近 7 天 · 工作流与智能体搭建
n8n
连接工具,搭建自动化流程与智能体
体感分53.6/10020 条评论
来源 全部
大家怎么看
近 7 天的 20 条评论中,评价褒贬并存。批评最集中在「稳定性」(5/9 条负面摘录)。好评最集中在「工作流与集成」(7/12 条正面摘录)。有用户认为n8n在数据导入与查询编排任务方面是不错的选择。有用户建议在自托管n8n中将二进制卷视为与数据库备份同等重要的备份目标,恢复测试应同时恢复两者,否则工作流可能加载但文件负载缺失。
近 7 天 · 工作流与智能体搭建
连接工具,搭建自动化流程与智能体
近 7 天的 20 条评论中,评价褒贬并存。批评最集中在「稳定性」(5/9 条负面摘录)。好评最集中在「工作流与集成」(7/12 条正面摘录)。有用户认为n8n在数据导入与查询编排任务方面是不错的选择。有用户建议在自托管n8n中将二进制卷视为与数据库备份同等重要的备份目标,恢复测试应同时恢复两者,否则工作流可能加载但文件负载缺失。
用户反馈
0 条评价摘录
展开原文
IMO n8n is overkill for what u r trying to do. While there seems to be some repetition, with the number of files, a simple script that Claude code can write in 5 seconds will do the job.
查看评论上下文
我想为我志愿服务的 NGO 建一个简单的知识中心。这是需求: - 一次性导入整个语料库(约 3000 份 PDF,每份 10 页,纯文本,质量良好,无需 OCR)。现在文件散落各处,我可能会把所有东西集中到一个 Microsoft Sharepoint 作为中央存储库(这是他们日常使用的) - 创建一个电子表格格式的索引,包含分类、标签、摘要和文档链接 - 建一个可在线访问的网络应用,需要密码保护,约 30 个用户可以访问(包括组织外部的人),每人每天平均发起一次查询语料库的请求(他们的 Anthropic 账户 API 调用预算不多,所以可以用那个) 这是第一次做这种东西,我想知道 n8n 是否适合构建这个?还是有现成的工具可以直接用?
机器翻译展开原文
I want to build a simple Knowledge Hub for a NGO I am volunteering for. This is the brief: - One off ingestion of the whole corpus (~3000 PDFs of 10 pages each, text only, good quality, no OCR needed). The files are all over the place now, and I am probably going to gather everything in one Microsoft Sharepoint as central repo (this is what they use day to day) - Building a spreadsheet format index with categories, tag, summary, link to the document - Building a web app that is accessible online, password protected, accessible by ~30 users (include people outside their org) running on average a request a day each to query the corpus (they have small budget for API calls on their antrhopic account so we can use that) This is the first time I am building something like this and wondering whether n8n is a good place to build this ? Or is there an off the shelf tool just for this I can use ?
展开原文
n8n is actually a decent fit for the ingestion + query orchestration part.
展开原文
I’d treat the binary volume as a first-class backup target alongside the database dump, not as an afterthought. A restore test should bring up both the database and that volume together; otherwise the workflows may load while their file payloads are missing.
展开原文
Very cool to have this natively in n8n
展开原文
the async polling thing is the real pain in n8n . you end up with a wait node loop that looks ugly and breaks if the timeout is off by even a little.
展开原文
make sure your error branch actually parses the status code separately from the body, most 500s from image hosts have useful info in the response body that n8n just doesnt surface by default
展开原文
I still keep n8n around for dumb glue though - cron scrapes, slack alerts, that kind of thing. Building THOSE with an agent is more effort than it's worth. Visual for the boring stuff, code for anything with state.
展开原文
You can close the parent-to-child gap without a timestamp search: have each sub-workflow return its own execution id from its last node. Execute Sub-workflow hands that back to the caller, so the parent can write its execution id and the child's into the same log row and the chain becomes a direct join instead of a time window.
展开原文
The built-in parent/child view is fine for one hop. It stops being useful the moment several runs overlap, which sounds like where you are.
展开原文
n8n encrypts credentials at rest, but it doesn't care whose API keys are inside them — if the Stripe/database/API credentials in the workflows belong to your personal accounts instead of the client's, the handover is a lie and everything breaks the day you revoke them. Provisioning every credential from the client's accounts before go-live, and documenting which service each credential belongs to, has saved me more than one "why did payments stop working" call six months later.
展开原文
So we’d still need the explicit logs for both success and cases where the decision looks off, but the Error Trigger approach is still useful if there’s an actual workflow failure.
查看评论上下文
一个补充角度:Error Trigger工作流。将其指向子工作流,它会在失败时触发,包括工作流名称、执行ID和完整的错误负载——也通过它传递你的关联ID并记录到同一个表中,这样失败就会直接出现在成功路径行的旁边,而不需要在执行列表中搜索。有两个注意事项:它只在失败时触发,所以你仍然需要明确的日志行来追踪成功路径;在一个繁忙的实例上,请检查你的执行修剪/保留设置(EXECUTIONS_DATA_PRUNE),这样历史数据库就不会在按时间戳调试时膨胀。
机器翻译展开原文
One complementary angle: the Error Trigger workflow. Point it at your sub-workflows and it fires on failure with the workflow name, execution ID, and the full error payload — pass your correlation ID through it too and log to the same table, and failures land right next to the success-path rows instead of requiring a hunt through the execution list. Two caveats: it only fires on failures, so you still need the explicit log rows for success-path tracing, and on a busy instance double-check your execution pruning/retention settings (EXECUTIONS_DATA_PRUNE) so the history DB doesn't balloon while you're debugging by timestamp.
展开原文
In our case, the workflow itself won’t necessarily throw an error since a wrong decision can still be a successful execution. So we’d still need the explicit logs for both success and cases where the decision looks off, but the Error Trigger approach is still useful if there’s an actual workflow failure.
展开原文
I’d add the external monitor to the handover. If it stays in your account, alerts go to you after the contract ends. In didit.run you can hand the workspace to the client and the ping urls stay the same.
展开原文
I was checking how others handle this in the n8n community, and maintaining a separate log seems like the better approach. I was initially thinking more about being able to navigate from the main workflow execution directly to the corresponding sub-workflow execution trace, similar to how the editor tab lets you navigate to the sub-workflow itself. Having the parent execution ID/correlation metadata exposed on the sub-workflow execution would make this much easier, especially for evaluation runs.
展开原文
The built in parent/child stuff in n8n is kinda spotty once you get past one level deep. Half the time the execution list just shows them as separate unrelated runs so good luck piecing it together after the fact
展开原文
n8n's parent/child link works until you're looking at 200 executions in a five-minute window.
展开原文
By default n8n holds file payloads in memory and writes them to PostgreSQL as base64, which quickly triggers container OOM crashes and balloons database backup sizes as soon as workflows handle PDFs or images.
展开原文
Offloading binaries to the filesystem keeps memory usage predictable and makes database dumps much faster.
展开原文
This is a solid workflow, especially the structured output part.
展开原文
Ask Fetchsandbox for the twin's signing secret and store it as a separate n8n credential/variable alongside the base URL, so sandbox vs live is one toggle, not two.
查看评论上下文
构建工作流中的支付由 stripe 处理,但我想知道是否有配置可以更改 fetchsandbox twin 的端点?
机器翻译展开原文
building workflow payments are handled by stripe but wondering is there a config I can change the endpoint fetchsandbox twin ?
展开原文
If you verify incoming webhooks against the wrong secret, everything fails closed and it looks like n8n just silently dropped the events.
展开原文
n8n is just one of many automation methods.. and been replaced altogether in my shop.
展开原文
idempotency key built from the chat message id fixed it, not the gate
查看评论上下文
我的触发了两次,因为对 synexa 的分类器调用卡住了,n8n 重试了整个分支。
机器翻译展开原文
mine double fired because the classifier call on synexa stalled and n8n retried the whole branch.
展开原文
mine double fired because the classifier call on synexa stalled and n8n retried the whole branch
查看评论上下文
我的退款代理在生产环境中失控了,把退款发放了两次。
机器翻译展开原文
My refund agent went rogue in prod and issued the refund twice.
展开原文
pour whatsapp, devis et publication, commence par n8n en self-host plutôt qu'un agent orchestrateur, ce sont surtout des workflows fixes avec une étape LLM au milieu.
展开原文
In n8n's WhatsApp Trigger node, I don't see any place to manually enter/match that same verify token — the node just has OAuth credentials (Client ID/Secret) and a Trigger On (Messages) dropdown. So I'm not sure how n8n is supposed to validate the token Meta sends during the handshake.
查看评论上下文
在"验证令牌"字段中输入了一个随机字符串(例如`dental2026`)
机器翻译展开原文
Typed a random string into the "Verify token" field (e.g. `dental2026`)
此筛选下暂无评价。