Worldcast: feeding live WorldMonitor news events into MiroFish for "what happens next" predictions #619
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Note 🤖 Automated maintainer response — Generated by the MiroFish triage agent and checked against Thanks for sharing Worldcast. This is a thoughtful community experiment. It is independently maintained and has not been reviewed or compatibility-certified by the MiroFish maintainers. One important compatibility note: the official project does not expose Current official main still requires |
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Hi everyone — I built a small bridge tool that uses MiroFish, and wanted to share it here in case it's useful or the community has feedback.
Worldcast is a thin bridge that takes any live news event from WorldMonitor (real-time news/intelligence globe), formats it into a structured seed document, and pipes it straight into MiroFish's simulation workflow. The resulting agent simulation gets summarized into plain-English bullets across markets, geopolitics, and supply chain — plus a checklist of specific, verifiable watch signals.
What the bridge does NOT do: modify MiroFish in any way. It calls
POST /api/simulateand pollsGET /api/report/:id, treating MF as a black box. Update MF withdocker compose pull.Example seed flow:
The simulation report comes back narrative-form; the bridge then asks the LLM to extract:
Then the real trick: the bridge keeps polling WM for new events every 60s, scores each against the open watch signals via a cheap LLM call, and fires a browser notification when the score crosses 0.8. That closes the loop from "MiroFish predicted X" to "X actually happened."
Repo: https://github.com/wilson-cheng1110/WorldPredict
Stack: Node.js bridge (~250 lines), vanilla-JS UI, configurable LLM (qwen-plus / Ollama / OpenAI). AGPL-3.0.
Questions for the MF community if anyone has time:
POST /api/simulateshape. In real MF the workflow is multi-step (ontology → graph → sim create → prepare → start → report). Should I expose those stages in the progress WS, or is the abstraction fine?Open to PRs, criticism, "this should just be a MF example app," etc.
Really impressive engine — thanks for building it.
大家好——我做了一个基于 MiroFish 的小工具,发上来分享一下,看看是否对大家有用,也欢迎社区反馈。
Worldcast 是一个很薄的桥接层。它把 WorldMonitor(实时新闻/情报地球仪)上任何一条新闻事件,格式化成结构化的 seed 文档,直接喂进 MiroFish 的仿真流程。仿真结果会被总结成市场 / 地缘政治 / 供应链三个维度的简明 bullet,再加上一份具体、可验证的观察信号清单。
桥接层不修改 MiroFish 任何代码。只调用
POST /api/simulate,轮询GET /api/report/:id,把 MF 当成黑盒。MF 升级直接docker compose pull。最后那个闭环是我觉得最有意思的部分:桥接层每 60 秒重新轮询 WM 的新事件,用一次轻量级 LLM 调用给每条新事件打分(与所有未确认的观察信号匹配),分数过 0.8 时浏览器弹通知。这样就把"MiroFish 预测了 X"变成"X 真的发生了"。
仓库: https://github.com/wilson-cheng1110/WorldPredict
技术栈: Node.js 桥接(约 250 行),纯 JS 单文件 UI,LLM 可配置(默认 qwen-plus,也支持 Ollama / OpenAI)。协议 AGPL-3.0。
有几个问题想请教社区:
POST /api/simulate。真实 MF 是多步骤(ontology → graph → sim → prepare → start → report)。这些阶段应该在 progress WebSocket 里暴露给前端吗?还是保持抽象比较好?欢迎 PR、批评、或者"这玩意儿应该直接放进 MF 的 examples"——什么反馈都欢迎。
引擎做得很赞,感谢。
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