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#!/bin/bash
set -eo pipefail
# 导入环境变量
source /home/pn/.env
# 错误处理函数
handle_error() {
echo "错误发生在第 $1 行"
exit 1
}
trap 'handle_error $LINENO' ERR
# 超时处理函数
timeout_handler() {
echo "操作超时"
exit 1
}
# 等待服务就绪的通用函数
wait_for_service() {
local service=$1
local host=$2
local port=$3
local timeout=${4:-$WAIT_TIMEOUT}
echo "等待 $service 就绪..."
local end=$((SECONDS + timeout))
while [ $SECONDS -lt $end ]; do
if nc -z "$host" "$port" >/dev/null 2>&1; then
echo "$service 已就绪"
return 0
fi
echo "尝试连接 $service at $host:$port..."
sleep 1
done
echo "$service 启动超时"
exit 1
}
# 启动 Redis 服务
start_redis() {
echo "Starting Redis server..."
redis-server --daemonize yes
sleep 1
if ! redis-cli ping > /dev/null 2>&1; then
echo "Failed to start Redis server"
exit 1
fi
# 设置 Redis 配置
redis-cli config set maxmemory 512mb
redis-cli config set maxmemory-policy allkeys-lru
echo ""
echo "Redis server started successfully"
echo ""
}
# 启动 Qdrant 服务
start_qdrant() {
echo "Starting Qdrant server..."
# 确保目录存在并有正确的权限
mkdir -p /home/pn/.n8n/qdrant/storage
mkdir -p /home/pn/.n8n/qdrant/config
mkdir -p /home/pn/.n8n/qdrant/snapshots
mkdir -p /home/pn/.n8n/qdrant/logs
# 设置正确的权限
chmod -R 755 /home/pn/.n8n/qdrant
chown -R pn:pn /home/pn/.n8n/qdrant
# 创建 Qdrant 配置文件
cat > /home/pn/.n8n/qdrant/config/config.yaml <<EOF
service:
host: 0.0.0.0
http_port: 6333
grpc_port: 6334
enable_cors: true
enable_tls: false
max_request_size_mb: 64
max_workers: 0
storage:
storage_path: /home/pn/.n8n/qdrant/storage
snapshots_path: /home/pn/.n8n/qdrant/snapshots
on_disk_payload: true
performance:
max_search_threads: 0
max_optimization_threads: 0
optimizers:
deleted_threshold: 0.2
vacuum_min_vector_number: 1000
default_segment_number: 0
max_segment_size_kb: null
indexing_threshold_kb: 20000
flush_interval_sec: 5
hnsw_index:
m: 16
ef_construct: 100
full_scan_threshold_kb: 10000
max_indexing_threads: 0
on_disk: false
logger:
on_disk:
enabled: true
log_file: /home/pn/.n8n/qdrant/logs/qdrant.log
log_level: INFO
telemetry_disabled: true
EOF
# 确保配置文件有正确的权限
chmod 644 /home/pn/.n8n/qdrant/config/config.yaml
# 使用配置文件启动 Qdrant
qdrant --config-path /home/pn/.n8n/qdrant/config/config.yaml > /home/pn/.n8n/qdrant/logs/startup.log 2>&1 &
# 等待 Qdrant 启动
local timeout=30
local end=$((SECONDS + timeout))
while [ $SECONDS -lt $end ]; do
if curl -s http://localhost:6333/health >/dev/null; then
echo "Qdrant server started successfully"
# 输出版本和状态信息
echo "Qdrant version:"
curl -s http://localhost:6333/version
# 预创建常用集合
echo "Creating default collections..."
# 创建文本向量集合 (768维,适用于多数文本嵌入模型)
curl -X PUT 'http://localhost:6333/collections/text_vectors' \
-H 'Content-Type: application/json' \
-d '{
"vectors": {
"size": 768,
"distance": "Cosine"
},
"optimizers_config": {
"default_segment_number": 2,
"indexing_threshold": 20000
},
"hnsw_config": {
"m": 16,
"ef_construct": 100,
"full_scan_threshold": 10000
}
}'
# 创建图像向量集合 (512维,适用于多数图像嵌入模型)
curl -X PUT 'http://localhost:6333/collections/image_vectors' \
-H 'Content-Type: application/json' \
-d '{
"vectors": {
"size": 512,
"distance": "Cosine"
},
"optimizers_config": {
"default_segment_number": 2,
"indexing_threshold": 20000
},
"hnsw_config": {
"m": 16,
"ef_construct": 100,
"full_scan_threshold": 10000
}
}'
# 创建通用向量集合 (1536维,适用于 OpenAI 的嵌入模型)
curl -X PUT 'http://localhost:6333/collections/openai_vectors' \
-H 'Content-Type: application/json' \
-d '{
"vectors": {
"size": 1536,
"distance": "Cosine"
},
"optimizers_config": {
"default_segment_number": 2,
"indexing_threshold": 20000
},
"hnsw_config": {
"m": 16,
"ef_construct": 100,
"full_scan_threshold": 10000
}
}'
# 验证集合创建状态
echo -e "\nVerifying collections:"
curl -s http://localhost:6333/collections
return 0
fi
echo "Waiting for Qdrant to start..."
sleep 1
# 检查是否有错误日志
if grep -i "error" /home/pn/.n8n/qdrant/logs/startup.log >/dev/null 2>&1; then
echo "Error found in Qdrant logs:"
tail -n 10 /home/pn/.n8n/qdrant/logs/startup.log
fi
done
echo "Failed to start Qdrant server"
echo "Last 10 lines of Qdrant log:"
tail -n 10 /home/pn/.n8n/qdrant/logs/startup.log
exit 1
}
# 检查服务状态
check_services() {
echo "检查服务状态..."
# 检查 Redis
echo "Redis 状态:"
redis-cli info | grep 'used_memory\|connected_clients\|total_connections_received'
# 检查 Qdrant
echo "Qdrant 状态:"
if curl -s http://localhost:6333/metrics >/dev/null; then
echo "Qdrant 运行正常"
curl -s http://localhost:6333/metrics
# 显示集合信息
echo "Qdrant 集合列表:"
curl -s http://localhost:6333/collections
else
echo "Qdrant 服务异常"
tail -n 10 /home/pn/.n8n/qdrant/qdrant.log
fi
}
# 主流程
main() {
current_time=$(date +"%Y-%m-%d %H:%M:%S")
echo "Starting services at $current_time"
# 输出配置信息
echo "Database Configuration:"
echo "Host: ${DB_POSTGRESDB_HOST}"
echo "Port: ${DB_POSTGRESDB_PORT}"
echo "User: ${DB_POSTGRESDB_USER}"
echo "Database: ${DB_POSTGRESDB_DATABASE}"
echo "Type: ${DB_TYPE}"
# 启动服务
wait_for_service "PostgreSQL" "${DB_POSTGRESDB_HOST}" "${DB_POSTGRESDB_PORT}"
echo ""
start_redis
echo ""
start_qdrant
echo ""
check_services
# 设置 N8N 环境变量
source /home/pn/n8n/config/n8n_env.sh
echo ""
echo "Starting n8n..."
exec n8n start
}
# 执行主流程
main "$@"
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