feat: 更新 Docker 配置，添加 Milvus 令牌支持，优化健康检查命令，移除 PostgreSQL 配置，调整环境变量，增强系统稳定性
This commit is contained in:
Wenjie Zhang
parent
9a162d5197
commit
5ed016298c
@ -25,32 +25,25 @@ services:
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- NEO4J_USERNAME=${NEO4J_USERNAME:-neo4j}
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- NEO4J_PASSWORD=${NEO4J_PASSWORD:-0123456789}
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- MILVUS_URI=${MILVUS_URI:-http://milvus:19530}
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- MILVUS_TOKEN=${MILVUS_TOKEN:-}
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- MINERU_OCR_URI=${MINERU_OCR_URI:-http://mineru:30000}
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- PADDLEX_URI=${PADDLEX_URI:-http://paddlex-ocr:8080}
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- MINIO_URI=${MINIO_URI:-http://milvus-minio:9000}
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# PostgreSQL 配置
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- POSTGRES_URI=postgresql://${POSTGRES_USER:-lightrag}:${POSTGRES_PASSWORD:-lightrag}@postgres-lightrag:5432/${POSTGRES_DATABASE:-lightrag}
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- POSTGRES_HOST=${POSTGRES_HOST:-postgres-lightrag}
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- POSTGRES_PORT=${POSTGRES_PORT:-5432}
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- POSTGRES_DATABASE=${POSTGRES_DATABASE:-lightrag}
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- POSTGRES_USER=${POSTGRES_USER:-lightrag}
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- POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-lightrag}
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# 连接池配置
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- POSTGRES_MAX_CONNECTIONS=50
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- POSTGRES_MIN_CONNECTIONS=5
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- MODEL_DIR=/models
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- RUNNING_IN_DOCKER=true
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- NO_PROXY=localhost,127.0.0.1,milvus,graph,milvus-minio,milvus-etcd-dev,etcd,minio
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- no_proxy=localhost,127.0.0.1,milvus,graph,milvus-minio,milvus-etcd-dev,etcd,minio
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command: uv run uvicorn server.main:app --host 0.0.0.0 --port 5050 --reload
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restart: unless-stopped
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healthcheck:
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test: ["CMD-SHELL", "curl -f http://localhost:5050/health || exit 1"]
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test: ["CMD-SHELL", "curl -f http://localhost:5050/api/health || exit 1"]
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interval: 30s
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timeout: 15s
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retries: 8
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start_period: 180s
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depends_on:
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postgres:
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condition: service_healthy
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# postgres:
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# condition: service_healthy
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milvus:
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condition: service_healthy
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minio:
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@ -80,31 +73,31 @@ services:
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# PostgreSQL 服务 - 基于官方推荐的 shangor/postgres-for-rag 镜像
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# 提供 KV store, VectorDB (pgvector) 和 GraphDB (Apache AGE) 功能
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postgres:
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image: shangor/postgres-for-rag:v1.0
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container_name: postgres-lightrag
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environment:
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- POSTGRES_DATABASE=${POSTGRES_DATABASE:-lightrag}
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- POSTGRES_USER=${POSTGRES_USER:-lightrag}
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- POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-lightrag}
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- POSTGRES_HOST_AUTH_METHOD=md5
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# 启用必要的扩展
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- POSTGRES_INITDB_ARGS=--auth-host=md5
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volumes:
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- ./docker/volumes/postgres/data:/var/lib/postgresql/data
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- ./docker/init-postgres.sh:/init-postgres.sh
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ports:
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- "5432:5432"
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healthcheck:
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test: ["CMD-SHELL", "PGPASSWORD=${POSTGRES_PASSWORD:-lightrag} psql -h localhost -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c \"SELECT ag_catalog.create_graph('test_ready');\" || PGPASSWORD=${POSTGRES_PASSWORD:-lightrag} psql -h localhost -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c 'SELECT 1'"]
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interval: 30s
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timeout: 15s
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retries: 15
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start_period: 120s
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networks:
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- app-network
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restart: unless-stopped
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command: ["bash", "/init-postgres.sh"]
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# postgres:
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# image: shangor/postgres-for-rag:v1.0
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# container_name: postgres-lightrag
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# environment:
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# - POSTGRES_DATABASE=${POSTGRES_DATABASE:-lightrag}
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# - POSTGRES_USER=${POSTGRES_USER:-lightrag}
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# - POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-lightrag}
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# - POSTGRES_HOST_AUTH_METHOD=md5
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# # 启用必要的扩展
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# - POSTGRES_INITDB_ARGS=--auth-host=md5
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# volumes:
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# - ./docker/volumes/postgres/data:/var/lib/postgresql/data
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# - ./docker/init-postgres.sh:/init-postgres.sh
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# ports:
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# - "5432:5432"
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# healthcheck:
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# test: ["CMD-SHELL", "PGPASSWORD=${POSTGRES_PASSWORD:-lightrag} psql -h localhost -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c \"SELECT ag_catalog.create_graph('test_ready');\" || PGPASSWORD=${POSTGRES_PASSWORD:-lightrag} psql -h localhost -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c 'SELECT 1'"]
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# interval: 30s
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# timeout: 15s
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# retries: 15
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# start_period: 120s
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# networks:
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# - app-network
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# restart: unless-stopped
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# command: ["bash", "/init-postgres.sh"]
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graph:
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image: neo4j:5.26
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@ -29,6 +29,11 @@ COPY ../pyproject.toml /app/pyproject.toml
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COPY ../.python-version /app/.python-version
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# 安装依赖项
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ENV HTTP_PROXY=http://172.19.13.5:7890 \
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HTTPS_PROXY=http://172.19.13.5:7890 \
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http_proxy=http://172.19.13.5:7890 \
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https_proxy=http://172.19.13.5:7890
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RUN --mount=type=cache,target=/root/.cache/uv \
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uv sync --no-install-project
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@ -38,4 +43,7 @@ COPY ../server /app/server
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# 同步项目
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RUN --mount=type=cache,target=/root/.cache/uv \
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uv sync
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uv sync
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# 取消代理
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RUN unset HTTP_PROXY HTTPS_PROXY http_proxy https_proxy
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@ -1,358 +0,0 @@
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#!/bin/bash
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# PostgreSQL 初始化脚本
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# 适用于 shangor/postgres-for-rag 镜像
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set -e
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echo "Starting PostgreSQL initialization..."
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# 启动 PostgreSQL 服务
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service postgresql start
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sleep 10
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echo "PostgreSQL service started, waiting for it to be ready..."
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# 等待 PostgreSQL 完全启动
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while ! su - postgres -c "pg_isready" > /dev/null 2>&1; do
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echo "Waiting for PostgreSQL to be ready..."
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sleep 5
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done
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# 额外等待以确保数据库完全启动
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echo "PostgreSQL is ready, waiting additional time for full initialization..."
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sleep 10
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echo "PostgreSQL is ready, creating user and database..."
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# 创建用户（如果不存在）
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if ! su - postgres -c "psql -tAc \"SELECT 1 FROM pg_roles WHERE rolname='${POSTGRES_USER:-lightrag}'\"" | grep -q 1; then
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echo "Creating user ${POSTGRES_USER:-lightrag}..."
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su - postgres -c "createuser -s ${POSTGRES_USER:-lightrag}"
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else
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echo "User ${POSTGRES_USER:-lightrag} already exists"
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fi
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# 创建数据库（如果不存在）
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if ! su - postgres -c "psql -tAc \"SELECT 1 FROM pg_database WHERE datname='${POSTGRES_DATABASE:-lightrag}'\"" | grep -q 1; then
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echo "Creating database ${POSTGRES_DATABASE:-lightrag}..."
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su - postgres -c "createdb -O ${POSTGRES_USER:-lightrag} ${POSTGRES_DATABASE:-lightrag}"
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else
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echo "Database ${POSTGRES_DATABASE:-lightrag} already exists"
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fi
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# 设置密码
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echo "Setting password for user ${POSTGRES_USER:-lightrag}..."
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su - postgres -c "psql -c \"ALTER USER ${POSTGRES_USER:-lightrag} PASSWORD '${POSTGRES_PASSWORD:-lightrag}';\""
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# 配置 pg_hba.conf 以允许密码认证
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echo "Configuring PostgreSQL authentication..."
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PG_HBA_CONF="/etc/postgresql/16/main/pg_hba.conf"
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# 备份原始配置
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cp $PG_HBA_CONF $PG_HBA_CONF.backup
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# 创建新的 pg_hba.conf 文件，确保 lightrag 用户的规则在前面
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cat > $PG_HBA_CONF << EOF
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# PostgreSQL Client Authentication Configuration File
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# ===================================================
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# TYPE DATABASE USER ADDRESS METHOD
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# LightRAG user authentication (must be first to take precedence)
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local ${POSTGRES_DATABASE:-lightrag} ${POSTGRES_USER:-lightrag} md5
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host ${POSTGRES_DATABASE:-lightrag} ${POSTGRES_USER:-lightrag} 127.0.0.1/32 md5
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host ${POSTGRES_DATABASE:-lightrag} ${POSTGRES_USER:-lightrag} ::1/128 md5
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host ${POSTGRES_DATABASE:-lightrag} ${POSTGRES_USER:-lightrag} 0.0.0.0/0 md5
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# Default configurations
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local all postgres peer
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local all all peer
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host all all 127.0.0.1/32 scram-sha-256
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host all all ::1/128 scram-sha-256
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local replication all peer
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host replication all 127.0.0.1/32 scram-sha-256
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host replication all ::1/128 scram-sha-256
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EOF
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# 重启 PostgreSQL 以应用 pg_hba.conf 更改
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echo "Restarting PostgreSQL to apply authentication changes..."
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service postgresql restart
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sleep 5
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echo "Installing extensions..."
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# 安装 vector 扩展
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echo "Installing vector extension..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"CREATE EXTENSION IF NOT EXISTS vector;\""
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# 安装 age 扩展
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echo "Installing age extension..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"CREATE EXTENSION IF NOT EXISTS age;\""
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echo "Configuring AGE extension..."
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# 加载 AGE 扩展
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"LOAD 'age';\""
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# 设置搜索路径
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"SET search_path = ag_catalog, public;\""
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# 创建图（如果不存在）
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echo "Creating LightRAG graph..."
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if su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -tAc \"SELECT 1 FROM ag_catalog.ag_graph WHERE name='lightrag'\"" | grep -q 1; then
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echo "Graph 'lightrag' already exists"
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else
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"SELECT ag_catalog.create_graph('lightrag');\""
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echo "Graph 'lightrag' created successfully"
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fi
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echo "Creating LightRAG application tables..."
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# 创建 LightRAG 需要的基础表
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echo "Creating lightrag_kv_store table..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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CREATE TABLE IF NOT EXISTS lightrag_kv_store (
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key VARCHAR PRIMARY KEY,
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value JSONB,
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created_at TIMESTAMP DEFAULT NOW(),
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updated_at TIMESTAMP DEFAULT NOW()
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);
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\""
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echo "Creating lightrag_doc_status table..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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CREATE TABLE IF NOT EXISTS lightrag_doc_status (
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doc_id VARCHAR PRIMARY KEY,
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status VARCHAR NOT NULL,
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metadata JSONB,
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created_at TIMESTAMP DEFAULT NOW(),
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updated_at TIMESTAMP DEFAULT NOW()
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);
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\""
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echo "Creating indexes for performance optimization..."
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# 为应用表创建索引
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echo "Creating KV store indexes..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_lightrag_kv_store_updated_at ON lightrag_kv_store(updated_at);
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\""
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echo "Creating doc status indexes..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_lightrag_doc_status_status ON lightrag_doc_status(status);
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CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_lightrag_doc_status_updated_at ON lightrag_doc_status(updated_at);
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\""
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# 等待图表创建完成后创建 AGE 相关索引
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echo "Waiting for graph tables to be fully initialized..."
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sleep 15
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# 验证 AGE 扩展是否正确加载
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echo "Verifying AGE extension is working..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"SELECT ag_catalog.create_graph('test_graph'); SELECT ag_catalog.drop_graph('test_graph', true);\"" || echo "AGE extension verification failed, but continuing..."
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echo "Creating AGE performance indexes..."
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# 检查并创建 Entity 表索引
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echo "Creating Entity table indexes..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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DO \$\$
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BEGIN
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-- Entity 表索引
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IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_schema = 'lightrag' AND table_name = 'Entity') THEN
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PERFORM 1;
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-- 主键索引通常自动创建，这里创建其他有用的索引
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = 'Entity' AND indexname = 'entity_node_id_gin_idx') THEN
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CREATE INDEX CONCURRENTLY entity_node_id_gin_idx ON lightrag.\\\"Entity\\\" USING gin(properties);
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END IF;
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END IF;
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EXCEPTION
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WHEN OTHERS THEN
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RAISE NOTICE 'Entity table not ready yet, skipping indexes';
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END
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\$\$;
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\""
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# 检查并创建 DIRECTED 关系表索引
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echo "Creating DIRECTED relationship indexes..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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DO \$\$
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BEGIN
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-- DIRECTED 关系表索引
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IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_schema = 'lightrag' AND table_name = 'DIRECTED') THEN
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = 'DIRECTED' AND indexname = 'directed_eid_idx') THEN
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CREATE INDEX CONCURRENTLY directed_eid_idx ON lightrag.\\\"DIRECTED\\\" (end_id);
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END IF;
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = 'DIRECTED' AND indexname = 'directed_sid_idx') THEN
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CREATE INDEX CONCURRENTLY directed_sid_idx ON lightrag.\\\"DIRECTED\\\" (start_id);
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END IF;
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = 'DIRECTED' AND indexname = 'directed_seid_idx') THEN
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CREATE INDEX CONCURRENTLY directed_seid_idx ON lightrag.\\\"DIRECTED\\\" (start_id, end_id);
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END IF;
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END IF;
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EXCEPTION
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WHEN OTHERS THEN
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RAISE NOTICE 'DIRECTED table not ready yet, skipping indexes';
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END
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\$\$;
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\""
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# 检查并创建 Edge 表索引
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echo "Creating Edge table indexes..."
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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DO \$\$
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BEGIN
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-- Edge 表索引
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IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_schema = 'lightrag' AND table_name = '_ag_label_edge') THEN
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = '_ag_label_edge' AND indexname = 'edge_sid_idx') THEN
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CREATE INDEX CONCURRENTLY edge_sid_idx ON lightrag.\\\"_ag_label_edge\\\" (start_id);
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END IF;
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = '_ag_label_edge' AND indexname = 'edge_eid_idx') THEN
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CREATE INDEX CONCURRENTLY edge_eid_idx ON lightrag.\\\"_ag_label_edge\\\" (end_id);
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END IF;
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IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE schemaname = 'lightrag' AND tablename = '_ag_label_edge' AND indexname = 'edge_seid_idx') THEN
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CREATE INDEX CONCURRENTLY edge_seid_idx ON lightrag.\\\"_ag_label_edge\\\" (start_id, end_id);
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END IF;
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END IF;
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EXCEPTION
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WHEN OTHERS THEN
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RAISE NOTICE 'Edge table not ready yet, skipping indexes';
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END
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\$\$;
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\""
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echo "Setting up permissions..."
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# 授权给 lightrag 用户
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA public TO ${POSTGRES_USER:-lightrag};
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GRANT ALL PRIVILEGES ON ALL SEQUENCES IN SCHEMA public TO ${POSTGRES_USER:-lightrag};
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GRANT ALL PRIVILEGES ON ALL FUNCTIONS IN SCHEMA public TO ${POSTGRES_USER:-lightrag};
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GRANT USAGE ON SCHEMA public TO ${POSTGRES_USER:-lightrag};
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\""
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# 为 AGE 图授权
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su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
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GRANT ALL PRIVILEGES ON SCHEMA lightrag TO ${POSTGRES_USER:-lightrag};
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GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA lightrag TO ${POSTGRES_USER:-lightrag};
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GRANT ALL PRIVILEGES ON ALL SEQUENCES IN SCHEMA lightrag TO ${POSTGRES_USER:-lightrag};
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GRANT USAGE ON SCHEMA lightrag TO ${POSTGRES_USER:-lightrag};
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\""
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echo "Applying PostgreSQL performance configuration..."
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# 应用性能配置
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su - postgres -c "psql -c \"ALTER SYSTEM SET shared_preload_libraries = 'age';\""
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su - postgres -c "psql -c \"ALTER SYSTEM SET max_connections = 200;\""
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su - postgres -c "psql -c \"ALTER SYSTEM SET shared_buffers = '256MB';\""
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su - postgres -c "psql -c \"ALTER SYSTEM SET effective_cache_size = '1GB';\""
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su - postgres -c "psql -c \"ALTER SYSTEM SET maintenance_work_mem = '64MB';\""
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su - postgres -c "psql -c \"ALTER SYSTEM SET random_page_cost = 1.1;\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET effective_io_concurrency = 200;\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET work_mem = '8MB';\""
|
||||
|
||||
# 连接和查询超时配置
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET statement_timeout = '300000';\"" # 5分钟查询超时
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET idle_in_transaction_session_timeout = '600000';\"" # 10分钟事务超时
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET tcp_keepalives_idle = '600';\"" # TCP keepalive 设置
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET tcp_keepalives_interval = '30';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET tcp_keepalives_count = '3';\""
|
||||
|
||||
# 查询优化配置
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET max_parallel_workers_per_gather = '2';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET max_parallel_workers = '4';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET enable_parallel_hash = 'on';\""
|
||||
|
||||
# 内存和查询限制优化
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET temp_buffers = '16MB';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET max_stack_depth = '2MB';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET huge_pages = 'try';\""
|
||||
|
||||
# 启用查询计划缓存和日志记录
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET plan_cache_mode = 'auto';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET log_statement = 'all';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET log_duration = 'on';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET log_min_duration_statement = '1000';\"" # 记录超过1秒的查询
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET log_disconnections = 'on';\""
|
||||
su - postgres -c "psql -c \"ALTER SYSTEM SET log_connections = 'on';\""
|
||||
|
||||
# 重新加载配置
|
||||
su - postgres -c "psql -c \"SELECT pg_reload_conf();\""
|
||||
|
||||
echo "Restarting PostgreSQL to apply configuration changes..."
|
||||
service postgresql restart
|
||||
sleep 5
|
||||
|
||||
echo "Verifying setup..."
|
||||
|
||||
# 验证扩展
|
||||
echo "Installed extensions:"
|
||||
su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"\\dx\""
|
||||
|
||||
# 验证图
|
||||
echo "Available graphs:"
|
||||
su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"SELECT name FROM ag_catalog.ag_graph;\""
|
||||
|
||||
# 验证表
|
||||
echo "Created tables:"
|
||||
su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
|
||||
SELECT schemaname, tablename
|
||||
FROM pg_tables
|
||||
WHERE schemaname IN ('public', 'lightrag')
|
||||
ORDER BY schemaname, tablename;
|
||||
\""
|
||||
|
||||
# 验证索引
|
||||
echo "Created indexes:"
|
||||
su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
|
||||
SELECT schemaname, tablename, indexname, indexdef
|
||||
FROM pg_indexes
|
||||
WHERE schemaname IN ('public', 'lightrag')
|
||||
ORDER BY schemaname, tablename, indexname;
|
||||
\""
|
||||
|
||||
# 测试连接
|
||||
echo "Testing database connection..."
|
||||
export PGPASSWORD="${POSTGRES_PASSWORD:-lightrag}"
|
||||
if PGPASSWORD="${POSTGRES_PASSWORD:-lightrag}" psql -h localhost -p 5432 -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c "SELECT version();" > /dev/null 2>&1; then
|
||||
echo "✅ Database connection test successful!"
|
||||
else
|
||||
echo "❌ Database connection test failed!"
|
||||
echo "Checking pg_hba.conf..."
|
||||
cat $PG_HBA_CONF | head -20
|
||||
echo "Checking PostgreSQL logs..."
|
||||
tail -20 /var/log/postgresql/postgresql-16-main.log
|
||||
fi
|
||||
|
||||
echo "✅ PostgreSQL setup completed successfully!"
|
||||
echo "Database: ${POSTGRES_DATABASE:-lightrag}"
|
||||
echo "User: ${POSTGRES_USER:-lightrag}"
|
||||
echo "Extensions: vector, age"
|
||||
echo "Graph: lightrag"
|
||||
echo "Tables: lightrag_kv_store, lightrag_doc_status + AGE graph tables"
|
||||
echo "Connection: postgresql://${POSTGRES_USER:-lightrag}:***@localhost:5432/${POSTGRES_DATABASE:-lightrag}"
|
||||
|
||||
# 最终验证数据库完全准备就绪
|
||||
echo "Performing final readiness check..."
|
||||
sleep 5
|
||||
if PGPASSWORD="${POSTGRES_PASSWORD:-lightrag}" psql -h localhost -p 5432 -U ${POSTGRES_USER:-lightrag} -d ${POSTGRES_DATABASE:-lightrag} -c "SELECT ag_catalog.create_graph('final_test'); SELECT ag_catalog.drop_graph('final_test', true);" > /dev/null 2>&1; then
|
||||
echo "✅ Database is fully ready for LightRAG operations!"
|
||||
else
|
||||
echo "⚠️ Database basic operations work, but AGE may need more time to be fully ready"
|
||||
fi
|
||||
|
||||
# 显示数据库统计信息
|
||||
echo "Database statistics:"
|
||||
su - postgres -c "psql -d ${POSTGRES_DATABASE:-lightrag} -c \"
|
||||
SELECT
|
||||
schemaname,
|
||||
COUNT(*) as table_count
|
||||
FROM pg_tables
|
||||
WHERE schemaname IN ('public', 'lightrag')
|
||||
GROUP BY schemaname;
|
||||
\""
|
||||
|
||||
# 保持容器运行并显示日志
|
||||
echo "PostgreSQL is ready for connections on port 5432"
|
||||
tail -f /var/log/postgresql/postgresql-16-main.log
|
||||
@ -1,72 +0,0 @@
|
||||
-- LightRAG PostgreSQL 初始化脚本
|
||||
-- 基于官方文档建议: https://github.com/HKUDS/LightRAG
|
||||
|
||||
-- 创建必要的扩展
|
||||
CREATE EXTENSION IF NOT EXISTS vector;
|
||||
CREATE EXTENSION IF NOT EXISTS age;
|
||||
|
||||
-- 加载 AGE 扩展
|
||||
LOAD 'age';
|
||||
|
||||
-- 设置搜索路径
|
||||
SET search_path = ag_catalog, "$user", public;
|
||||
|
||||
-- 创建 LightRAG 图（如果不存在）
|
||||
-- 注意：这里使用 'lightrag' 作为图名，可以根据需要修改
|
||||
SELECT create_graph('lightrag');
|
||||
|
||||
-- 为 AGE 创建索引以提高性能
|
||||
-- 替换下面的 'lightrag' 为您的实际图名
|
||||
|
||||
-- Entity 表索引
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS entity_p_idx ON lightrag."Entity" (id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS entity_idx_node_id ON lightrag."Entity" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS entity_node_id_gin_idx ON lightrag."Entity" using gin(properties);
|
||||
|
||||
-- Vertex 表索引
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS vertex_p_idx ON lightrag."_ag_label_vertex" (id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS vertex_idx_node_id ON lightrag."_ag_label_vertex" (ag_catalog.agtype_access_operator(properties, '"node_id"'::agtype));
|
||||
|
||||
-- DIRECTED 关系表索引
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS directed_p_idx ON lightrag."DIRECTED" (id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS directed_eid_idx ON lightrag."DIRECTED" (end_id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS directed_sid_idx ON lightrag."DIRECTED" (start_id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS directed_seid_idx ON lightrag."DIRECTED" (start_id,end_id);
|
||||
|
||||
-- Edge 表索引
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS edge_p_idx ON lightrag."_ag_label_edge" (id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS edge_sid_idx ON lightrag."_ag_label_edge" (start_id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS edge_eid_idx ON lightrag."_ag_label_edge" (end_id);
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS edge_seid_idx ON lightrag."_ag_label_edge" (start_id,end_id);
|
||||
|
||||
-- 集群表以提高性能
|
||||
ALTER TABLE lightrag."DIRECTED" CLUSTER ON directed_sid_idx;
|
||||
|
||||
-- 创建 LightRAG 需要的基础表（如果使用 PostgreSQL 作为 KV store）
|
||||
CREATE TABLE IF NOT EXISTS lightrag_kv_store (
|
||||
key VARCHAR PRIMARY KEY,
|
||||
value JSONB,
|
||||
created_at TIMESTAMP DEFAULT NOW(),
|
||||
updated_at TIMESTAMP DEFAULT NOW()
|
||||
);
|
||||
|
||||
-- 创建索引
|
||||
CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_lightrag_kv_store_updated_at ON lightrag_kv_store(updated_at);
|
||||
|
||||
-- 创建文档状态表
|
||||
CREATE TABLE IF NOT EXISTS lightrag_doc_status (
|
||||
doc_id VARCHAR PRIMARY KEY,
|
||||
status VARCHAR NOT NULL,
|
||||
metadata JSONB,
|
||||
created_at TIMESTAMP DEFAULT NOW(),
|
||||
updated_at TIMESTAMP DEFAULT NOW()
|
||||
);
|
||||
|
||||
-- 授权给 lightrag 用户
|
||||
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA public TO lightrag;
|
||||
GRANT ALL PRIVILEGES ON ALL SEQUENCES IN SCHEMA public TO lightrag;
|
||||
GRANT ALL PRIVILEGES ON ALL FUNCTIONS IN SCHEMA public TO lightrag;
|
||||
|
||||
-- 为 AGE 图授权
|
||||
GRANT ALL PRIVILEGES ON SCHEMA lightrag TO lightrag;
|
||||
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA lightrag TO lightrag;
|
||||
@ -10,7 +10,6 @@ dependencies = [
|
||||
"dashscope>=1.23.2",
|
||||
"docx2txt>=0.9",
|
||||
"fastapi>=0.115.12",
|
||||
"graspologic>=3.3.0",
|
||||
"langchain-community>=0.3.22",
|
||||
"langchain-deepseek>=0.1.3",
|
||||
"langchain-huggingface>=0.2.0",
|
||||
@ -42,7 +41,6 @@ dependencies = [
|
||||
"tavily-python>=0.7.0",
|
||||
"unstructured>=0.17.2",
|
||||
"uvicorn[standard]>=0.34.2",
|
||||
"zhipuai>=2.1.5.20250421",
|
||||
]
|
||||
[tool.ruff]
|
||||
line-length = 210 # 代码最大行宽
|
||||
@ -59,11 +57,3 @@ dev = [
|
||||
"ruff>=0.12.1",
|
||||
"vllm>=0.8.5.post1",
|
||||
]
|
||||
|
||||
# uv 配置 - 使用清华大学镜像源
|
||||
[tool.uv]
|
||||
index-url = "https://pypi.tuna.tsinghua.edu.cn/simple/"
|
||||
extra-index-url = [
|
||||
"https://mirrors.aliyun.com/pypi/simple/",
|
||||
"https://pypi.douban.com/simple/"
|
||||
]
|
||||
|
||||
@ -1,8 +1,4 @@
|
||||
import json
|
||||
import os
|
||||
import asyncio
|
||||
import traceback
|
||||
from typing import List, Dict, Any, Optional
|
||||
from fastapi import APIRouter, Query, HTTPException, Depends
|
||||
from server.utils.auth_middleware import get_admin_user
|
||||
from server.models.user_model import User
|
||||
@ -23,13 +19,13 @@ async def get_subgraph(
|
||||
):
|
||||
"""
|
||||
使用 LightRAG 原生方法获取知识图谱子图
|
||||
|
||||
|
||||
Args:
|
||||
db_id: LightRAG 数据库实例ID
|
||||
node_label: 节点标签，用于查找起始节点，使用 "*" 获取全图
|
||||
max_depth: 子图的最大深度
|
||||
max_nodes: 返回的最大节点数量
|
||||
|
||||
|
||||
Returns:
|
||||
包含节点和边的知识图谱数据
|
||||
"""
|
||||
@ -95,10 +91,10 @@ async def get_graph_labels(
|
||||
):
|
||||
"""
|
||||
获取知识图谱中的所有标签
|
||||
|
||||
|
||||
Args:
|
||||
db_id: LightRAG 数据库实例ID
|
||||
|
||||
|
||||
Returns:
|
||||
图谱中所有可用的标签列表
|
||||
"""
|
||||
@ -132,7 +128,7 @@ async def get_available_databases(
|
||||
):
|
||||
"""
|
||||
获取所有可用的 LightRAG 数据库
|
||||
|
||||
|
||||
Returns:
|
||||
可用的数据库列表
|
||||
"""
|
||||
|
||||
@ -7,7 +7,7 @@ from neo4j import GraphDatabase as GD
|
||||
from neo4j import Query
|
||||
|
||||
from src import config
|
||||
from src.models.embedding import get_embedding_model
|
||||
from src.models import select_embedding_model
|
||||
from src.utils import logger
|
||||
|
||||
warnings.filterwarnings("ignore", category=UserWarning)
|
||||
@ -22,7 +22,7 @@ class GraphDatabase:
|
||||
self.status = "closed"
|
||||
self.kgdb_name = "neo4j"
|
||||
self.embed_model_name = os.getenv("GRAPH_EMBED_MODEL_NAME") or "siliconflow/BAAI/bge-m3"
|
||||
self.embed_model = get_embedding_model(self.embed_model_name)
|
||||
self.embed_model = select_embedding_model(self.embed_model_name)
|
||||
self.work_dir = os.path.join(config.save_dir, "knowledge_graph", self.kgdb_name)
|
||||
os.makedirs(self.work_dir, exist_ok=True)
|
||||
|
||||
@ -590,9 +590,11 @@ class GraphDatabase:
|
||||
source_id = source.element_id
|
||||
target_id = target.element_id
|
||||
|
||||
assert node_dict is not None, "node_dict is required"
|
||||
source_name = node_dict[source_id]["name"] if source_name is None else source_name
|
||||
target_name = node_dict[target_id]["name"] if target_name is None else target_name
|
||||
# 如果没有提供 source_name 或 target_name，则需要 node_dict
|
||||
if source_name is None or target_name is None:
|
||||
assert node_dict is not None, "node_dict is required when source_name or target_name is None"
|
||||
source_name = node_dict[source_id]["name"] if source_name is None else source_name
|
||||
target_name = node_dict[target_id]["name"] if target_name is None else target_name
|
||||
|
||||
relationship_type = relationship._properties.get("type", "unknown")
|
||||
if relationship_type == "unknown":
|
||||
|
||||
@ -92,11 +92,12 @@ class LightRagBasedKB:
|
||||
# 使用配置的 LLM 和 embedding 函数
|
||||
rag = LightRAG(
|
||||
working_dir=working_dir,
|
||||
workspace=db_id,
|
||||
llm_model_func=self._get_llm_func(llm_info),
|
||||
embedding_func=self._get_embedding_func(embed_info),
|
||||
vector_storage="MilvusVectorDBStorage",
|
||||
kv_storage="JsonKVStorage",
|
||||
graph_storage="PGGraphStorage",
|
||||
graph_storage="Neo4JStorage",
|
||||
doc_status_storage="JsonDocStatusStorage",
|
||||
log_file_path=os.path.join(self.work_dir, db_id, "lightrag.log"),
|
||||
)
|
||||
@ -127,16 +128,16 @@ class LightRagBasedKB:
|
||||
# provider_info = config.model_names[llm_info.get("provider")]
|
||||
# api_key = os.getenv(provider_info.get("env")[0] or "OPENAI_API_KEY") or "no_api_key"
|
||||
# base_url = get_docker_safe_url(provider_info.get("base_url", "http://localhost:8081/v1"))
|
||||
from src.models import get_custom_model
|
||||
llm_info = get_custom_model("qwen3:32b-RFnC")
|
||||
from src.models import select_model
|
||||
model = select_model("dashscope", "qwen-max-latest")
|
||||
async def llm_model_func(prompt, system_prompt=None, history_messages=[], **kwargs):
|
||||
return await openai_complete_if_cache(
|
||||
llm_info.get("name", "qwen3-1.7b"),
|
||||
prompt,
|
||||
model=model.model_name,
|
||||
prompt=prompt,
|
||||
system_prompt=system_prompt,
|
||||
history_messages=history_messages,
|
||||
api_key=llm_info.get("api_key"),
|
||||
base_url=get_docker_safe_url(llm_info.get("api_base")),
|
||||
api_key=model.api_key,
|
||||
base_url=model.base_url,
|
||||
extra_body={"enable_thinking": False},
|
||||
**kwargs,
|
||||
)
|
||||
@ -144,16 +145,16 @@ class LightRagBasedKB:
|
||||
|
||||
def _get_embedding_func(self, embed_info: dict):
|
||||
"""获取 embedding 函数"""
|
||||
api_key = os.getenv(embed_info.get("api_key", "OPENAI_API_KEY")) or "no_api_key"
|
||||
base_url = embed_info.get("base_url", "http://localhost:8081/v1").replace("/embeddings", "")
|
||||
from src.models import select_embedding_model
|
||||
model = select_embedding_model("siliconflow/BAAI/bge-m3")
|
||||
return EmbeddingFunc(
|
||||
embedding_dim=embed_info.get("dimension") or 1024,
|
||||
embedding_dim=model.dimension,
|
||||
max_token_size=4096,
|
||||
func=lambda texts: openai_embed(
|
||||
texts=texts,
|
||||
model=embed_info.get("model_name") or "Qwen3-Embedding-0.6B",
|
||||
api_key=api_key,
|
||||
base_url=get_docker_safe_url(base_url)
|
||||
model=model.model,
|
||||
api_key=model.api_key,
|
||||
base_url=model.base_url.replace("/embeddings", ""),
|
||||
),
|
||||
)
|
||||
|
||||
@ -335,7 +336,8 @@ class LightRagBasedKB:
|
||||
# 根据内容类型处理内容
|
||||
if content_type == "file":
|
||||
markdown_content = await self._process_file_to_markdown(item, params=params)
|
||||
logger.info(f"Markdown content: {markdown_content[:100].replace('\n', ' ')}...")
|
||||
markdown_content_lines = markdown_content[:100].replace('\n', ' ')
|
||||
logger.info(f"Markdown content: {markdown_content_lines}...")
|
||||
else: # URL
|
||||
markdown_content = await self._process_url_to_markdown(item, params=params)
|
||||
|
||||
|
||||
@ -4,6 +4,7 @@ import traceback
|
||||
from src import config
|
||||
from src.utils.logging_config import logger
|
||||
from src.models.chat_model import OpenAIBase
|
||||
from src.models.embedding import OllamaEmbedding, OtherEmbedding
|
||||
|
||||
def select_model(model_provider, model_name=None):
|
||||
"""根据模型提供者选择模型"""
|
||||
@ -38,6 +39,24 @@ def select_model(model_provider, model_name=None):
|
||||
except Exception as e:
|
||||
raise ValueError(f"Model provider {model_provider} load failed, {e} \n {traceback.format_exc()}")
|
||||
|
||||
|
||||
def select_embedding_model(model_id):
|
||||
provider, model_name = model_id.split('/', 1) if model_id else ("", "")
|
||||
support_embed_models = config.embed_model_names.keys()
|
||||
assert model_id in support_embed_models, f"Unsupported embed model: {model_id}, only support {support_embed_models}"
|
||||
logger.debug(f"Loading embedding model {model_id}")
|
||||
if provider == "local":
|
||||
raise ValueError("Local embedding model is not supported, please use other embedding models")
|
||||
|
||||
elif provider == "ollama":
|
||||
model = OllamaEmbedding(model_id)
|
||||
|
||||
else:
|
||||
model = OtherEmbedding(model_id)
|
||||
|
||||
return model
|
||||
|
||||
|
||||
def get_custom_model(model_id):
|
||||
"""return model_info"""
|
||||
assert config.custom_models is not None, "custom_models is not set"
|
||||
|
||||
@ -3,7 +3,6 @@ import json
|
||||
import requests
|
||||
import asyncio
|
||||
from abc import abstractmethod
|
||||
from zhipuai import ZhipuAI
|
||||
from langchain_huggingface import HuggingFaceEmbeddings
|
||||
|
||||
from src import config
|
||||
@ -19,6 +18,7 @@ class BaseEmbeddingModel:
|
||||
self.model = self.info["name"]
|
||||
self.dimension = self.info.get("dimension", None)
|
||||
self.url = get_docker_safe_url(self.info["base_url"])
|
||||
self.base_url = get_docker_safe_url(self.info["base_url"])
|
||||
self.api_key = os.getenv(self.info["api_key"], self.info["api_key"])
|
||||
|
||||
@abstractmethod
|
||||
@ -110,19 +110,3 @@ class OtherEmbedding(BaseEmbeddingModel):
|
||||
"model": self.model,
|
||||
"input": message,
|
||||
}
|
||||
|
||||
def get_embedding_model(model_id):
|
||||
provider, model_name = model_id.split('/', 1) if model_id else ("", "")
|
||||
support_embed_models = config.embed_model_names.keys()
|
||||
assert model_id in support_embed_models, f"Unsupported embed model: {model_id}, only support {support_embed_models}"
|
||||
logger.debug(f"Loading embedding model {model_id}")
|
||||
if provider == "local":
|
||||
raise ValueError("Local embedding model is not supported, please use other embedding models")
|
||||
|
||||
elif provider == "ollama":
|
||||
model = OllamaEmbedding(model_id)
|
||||
|
||||
else:
|
||||
model = OtherEmbedding(model_id)
|
||||
|
||||
return model
|
||||
|
||||
@ -47,19 +47,19 @@ export const useGraphStore = defineStore('graph', {
|
||||
// 首先尝试通过dynamicId匹配
|
||||
let foundEdge = state.rawGraph.edges.find(edge => edge.dynamicId === state.selectedEdge)
|
||||
if (foundEdge) return foundEdge
|
||||
|
||||
|
||||
// 如果没找到，尝试通过原始ID匹配
|
||||
foundEdge = state.rawGraph.edges.find(edge => edge.id === state.selectedEdge)
|
||||
if (foundEdge) return foundEdge
|
||||
|
||||
|
||||
// 最后尝试通过source->target格式匹配
|
||||
const [source, target] = state.selectedEdge.split('->')
|
||||
if (source && target) {
|
||||
foundEdge = state.rawGraph.edges.find(edge =>
|
||||
foundEdge = state.rawGraph.edges.find(edge =>
|
||||
edge.source === source.trim() && edge.target === target.trim()
|
||||
)
|
||||
}
|
||||
|
||||
|
||||
return foundEdge || null
|
||||
},
|
||||
|
||||
@ -200,7 +200,7 @@ export const useGraphStore = defineStore('graph', {
|
||||
const nodeId = String(node.id)
|
||||
const labels = node.labels || [node.entity_type || 'unknown']
|
||||
const entityType = node.entity_type || labels[0] || 'unknown'
|
||||
|
||||
|
||||
const processedNode = {
|
||||
id: nodeId,
|
||||
labels: Array.isArray(labels) ? labels.map(String) : [String(labels)],
|
||||
@ -246,10 +246,10 @@ export const useGraphStore = defineStore('graph', {
|
||||
const sourceId = String(edge.source)
|
||||
const targetId = String(edge.target)
|
||||
const dynamicId = `${sourceId}-${targetId}-${index}`
|
||||
|
||||
|
||||
// 适配新的LightRAG API格式
|
||||
const weight = Number(edge.properties?.weight || edge.weight || 1.0)
|
||||
|
||||
|
||||
const processedEdge = {
|
||||
id: String(edge.id),
|
||||
source: sourceId,
|
||||
@ -345,7 +345,7 @@ export const useGraphStore = defineStore('graph', {
|
||||
try {
|
||||
// 使用动态ID作为Sigma边ID，避免重复
|
||||
const sigmaEdgeId = edge.dynamicId || `${edge.source}->${edge.target}`
|
||||
|
||||
|
||||
// 检查是否已存在相同的边
|
||||
if (!sigmaGraph.hasEdge(sigmaEdgeId)) {
|
||||
sigmaGraph.addEdgeWithKey(sigmaEdgeId, String(edge.source), String(edge.target), edgeAttributes)
|
||||
|
||||
@ -289,20 +289,6 @@
|
||||
<a-input-number size="small" v-model:value="meta.top_k" :min="1" :max="100" />
|
||||
</div>
|
||||
</div>
|
||||
<div class="params-group">
|
||||
<div class="params-item">
|
||||
<p>片段最大Token数：</p>
|
||||
<a-input-number size="small" v-model:value="meta.max_token_for_text_unit" :min="1" :max="4000" />
|
||||
</div>
|
||||
<div class="params-item">
|
||||
<p>关系描述最大Token数：</p>
|
||||
<a-input-number size="small" v-model:value="meta.max_token_for_global_context" :min="1" :max="4000" />
|
||||
</div>
|
||||
<div class="params-item">
|
||||
<p>实体描述最大Token数：</p>
|
||||
<a-input-number size="small" v-model:value="meta.max_token_for_local_context" :min="1" :max="4000" />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sider-bottom">
|
||||
@ -314,8 +300,8 @@
|
||||
<a-tab-pane key="knowledge-graph" force-render>
|
||||
<template #tab><span><Waypoints size="14" class="mr-3 bn-1px" />知识图谱（开发中）</span></template>
|
||||
<div class="knowledge-graph-container db-tab-container">
|
||||
<KnowledgeGraphViewer
|
||||
:initial-database-id="databaseId"
|
||||
<KnowledgeGraphViewer
|
||||
:initial-database-id="databaseId"
|
||||
:hide-db-selector="true"
|
||||
/>
|
||||
</div>
|
||||
@ -396,9 +382,6 @@ const meta = reactive({
|
||||
only_need_context: true,
|
||||
only_need_prompt: false,
|
||||
top_k: 10,
|
||||
max_token_for_text_unit: 4000,
|
||||
max_token_for_global_context: 4000,
|
||||
max_token_for_local_context: 4000,
|
||||
});
|
||||
|
||||
const enable_ocr_options = ref([
|
||||
@ -1541,10 +1524,10 @@ const toggleAutoRefresh = (checked) => {
|
||||
|
||||
.knowledge-graph-container {
|
||||
height: calc(100vh - 200px);
|
||||
|
||||
|
||||
:deep(.knowledge-graph-viewer) {
|
||||
height: 100%;
|
||||
|
||||
|
||||
.sigma-container {
|
||||
height: calc(100% - 80px);
|
||||
}
|
||||
|
||||
@ -231,9 +231,9 @@ const onSearch = () => {
|
||||
// return
|
||||
// }
|
||||
|
||||
if (!confirm(`构建图数据库时向量模型为 ${graphInfo?.value?.embed_model_name}，当前向量模型为 ${cur_embed_model.value}，是否继续查询？`)) {
|
||||
return
|
||||
}
|
||||
// if (!confirm(`构建图数据库时向量模型为 ${graphInfo?.value?.embed_model_name}，当前向量模型为 ${cur_embed_model.value}，是否继续查询？`)) {
|
||||
// return
|
||||
// }
|
||||
}
|
||||
|
||||
if (!state.searchInput) {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user