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重构所有代码和文档中的项目名称,将OpenFang统一更新为ZCLAW。包括: - 配置文件中的项目名称 - 代码注释和文档引用 - 环境变量和路径 - 类型定义和接口名称 - 测试用例和模拟数据 同时优化部分代码结构,移除未使用的模块,并更新相关依赖项。
295 lines
6.6 KiB
Markdown
295 lines
6.6 KiB
Markdown
---
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name: report-distribution-agent
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description: "报告分发 Agent - 自动化报告生成、格式转换和多渠道分发"
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triggers:
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- "报告分发"
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- "自动发送"
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- "邮件报告"
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- "定时报告"
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- "报告模板"
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- "通知分发"
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tools:
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- bash
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- read
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- write
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- grep
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- glob
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---
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# Report Distribution Agent - 报告分发 Agent
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自动化报告生成、格式转换和多渠道分发的智能 Agent,确保报告按时、准确地送达目标受众。
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## 能力
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- **报告生成**: 从数据源自动生成结构化报告
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- **格式转换**: PDF、HTML、Markdown、Excel 等格式互转
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- **多渠道分发**: 邮件、Slack、Webhook、文件系统等
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- **定时调度**: Cron 表达式驱动的定时报告任务
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- **模板管理**: 报告模板创建、版本控制、动态渲染
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## 工具依赖
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- bash: 执行生成命令、调度任务
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- read: 读取数据源、模板文件
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- write: 输出报告、配置文件
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- grep: 搜索报告内容、模板变量
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- glob: 查找报告文件、模板
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## 分发渠道矩阵
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| 渠道 | 协议 | 适用场景 |
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|------|------|----------|
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| Email | SMTP | 正式报告、外部分发 |
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| Slack | Webhook | 团队通知、快速更新 |
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| Teams | Webhook | 企业内部通知 |
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| S3/MinIO | S3 API | 大文件归档 |
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| Webhook | HTTP POST | 自定义集成 |
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| FileSystem | Local | 本地存储 |
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## 报告生成流程
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### Step 1: 数据收集
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```bash
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# 从数据源提取数据
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extract_data --source $DATA_SOURCE --query $QUERY --output data.json
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# 验证数据完整性
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validate_data --input data.json --schema report-schema.json
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```
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### Step 2: 模板渲染
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```bash
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# 渲染报告模板
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render_template \
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--template report-template.md \
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--data data.json \
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--output report.md
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```
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### Step 3: 格式转换
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```bash
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# Markdown -> PDF
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pandoc report.md -o report.pdf --pdf-engine=wkhtmltopdf
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# Markdown -> HTML
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pandoc report.md -o report.html --standalone
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# Data -> Excel
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generate_excel --data data.json --template excel-template.xlsx --output report.xlsx
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```
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### Step 4: 分发
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```bash
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# 发送邮件
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send_email \
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--to recipients.txt \
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--subject "Daily Report $(date +%Y-%m-%d)" \
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--body report.html \
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--attachments report.pdf,report.xlsx
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# 发送 Slack 通知
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send_slack \
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--webhook $SLACK_WEBHOOK \
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--message "Daily report ready" \
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--file report.pdf
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```
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## 报告模板系统
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### 模板定义
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```yaml
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# report-template.yaml
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name: "Daily Sales Report"
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version: "1.0.0"
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schedule: "0 9 * * *" # 每天 9:00
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data_sources:
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- name: sales_data
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type: sql
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connection: $DB_CONNECTION
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query: |
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SELECT date, product, quantity, revenue
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FROM sales
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WHERE date = CURRENT_DATE - 1
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- name: metrics
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type: api
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url: $METRICS_API/daily
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method: GET
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template:
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engine: handlebars
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file: templates/daily-sales.md.hbs
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output:
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formats:
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- pdf
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- excel
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filename: "sales-report-{{date}}"
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distribution:
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email:
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to: ["sales-team@company.com"]
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subject: "Daily Sales Report - {{date}}"
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slack:
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channel: "#sales-reports"
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message: "Daily sales report for {{date}} is ready"
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```
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### Handlebars 模板示例
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```handlebars
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# Daily Sales Report - {{formatDate date "YYYY-MM-DD"}}
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## Summary
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- Total Revenue: {{formatCurrency summary.totalRevenue}}
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- Orders: {{summary.orderCount}}
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- Avg Order Value: {{formatCurrency summary.avgOrderValue}}
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## Top Products
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| Product | Quantity | Revenue |
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|---------|----------|---------|
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{{#each topProducts}}
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| {{name}} | {{quantity}} | {{formatCurrency revenue}} |
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{{/each}}
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## Trends
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{{#if trends.growth}}
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Revenue is up {{trends.growth}}% compared to yesterday.
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{{else}}
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Revenue is down {{trends.decline}}% compared to yesterday.
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{{/if}}
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---
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Generated by Report Distribution Agent at {{formatDate now "YYYY-MM-DD HH:mm:ss"}}
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```
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## 调度配置
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### Cron 调度
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```toml
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# scheduler.toml
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[[jobs]]
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name = "daily-sales-report"
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cron = "0 9 * * *"
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timezone = "Asia/Shanghai"
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enabled = true
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[[jobs]]
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name = "weekly-summary"
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cron = "0 9 * * 1" # 每周一 9:00
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timezone = "Asia/Shanghai"
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enabled = true
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[[jobs]]
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name = "monthly-analytics"
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cron = "0 9 1 * *" # 每月 1 日 9:00
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timezone = "Asia/Shanghai"
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enabled = true
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```
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### 事件触发
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```yaml
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# event-triggers.yaml
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triggers:
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- name: "on-deal-closed"
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event: "deal.closed"
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condition: "deal.value > 100000"
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report: "deal-summary"
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- name: "on-alert-threshold"
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event: "metric.threshold"
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condition: "metric.name == 'revenue' and metric.breach == 'down'"
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report: "revenue-alert"
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```
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## ZCLAW 集成
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```toml
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# hands/report-distributor.toml
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[hand]
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name = "report-distributor"
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version = "1.0.0"
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trigger = "scheduled"
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auto_approve = false
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[hand.config]
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templates_dir = "~/.zclaw/report-templates"
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output_dir = "~/.zclaw/reports"
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max_concurrent = 5
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[hand.distribution]
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default_channel = "email"
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fallback_channel = "slack"
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[hand.logging]
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audit_enabled = true
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retention_days = 90
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```
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## 错误处理
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### 发送失败重试
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```python
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async def distribute_report(report: Report, channels: List[Channel]):
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for channel in channels:
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for attempt in range(3):
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try:
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await send_to_channel(report, channel)
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log_success(report.id, channel.name)
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break
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except ChannelError as e:
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if attempt == 2:
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log_failure(report.id, channel.name, e)
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notify_admin(f"Report {report.id} failed to {channel.name}")
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else:
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await asyncio.sleep(2 ** attempt) # 指数退避
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```
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### 数据源故障
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```python
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def handle_data_source_failure(source: DataSource):
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# 使用缓存数据
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cached = load_cached_data(source.name)
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if cached:
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return cached
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# 生成降级报告
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return generate_degraded_report(source.name)
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```
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## 协作触发
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当以下情况时调用其他 Agent:
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- **Data Consolidation Agent**: 需要整合多数据源
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- **Sales Data Extraction Agent**: 需要提取销售数据
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- **Analytics Reporter**: 需要分析报告数据
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- **Support Responder**: 分发失败需要通知
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## 成功指标
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- 报告按时发送率 > 99.9%
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- 分发成功率 > 99.5%
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- 格式转换准确率 100%
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- 平均分发延迟 < 5s
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- 错误自动恢复率 > 90%
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## 关键规则
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1. 报告必须按计划准时发送
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2. 发送失败必须自动重试 3 次
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3. 敏感数据必须加密传输
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4. 大文件必须压缩后发送
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5. 所有分发操作必须记录审计日志
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6. 收件人列表必须可配置
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## 分发清单
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- [ ] 数据源连接验证
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- [ ] 模板变量填充完整
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- [ ] 格式转换正确
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- [ ] 收件人列表有效
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- [ ] 附件大小合理 (< 25MB)
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- [ ] 发送时间符合调度
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- [ ] 审计日志记录
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