HaHafeng
96290d2f76
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
83 lines
2.1 KiB
Markdown
83 lines
2.1 KiB
Markdown
# 环境变量配置示例
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复制以下内容到 `.env` 文件中：
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```bash
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# ===========================================
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# AI Clinical Research Platform - 环境变量配置
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# ===========================================
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# ==================== 应用配置 ====================
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NODE_ENV=development
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PORT=3001
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HOST=0.0.0.0
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LOG_LEVEL=debug
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SERVICE_NAME=aiclinical-backend
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# ==================== 数据库配置 ====================
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DATABASE_URL=postgresql://postgres:postgres@localhost:5432/ai_clinical
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# ==================== 存储配置 ====================
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# 存储类型：local | oss
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STORAGE_TYPE=local
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# --- 本地存储配置（STORAGE_TYPE=local）---
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LOCAL_STORAGE_DIR=uploads
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LOCAL_STORAGE_URL=http://localhost:3001/uploads
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# --- 阿里云OSS配置（STORAGE_TYPE=oss）---
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# OSS_REGION=oss-cn-beijing
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# OSS_BUCKET=ai-clinical-data-dev
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# OSS_BUCKET_STATIC=ai-clinical-static-dev
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# OSS_ACCESS_KEY_ID=your-access-key-id
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# OSS_ACCESS_KEY_SECRET=your-access-key-secret
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# OSS_INTERNAL=false
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# OSS_SIGNED_URL_EXPIRES=3600
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# ==================== 安全配置 ====================
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JWT_SECRET=your-secret-key-change-in-production
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JWT_EXPIRES_IN=7d
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CORS_ORIGIN=http://localhost:5173
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# ==================== LLM API配置 ====================
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DEEPSEEK_API_KEY=
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DEEPSEEK_BASE_URL=https://api.deepseek.com
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DASHSCOPE_API_KEY=
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GEMINI_API_KEY=
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# ==================== 文件上传配置 ====================
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UPLOAD_MAX_SIZE=31457280
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```
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## OSS 开发环境配置
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如果要测试 OSS，将 `STORAGE_TYPE` 改为 `oss` 并填写以下配置：
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```bash
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STORAGE_TYPE=oss
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OSS_REGION=oss-cn-beijing
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OSS_BUCKET=ai-clinical-data-dev
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OSS_BUCKET_STATIC=ai-clinical-static-dev
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OSS_ACCESS_KEY_ID=LTAI5tBHkL39GjdLfcr77Y3f
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OSS_ACCESS_KEY_SECRET=<从安全渠道获取>
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OSS_INTERNAL=false
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OSS_SIGNED_URL_EXPIRES=3600
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```
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## OSS 生产环境配置（SAE）
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```bash
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STORAGE_TYPE=oss
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OSS_REGION=oss-cn-beijing
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OSS_BUCKET=ai-clinical-data
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OSS_BUCKET_STATIC=ai-clinical-static
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OSS_ACCESS_KEY_ID=LTAI5tBHkL39GjdLfcr77Y3f
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OSS_ACCESS_KEY_SECRET=<从安全渠道获取>
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OSS_INTERNAL=true # 🔴 生产必须用内网
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OSS_SIGNED_URL_EXPIRES=3600
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```
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