Fine-tuning/backend/.env

# ============================================================
# 后端专属配置
# ============================================================

# 服务地址（服务器部署时改为 0.0.0.0）
BACKEND_HOST=0.0.0.0
BACKEND_PORT=8010
BACKEND_ENV=production
BACKEND_LOG_LEVEL=INFO
BACKEND_CORS_ORIGINS=http://192.168.91.253:5173,http://192.168.92.151:3000,http://192.168.92.151

# 数据库（使用 PostgreSQL 容器，默认值在 config.py 中）
# DATABASE_URL=postgresql+asyncpg://finetune:finetune123@localhost:5432/finetuning

# 数据路径（Linux 服务器路径）
DATA_DIR=/home/lq/Fine-tuning/backend/data

# GPU 配置（推理使用的物理 GPU，逗号分隔，多卡自动 model parallelism）
# INFERENCE_CUDA_DEVICES=2,3

# 训练默认参数
DEFAULT_PEFT_METHOD=lora
DEFAULT_EPOCHS=3
DEFAULT_BATCH_SIZE=4
DEFAULT_GRADIENT_ACCUMULATION=4
DEFAULT_LR=2e-4
DEFAULT_MAX_SEQ_LENGTH=2048
DEFAULT_WARMUP_RATIO=0.05
DEFAULT_SAVE_STRATEGY=epoch
DEFAULT_EVAL_STRATEGY=epoch
DEFAULT_EVAL_STEPS=100

# LoRA
LORA_R=16
LORA_ALPHA=32
LORA_DROPOUT=0.05
LORA_TARGET_MODULES=all-linear

# QLoRA
QLORA_BITS=4
QLORA_TYPE=nf4
QLORA_DOUBLE_QUANT=true

# 上传限制
MAX_UPLOAD_SIZE_MB=500
ALLOWED_DATASET_FORMATS=jsonl,csv,parquet,json

# --- SSO 统一认证 ---
SSO_BASE_URL=http://192.168.92.61:8200
SSO_CLIENT_ID=hmDeOtXZVbeo2AZ-x58yPssZLg4Tcb1W
SSO_CLIENT_SECRET=pj9UirhGUFPsFnCizCz-Qo1dOGi3kxRIrDKKmJZu2aRCPgtTogTubDRW1weM4KNL
SSO_REDIRECT_URI=http://192.168.92.151:3000/auth/callback
SSO_FRONTEND_URL=http://192.168.92.151:3000
SSO_SCOPE=email
SSO_LOGOUT_REDIRECT_URL=http://192.168.92.61:9200/login
JWT_SECRET_KEY=change-me-in-production-use-a-long-random-string
JWT_ACCESS_EXPIRE_MINUTES=20
JWT_REFRESH_EXPIRE_HOURS=24

# --- 标注平台 ---
ANNOTATION_PLATFORM_BASE_URL=http://192.168.92.61:9003
ANNOTATION_PLATFORM_APP_ID=nlKLQJdJK3f5ub7UDfQ_E71z2Lo3YSQx
ANNOTATION_PLATFORM_APP_SECRET=wh0HU_9T83rYMjfLFToNxFOKcrk_8H7Ba_27nNGlPqtTf9ROCytsOgp2ue0ol5mm