Félix Malfait
e7ebf51e50
## Overview This PR replaces the dynamic agent handoff system with a more predictable planning-based router that decides upfront how to handle multi-agent coordination. ## Major Changes ### 🔄 Architecture Shift: Handoffs → Planning **Removed:** - `AgentHandoffEntity` and handoff tracking system - `AgentHandoffService` and `AgentHandoffExecutorService` - Dynamic agent-to-agent transfers during execution - Handoff tool generation and description templates **Added:** - `AiRouterService` with two strategies: `simple` (single agent) and `planned` (multi-agent) - `AgentPlanExecutorService` for executing multi-step plans - Plan validation (cycle detection, dependency resolution) - `UnifiedRouterResult` type with discriminated union ### 🤖 New Standard Agents Added two new specialized agents: - **Researcher Agent**: Web search, fact-finding, competitive intelligence - **Code Agent**: TypeScript function generation for serverless workflows ### 🏗️ Router Refactoring (Latest) Split router responsibilities into focused services: - `AiRouterStrategyDeciderService`: Decides simple vs planned strategy - `AiRouterPlanGeneratorService`: Generates and validates execution plans - `AiRouterService`: Coordinates between services (reduced from 426→275 lines) ### ⚙️ Configuration Improvements - Added `outputStrategy` to agent definitions (`direct` vs `synthesize`) - Removed hardcoded special cases for workflow-builder - Added `plannerModel` field to workspace entity - Increased `MAX_STEPS` from 10 to 25 for complex workflows ### 📝 Agent Prompt Refinements Significantly simplified prompts for better clarity: - Workflow Builder: 51→36 lines - Helper: 49→28 lines - Data Manipulator: Enhanced with sorting guidance ### 🔍 Enhanced Debugging - Plan reasoning and step count in data message parts - Router debug info with token usage tracking - Better logging throughout execution pipeline ## Benefits 1. **Simpler Mental Model**: Router decides upfront vs dynamic transfers 2. **Better Predictability**: Users see the plan before execution 3. **Cleaner Architecture**: SRP with focused services 4. **Configuration Over Code**: Agent behavior via config, not hardcoded logic 5. **Plan Validation**: Catches invalid dependencies and cycles ## Migration Notes - Database migration removes `agentHandoff` table - Adds `plannerModel` column to workspace table - No API breaking changes (agent endpoints unchanged) ## Testing - Integration tests updated to remove handoff dependencies - Agent tool test utilities simplified - Plan validation covered by new logic ## Next Steps (Future PRs) - Parallel execution of independent plan steps - Dynamic re-planning based on results - Plan caching for common routing patterns - Error recovery strategies in plan executor
46 lines
1.0 KiB
TypeScript
46 lines
1.0 KiB
TypeScript
import {
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Column,
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CreateDateColumn,
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Entity,
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Index,
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JoinColumn,
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ManyToOne,
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OneToMany,
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PrimaryGeneratedColumn,
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Relation,
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} from 'typeorm';
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import { AgentChatThreadEntity } from 'src/engine/metadata-modules/ai-chat/entities/agent-chat-thread.entity';
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import { AgentChatMessagePartEntity } from './agent-chat-message-part.entity';
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export enum AgentChatMessageRole {
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USER = 'user',
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ASSISTANT = 'assistant',
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}
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@Entity('agentChatMessage')
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export class AgentChatMessageEntity {
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@PrimaryGeneratedColumn('uuid')
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id: string;
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@Column('uuid')
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@Index()
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threadId: string;
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@ManyToOne(() => AgentChatThreadEntity, (thread) => thread.messages, {
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onDelete: 'CASCADE',
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})
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@JoinColumn({ name: 'threadId' })
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thread: Relation<AgentChatThreadEntity>;
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@Column({ type: 'enum', enum: AgentChatMessageRole })
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role: AgentChatMessageRole;
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@OneToMany(() => AgentChatMessagePartEntity, (part) => part.message)
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parts: Relation<AgentChatMessagePartEntity[]>;
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@CreateDateColumn()
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createdAt: Date;
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}
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