feat(aia): Implement Protocol Agent MVP with reusable Agent framework
Sprint 1-3 Completed (Backend + Frontend): Backend (Sprint 1-2): - Implement 5-layer Agent framework (Query->Planner->Executor->Tools->Reflection) - Create agent_schema with 6 tables (agent_definitions, stages, prompts, sessions, traces, reflexion_rules) - Create protocol_schema with 2 tables (protocol_contexts, protocol_generations) - Implement Protocol Agent core services (Orchestrator, ContextService, PromptBuilder) - Integrate LLM service adapter (DeepSeek/Qwen/GPT-5/Claude) - 6 API endpoints with full authentication - 10/10 API tests passed Frontend (Sprint 3): - Add Protocol Agent entry in AgentHub (indigo theme card) - Implement ProtocolAgentPage with 3-column layout - Collapsible sidebar (Gemini style, 48px <-> 280px) - StatePanel with 5 stage cards (scientific_question, pico, study_design, sample_size, endpoints) - ChatArea with sync button and action cards integration - 100% prototype design restoration (608 lines CSS) - Detailed endpoints structure: baseline, exposure, outcomes, confounders Features: - 5-stage dialogue flow for research protocol design - Conversation-driven interaction with sync-to-protocol button - Real-time context state management - One-click protocol generation button (UI ready, backend pending) Database: - agent_schema: 6 tables for reusable Agent framework - protocol_schema: 2 tables for Protocol Agent - Seed data: 1 agent + 5 stages + 9 prompts + 4 reflexion rules Code Stats: - Backend: 13 files, 4338 lines - Frontend: 14 files, 2071 lines - Total: 27 files, 6409 lines Status: MVP core functionality completed, pending frontend-backend integration testing Next: Sprint 4 - One-click protocol generation + Word export
This commit is contained in:
@@ -121,6 +121,8 @@ ORDER BY ordinal_position;
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@@ -134,6 +134,8 @@ runMigration()
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@@ -68,6 +68,8 @@ COMMENT ON COLUMN "dc_schema"."dc_tool_c_sessions"."column_mapping" IS '列名
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@@ -95,6 +95,8 @@ COMMENT ON COLUMN dc_schema.dc_tool_c_sessions.expires_at IS '过期时间（创
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@@ -66,3 +66,5 @@ USING gin (metadata jsonb_path_ops);
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@@ -33,3 +33,5 @@ USING gin (tags);
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@@ -6,7 +6,7 @@ generator client {
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datasource db {
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provider = "postgresql"
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url = env("DATABASE_URL")
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schemas = ["admin_schema", "aia_schema", "asl_schema", "capability_schema", "common_schema", "dc_schema", "ekb_schema", "iit_schema", "pkb_schema", "platform_schema", "public", "rvw_schema", "ssa_schema", "st_schema"]
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schemas = ["admin_schema", "agent_schema", "aia_schema", "asl_schema", "capability_schema", "common_schema", "dc_schema", "ekb_schema", "iit_schema", "pkb_schema", "platform_schema", "protocol_schema", "public", "rvw_schema", "ssa_schema", "st_schema"]
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}
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/// 应用缓存表 - Postgres-Only架构
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@@ -1393,3 +1393,303 @@ model EkbChunk {
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@@map("ekb_chunk")
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@@schema("ekb_schema")
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}
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// ============================================================
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// Agent Framework Schema (agent_schema)
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// 通用Agent框架 - 可复用于多种Agent类型
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// ============================================================
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/// Agent定义表 - 存储Agent的基本配置
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model AgentDefinition {
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id String @id @default(uuid())
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code String @unique /// 唯一标识: protocol_agent, stat_agent
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name String /// 显示名称
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description String? /// 描述
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version String @default("1.0.0") /// 版本号
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/// Agent配置
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config Json? @db.JsonB /// 全局配置 { defaultModel, maxTurns, timeout }
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/// 状态
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isActive Boolean @default(true) @map("is_active")
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/// 关联
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stages AgentStage[]
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prompts AgentPrompt[]
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sessions AgentSession[]
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reflexionRules ReflexionRule[]
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@index([code], map: "idx_agent_def_code")
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@@index([isActive], map: "idx_agent_def_active")
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@@map("agent_definitions")
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@@schema("agent_schema")
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}
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/// Agent阶段配置表 - 定义Agent的工作流阶段
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model AgentStage {
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id String @id @default(uuid())
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agentId String @map("agent_id") /// 关联的Agent
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/// 阶段标识
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stageCode String @map("stage_code") /// 阶段代码: scientific_question, pico
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stageName String @map("stage_name") /// 阶段名称: 科学问题梳理
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sortOrder Int @map("sort_order") /// 排序顺序
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/// 阶段配置
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config Json? @db.JsonB /// 阶段特定配置
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/// 状态机配置
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nextStages String[] @map("next_stages") /// 可转换的下一阶段列表
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isInitial Boolean @default(false) @map("is_initial") /// 是否为起始阶段
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isFinal Boolean @default(false) @map("is_final") /// 是否为结束阶段
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/// 关联
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agent AgentDefinition @relation(fields: [agentId], references: [id], onDelete: Cascade)
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prompts AgentPrompt[]
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@unique([agentId, stageCode], map: "unique_agent_stage")
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@@index([agentId], map: "idx_agent_stage_agent")
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@@index([sortOrder], map: "idx_agent_stage_order")
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@@map("agent_stages")
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@@schema("agent_schema")
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}
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/// Agent Prompt模板表 - 存储各阶段的Prompt
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model AgentPrompt {
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id String @id @default(uuid())
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agentId String @map("agent_id") /// 关联的Agent
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stageId String? @map("stage_id") /// 关联的阶段（可选，null表示通用Prompt）
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/// Prompt标识
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promptType String @map("prompt_type") /// system, stage, extraction, reflexion
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promptCode String @map("prompt_code") /// 唯一代码
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/// Prompt内容
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content String @db.Text /// Prompt模板内容（支持变量）
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variables String[] /// 预期变量列表
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/// 版本控制
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version Int @default(1) /// 版本号
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isActive Boolean @default(true) @map("is_active")
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/// 关联
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agent AgentDefinition @relation(fields: [agentId], references: [id], onDelete: Cascade)
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stage AgentStage? @relation(fields: [stageId], references: [id], onDelete: SetNull)
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@unique([agentId, promptCode, version], map: "unique_agent_prompt_version")
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@@index([agentId, promptType], map: "idx_agent_prompt_type")
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@@index([stageId], map: "idx_agent_prompt_stage")
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@@map("agent_prompts")
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@@schema("agent_schema")
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}
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/// Agent会话表 - 存储Agent的运行时会话状态
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model AgentSession {
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id String @id @default(uuid())
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agentId String @map("agent_id") /// 关联的Agent定义
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conversationId String @map("conversation_id") /// 关联的对话ID（aia_schema.conversations）
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userId String @map("user_id") /// 用户ID
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/// 当前状态
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currentStage String @map("current_stage") /// 当前阶段代码
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status String @default("active") /// active, completed, paused, error
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/// 上下文数据（具体Agent的上下文存储在对应schema）
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contextRef String? @map("context_ref") /// 上下文引用ID（如protocol_schema.protocol_contexts.id）
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/// 统计信息
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turnCount Int @default(0) @map("turn_count") /// 对话轮数
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totalTokens Int @default(0) @map("total_tokens") /// 总Token数
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/// 关联
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agent AgentDefinition @relation(fields: [agentId], references: [id])
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traces AgentTrace[]
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@unique([conversationId], map: "unique_agent_session_conv")
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@@index([agentId], map: "idx_agent_session_agent")
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@@index([userId], map: "idx_agent_session_user")
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@@index([status], map: "idx_agent_session_status")
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@@map("agent_sessions")
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@@schema("agent_schema")
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}
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/// Agent执行追踪表 - 记录每一步的执行详情
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model AgentTrace {
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id String @id @default(uuid())
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sessionId String @map("session_id") /// 关联的会话
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/// 追踪信息
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traceId String @map("trace_id") /// 请求追踪ID（用于关联日志）
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stepIndex Int @map("step_index") /// 步骤序号
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stepType String @map("step_type") /// query, plan, execute, reflect, tool_call
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/// 输入输出
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input Json? @db.JsonB /// 步骤输入
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output Json? @db.JsonB /// 步骤输出
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/// 执行信息
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stageCode String? @map("stage_code") /// 执行时的阶段
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modelUsed String? @map("model_used") /// 使用的模型
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tokensUsed Int? @map("tokens_used") /// 消耗的Token
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durationMs Int? @map("duration_ms") /// 执行时长（毫秒）
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/// 错误信息
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errorType String? @map("error_type") /// 错误类型
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errorMsg String? @map("error_msg") /// 错误信息
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/// 关联
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session AgentSession @relation(fields: [sessionId], references: [id], onDelete: Cascade)
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createdAt DateTime @default(now()) @map("created_at")
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@@index([sessionId, stepIndex], map: "idx_agent_trace_session_step")
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@@index([traceId], map: "idx_agent_trace_trace_id")
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@@index([stepType], map: "idx_agent_trace_step_type")
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@@map("agent_traces")
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@@schema("agent_schema")
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}
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/// Reflexion规则表 - 定义质量检查规则
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model ReflexionRule {
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id String @id @default(uuid())
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agentId String @map("agent_id") /// 关联的Agent
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/// 规则标识
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ruleCode String @map("rule_code") /// 规则代码
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ruleName String @map("rule_name") /// 规则名称
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/// 触发条件
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triggerStage String? @map("trigger_stage") /// 触发阶段（null表示全局）
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triggerTiming String @map("trigger_timing") /// on_sync, on_stage_complete, on_generate
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/// 规则类型
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ruleType String @map("rule_type") /// rule_based, prompt_based
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/// 规则内容
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conditions Json? @db.JsonB /// 规则条件（rule_based时使用）
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promptTemplate String? @map("prompt_template") @db.Text /// Prompt模板（prompt_based时使用）
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/// 行为配置
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severity String @default("warning") /// error, warning, info
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failureAction String @default("warn") @map("failure_action") /// block, warn, log
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/// 状态
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isActive Boolean @default(true) @map("is_active")
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sortOrder Int @default(0) @map("sort_order")
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/// 关联
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agent AgentDefinition @relation(fields: [agentId], references: [id], onDelete: Cascade)
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@unique([agentId, ruleCode], map: "unique_agent_rule")
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@@index([agentId, triggerStage], map: "idx_reflexion_rule_agent_stage")
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@@index([isActive], map: "idx_reflexion_rule_active")
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@@map("reflexion_rules")
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@@schema("agent_schema")
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}
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// ============================================================
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// Protocol Agent Schema (protocol_schema)
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// Protocol Agent专用 - 研究方案制定
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// ============================================================
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/// Protocol Context表 - 存储研究方案的核心上下文数据
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model ProtocolContext {
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id String @id @default(uuid())
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conversationId String @unique @map("conversation_id") /// 关联的对话ID
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userId String @map("user_id")
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/// 当前状态
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currentStage String @default("scientific_question") @map("current_stage")
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status String @default("in_progress") /// in_progress, completed, abandoned
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/// ===== 5个核心阶段数据 =====
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/// 阶段1: 科学问题
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scientificQuestion Json? @map("scientific_question") @db.JsonB
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/// { content, background, significance, confirmed, confirmedAt }
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/// 阶段2: PICO
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pico Json? @db.JsonB
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/// { P: {value, details}, I: {}, C: {}, O: {}, confirmed, confirmedAt }
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/// 阶段3: 研究设计
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studyDesign Json? @map("study_design") @db.JsonB
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/// { type, blinding, randomization, duration, multiCenter, confirmed }
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/// 阶段4: 样本量
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sampleSize Json? @map("sample_size") @db.JsonB
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/// { total, perGroup, alpha, power, effectSize, dropoutRate, justification, confirmed }
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/// 阶段5: 观察指标（终点指标）
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endpoints Json? @db.JsonB
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/// { primary: [{name, definition, method, timePoint}], secondary: [], safety: [], confirmed }
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/// ===== 元数据 =====
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completedStages String[] @default([]) @map("completed_stages") /// 已完成的阶段列表
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lastActiveAt DateTime @default(now()) @map("last_active_at")
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/// 关联
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generations ProtocolGeneration[]
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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@@index([userId], map: "idx_protocol_context_user")
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@@index([status], map: "idx_protocol_context_status")
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@@index([currentStage], map: "idx_protocol_context_stage")
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@@map("protocol_contexts")
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@@schema("protocol_schema")
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}
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/// Protocol生成记录表 - 存储一键生成的研究方案
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model ProtocolGeneration {
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id String @id @default(uuid())
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contextId String @map("context_id") /// 关联的Context
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userId String @map("user_id")
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/// 生成内容
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generatedContent String @map("generated_content") @db.Text /// 生成的研究方案全文（Markdown）
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contentVersion Int @default(1) @map("content_version") /// 版本号
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||||
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/// 使用的Prompt
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promptUsed String @map("prompt_used") @db.Text /// 实际使用的Prompt
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/// 生成参数
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modelUsed String @map("model_used") /// 使用的模型
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tokensUsed Int? @map("tokens_used") /// 消耗的Token
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durationMs Int? @map("duration_ms") /// 生成耗时（毫秒）
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/// 导出记录
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wordFileKey String? @map("word_file_key") /// Word文件OSS Key
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lastExportedAt DateTime? @map("last_exported_at")
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||||
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/// 状态
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status String @default("completed") /// generating, completed, failed
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errorMessage String? @map("error_message")
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/// 关联
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context ProtocolContext @relation(fields: [contextId], references: [id], onDelete: Cascade)
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createdAt DateTime @default(now()) @map("created_at")
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updatedAt DateTime @updatedAt @map("updated_at")
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||||
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@@index([contextId], map: "idx_protocol_gen_context")
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@@index([userId, createdAt], map: "idx_protocol_gen_user_time")
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@@map("protocol_generations")
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@@schema("protocol_schema")
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||||
}
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||||
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||||
560
backend/prisma/seeds/protocol-agent-seed.ts
Normal file
560
backend/prisma/seeds/protocol-agent-seed.ts
Normal file
@@ -0,0 +1,560 @@
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||||
/**
|
||||
* Protocol Agent 初始配置数据种子
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||||
*
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||||
* 运行方式: npx tsx prisma/seeds/protocol-agent-seed.ts
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||||
*/
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||||
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||||
import { PrismaClient } from '@prisma/client';
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||||
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||||
const prisma = new PrismaClient();
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||||
|
||||
async function main() {
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||||
console.log('🌱 Seeding Protocol Agent configuration...');
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||||
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||||
// 1. 创建Agent定义
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||||
const agentDefinition = await prisma.agentDefinition.upsert({
|
||||
where: { code: 'protocol_agent' },
|
||||
update: {},
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||||
create: {
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||||
code: 'protocol_agent',
|
||||
name: '研究方案制定助手',
|
||||
description: '帮助研究者系统地制定临床研究方案，覆盖科学问题、PICO、研究设计、样本量和观察指标5个核心阶段',
|
||||
version: '1.0.0',
|
||||
config: {
|
||||
defaultModel: 'deepseek-v3',
|
||||
maxTurns: 100,
|
||||
timeout: 60000,
|
||||
enableTrace: true,
|
||||
enableReflexion: true,
|
||||
},
|
||||
isActive: true,
|
||||
},
|
||||
});
|
||||
|
||||
console.log('✅ Created Agent Definition:', agentDefinition.code);
|
||||
|
||||
// 2. 创建5个阶段
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||||
const stages = [
|
||||
{
|
||||
stageCode: 'scientific_question',
|
||||
stageName: '科学问题梳理',
|
||||
sortOrder: 1,
|
||||
isInitial: true,
|
||||
isFinal: false,
|
||||
nextStages: ['pico'],
|
||||
config: {
|
||||
requiredFields: ['content'],
|
||||
minContentLength: 10,
|
||||
},
|
||||
},
|
||||
{
|
||||
stageCode: 'pico',
|
||||
stageName: 'PICO要素',
|
||||
sortOrder: 2,
|
||||
isInitial: false,
|
||||
isFinal: false,
|
||||
nextStages: ['study_design'],
|
||||
config: {
|
||||
requiredFields: ['P', 'I', 'C', 'O'],
|
||||
},
|
||||
},
|
||||
{
|
||||
stageCode: 'study_design',
|
||||
stageName: '研究设计',
|
||||
sortOrder: 3,
|
||||
isInitial: false,
|
||||
isFinal: false,
|
||||
nextStages: ['sample_size'],
|
||||
config: {
|
||||
requiredFields: ['type'],
|
||||
},
|
||||
},
|
||||
{
|
||||
stageCode: 'sample_size',
|
||||
stageName: '样本量计算',
|
||||
sortOrder: 4,
|
||||
isInitial: false,
|
||||
isFinal: false,
|
||||
nextStages: ['endpoints'],
|
||||
config: {
|
||||
requiredFields: ['total'],
|
||||
},
|
||||
},
|
||||
{
|
||||
stageCode: 'endpoints',
|
||||
stageName: '观察指标',
|
||||
sortOrder: 5,
|
||||
isInitial: false,
|
||||
isFinal: true,
|
||||
nextStages: [],
|
||||
config: {
|
||||
requiredFields: ['primary'],
|
||||
},
|
||||
},
|
||||
];
|
||||
|
||||
for (const stage of stages) {
|
||||
await prisma.agentStage.upsert({
|
||||
where: {
|
||||
agentId_stageCode: {
|
||||
agentId: agentDefinition.id,
|
||||
stageCode: stage.stageCode,
|
||||
},
|
||||
},
|
||||
update: stage,
|
||||
create: {
|
||||
agentId: agentDefinition.id,
|
||||
...stage,
|
||||
},
|
||||
});
|
||||
console.log(` ✅ Stage: ${stage.stageName}`);
|
||||
}
|
||||
|
||||
// 3. 创建Prompt模板
|
||||
const prompts = [
|
||||
// 系统Prompt
|
||||
{
|
||||
promptType: 'system',
|
||||
promptCode: 'protocol_system',
|
||||
content: `你是一位经验丰富的临床研究方法学专家，正在帮助研究者制定研究方案。
|
||||
|
||||
你的职责：
|
||||
1. 系统引导用户完成研究方案的5个核心要素：科学问题、PICO、研究设计、样本量、观察指标
|
||||
2. 提供专业、准确的方法学建议
|
||||
3. 确保研究设计的科学性和可行性
|
||||
4. 使用通俗易懂的语言，同时保持学术严谨性
|
||||
|
||||
当前阶段: {{context.currentStage}}
|
||||
已完成阶段: {{context.completedStages}}
|
||||
|
||||
请根据用户的输入，提供专业指导。`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// 科学问题阶段Prompt
|
||||
{
|
||||
promptType: 'stage',
|
||||
promptCode: 'stage_scientific_question',
|
||||
stageCode: 'scientific_question',
|
||||
content: `【科学问题梳理阶段】
|
||||
|
||||
你正在帮助用户梳理研究的科学问题。一个好的科学问题应该：
|
||||
- 明确、具体、可操作
|
||||
- 有实际的临床或学术意义
|
||||
- 可通过研究方法验证
|
||||
|
||||
{{#if context.scientificQuestion}}
|
||||
用户当前的科学问题草稿：
|
||||
{{context.scientificQuestion.content}}
|
||||
{{/if}}
|
||||
|
||||
请引导用户：
|
||||
1. 描述研究背景和动机
|
||||
2. 明确想要解决的核心问题
|
||||
3. 阐述研究的潜在意义
|
||||
|
||||
当用户表达清晰后，帮助整理成规范的科学问题陈述，并提供"同步到方案"按钮。`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// PICO阶段Prompt
|
||||
{
|
||||
promptType: 'stage',
|
||||
promptCode: 'stage_pico',
|
||||
stageCode: 'pico',
|
||||
content: `【PICO要素梳理阶段】
|
||||
|
||||
PICO是临床研究问题结构化的核心框架：
|
||||
- P (Population): 研究人群
|
||||
- I (Intervention): 干预措施
|
||||
- C (Comparison): 对照措施
|
||||
- O (Outcome): 结局指标
|
||||
|
||||
{{#if context.pico}}
|
||||
当前PICO：
|
||||
- P: {{context.pico.P.value}}
|
||||
- I: {{context.pico.I.value}}
|
||||
- C: {{context.pico.C.value}}
|
||||
- O: {{context.pico.O.value}}
|
||||
{{/if}}
|
||||
|
||||
请引导用户逐一明确四个要素，确保：
|
||||
1. P: 纳入标准、排除标准清晰
|
||||
2. I: 干预措施具体可操作
|
||||
3. C: 对照组设置合理
|
||||
4. O: 结局指标可测量、有临床意义
|
||||
|
||||
当四要素都明确后，提供"同步到方案"按钮。`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// 研究设计阶段Prompt
|
||||
{
|
||||
promptType: 'stage',
|
||||
promptCode: 'stage_study_design',
|
||||
stageCode: 'study_design',
|
||||
content: `【研究设计阶段】
|
||||
|
||||
根据科学问题和PICO，需要确定合适的研究设计：
|
||||
|
||||
科学问题：{{context.scientificQuestion.content}}
|
||||
PICO：
|
||||
- P: {{context.pico.P.value}}
|
||||
- I: {{context.pico.I.value}}
|
||||
|
||||
常见研究类型：
|
||||
- 随机对照试验(RCT)：最高证据等级，适合验证干预效果
|
||||
- 队列研究：适合观察性研究，探索风险因素
|
||||
- 病例对照研究：适合罕见疾病研究
|
||||
- 横断面研究：描述性研究
|
||||
|
||||
请引导用户确定：
|
||||
1. 研究类型
|
||||
2. 盲法设计（如适用）
|
||||
3. 随机化方法（如适用）
|
||||
4. 研究周期
|
||||
5. 是否多中心
|
||||
|
||||
设计确定后，提供"同步到方案"按钮。`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// 样本量阶段Prompt
|
||||
{
|
||||
promptType: 'stage',
|
||||
promptCode: 'stage_sample_size',
|
||||
stageCode: 'sample_size',
|
||||
content: `【样本量计算阶段】
|
||||
|
||||
样本量计算需要考虑：
|
||||
- α (显著性水平): 通常0.05
|
||||
- β (统计效力): 通常0.8-0.9
|
||||
- 预期效应量
|
||||
- 预计脱落率
|
||||
|
||||
研究设计：{{context.studyDesign.type}}
|
||||
主要结局：{{context.pico.O.value}}
|
||||
|
||||
请引导用户：
|
||||
1. 确定检验类型（优效、非劣效、等效）
|
||||
2. 估计预期效应量（基于文献或预试验）
|
||||
3. 设定显著性水平和统计效力
|
||||
4. 考虑脱落率调整
|
||||
|
||||
可以使用样本量计算工具辅助计算。
|
||||
|
||||
样本量确定后，提供"同步到方案"按钮。`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// 观察指标阶段Prompt
|
||||
{
|
||||
promptType: 'stage',
|
||||
promptCode: 'stage_endpoints',
|
||||
stageCode: 'endpoints',
|
||||
content: `【观察指标设计阶段】
|
||||
|
||||
观察指标是评价研究结果的关键：
|
||||
|
||||
研究类型：{{context.studyDesign.type}}
|
||||
PICO-O：{{context.pico.O.value}}
|
||||
|
||||
需要明确的指标类型：
|
||||
1. **主要结局指标(Primary Endpoint)**：
|
||||
- 与科学问题直接相关
|
||||
- 用于样本量计算
|
||||
- 每个研究通常只有1-2个
|
||||
|
||||
2. **次要结局指标(Secondary Endpoints)**：
|
||||
- 支持主要结局的补充指标
|
||||
- 可以有多个
|
||||
|
||||
3. **安全性指标(Safety Endpoints)**：
|
||||
- 不良事件、实验室检查等
|
||||
|
||||
4. **探索性指标(Exploratory)**：
|
||||
- 为未来研究提供线索
|
||||
|
||||
请引导用户定义每个指标的：
|
||||
- 名称
|
||||
- 操作定义
|
||||
- 测量方法
|
||||
- 评价时点
|
||||
|
||||
所有指标确定后，提供"同步到方案"按钮。
|
||||
|
||||
🎉 完成观察指标后，您可以点击"一键生成研究方案"生成完整方案文档！`,
|
||||
variables: ['context'],
|
||||
},
|
||||
// 数据提取Prompt
|
||||
{
|
||||
promptType: 'extraction',
|
||||
promptCode: 'extraction_scientific_question',
|
||||
stageCode: 'scientific_question',
|
||||
content: `请从以下对话中提取科学问题信息：
|
||||
|
||||
用户消息：{{userMessage}}
|
||||
|
||||
请以JSON格式输出：
|
||||
{
|
||||
"content": "完整的科学问题陈述",
|
||||
"background": "研究背景",
|
||||
"significance": "研究意义",
|
||||
"readyToSync": true/false
|
||||
}
|
||||
|
||||
如果信息不完整，readyToSync设为false。`,
|
||||
variables: ['userMessage'],
|
||||
},
|
||||
{
|
||||
promptType: 'extraction',
|
||||
promptCode: 'extraction_pico',
|
||||
stageCode: 'pico',
|
||||
content: `请从以下对话中提取PICO要素：
|
||||
|
||||
用户消息：{{userMessage}}
|
||||
当前PICO：{{currentPico}}
|
||||
|
||||
请以JSON格式输出：
|
||||
{
|
||||
"P": { "value": "研究人群", "details": "详细描述" },
|
||||
"I": { "value": "干预措施", "details": "详细描述" },
|
||||
"C": { "value": "对照措施", "details": "详细描述" },
|
||||
"O": { "value": "结局指标", "details": "详细描述" },
|
||||
"readyToSync": true/false
|
||||
}
|
||||
|
||||
只更新用户提到的字段，保留其他字段不变。
|
||||
如果PICO四要素都已完整，readyToSync设为true。`,
|
||||
variables: ['userMessage', 'currentPico'],
|
||||
},
|
||||
// 研究方案生成Prompt
|
||||
{
|
||||
promptType: 'generation',
|
||||
promptCode: 'generate_protocol',
|
||||
content: `你是一位资深的临床研究方法学专家，请基于以下核心要素生成一份完整、规范的临床研究方案。
|
||||
|
||||
## 核心要素
|
||||
|
||||
### 科学问题
|
||||
{{scientificQuestion.content}}
|
||||
{{#if scientificQuestion.background}}背景：{{scientificQuestion.background}}{{/if}}
|
||||
|
||||
### PICO要素
|
||||
- **研究人群(P)**: {{pico.P.value}}
|
||||
{{pico.P.details}}
|
||||
- **干预措施(I)**: {{pico.I.value}}
|
||||
{{pico.I.details}}
|
||||
- **对照措施(C)**: {{pico.C.value}}
|
||||
{{pico.C.details}}
|
||||
- **结局指标(O)**: {{pico.O.value}}
|
||||
{{pico.O.details}}
|
||||
|
||||
### 研究设计
|
||||
- 研究类型: {{studyDesign.type}}
|
||||
- 盲法设计: {{studyDesign.blinding}}
|
||||
- 随机化方法: {{studyDesign.randomization}}
|
||||
- 研究周期: {{studyDesign.duration}}
|
||||
{{#if studyDesign.multiCenter}}- 多中心: 是，{{studyDesign.centerCount}}个中心{{/if}}
|
||||
|
||||
### 样本量
|
||||
- 总样本量: {{sampleSize.total}}
|
||||
- 每组样本量: {{sampleSize.perGroup}}
|
||||
- 计算依据: {{sampleSize.justification}}
|
||||
|
||||
### 观察指标
|
||||
**主要结局指标:**
|
||||
{{#each endpoints.primary}}
|
||||
- {{name}}: {{definition}} ({{method}}, {{timePoint}})
|
||||
{{/each}}
|
||||
|
||||
**次要结局指标:**
|
||||
{{#each endpoints.secondary}}
|
||||
- {{name}}: {{definition}}
|
||||
{{/each}}
|
||||
|
||||
**安全性指标:**
|
||||
{{#each endpoints.safety}}
|
||||
- {{name}}: {{definition}}
|
||||
{{/each}}
|
||||
|
||||
---
|
||||
|
||||
## 生成要求
|
||||
|
||||
请生成包含以下章节的完整研究方案：
|
||||
|
||||
1. **研究背景与立题依据**
|
||||
- 疾病/问题背景
|
||||
- 国内外研究现状
|
||||
- 研究的必要性和意义
|
||||
|
||||
2. **研究目的**
|
||||
- 主要目的
|
||||
- 次要目的
|
||||
|
||||
3. **研究方法**
|
||||
- 研究类型与设计
|
||||
- 研究对象
|
||||
- 干预措施
|
||||
- 对照设置
|
||||
- 随机化与盲法
|
||||
|
||||
4. **受试者选择**
|
||||
- 入选标准
|
||||
- 排除标准
|
||||
- 退出/剔除标准
|
||||
|
||||
5. **观察指标与评价标准**
|
||||
- 主要疗效指标
|
||||
- 次要疗效指标
|
||||
- 安全性指标
|
||||
- 评价时点
|
||||
|
||||
6. **统计分析计划**
|
||||
- 样本量估算
|
||||
- 分析数据集定义
|
||||
- 统计方法
|
||||
|
||||
7. **质量控制**
|
||||
- 数据管理
|
||||
- 质量保证措施
|
||||
|
||||
8. **伦理考虑**
|
||||
- 伦理审查
|
||||
- 知情同意
|
||||
- 受试者保护
|
||||
|
||||
9. **研究进度安排**
|
||||
- 时间节点
|
||||
- 里程碑
|
||||
|
||||
请使用专业、规范的学术语言，确保内容完整、逻辑清晰、符合临床研究规范。`,
|
||||
variables: ['scientificQuestion', 'pico', 'studyDesign', 'sampleSize', 'endpoints'],
|
||||
},
|
||||
];
|
||||
|
||||
// 获取阶段ID映射
|
||||
const stageIdMap = new Map<string, string>();
|
||||
const savedStages = await prisma.agentStage.findMany({
|
||||
where: { agentId: agentDefinition.id },
|
||||
});
|
||||
for (const stage of savedStages) {
|
||||
stageIdMap.set(stage.stageCode, stage.id);
|
||||
}
|
||||
|
||||
// 创建Prompts
|
||||
for (const prompt of prompts) {
|
||||
const stageId = prompt.stageCode ? stageIdMap.get(prompt.stageCode) : null;
|
||||
|
||||
await prisma.agentPrompt.upsert({
|
||||
where: {
|
||||
agentId_promptCode_version: {
|
||||
agentId: agentDefinition.id,
|
||||
promptCode: prompt.promptCode,
|
||||
version: 1,
|
||||
},
|
||||
},
|
||||
update: {
|
||||
content: prompt.content,
|
||||
variables: prompt.variables,
|
||||
},
|
||||
create: {
|
||||
agentId: agentDefinition.id,
|
||||
stageId: stageId,
|
||||
promptType: prompt.promptType,
|
||||
promptCode: prompt.promptCode,
|
||||
content: prompt.content,
|
||||
variables: prompt.variables,
|
||||
version: 1,
|
||||
isActive: true,
|
||||
},
|
||||
});
|
||||
console.log(` ✅ Prompt: ${prompt.promptCode}`);
|
||||
}
|
||||
|
||||
// 4. 创建Reflexion规则
|
||||
const reflexionRules = [
|
||||
{
|
||||
ruleCode: 'scientific_question_completeness',
|
||||
ruleName: '科学问题完整性检查',
|
||||
triggerStage: 'scientific_question',
|
||||
triggerTiming: 'on_sync',
|
||||
ruleType: 'rule_based',
|
||||
conditions: {
|
||||
content: { required: true, minLength: 10 },
|
||||
},
|
||||
severity: 'warning',
|
||||
failureAction: 'warn',
|
||||
sortOrder: 1,
|
||||
},
|
||||
{
|
||||
ruleCode: 'pico_completeness',
|
||||
ruleName: 'PICO要素完整性检查',
|
||||
triggerStage: 'pico',
|
||||
triggerTiming: 'on_sync',
|
||||
ruleType: 'rule_based',
|
||||
conditions: {
|
||||
P: 'required',
|
||||
I: 'required',
|
||||
C: 'required',
|
||||
O: 'required',
|
||||
},
|
||||
severity: 'error',
|
||||
failureAction: 'warn',
|
||||
sortOrder: 2,
|
||||
},
|
||||
{
|
||||
ruleCode: 'sample_size_validity',
|
||||
ruleName: '样本量有效性检查',
|
||||
triggerStage: 'sample_size',
|
||||
triggerTiming: 'on_sync',
|
||||
ruleType: 'rule_based',
|
||||
conditions: {
|
||||
total: { required: true, min: 1 },
|
||||
},
|
||||
severity: 'error',
|
||||
failureAction: 'warn',
|
||||
sortOrder: 3,
|
||||
},
|
||||
{
|
||||
ruleCode: 'endpoints_primary_required',
|
||||
ruleName: '主要终点指标必填',
|
||||
triggerStage: 'endpoints',
|
||||
triggerTiming: 'on_sync',
|
||||
ruleType: 'rule_based',
|
||||
conditions: {
|
||||
primary: { notEmpty: true },
|
||||
},
|
||||
severity: 'error',
|
||||
failureAction: 'warn',
|
||||
sortOrder: 4,
|
||||
},
|
||||
];
|
||||
|
||||
for (const rule of reflexionRules) {
|
||||
await prisma.reflexionRule.upsert({
|
||||
where: {
|
||||
agentId_ruleCode: {
|
||||
agentId: agentDefinition.id,
|
||||
ruleCode: rule.ruleCode,
|
||||
},
|
||||
},
|
||||
update: rule,
|
||||
create: {
|
||||
agentId: agentDefinition.id,
|
||||
...rule,
|
||||
isActive: true,
|
||||
},
|
||||
});
|
||||
console.log(` ✅ Rule: ${rule.ruleName}`);
|
||||
}
|
||||
|
||||
console.log('\n🎉 Protocol Agent configuration seeded successfully!');
|
||||
}
|
||||
|
||||
main()
|
||||
.catch((e) => {
|
||||
console.error('❌ Seed failed:', e);
|
||||
process.exit(1);
|
||||
})
|
||||
.finally(async () => {
|
||||
await prisma.$disconnect();
|
||||
});
|
||||
|
||||
|
||||
Reference in New Issue
Block a user