Restructure the AI workflow from a single-agent model to a specialized
multi-agent system with distinct roles:
- Add AgentType enum (Main, Orchestration, Planning, Execution) to define
agent specializations
- Replace AIControllerService and AIFunctionService with modular agent
classes in Services/AIServices/:
- MainAgent: Handles user interaction and delegates to orchestration
- OrchestrationAgent: Coordinates plan execution and step-by-step workflow
- PlanningAgent: Creates and revises execution plans
- ExecutionAgent: Executes individual plan steps
- AIController: Base class providing common agent loop functionality
- Create specialized prompts (OrchestrationPrompt, ExecutionPrompt) for
agent-specific behavior
- Add OrchestrationResult type to communicate workflow control decisions
(continue, abort, replan)
- Introduce agent-specific function scoping:
- ExecuteWorkflow for main agent
- CompleteTask for execution agent
- CompleteStep/Replan/CancelPlan for orchestration agent
- SubmitPlan/AskUserQuestionPlanning for planning agent
- Update BaseAIClass to use agentType property instead of isPlanningAgent
boolean for model selection
- Simplify ExecutionPlan and ExecutionStep types by removing execution
state tracking (moved to agent coordination)
- Remove PlanningEnabledAppendix and ExecutionStatus enum (superseded by
agent architecture)
- Add comprehensive integration tests for agent workflows
This architecture provides better separation of concerns, clearer agent
responsibilities, and more robust plan execution with explicit orchestration
control flow.
Add distinct AskUserQuestionPlanning and AskUserQuestionExecution functions to enable user consultation during both planning and execution phases. Update system prompt to clarify when to seek user input vs. replan. Fix plan area rendering timing and improve execution flow handling.
- Add currentProvider getter to AI classes for provider access
- Enhance planning prompt to discourage over-engineering and scope creep
- Return Unknown enum instead of throwing for invalid AI functions
- Add completion reminders to execution steps
- Fix ChatPlanArea height calculation timing
- Update tests to handle Unknown function gracefully
Introduce separate planning model setting to allow using different models for planning vs execution. Add visual countdown display when rate limits are hit, with improved retry delay parsing across providers (Claude, OpenAI, Gemini). Refactor settings tab into Views directory and enhance mobile layout for input controls.
Add new CompletePlan function with schema and validation to allow agents to explicitly signal when all execution steps are done. Update system prompt to include completion confirmation step. Refactor execution loop to recursively prompt for completion if incomplete, with MAX_EXECUTION_DEPTH limit replacing MAX_PLANNING_ITERATIONS. Remove automatic incomplete execution handling in favor of explicit agent-driven completion.
- Add planning mode toggle and AskUserQuestion function for interactive planning
- Fix Gemini cross-provider function call detection using toolId presence
- Update OpenAI naming service to handle new response format
- Improve system prompts by removing complexity gate, streamlining to action-first principle
- Add InputDisplay component and question mode to ChatInput
- Refactor execution plan error messages to show all incomplete steps
- Update tests to reflect cross-provider function call format changes
Restructure system prompt to enforce mandatory complexity evaluation before action. Replace verbose multi-step planning framework with concise gate-based decision model. Add UI for execution plan visibility. Improve planning/execution separation by blocking execution tools during planning phase. Remove cancellation indicator component. Fix conversation deletion bug preventing saves after delete. Strengthen type safety for AIFunction names. Simplify function summary format for planning agent. Update test mocks for new callback signatures.
- Move parseFunctionCall/parseFunctionResponse to ResponseHelper
- Enhance orphaned call/response filtering with detailed debug logs
- Add toolId to conversation content for better tracking
- Fix planning workflow execution mechanics and step numbering
- Remove unused planning agent appendix and detailedAppendixForPlanningAgent
- Add conversation save callbacks throughout AI controller loops
- Improve multi-agent function handling to avoid exceptions
- Update all tests to include toolId fields for proper filtering
Previously the next step description was embedded in the completion message string.
Now return it as a separate structured object with step number, description,
instruction, and optional context for better programmatic access.
- Move prompts from AIClasses to AIPrompts directory
- Replace centralized IPrompt injection with direct property setters on IAIClass
- Remove allowDestructiveActions parameter from streamRequest methods
- Add toolDefinitions, systemPrompt, and userInstruction properties to IAIClass
- Refactor AIFunctionDefinitions to static methods with agent-specific tool sets
- Add planning agent function definitions (CreatePlan, Replan, CompleteStep, SubmitPlan)
- Create AIControllerService to handle agent orchestration
- Add execution plan related copy strings and replacement utility
- Update all AI providers (Claude, Gemini, OpenAI) to use new architecture
