666ghj/MiroFish

MiroFish

A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎,预测万物

RepositoryHomepage
45/100Agents
Stars61,921
Forks9,713
LanguagePython
LicenseAGPL-3.0

Usage guide

MiroFish is an open-source project around agent-memory, financial-forecasting, future-prediction with 61,921 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.

Repository license: AGPL-3.0Commercial use requires review

Key features

  • Implemented mainly in Python, useful for judging integration effort in a similar stack.
  • GitHub detected the AGPL-3.0 repository license, which does not by itself confirm commercial permission. Review repository obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
  • The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.

Best for

  • Evaluating MiroFish for Python AI workflows.
  • Comparing a GitHub project with 61,921 stars and current repository activity.

Pros

  • MiroFish has visible GitHub traction with 61,921 stars. Topics: agent-memory, financial-forecasting, future-prediction.
  • The project provides an external homepage for deeper evaluation.

Cons

  • Production fit still depends on documentation depth, issue activity, and release cadence.
  • License review should confirm the AGPL-3.0 terms fit your use case.

Production readiness

MiroFish should be validated with its README, release history, open issues, and integration requirements before production use.

License risk

AGPL-3.0 is reported by GitHub; review the repository license before redistribution or commercial use.

Featured video

John Forfar

YouTube

PREDICT ANYTHING with 10,000+ Agents (even oil price based on next attack) - Mirofish Demo

40,106 views · 2026-03-18

Install tutorial

Before you install

  • Python runtime and an isolated virtual environment
  • Docker Engine with enough disk space for images and volumes
  • A clean working directory for the first test run
1
Step 1

Check the runtime environment

MiroFish has Docker in the setup path. Confirm Docker Engine works and reserve enough disk space for images and volumes.

2
Step 2

Get the project files

Start from the official repository or package so the first run matches the documented behavior.

terminal
$ git clone https://github.com/666ghj/MiroFish.git
3
Step 3

Install or build dependencies

Run the next setup command detected from the project documentation.

terminal
$ docker-compose.yml

Troubleshooting

  • If Docker startup fails, check port conflicts, image pull permissions, and volume paths first.
  • If installation fails, first confirm the command is being run from the README-specified directory.
  • If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
  • If output looks wrong, return to the smallest documented MiroFish example before adding complex data.
  • For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
What is MiroFish?

MiroFish is an open-source ai agents project. A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎,预测万物

How do I install MiroFish?

Start with the official README. The first detected setup step is: git clone https://github.com/666ghj/MiroFish.git.

Is MiroFish beginner-friendly?

If you already know the Python ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.

Can MiroFish be used commercially?

GitHub detected the AGPL-3.0 repository license, which does not by itself confirm commercial permission. Review repository obligations and any model weights, datasets, dependencies, or external services before commercial adoption.

Does MiroFish need a GPU?

GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.

How should I decide whether to adopt MiroFish?

Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.

Star trend

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