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* initial mcp * food ordering with mcp * prompt eng * splitting out goals and updating docs * a diff so I can get tests from codex * a diff so I can get tests from codex * oops, missing files * tests, file formatting * readme and setup updates * setup.md link fixes * readme change * readme change * readme change * stripe food setup script * single agent mode default * prompt engineering for better multi agent performance * performance should be greatly improved * Update goals/finance.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update activities/tool_activities.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * co-pilot PR suggested this change, and now fixed it * stronger wording around json format response * formatting * moved docs to dir * moved image assets under docs * cleanup env example, stripe guidance * cleanup --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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Changelog
All notable changes to this project will be documented in this file.
0.2.0 - 2025-04-24
Added
- Multi‑goal agent architecture with dynamic goal switching (
goal_choose_agent_type,ListAgents,ChangeGoal).- See the architecture guide and setup guide.
- New goal categories & agents: HR PTO scheduling/checking, paycheck integration, Financial (balances, money movement, loan application), E‑commerce order tracking.
- Force Confirmation:
SHOW_CONFIRMwill show a confirmation box before allowing the agent to run a tool. - Grok (
x.ai) LLM provider support viaGROK_API_KEY. - Extensive docs:
setup.md,architecture.md,architecture-decisions.md,adding-goals-and-tools.md, plus new diagrams & assets.
Changed
- UI Confirmation Box is less 'debug' looking and prettier.
- Package renamed to
temporal_AI_agentand version bumped to 0.2.0 inpyproject.toml. - Environment variables changed (see
.env_example): (RAPIDAPI_HOST_*,AGENT_GOALdefaults,GOAL_CATEGORIES,SHOW_CONFIRM,FIN_START_REAL_WORKFLOW).
[0.1.0] - 2025-01-04
Added
- Initial release of the Temporal AI Agent demo.
- Single goal agent architecture with a single goal and agent type.
- This is the agent demoed in the YouTube video.
