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https://github.com/temporal-community/temporal-ai-agent.git
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Merge branch 'development' of https://github.com/joshmsmith/temporal-ai-agent into development
This commit is contained in:
@@ -8,7 +8,7 @@
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"hrsAddedPerMonth": 8
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},
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{
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"email": "lainecaseysmith@gmail.com",
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"email": "laine@awesome.com",
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"currentPTOHrs": 40,
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"hrsAddedPerMonth": 12
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}
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@@ -8,17 +8,17 @@ TREASURE_LOCATION = {
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}
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HINTS = [
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"state of Washington",
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"city of Seattle",
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"country of " + TREASURE_LOCATION["country"],
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"state of " + TREASURE_LOCATION["state_full"],
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"city of " + TREASURE_LOCATION["city"],
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"at a company HQ",
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"The company's tech traces its roots to a project called Cadence", #thanks, Grok
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"The company offers a tool that lets developers write code as if it's running forever, no matter what crashes", #thanks, Grok
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]
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''' Grok provided hints:
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Here are additional company-specific clues about Temporal that could help players in your game guess the address (300 Lenora St, Seattle, WA) by focusing on the company itself. These are designed to be intriguing and game-friendly:
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''' Additional Grok provided hints about Temporal:
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"This company was founded by two engineers who previously worked on a system named after a South American river at Uber."
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"Their platform is all about orchestrating workflows that can survive failures—like a conductor keeping the music going."
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"They offer a tool that lets developers write code as if it’s running forever, no matter what crashes."
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"The company’s tech traces its roots to a project called Cadence, which they took to the next level."
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"Their mission is tied to making distributed systems feel as simple as writing a single app."
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"They’ve got a knack for ‘durability’—both in their software and their growing reputation."
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"This outfit spun out of experiences at AWS and Uber, blending cloud and ride-sharing know-how."
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@@ -34,7 +34,6 @@ def give_hint(args: dict) -> dict:
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index = hint_total % len(HINTS)
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hint_text = HINTS[index]
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print(f"hint_total: {hint_total}, length: {len(HINTS)}, index: {index}")
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hint_total = hint_total + 1
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return {
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"hint_number": hint_total,
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@@ -50,6 +50,7 @@ guess_location_tool = ToolDefinition(
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),
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],
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)
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# ----- Travel use cases tools -----
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search_flights_tool = ToolDefinition(
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name="SearchFlights",
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@@ -198,12 +199,12 @@ future_pto_calc_tool = ToolDefinition(
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ToolArgument(
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name="start_date",
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type="string",
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description="Start date of proposed PTO",
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description="Start date of proposed PTO, sent in the form yyyy-mm-dd",
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),
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ToolArgument(
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name="end_date",
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type="string",
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description="End date of proposed PTO",
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description="End date of proposed PTO, sent in the form yyyy-mm-dd",
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),
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ToolArgument(
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name="email",
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@@ -221,12 +222,12 @@ book_pto_tool = ToolDefinition(
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ToolArgument(
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name="start_date",
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type="string",
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description="Start date of proposed PTO",
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description="Start date of proposed PTO, sent in the form yyyy-mm-dd",
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),
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ToolArgument(
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name="end_date",
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type="string",
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description="End date of proposed PTO",
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description="End date of proposed PTO, sent in the form yyyy-mm-dd",
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),
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ToolArgument(
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name="email",
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@@ -26,11 +26,11 @@ with workflow.unsafe.imports_passed_through():
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# Constants
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MAX_TURNS_BEFORE_CONTINUE = 250
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SHOW_CONFIRM = True
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show_confirm_env = os.getenv("SHOW_CONFIRM")
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if show_confirm_env is not None:
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if show_confirm_env == "False":
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SHOW_CONFIRM = False
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if show_confirm_env is not None and show_confirm_env.lower() == "false":
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SHOW_CONFIRM = False
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else:
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SHOW_CONFIRM = True
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#ToolData as part of the workflow is what's accessible to the UI - see LLMResponse.jsx for example
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class ToolData(TypedDict, total=False):
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