| VetCopilot-DAPT v3.1 部署 | |
| ========================= | |
| 包含目录: | |
| vetcopilot-app/ — 前端 (React/TypeScript + Vite + PWA) | |
| vetcopilot-backend/ — 后端 (FastAPI + SQLAlchemy + LCPS Client) | |
| vetnetv2.0/ — DAPT AI 引擎 (Qwen2.5-3B + LCPS 2.0 + FAISS RAG) | |
| deploy_dapt.sh — 一键部署脚本 | |
| 快速启动: | |
| chmod +x deploy_dapt.sh && ./deploy_dapt.sh | |
| 手动启动: | |
| 1. 启动 AI 引擎: | |
| cd vetnetv2.0 | |
| VET_MODEL=./vet-qwen3b-v3-dapt PORT=8000 python server_gpu.py | |
| 2. 启动后端: | |
| cd vetcopilot-backend | |
| PORT=8080 python -m uvicorn app.main:app --host 0.0.0.0 | |
| 3. 启动前端 (开发): | |
| cd vetcopilot-app | |
| npm install && npm run dev | |
| API 端点: | |
| GET :8000/health — AI 引擎健康检查 | |
| POST :8000/api/v1/diagnose — LCPS 诊断 (VetCopilot 标准接口) | |
| POST :8000/run — LCPS 诊断 (兼容旧接口) | |
| POST :8000/chat — 兽医自由问答 | |
| GET :8080/api/health — 应用健康检查 | |
| POST :8080/api/consultations/start — 开始问诊 | |
| 模型下载: | |
| # 从 ModelScope 下载 DAPT 模型权重 | |
| pip install modelscope | |
| python -c "from modelscope.hub.snapshot_download import snapshot_download; snapshot_download('WWSCA123/vet-qwen3b-v3-dapt-inference', local_dir='./vet-qwen3b-v3-dapt')" | |
| # 下载 tokenizer (从 HF mirror) | |
| python -c "from huggingface_hub import snapshot_download; import shutil, os; d=snapshot_download('Qwen/Qwen2.5-3B-Instruct', allow_patterns=['tokenizer*','vocab*','merges*','generation_config*']); [shutil.copy(os.path.join(d,f), f'./vet-qwen3b-v3-dapt/{f}') for f in os.listdir(d)]" | |