Original Summary

I work on AgenticOS at Vstorm. It's an open-source (Apache 2.0) platform for building your own AI agents and running them on your own infrastructure. You set an agent up in the browser with instructions, a model and tools, give it documents, and use it from the web chat, Slack, Mattermost, Telegram or your own app through the API. The video shows two short tasks: A CSV into tables and a chart . I attach a sales CSV with 1,000 synthetic rows and ask for totals by month, region, product and channel, plus a chart. Before calculating, the agent checks the file for duplicate IDs, blank regions and invalid dates (my prompt didn't ask for that), then runs Python, shows the code and draws the chart. Every total it shows matches a separate calculation on the same file. An answer from a document, with its source . I upload a fictional three-sentence refund policy and ask whether an unused item that arrived 12 days ago can be returned. The agent searches the document, says yes, quotes the 30-day sentence and links the passage it used. What else is in it: Knowledge bases you attach to agents, so answers come from your documents Skills , written procedures an agent can load when relevant A searchable catalog of 5,700+ MCP server entries, or add a compatible server by URL Artifacts , reports and small dashboards an agent creates, with versions Run history with tokens and recorded cost, plus human approval for supported tool actions Routines that run an agent on a schedule or on a configured event It runs on cloud or local models, is built on Pydantic AI and self-hosts with Docker Compose. If you have Docker with Compose (macOS, Linux or WSL2), the quick start is one command: https://github.com/vstorm-co/agenticos   submitted by   /u/VanillaOk4593 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/3 01:40:15