
+
+def roll_dice(sides: int = 6, count: int = 1) -> dict:
+    if sides < 2:
+        return {
+            "error": "A die must have at least 2 sides",
+            "rolls": [],
+            "total": 0,
+        }
+
+    if count < 1:
+        return {
+            "error": "Must roll at least 1 die",
+            "rolls": [],
+            "total": 0,
+        }
+    rolls = [random.randint(1, sides) for _ in range(count)]
+    total = sum(rolls)
+
+    # Add a pause between rolls to demonstrate loading states
+    time.sleep(2)
+
+    return {
+        "rolls": rolls,
+        "total": total,
+        "description": f"Rolled a {count}d{sides} to total {total}",
+    }
+
+
+# Tool definition for OpenAI API
+#
+# https://platform.openai.com/docs/guides/function-calling
+roll_dice_definition: FunctionToolParam = {
+    "type": "function",
+    "name": "roll_dice",
+    "description": "Roll one or more dice with a specified number of sides. Use this when the user wants to roll dice or generate random numbers within a range.",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "sides": {
+                "type": "integer",
+                "description": "The number of sides on the die (e.g., 6 for a standard die, 20 for a d20)",
+                "default": 6,
+            },
+            "count": {
+                "type": "integer",
+                "description": "The number of dice to roll",
+                "default": 1,
+            },
+        },
+        "required": ["sides", "count"],
+    },
+    "strict": False,
+}

app.py

@@ -2,7 +2,6 @@
 import os
 
 from dotenv import load_dotenv
-
 from slack_bolt import App
 from slack_bolt.adapter.socket_mode import SocketModeHandler
 from slack_sdk import WebClient
@@ -22,6 +21,7 @@
         token=os.environ.get("SLACK_BOT_TOKEN"),
     ),
 )
+
 # Register Listeners
 register_listeners(app)
 

listeners/assistant/assistant_thread_started.py

@@ -1,5 +1,4 @@
 from logging import Logger
-from typing import Dict, List
 
 from slack_bolt import Say, SetSuggestedPrompts
 
@@ -18,24 +17,19 @@ def assistant_thread_started(
         logger: Logger instance for error tracking
     """
     try:
-        say("How can I help you?")
-
-        prompts: List[Dict[str, str]] = [
-            {
-                "title": "What does Slack stand for?",
-                "message": "Slack, a business communication service, was named after an acronym. Can you guess what it stands for?",
-            },
-            {
-                "title": "Write a draft announcement",
-                "message": "Can you write a draft announcement about a new feature my team just released? It must include how impactful it is.",
-            },
-            {
-                "title": "Suggest names for my Slack app",
-                "message": "Can you suggest a few names for my Slack app? The app helps my teammates better organize information and plan priorities and action items.",
-            },
-        ]
-
-        set_suggested_prompts(prompts=prompts)
+        say("What would you like to do today?")
+        set_suggested_prompts(
+            prompts=[
+                {
+                    "title": "Prompt a task with thinking steps",
+                    "message": "Wonder a few deep thoughts.",
+                },
+                {
+                    "title": "Roll dice for a random number",
+                    "message": "Roll two 12-sided dice and three 6-sided dice for a psuedo-random score.",
+                },
+            ]
+        )
     except Exception as e:
         logger.exception(f"Failed to handle an assistant_thread_started event: {e}", e)
         say(f":warning: Something went wrong! ({e})")