hack/tools/scripts/llm-key-hunter/results/_cache/content/anothersunset_zhixianyunshu.json

{"repo": "anothersunset/zhixianyunshu", "files": {"zhiqian/deploy/kustomize/base/rag-deployment.yaml": {"450a71e5cdc3cfb27544c338af7e73ac5bd5efab": {"t": 1785745215.5284715, "n": 1674, "h": "652fd2a34ddf73be", "c": "# v2-step-18: rag FastAPI Deployment\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: zhiqian-rag\n  labels:\n    app.kubernetes.io/name: rag\n    app.kubernetes.io/component: retrieval\nspec:\n  replicas: 1\n  strategy:\n    type: RollingUpdate\n    rollingUpdate:\n      maxSurge: 1\n      maxUnavailable: 0\n  selector:\n    matchLabels:\n      app.kubernetes.io/name: rag\n      app.kubernetes.io/component: retrieval\n  template:\n    metadata:\n      labels:\n        app.kubernetes.io/name: rag\n        app.kubernetes.io/component: retrieval\n    spec:\n      securityContext:\n        runAsNonRoot: true\n        runAsUser: 1000\n      containers:\n        - name: rag\n          image: zhiqian/rag:2.0.0\n          imagePullPolicy: IfNotPresent\n          ports:\n            - name: http\n              containerPort: 8001\n              protocol: TCP\n          envFrom:\n            - configMapRef:\n                name: zhiqian-rag-env\n          env:\n            - name: DEEPSEEK_API_KEY\n              valueFrom:\n                secretKeyRef:\n                  name: zhiqian-backend-secret\n                  key: deepseek-api-key\n          livenessProbe:\n            httpGet:\n              path: /health\n              port: http\n            initialDelaySeconds: 30\n            periodSeconds: 30\n            timeoutSeconds: 5\n          readinessProbe:\n            httpGet:\n              path: /health\n              port: http\n            initialDelaySeconds: 15\n            periodSeconds: 10\n            timeoutSeconds: 3\n          resources:\n            requests:\n              cpu: 200m\n              memory: 512Mi\n            limits:\n              cpu: 2000m\n              memory: 4Gi\n"}, "9833e4dce4b1fc7f63debc9bcd33309590b0ae91": {"t": 1785748801.360206, "n": 1674, "h": "652fd2a34ddf73be", "c": "# v2-step-18: rag FastAPI Deployment\napiVersion: apps/v1\nkind: Deployment\nmetadata:\n  name: zhiqian-rag\n  labels:\n    app.kubernetes.io/name: rag\n    app.kubernetes.io/component: retrieval\nspec:\n  replicas: 1\n  strategy:\n    type: RollingUpdate\n    rollingUpdate:\n      maxSurge: 1\n      maxUnavailable: 0\n  selector:\n    matchLabels:\n      app.kubernetes.io/name: rag\n      app.kubernetes.io/component: retrieval\n  template:\n    metadata:\n      labels:\n        app.kubernetes.io/name: rag\n        app.kubernetes.io/component: retrieval\n    spec:\n      securityContext:\n        runAsNonRoot: true\n        runAsUser: 1000\n      containers:\n        - name: rag\n          image: zhiqian/rag:2.0.0\n          imagePullPolicy: IfNotPresent\n          ports:\n            - name: http\n              containerPort: 8001\n              protocol: TCP\n          envFrom:\n            - configMapRef:\n                name: zhiqian-rag-env\n          env:\n            - name: DEEPSEEK_API_KEY\n              valueFrom:\n                secretKeyRef:\n                  name: zhiqian-backend-secret\n                  key: deepseek-api-key\n          livenessProbe:\n            httpGet:\n              path: /health\n              port: http\n            initialDelaySeconds: 30\n            periodSeconds: 30\n            timeoutSeconds: 5\n          readinessProbe:\n            httpGet:\n              path: /health\n              port: http\n            initialDelaySeconds: 15\n            periodSeconds: 10\n            timeoutSeconds: 3\n          resources:\n            requests:\n              cpu: 200m\n              memory: 512Mi\n            limits:\n              cpu: 2000m\n              memory: 4Gi\n"}}, "zhiqian/deploy/docker-compose.yml": {"450a71e5cdc3cfb27544c338af7e73ac5bd5efab": {"t": 1785746339.8696232, "n": 6378, "h": "a6956220897e08af", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n      - ./init-temporal-db.sql:/docker-entrypoint-initdb.d/10_temporal.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  # v2-step-14: Temporal server (auto-setup, 依赖 postgres)\n  # 启动方式: docker compose --profile temporal up -d\n  # 需要在 .env 中设置 TEMPORAL_ENABLED=true 让 backend 连这里\n  temporal:\n    image: temporalio/auto-setup:1.25.0\n    container_name: zhiqian-temporal\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      DB: postgres12\n      DB_PORT: 5432\n      POSTGRES_USER: zhiqian\n      POSTGRES_PWD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_SEEDS: postgres\n      DBNAME: temporal\n      VISIBILITY_DBNAME: temporal_visibility\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CLI_ADDRESS: temporal:7233\n    ports:\n      - \"7233:7233\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"tctl\", \"--address\", \"temporal:7233\", \"cluster\", \"health\"]\n      interval: 15s\n      timeout: 5s\n      retries: 12\n      start_period: 60s\n\n  temporal-ui:\n    image: temporalio/ui:2.31.2\n    container_name: zhiqian-temporal-ui\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CORS_ORIGINS: http://localhost:3000,http://localhost:8233\n    ports:\n      - \"8233:8080\"\n    depends_on:\n      - temporal\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      LLM_THINKING_ENABLED: ${LLM_THINKING_ENABLED:-true}\n      LLM_REASONING_EFFORT: ${LLM_REASONING_EFFORT:-high}\n      # v2-step-08: Langfuse 后端全链观测。留空即 disabled\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      # v2-step-14: Temporal durable workflow。默认 false。\n      # TEMPORAL_ENABLED=true 且 docker compose --profile temporal up 后才走 Temporal 路径。\n      TEMPORAL_ENABLED: ${TEMPORAL_ENABLED:-false}\n      TEMPORAL_TARGET: ${TEMPORAL_TARGET:-temporal:7233}\n      TEMPORAL_NAMESPACE: ${TEMPORAL_NAMESPACE:-default}\n      TEMPORAL_TASK_QUEUE: ${TEMPORAL_TASK_QUEUE:-zhiqian-migration}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-/models/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-/models/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n      TRANSFORMERS_OFFLINE: 1\n    volumes:\n      - ragdata:/data\n      # Bind mount: 直接挂载宿主机模型目录，零拷贝\n      - ${HF_CACHE_DIR:-C:/Users/anoth/.hf_cache}/modelscope/BAAI/bge-m3:/models/bge-m3:ro\n      - ${HF_CACHE_DIR:-C:/Users/anoth/.hf_cache}/modelscope/BAAI/bge-reranker-v2-m3:/models/bge-reranker-v2-m3:ro\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "3d3749d13fd6199027b417ff621974161d367e57": {"t": 1785748800.8432949, "n": 6378, "h": "a6956220897e08af", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n      - ./init-temporal-db.sql:/docker-entrypoint-initdb.d/10_temporal.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  # v2-step-14: Temporal server (auto-setup, 依赖 postgres)\n  # 启动方式: docker compose --profile temporal up -d\n  # 需要在 .env 中设置 TEMPORAL_ENABLED=true 让 backend 连这里\n  temporal:\n    image: temporalio/auto-setup:1.25.0\n    container_name: zhiqian-temporal\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      DB: postgres12\n      DB_PORT: 5432\n      POSTGRES_USER: zhiqian\n      POSTGRES_PWD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_SEEDS: postgres\n      DBNAME: temporal\n      VISIBILITY_DBNAME: temporal_visibility\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CLI_ADDRESS: temporal:7233\n    ports:\n      - \"7233:7233\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"tctl\", \"--address\", \"temporal:7233\", \"cluster\", \"health\"]\n      interval: 15s\n      timeout: 5s\n      retries: 12\n      start_period: 60s\n\n  temporal-ui:\n    image: temporalio/ui:2.31.2\n    container_name: zhiqian-temporal-ui\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CORS_ORIGINS: http://localhost:3000,http://localhost:8233\n    ports:\n      - \"8233:8080\"\n    depends_on:\n      - temporal\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      LLM_THINKING_ENABLED: ${LLM_THINKING_ENABLED:-true}\n      LLM_REASONING_EFFORT: ${LLM_REASONING_EFFORT:-high}\n      # v2-step-08: Langfuse 后端全链观测。留空即 disabled\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      # v2-step-14: Temporal durable workflow。默认 false。\n      # TEMPORAL_ENABLED=true 且 docker compose --profile temporal up 后才走 Temporal 路径。\n      TEMPORAL_ENABLED: ${TEMPORAL_ENABLED:-false}\n      TEMPORAL_TARGET: ${TEMPORAL_TARGET:-temporal:7233}\n      TEMPORAL_NAMESPACE: ${TEMPORAL_NAMESPACE:-default}\n      TEMPORAL_TASK_QUEUE: ${TEMPORAL_TASK_QUEUE:-zhiqian-migration}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-/models/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-/models/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n      TRANSFORMERS_OFFLINE: 1\n    volumes:\n      - ragdata:/data\n      # Bind mount: 直接挂载宿主机模型目录，零拷贝\n      - ${HF_CACHE_DIR:-C:/Users/anoth/.hf_cache}/modelscope/BAAI/bge-m3:/models/bge-m3:ro\n      - ${HF_CACHE_DIR:-C:/Users/anoth/.hf_cache}/modelscope/BAAI/bge-reranker-v2-m3:/models/bge-reranker-v2-m3:ro\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "6289d20e0c9fe48f73b519670c34a6cc06a0ef74": {"t": 1785748801.94169, "n": 6121, "h": "959b8330f882a60f", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n      - ./init-temporal-db.sql:/docker-entrypoint-initdb.d/10_temporal.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  # v2-step-14: Temporal server (auto-setup, 依赖 postgres)\n  # 启动方式: docker compose --profile temporal up -d\n  # 需要在 .env 中设置 TEMPORAL_ENABLED=true 让 backend 连这里\n  temporal:\n    image: temporalio/auto-setup:1.25.0\n    container_name: zhiqian-temporal\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      DB: postgres12\n      DB_PORT: 5432\n      POSTGRES_USER: zhiqian\n      POSTGRES_PWD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_SEEDS: postgres\n      DBNAME: temporal\n      VISIBILITY_DBNAME: temporal_visibility\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CLI_ADDRESS: temporal:7233\n    ports:\n      - \"7233:7233\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"tctl\", \"--address\", \"temporal:7233\", \"cluster\", \"health\"]\n      interval: 15s\n      timeout: 5s\n      retries: 12\n      start_period: 60s\n\n  temporal-ui:\n    image: temporalio/ui:2.31.2\n    container_name: zhiqian-temporal-ui\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CORS_ORIGINS: http://localhost:3000,http://localhost:8233\n    ports:\n      - \"8233:8080\"\n    depends_on:\n      - temporal\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      LLM_THINKING_ENABLED: ${LLM_THINKING_ENABLED:-true}\n      LLM_REASONING_EFFORT: ${LLM_REASONING_EFFORT:-high}\n      # v2-step-08: Langfuse 后端全链观测。留空即 disabled\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      # v2-step-14: Temporal durable workflow。默认 false。\n      # TEMPORAL_ENABLED=true 且 docker compose --profile temporal up 后才走 Temporal 路径。\n      TEMPORAL_ENABLED: ${TEMPORAL_ENABLED:-false}\n      TEMPORAL_TARGET: ${TEMPORAL_TARGET:-temporal:7233}\n      TEMPORAL_NAMESPACE: ${TEMPORAL_NAMESPACE:-default}\n      TEMPORAL_TASK_QUEUE: ${TEMPORAL_TASK_QUEUE:-zhiqian-migration}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "39ac14c653f35d43deb02685190205b76503e9a1": {"t": 1785748803.0185356, "n": 6005, "h": "b491b4ed8647c239", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n      - ./init-temporal-db.sql:/docker-entrypoint-initdb.d/10_temporal.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  # v2-step-14: Temporal server (auto-setup, 依赖 postgres)\n  # 启动方式: docker compose --profile temporal up -d\n  # 需要在 .env 中设置 TEMPORAL_ENABLED=true 让 backend 连这里\n  temporal:\n    image: temporalio/auto-setup:1.25.0\n    container_name: zhiqian-temporal\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      DB: postgres12\n      DB_PORT: 5432\n      POSTGRES_USER: zhiqian\n      POSTGRES_PWD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_SEEDS: postgres\n      DBNAME: temporal\n      VISIBILITY_DBNAME: temporal_visibility\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CLI_ADDRESS: temporal:7233\n    ports:\n      - \"7233:7233\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"tctl\", \"--address\", \"temporal:7233\", \"cluster\", \"health\"]\n      interval: 15s\n      timeout: 5s\n      retries: 12\n      start_period: 60s\n\n  temporal-ui:\n    image: temporalio/ui:2.31.2\n    container_name: zhiqian-temporal-ui\n    restart: unless-stopped\n    profiles: [\"temporal\"]\n    environment:\n      TEMPORAL_ADDRESS: temporal:7233\n      TEMPORAL_CORS_ORIGINS: http://localhost:3000,http://localhost:8233\n    ports:\n      - \"8233:8080\"\n    depends_on:\n      - temporal\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      # v2-step-08: Langfuse 后端全链观测。留空即 disabled\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      # v2-step-14: Temporal durable workflow。默认 false。\n      # TEMPORAL_ENABLED=true 且 docker compose --profile temporal up 后才走 Temporal 路径。\n      TEMPORAL_ENABLED: ${TEMPORAL_ENABLED:-false}\n      TEMPORAL_TARGET: ${TEMPORAL_TARGET:-temporal:7233}\n      TEMPORAL_NAMESPACE: ${TEMPORAL_NAMESPACE:-default}\n      TEMPORAL_TASK_QUEUE: ${TEMPORAL_TASK_QUEUE:-zhiqian-migration}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "1ca293a26a759be82c2187635965d84ddcdfdb9a": {"t": 1785748804.2523763, "n": 4383, "h": "77f0353b397db177", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      # v2-step-08: Langfuse 后端全链观测。留空即 disabled,不影响功能。\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      # v2-step-06: Chunking\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      # v2-step-07: Langfuse 全链观测 (留空即 disabled)\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "ceb2703477fb12e3453db571e443990336a31447": {"t": 1785748805.4740767, "n": 4157, "h": "c6795509ee8c5d81", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      # v2-step-06: Chunking\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      # v2-step-07: Langfuse 全链观测 (留空即 disabled)\n      LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY:-}\n      LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY:-}\n      LANGFUSE_HOST: ${LANGFUSE_HOST:-https://cloud.langfuse.com}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "4670edd5d4003c6ab3cb900c7c950bb33aba70f6": {"t": 1785748806.6921072, "n": 3938, "h": "ab8397dd3cf8ed73", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      # v2-step-06: Chunking\n      RAG_CHUNK_STRATEGY: ${RAG_CHUNK_STRATEGY:-semantic}\n      RAG_CHUNK_SIM_THRESHOLD: ${RAG_CHUNK_SIM_THRESHOLD:-0.62}\n      RAG_CHUNK_MAX_CHARS: ${RAG_CHUNK_MAX_CHARS:-1200}\n      RAG_LATE_CHUNK_MAX_CHARS: ${RAG_LATE_CHUNK_MAX_CHARS:-600}\n      RAG_LATE_CHUNK_OVERLAP: ${RAG_LATE_CHUNK_OVERLAP:-80}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "104381a8e33048d5162b58fca77eb21d335261e2": {"t": 1785748807.9113543, "n": 3738, "h": "9d95484fc4410bc0", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  # v2-step-05：Qdrant 向量库。默认不启（仅在 --profile ml 时启动）。\n  # 不启时 RAG 服务会检测到 Qdrant 不可达，自动退化到单走 BM25 路径。\n  qdrant:\n    image: qdrant/qdrant:v1.11.3\n    container_name: zhiqian-qdrant\n    restart: unless-stopped\n    profiles: [\"ml\"]\n    volumes:\n      - qdrantdata:/qdrant/storage\n    ports:\n      - \"6333:6333\"\n      - \"6334:6334\"\n    healthcheck:\n      test: [\"CMD\", \"bash\", \"-c\", \"timeout 1 bash -c '</dev/tcp/127.0.0.1/6333' && echo ok\"]\n      interval: 10s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      # v2-step-05：Qdrant + RRF\n      RAG_USE_QDRANT: ${RAG_USE_QDRANT:-true}\n      RAG_QDRANT_URL: ${RAG_QDRANT_URL:-http://qdrant:6333}\n      RAG_QDRANT_API_KEY: ${RAG_QDRANT_API_KEY:-}\n      RAG_RRF_K: ${RAG_RRF_K:-60}\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n  qdrantdata:\n"}, "d6b4ac5824daae83250beff2d35a3eb6c3f1ced8": {"t": 1785748809.1605284, "n": 3208, "h": "b3b40d332bcffe31", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n      args:\n        # v2-step-04：默认 0 保持轻依赖；BUILD_ML=1 启用 BGE-M3 + Reranker 真模型。\n        BUILD_ML: ${RAG_BUILD_ML:-0}\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n      # v2-step-04：BGE-M3 / Reranker 运行期开关。BUILD_ML=0 时这些变量也能设 true，代码会自动检测并退化。\n      RAG_USE_BGE_M3: ${RAG_USE_BGE_M3:-true}\n      RAG_BGE_MODEL: ${RAG_BGE_MODEL:-BAAI/bge-m3}\n      RAG_BGE_FP16: ${RAG_BGE_FP16:-true}\n      RAG_USE_RERANKER: ${RAG_USE_RERANKER:-true}\n      RAG_RERANKER_MODEL: ${RAG_RERANKER_MODEL:-BAAI/bge-reranker-v2-m3}\n      RAG_RERANKER_FP16: ${RAG_RERANKER_FP16:-true}\n      RAG_EMBEDDING_DIM: ${RAG_EMBEDDING_DIM:-1024}\n      # HuggingFace 镜像源（仅在 BUILD_ML=1 且需要拉取模型时生效）\n      HF_ENDPOINT: ${HF_ENDPOINT:-https://hf-mirror.com}\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 30s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n"}, "790b10f2382ffa782077ff539159dd10a99c6d64": {"t": 1785748810.26697, "n": 2596, "h": "749ca77e2020b659", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      # v2-step-02 新增：LLM 变量透传。未设置则为空字串，后端走 MockLlmClient。\n      LLM_PROVIDER: ${LLM_PROVIDER:-deepseek}\n      LLM_API_KEY: ${LLM_API_KEY:-}\n      LLM_BASE_URL: ${LLM_BASE_URL:-https://api.deepseek.com/v1}\n      LLM_CHAT_MODEL: ${LLM_CHAT_MODEL:-deepseek-chat}\n      LLM_REASONER_MODEL: ${LLM_REASONER_MODEL:-deepseek-reasoner}\n      LLM_TEMPERATURE: ${LLM_TEMPERATURE:-0.2}\n      LLM_MAX_TOKENS: ${LLM_MAX_TOKENS:-2048}\n      LLM_TIMEOUT_SECONDS: ${LLM_TIMEOUT_SECONDS:-60}\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 20s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n"}, "eb9342499731cc21fbd423d9b9b05f7c8f226959": {"t": 1785748811.3246198, "n": 2121, "h": "3f79fba06addedff", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:?请在 .env 中设置 POSTGRES_PASSWORD}\n      APP_JWT_SECRET: ${JWT_SECRET:?请在 .env 中设置 JWT_SECRET}\n      APP_ADMIN_PASSWORD: ${ADMIN_PASSWORD:?请在 .env 中设置 ADMIN_PASSWORD}\n      APP_RAG_BASE_URL: http://rag:8001\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 20s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n"}, "ac79f9bc38873d56ad0197d0107627b96a685df0": {"t": 1785748812.4498308, "n": 2065, "h": "11e91c7b40e4bea2", "c": "name: zhiqian\n\nservices:\n  postgres:\n    image: postgres:16-alpine\n    container_name: zhiqian-postgres\n    restart: unless-stopped\n    environment:\n      POSTGRES_USER: zhiqian\n      POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-zhiqian123}\n      POSTGRES_DB: zhiqian\n    volumes:\n      - pgdata:/var/lib/postgresql/data\n      - ./init-db.sql:/docker-entrypoint-initdb.d/00_init.sql:ro\n    ports:\n      - \"5432:5432\"\n    healthcheck:\n      test: [\"CMD-SHELL\", \"pg_isready -U zhiqian -d zhiqian\"]\n      interval: 5s\n      timeout: 5s\n      retries: 10\n\n  backend:\n    build:\n      context: ../backend\n      dockerfile: Dockerfile\n    container_name: zhiqian-backend\n    restart: unless-stopped\n    environment:\n      SPRING_DATASOURCE_URL: jdbc:postgresql://postgres:5432/zhiqian\n      SPRING_DATASOURCE_USERNAME: zhiqian\n      SPRING_DATASOURCE_PASSWORD: ${POSTGRES_PASSWORD:-zhiqian123}\n      APP_JWT_SECRET: ${JWT_SECRET:-change-me-please-change-me-please-32bytes-min}\n      APP_RAG_BASE_URL: http://rag:8001\n      JAVA_TOOL_OPTIONS: \"-Xms256m -Xmx768m\"\n    ports:\n      - \"8080:8080\"\n    depends_on:\n      postgres:\n        condition: service_healthy\n    healthcheck:\n      test: [\"CMD\", \"wget\", \"-qO-\", \"http://localhost:8080/actuator/health\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 40s\n\n  rag:\n    build:\n      context: ../rag\n      dockerfile: Dockerfile\n    container_name: zhiqian-rag\n    restart: unless-stopped\n    environment:\n      ZHIQIAN_RAG_CHROMA_PATH: /data/.chroma\n    volumes:\n      - ragdata:/data\n    ports:\n      - \"8001:8001\"\n    healthcheck:\n      test: [\"CMD\", \"python\", \"-c\", \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://localhost:8001/health').status==200 else 1)\"]\n      interval: 10s\n      timeout: 5s\n      retries: 12\n      start_period: 20s\n\n  web:\n    build:\n      context: ../web\n      dockerfile: Dockerfile\n    container_name: zhiqian-web\n    restart: unless-stopped\n    ports:\n      - \"80:80\"\n    depends_on:\n      - backend\n      - rag\n\nvolumes:\n  pgdata:\n  ragdata:\n"}}, "zhiqian/backend/src/main/resources/application.yml": {"450a71e5cdc3cfb27544c338af7e73ac5bd5efab": {"t": 1785746948.0518847, "n": 2453, "h": "0b9407b3eb66bd24", "c": "server:\n  port: 8080\n  tomcat:\n    connection-timeout: 300000   # 5min — 单次 migrate 请求可能包含 6 阶段 × 多次 LLM 调用\n    threads:\n      max: 32                    # Tomcat 线程减少，实际 LLM 工作在 migrateExecutor 线程池\n    accept-count: 200            # 排队队列加长，防止连接被拒\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02: LLM 接入配置 =====\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n    thinking-enabled: ${LLM_THINKING_ENABLED:true}\n    reasoning-effort: ${LLM_REASONING_EFFORT:high}\n  # ===== v2-step-08: Langfuse 后端全链观测 =====\n  langfuse:\n    enabled: ${LANGFUSE_ENABLED:true}\n    host: ${LANGFUSE_HOST:https://cloud.langfuse.com}\n    public-key: ${LANGFUSE_PUBLIC_KEY:}\n    secret-key: ${LANGFUSE_SECRET_KEY:}\n  # ===== v2-step-14: Temporal durable workflow =====\n  # enabled=false (默认) 时不装载任何 Temporal bean, 原 AgentRunner 路径完全不变。\n  # 启用后必需 docker compose --profile temporal up 拉起 temporal-server。\n  temporal:\n    enabled: ${TEMPORAL_ENABLED:false}\n    service-target: ${TEMPORAL_TARGET:127.0.0.1:7233}\n    namespace: ${TEMPORAL_NAMESPACE:default}\n    task-queue: ${TEMPORAL_TASK_QUEUE:zhiqian-migration}\n    workflow-execution-timeout-minutes: ${TEMPORAL_WF_TIMEOUT_MIN:60}\n    activity-start-to-close-timeout-seconds: ${TEMPORAL_ACT_TIMEOUT_SEC:600}\n    activity-max-attempts: ${TEMPORAL_ACT_MAX_ATTEMPTS:3}\n    worker-concurrent-activity-execution-size: ${TEMPORAL_WORKER_CONCURRENCY:8}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "3d3749d13fd6199027b417ff621974161d367e57": {"t": 1785748801.0481782, "n": 2453, "h": "0b9407b3eb66bd24", "c": "server:\n  port: 8080\n  tomcat:\n    connection-timeout: 300000   # 5min — 单次 migrate 请求可能包含 6 阶段 × 多次 LLM 调用\n    threads:\n      max: 32                    # Tomcat 线程减少，实际 LLM 工作在 migrateExecutor 线程池\n    accept-count: 200            # 排队队列加长，防止连接被拒\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02: LLM 接入配置 =====\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n    thinking-enabled: ${LLM_THINKING_ENABLED:true}\n    reasoning-effort: ${LLM_REASONING_EFFORT:high}\n  # ===== v2-step-08: Langfuse 后端全链观测 =====\n  langfuse:\n    enabled: ${LANGFUSE_ENABLED:true}\n    host: ${LANGFUSE_HOST:https://cloud.langfuse.com}\n    public-key: ${LANGFUSE_PUBLIC_KEY:}\n    secret-key: ${LANGFUSE_SECRET_KEY:}\n  # ===== v2-step-14: Temporal durable workflow =====\n  # enabled=false (默认) 时不装载任何 Temporal bean, 原 AgentRunner 路径完全不变。\n  # 启用后必需 docker compose --profile temporal up 拉起 temporal-server。\n  temporal:\n    enabled: ${TEMPORAL_ENABLED:false}\n    service-target: ${TEMPORAL_TARGET:127.0.0.1:7233}\n    namespace: ${TEMPORAL_NAMESPACE:default}\n    task-queue: ${TEMPORAL_TASK_QUEUE:zhiqian-migration}\n    workflow-execution-timeout-minutes: ${TEMPORAL_WF_TIMEOUT_MIN:60}\n    activity-start-to-close-timeout-seconds: ${TEMPORAL_ACT_TIMEOUT_SEC:600}\n    activity-max-attempts: ${TEMPORAL_ACT_MAX_ATTEMPTS:3}\n    worker-concurrent-activity-execution-size: ${TEMPORAL_WORKER_CONCURRENCY:8}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "6289d20e0c9fe48f73b519670c34a6cc06a0ef74": {"t": 1785748802.127709, "n": 2226, "h": "d0c6d015a8ba8d24", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02: LLM 接入配置 =====\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n    thinking-enabled: ${LLM_THINKING_ENABLED:true}\n    reasoning-effort: ${LLM_REASONING_EFFORT:high}\n  # ===== v2-step-08: Langfuse 后端全链观测 =====\n  langfuse:\n    enabled: ${LANGFUSE_ENABLED:true}\n    host: ${LANGFUSE_HOST:https://cloud.langfuse.com}\n    public-key: ${LANGFUSE_PUBLIC_KEY:}\n    secret-key: ${LANGFUSE_SECRET_KEY:}\n  # ===== v2-step-14: Temporal durable workflow =====\n  # enabled=false (默认) 时不装载任何 Temporal bean, 原 AgentRunner 路径完全不变。\n  # 启用后必需 docker compose --profile temporal up 拉起 temporal-server。\n  temporal:\n    enabled: ${TEMPORAL_ENABLED:false}\n    service-target: ${TEMPORAL_TARGET:127.0.0.1:7233}\n    namespace: ${TEMPORAL_NAMESPACE:default}\n    task-queue: ${TEMPORAL_TASK_QUEUE:zhiqian-migration}\n    workflow-execution-timeout-minutes: ${TEMPORAL_WF_TIMEOUT_MIN:60}\n    activity-start-to-close-timeout-seconds: ${TEMPORAL_ACT_TIMEOUT_SEC:600}\n    activity-max-attempts: ${TEMPORAL_ACT_MAX_ATTEMPTS:3}\n    worker-concurrent-activity-execution-size: ${TEMPORAL_WORKER_CONCURRENCY:8}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "39ac14c653f35d43deb02685190205b76503e9a1": {"t": 1785748803.2438421, "n": 2124, "h": "5f4f04d7915a9523", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02: LLM 接入配置 =====\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n  # ===== v2-step-08: Langfuse 后端全链观测 =====\n  langfuse:\n    enabled: ${LANGFUSE_ENABLED:true}\n    host: ${LANGFUSE_HOST:https://cloud.langfuse.com}\n    public-key: ${LANGFUSE_PUBLIC_KEY:}\n    secret-key: ${LANGFUSE_SECRET_KEY:}\n  # ===== v2-step-14: Temporal durable workflow =====\n  # enabled=false (默认) 时不装载任何 Temporal bean, 原 AgentRunner 路径完全不变。\n  # 启用后必需 docker compose --profile temporal up 拉起 temporal-server。\n  temporal:\n    enabled: ${TEMPORAL_ENABLED:false}\n    service-target: ${TEMPORAL_TARGET:127.0.0.1:7233}\n    namespace: ${TEMPORAL_NAMESPACE:default}\n    task-queue: ${TEMPORAL_TASK_QUEUE:zhiqian-migration}\n    workflow-execution-timeout-minutes: ${TEMPORAL_WF_TIMEOUT_MIN:60}\n    activity-start-to-close-timeout-seconds: ${TEMPORAL_ACT_TIMEOUT_SEC:600}\n    activity-max-attempts: ${TEMPORAL_ACT_MAX_ATTEMPTS:3}\n    worker-concurrent-activity-execution-size: ${TEMPORAL_WORKER_CONCURRENCY:8}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "1ca293a26a759be82c2187635965d84ddcdfdb9a": {"t": 1785748804.385864, "n": 1665, "h": "fa44afa34446b195", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02 新增：LLM 接入配置 =====\n  # 默认指向 DeepSeek-V3.1，使用 OpenAI 兼容协议。\n  # api-key 为空时后端会启用 MockLlmClient（仅回显），不阻塞启动。\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n  # ===== v2-step-08 新增：Langfuse 后端全链观测 =====\n  # public-key/secret-key 留空即 disabled，行为完全不变，不影响功能。\n  # 配上后，task.migration root trace + 6 stage span + 每次 LLM 调用 generation 都会上报。\n  langfuse:\n    enabled: ${LANGFUSE_ENABLED:true}\n    host: ${LANGFUSE_HOST:https://cloud.langfuse.com}\n    public-key: ${LANGFUSE_PUBLIC_KEY:}\n    secret-key: ${LANGFUSE_SECRET_KEY:}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "790b10f2382ffa782077ff539159dd10a99c6d64": {"t": 1785748805.5553286, "n": 1304, "h": "83a3a6b48e931a01", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n  # ===== v2-step-02 新增：LLM 接入配置 =====\n  # 默认指向 DeepSeek-V3.1，使用 OpenAI 兼容协议。\n  # api-key 为空时后端会启用 MockLlmClient（仅回显），不阻塞启动。\n  llm:\n    provider: ${LLM_PROVIDER:deepseek}\n    api-key: ${LLM_API_KEY:}\n    base-url: ${LLM_BASE_URL:https://api.deepseek.com/v1}\n    chat-model: ${LLM_CHAT_MODEL:deepseek-chat}\n    reasoner-model: ${LLM_REASONER_MODEL:deepseek-reasoner}\n    temperature: ${LLM_TEMPERATURE:0.2}\n    max-tokens: ${LLM_MAX_TOKENS:2048}\n    timeout-seconds: ${LLM_TIMEOUT_SECONDS:60}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "eb9342499731cc21fbd423d9b9b05f7c8f226959": {"t": 1785748806.6224804, "n": 812, "h": "62013e25a2e0105a", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:60}\n  admin:\n    password: ${APP_ADMIN_PASSWORD}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "7907a90cf614d5c136b037f852c898a5d369cc2b": {"t": 1785748807.766152, "n": 825, "h": "dfc5db553507a973", "c": "server:\n  port: 8080\n  servlet:\n    encoding:\n      charset: UTF-8\n      enabled: true\n      force: true\n\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: ${SPRING_DATASOURCE_URL:jdbc:postgresql://localhost:5432/zhiqian}\n    username: ${SPRING_DATASOURCE_USERNAME:zhiqian}\n    password: ${SPRING_DATASOURCE_PASSWORD:zhiqian123}\n    driver-class-name: org.postgresql.Driver\n  flyway:\n    enabled: true\n    baseline-on-migrate: true\n    locations: classpath:db/migration\n\nmanagement:\n  endpoints:\n    web:\n      exposure:\n        include: health,info\n\napp:\n  jwt:\n    secret: ${APP_JWT_SECRET:change-me-please-change-me-please-32bytes-min}\n    ttl-minutes: ${APP_JWT_TTL_MINUTES:720}\n  rag:\n    base-url: ${APP_RAG_BASE_URL:http://localhost:8001}\n\nlogging:\n  level:\n    root: INFO\n    com.zhiqian: DEBUG\n"}, "31c555708565771221a992c72a36435992460974": {"t": 1785748808.950704, "n": 637, "h": "7476e41447a9eb95", "c": "server:\n  port: 8080\nspring:\n  application:\n    name: zhiqian-backend\n  datasource:\n    url: jdbc:mysql://localhost:3306/zhiqian?useUnicode=true&characterEncoding=utf8&serverTimezone=Asia/Shanghai\n    username: zhiqian\n    password: zhiqian\n    driver-class-name: com.mysql.cj.jdbc.Driver\n  flyway:\n    enabled: true\n    locations: classpath:db/migration\n  servlet:\n    multipart:\n      max-file-size: 512MB\n      max-request-size: 512MB\nzhiqian:\n  jwt:\n    secret: please-change-in-prod-32-bytes-min\n    expire-hours: 24\n  rag:\n    base-url: http://localhost:8001\n  analyzer:\n    workspace: ./workspace\n  llm:\n    default-provider: glm\n"}}, "zhiqian/deploy/helm/zhiqian/values.yaml": {"450a71e5cdc3cfb27544c338af7e73ac5bd5efab": {"t": 1785747057.2554524, "n": 4005, "h": "08c99e16bd4e9a11", "c": "# v2-step-18: Helm values for ZhiQian YunShu\n# 生产部署时 override 关键项: image.tag / postgres.password / backend.secrets.jwtSecret /\n# backend.secrets.deepseekApiKey / ingress.hosts / persistence.size\n# ----\n\nglobal:\n  imageRegistry: \"\"    # 例 ghcr.io/anothersunset/, 为空时走 docker.io / 本地\n  imagePullSecrets: []\n  storageClass: \"\"\n\nnameOverride: \"\"\nfullnameOverride: \"\"\n\n# ===== 三个服务 =====\nbackend:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/backend\n    tag: \"\"   # 为空时使用 .Chart.AppVersion\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 8080\n  resources:\n    requests:\n      cpu: 200m\n      memory: 512Mi\n    limits:\n      cpu: 1500m\n      memory: 2Gi\n  config:\n    # 可被 override 的非敏感配置\n    llm:\n      provider: deepseek\n      baseUrl: https://api.deepseek.com\n      chatModel: deepseek-chat\n      reasonerModel: deepseek-reasoner\n      temperature: 0.2\n      maxTokens: 2048\n      timeoutSeconds: 60\n    langfuse:\n      enabled: false\n      host: https://cloud.langfuse.com\n    temporal:\n      enabled: false\n      serviceTarget: temporal:7233\n      namespace: default\n      taskQueue: zhiqian-migration\n  secrets:\n    # 使用 helm install --set backend.secrets.jwtSecret=... 覆盖, 或 secretRef 外部报存\n    jwtSecret: \"please-change-me-to-a-long-random-string-at-least-32-chars\"\n    deepseekApiKey: \"\"\n    langfusePublicKey: \"\"\n    langfuseSecretKey: \"\"\n  livenessProbe:\n    httpGet:\n      path: /actuator/health/liveness\n      port: http\n    initialDelaySeconds: 60\n    periodSeconds: 30\n  readinessProbe:\n    httpGet:\n      path: /actuator/health/readiness\n      port: http\n    initialDelaySeconds: 30\n    periodSeconds: 10\n  podSecurityContext:\n    runAsNonRoot: true\n    runAsUser: 1000\n    fsGroup: 1000\n  nodeSelector: {}\n  tolerations: []\n  affinity: {}\n\nrag:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/rag\n    tag: \"\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 8001\n  resources:\n    requests:\n      cpu: 200m\n      memory: 512Mi\n    limits:\n      cpu: 2000m\n      memory: 4Gi   # ML 模型需要, 启用 BGE-M3 时 ≥ 3Gi\n  env:\n    RAG_CHUNK_STRATEGY: semantic\n    RAG_CHUNK_SIM_THRESHOLD: \"0.62\"\n    RAG_OUTLINES_ENABLED: \"false\"\n    RAG_CRAG_USE_LLM_EVAL: \"0\"\n    HF_ENDPOINT: https://hf-mirror.com\n  qdrant:\n    enabled: false   # 默认 BM25 单路降级; 上营由 ArgoCD overlay 开\n    url: http://qdrant:6333\n  livenessProbe:\n    httpGet:\n      path: /health\n      port: http\n    initialDelaySeconds: 30\n    periodSeconds: 30\n  readinessProbe:\n    httpGet:\n      path: /health\n      port: http\n    initialDelaySeconds: 15\n    periodSeconds: 10\n  podSecurityContext:\n    runAsNonRoot: true\n    runAsUser: 1000\n    fsGroup: 1000\n\nweb:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/web\n    tag: \"\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 80\n  resources:\n    requests:\n      cpu: 50m\n      memory: 64Mi\n    limits:\n      cpu: 200m\n      memory: 256Mi\n\n# ===== PostgreSQL =====\npostgres:\n  enabled: true\n  image:\n    repository: postgres\n    tag: \"16-alpine\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 5432\n  auth:\n    username: zhiqian\n    password: zhiqian-change-me\n    database: zhiqian\n  persistence:\n    enabled: true\n    size: 10Gi\n    accessMode: ReadWriteOnce\n  resources:\n    requests:\n      cpu: 100m\n      memory: 256Mi\n    limits:\n      cpu: 1000m\n      memory: 1Gi\n\n# ===== Ingress =====\ningress:\n  enabled: false\n  className: nginx\n  annotations:\n    nginx.ingress.kubernetes.io/proxy-body-size: 50m\n    nginx.ingress.kubernetes.io/proxy-read-timeout: \"300\"\n  hosts:\n    - host: zhiqian.local\n      paths:\n        - path: /api\n          pathType: Prefix\n          service: backend\n        - path: /rag\n          pathType: Prefix\n          service: rag\n        - path: /\n          pathType: Prefix\n          service: web\n  tls: []\n  #  - secretName: zhiqian-tls\n  #    hosts: [zhiqian.local]\n\nserviceAccount:\n  create: true\n  annotations: {}\n  name: \"\"\n"}, "c2851ba9e60a5f8ca6dda387146f4b4c7d91b1b1": {"t": 1785748801.7968087, "n": 4005, "h": "08c99e16bd4e9a11", "c": "# v2-step-18: Helm values for ZhiQian YunShu\n# 生产部署时 override 关键项: image.tag / postgres.password / backend.secrets.jwtSecret /\n# backend.secrets.deepseekApiKey / ingress.hosts / persistence.size\n# ----\n\nglobal:\n  imageRegistry: \"\"    # 例 ghcr.io/anothersunset/, 为空时走 docker.io / 本地\n  imagePullSecrets: []\n  storageClass: \"\"\n\nnameOverride: \"\"\nfullnameOverride: \"\"\n\n# ===== 三个服务 =====\nbackend:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/backend\n    tag: \"\"   # 为空时使用 .Chart.AppVersion\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 8080\n  resources:\n    requests:\n      cpu: 200m\n      memory: 512Mi\n    limits:\n      cpu: 1500m\n      memory: 2Gi\n  config:\n    # 可被 override 的非敏感配置\n    llm:\n      provider: deepseek\n      baseUrl: https://api.deepseek.com\n      chatModel: deepseek-chat\n      reasonerModel: deepseek-reasoner\n      temperature: 0.2\n      maxTokens: 2048\n      timeoutSeconds: 60\n    langfuse:\n      enabled: false\n      host: https://cloud.langfuse.com\n    temporal:\n      enabled: false\n      serviceTarget: temporal:7233\n      namespace: default\n      taskQueue: zhiqian-migration\n  secrets:\n    # 使用 helm install --set backend.secrets.jwtSecret=... 覆盖, 或 secretRef 外部报存\n    jwtSecret: \"please-change-me-to-a-long-random-string-at-least-32-chars\"\n    deepseekApiKey: \"\"\n    langfusePublicKey: \"\"\n    langfuseSecretKey: \"\"\n  livenessProbe:\n    httpGet:\n      path: /actuator/health/liveness\n      port: http\n    initialDelaySeconds: 60\n    periodSeconds: 30\n  readinessProbe:\n    httpGet:\n      path: /actuator/health/readiness\n      port: http\n    initialDelaySeconds: 30\n    periodSeconds: 10\n  podSecurityContext:\n    runAsNonRoot: true\n    runAsUser: 1000\n    fsGroup: 1000\n  nodeSelector: {}\n  tolerations: []\n  affinity: {}\n\nrag:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/rag\n    tag: \"\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 8001\n  resources:\n    requests:\n      cpu: 200m\n      memory: 512Mi\n    limits:\n      cpu: 2000m\n      memory: 4Gi   # ML 模型需要, 启用 BGE-M3 时 ≥ 3Gi\n  env:\n    RAG_CHUNK_STRATEGY: semantic\n    RAG_CHUNK_SIM_THRESHOLD: \"0.62\"\n    RAG_OUTLINES_ENABLED: \"false\"\n    RAG_CRAG_USE_LLM_EVAL: \"0\"\n    HF_ENDPOINT: https://hf-mirror.com\n  qdrant:\n    enabled: false   # 默认 BM25 单路降级; 上营由 ArgoCD overlay 开\n    url: http://qdrant:6333\n  livenessProbe:\n    httpGet:\n      path: /health\n      port: http\n    initialDelaySeconds: 30\n    periodSeconds: 30\n  readinessProbe:\n    httpGet:\n      path: /health\n      port: http\n    initialDelaySeconds: 15\n    periodSeconds: 10\n  podSecurityContext:\n    runAsNonRoot: true\n    runAsUser: 1000\n    fsGroup: 1000\n\nweb:\n  enabled: true\n  replicaCount: 1\n  image:\n    repository: zhiqian/web\n    tag: \"\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 80\n  resources:\n    requests:\n      cpu: 50m\n      memory: 64Mi\n    limits:\n      cpu: 200m\n      memory: 256Mi\n\n# ===== PostgreSQL =====\npostgres:\n  enabled: true\n  image:\n    repository: postgres\n    tag: \"16-alpine\"\n    pullPolicy: IfNotPresent\n  service:\n    type: ClusterIP\n    port: 5432\n  auth:\n    username: zhiqian\n    password: zhiqian-change-me\n    database: zhiqian\n  persistence:\n    enabled: true\n    size: 10Gi\n    accessMode: ReadWriteOnce\n  resources:\n    requests:\n      cpu: 100m\n      memory: 256Mi\n    limits:\n      cpu: 1000m\n      memory: 1Gi\n\n# ===== Ingress =====\ningress:\n  enabled: false\n  className: nginx\n  annotations:\n    nginx.ingress.kubernetes.io/proxy-body-size: 50m\n    nginx.ingress.kubernetes.io/proxy-read-timeout: \"300\"\n  hosts:\n    - host: zhiqian.local\n      paths:\n        - path: /api\n          pathType: Prefix\n          service: backend\n        - path: /rag\n          pathType: Prefix\n          service: rag\n        - path: /\n          pathType: Prefix\n          service: web\n  tls: []\n  #  - secretName: zhiqian-tls\n  #    hosts: [zhiqian.local]\n\nserviceAccount:\n  create: true\n  annotations: {}\n  name: \"\"\n"}}, "zhiqian/deploy/kustomize/base/backend-configmap.yaml": {"450a71e5cdc3cfb27544c338af7e73ac5bd5efab": {"t": 1785747059.1829314, "n": 1354, "h": "fec882ace8ef12af", "c": "# v2-step-18: backend application config (non-secret)\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: zhiqian-backend-config\n  labels:\n    app.kubernetes.io/name: backend\n    app.kubernetes.io/component: api\ndata:\n  application.yaml: |\n    spring:\n      datasource:\n        url: jdbc:postgresql://zhiqian-postgres:5432/zhiqian\n        username: zhiqian\n        password: ${SPRING_DATASOURCE_PASSWORD}\n      flyway:\n        enabled: true\n        baseline-on-migrate: true\n    server:\n      port: 8080\n    management:\n      endpoints:\n        web:\n          exposure:\n            include: health,info,metrics\n      endpoint:\n        health:\n          probes:\n            enabled: true\n    app:\n      jwt:\n        secret: ${APP_JWT_SECRET}\n        expire-minutes: 1440\n      llm:\n        provider: deepseek\n        api-key: ${APP_LLM_API_KEY}\n        base-url: https://api.deepseek.com\n        chat-model: deepseek-chat\n        reasoner-model: deepseek-reasoner\n        temperature: 0.2\n        max-tokens: 2048\n        timeout-seconds: 60\n      langfuse:\n        enabled: false\n        host: https://cloud.langfuse.com\n        public-key: ${APP_LANGFUSE_PUBLIC_KEY}\n        secret-key: ${APP_LANGFUSE_SECRET_KEY}\n      temporal:\n        enabled: false\n        service-target: temporal:7233\n        namespace: default\n        task-queue: zhiqian-migration\n"}, "9833e4dce4b1fc7f63debc9bcd33309590b0ae91": {"t": 1785748801.34762, "n": 1354, "h": "fec882ace8ef12af", "c": "# v2-step-18: backend application config (non-secret)\napiVersion: v1\nkind: ConfigMap\nmetadata:\n  name: zhiqian-backend-config\n  labels:\n    app.kubernetes.io/name: backend\n    app.kubernetes.io/component: api\ndata:\n  application.yaml: |\n    spring:\n      datasource:\n        url: jdbc:postgresql://zhiqian-postgres:5432/zhiqian\n        username: zhiqian\n        password: ${SPRING_DATASOURCE_PASSWORD}\n      flyway:\n        enabled: true\n        baseline-on-migrate: true\n    server:\n      port: 8080\n    management:\n      endpoints:\n        web:\n          exposure:\n            include: health,info,metrics\n      endpoint:\n        health:\n          probes:\n            enabled: true\n    app:\n      jwt:\n        secret: ${APP_JWT_SECRET}\n        expire-minutes: 1440\n      llm:\n        provider: deepseek\n        api-key: ${APP_LLM_API_KEY}\n        base-url: https://api.deepseek.com\n        chat-model: deepseek-chat\n        reasoner-model: deepseek-reasoner\n        temperature: 0.2\n        max-tokens: 2048\n        timeout-seconds: 60\n      langfuse:\n        enabled: false\n        host: https://cloud.langfuse.com\n        public-key: ${APP_LANGFUSE_PUBLIC_KEY}\n        secret-key: ${APP_LANGFUSE_SECRET_KEY}\n      temporal:\n        enabled: false\n        service-target: temporal:7233\n        namespace: default\n        task-queue: zhiqian-migration\n"}}}}