146 lines
4.2 KiB
Bash
Executable File
146 lines
4.2 KiB
Bash
Executable File
#!/bin/bash
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# 任务名称：微信用户反馈每分钟同步到收集表格
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# 执行时间：* * * * * 每分钟执行
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# 归属 Agent：小葵 xiaokui
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set +e
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# 环境配置
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export PATH=/root/.nvm/versions/node/v24.14.0/bin:$PATH
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LOG_FILE="/var/log/sync_wechat_feedback.log"
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WORKSPACE="/root/.openclaw/workspace-xiaokui"
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LAST_SYNC_ID_FILE="$WORKSPACE/data/last_wechat_sync_id"
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TMP_DATA="$WORKSPACE/tmp/wechat_feedback.json"
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# 数据库配置
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DB_HOST="bj-cdb-8frbdwju.sql.tencentcdb.com"
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DB_PORT="25413"
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DB_USER="read_only"
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DB_PASS="fdsfiidier^\$*hjfdijjd232"
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DB_NAME="vala_test"
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# 目标表格配置
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TARGET_SPREADSHEET_TOKEN="AOxbsifk3hybRZteGowcMxNnnqc"
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TARGET_SHEET_ID="f17380"
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log() {
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echo "[$(date +'%Y-%m-%d %H:%M:%S')] $1" >> "$LOG_FILE"
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}
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# 初始化上次同步ID
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if [ ! -f "$LAST_SYNC_ID_FILE" ]; then
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echo "0" > "$LAST_SYNC_ID_FILE"
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fi
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LAST_SYNC_ID=$(cat "$LAST_SYNC_ID_FILE")
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log "=== 微信反馈同步任务开始 ==="
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log "上次同步最大ID：$LAST_SYNC_ID"
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# 1. 读取微信新增反馈数据
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log "读取微信新增反馈数据..."
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mysql -h "$DB_HOST" -P "$DB_PORT" -u "$DB_USER" -p"$DB_PASS" "$DB_NAME" -N -e "
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SELECT id, msg_time, sender_name, msg_type, content
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FROM wechat_group_message
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WHERE id > $LAST_SYNC_ID
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ORDER BY msg_time DESC;" > /tmp/wechat_raw.txt
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if [ ! -s /tmp/wechat_raw.txt ]; then
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log "无新增微信反馈数据，退出"
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exit 0
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fi
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# 2. 转换为表格格式
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log "转换数据格式..."
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NEW_DATA=$(awk '
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BEGIN {
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print "["
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first = 1
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}
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{
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if (first == 0) print ","
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first = 0
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id = $1
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time = $2 " " $3
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sender = $4
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type = $5
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content = substr($0, index($0,$6))
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# 处理字段
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text = ""
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image = ""
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video = ""
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if (type == "text") {
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text = content
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} else if (type == "image") {
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image = content
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} else if (type == "video") {
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video = content
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} else {
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text = "[" type "] " content
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}
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gsub(/"/, "\\\"", text)
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gsub(/"/, "\\\"", image)
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gsub(/"/, "\\\"", video)
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printf "[\"\", \"\", \"\", \"\", \"%s\", \"微信\", \"%s\", \"\", \"\", \"%s\", \"%s\", \"%s\", \"\", \"待确认\", \"\"]", time, sender, text, image, video
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}
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END {
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print "\n]"
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}' /tmp/wechat_raw.txt)
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NEW_COUNT=$(echo "$NEW_DATA" | jq length)
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NEW_MAX_ID=$(tail -1 /tmp/wechat_raw.txt | awk '{print $1}')
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log "发现 $NEW_COUNT 条新增微信反馈数据，最大ID：$NEW_MAX_ID"
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# 3. 读取目标表格现有数据（飞书+微信）
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log "读取目标表格现有数据..."
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TARGET_RAW=$(LARKSUITE_CLI_CONFIG_DIR=/root/.openclaw/credentials/xiaoyan lark-cli sheets +read --spreadsheet-token "$TARGET_SPREADSHEET_TOKEN" --range "$TARGET_SHEET_ID!A2:O" --as bot)
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TARGET_DATA=$(echo "$TARGET_RAW" | jq '.data.valueRange.values | map(select(.[0] != null and .[0] != ""))')
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if [ "$TARGET_DATA" == "null" ] || [ -z "$TARGET_DATA" ]; then
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TARGET_DATA="[]"
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fi
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# 4. 合并数据并按时间倒序排列
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echo "$NEW_DATA" > /tmp/new.json
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echo "$TARGET_DATA" > /tmp/existing.json
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ALL_DATA=$(jq -s 'add | sort_by(.[4]) | reverse' /tmp/new.json /tmp/existing.json)
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# 5. 重新生成序号
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ALL_DATA=$(echo "$ALL_DATA" | jq 'to_entries | map(.value[0] = (.key + 1 | tostring) | .value)')
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echo "$ALL_DATA" > "$TMP_DATA"
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ROW_COUNT=$(echo "$ALL_DATA" | jq length)
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END_ROW=$((ROW_COUNT + 1))
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# 6. 清空目标表格并写入合并后的数据
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log "写入合并后的数据，共 $ROW_COUNT 条..."
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# 先清空原有数据
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EMPTY_DATA=$(printf '[]%.0s' {1..200} | jq -s '.')
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LARKSUITE_CLI_CONFIG_DIR=/root/.openclaw/credentials/xiaoyan lark-cli sheets +write \
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--spreadsheet-token "$TARGET_SPREADSHEET_TOKEN" \
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--range "$TARGET_SHEET_ID!A2:O201" \
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--values "$EMPTY_DATA" \
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--as bot >/dev/null 2>&1
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# 写入新数据
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LARKSUITE_CLI_CONFIG_DIR=/root/.openclaw/credentials/xiaoyan lark-cli sheets +write \
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--spreadsheet-token "$TARGET_SPREADSHEET_TOKEN" \
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--range "$TARGET_SHEET_ID!A2:O$END_ROW" \
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--values "$(cat $TMP_DATA)" \
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--as bot
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# 7. 更新上次同步ID
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echo "$NEW_MAX_ID" > "$LAST_SYNC_ID_FILE"
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log "✅ 同步完成：新增 $NEW_COUNT 条微信反馈，当前总记录数 $ROW_COUNT 条，已按时间倒序排列"
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# 清理临时文件
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rm -f /tmp/wechat_raw.txt /tmp/new.json /tmp/existing.json "$TMP_DATA"
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log "=== 同步任务完成 ==="
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exit 0
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