# 666ghj/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

Repository: https://github.com/666ghj/MiroFish
Canonical: https://ross.abutalabs.com/products/mirofish
Homepage: https://mirofish.ai
Language: Python
License: AGPL-3.0
License Family: copyleft
Topics: agent-memory, financial-forecasting, future-prediction, knowledge-graph, llms, multi-agent-simulation, public-opinion-analysis, python3, social-prediction, swarm-intelligence
Last push: 2026-08-17T05:17:34+00:00

## Health v2 (maintenance only)
Score: 70/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 62, longevity 20
- inputs: {"age_days": 280, "days_push": 16, "days_rel": 179, "gap_med": 37.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 71572, forks 11127 (observed 2026-08-28T04:12:21.035758+00:00)

## What it is
MiroFish is a Python-based swarm intelligence prediction engine that builds high-fidelity parallel digital worlds populated by thousands of LLM-powered agents with memory and personalities. Users upload seed materials and describe prediction goals in natural language, and the engine simulates social evolution to produce detailed forecasts and an interactive digital world.

## Use cases
- simulate how public opinion evolves after breaking news
- forecast financial market reactions to policy drafts
- rehearse policy decisions in a digital sandbox before rollout
- run multi-agent social simulations with thousands of LLM agents
- predict outcomes of events using swarm intelligence
- test public relations scenarios with agent-based modeling
- build an interactive digital world from a story or report

## When to choose
- you need agent-based social or financial forecasting driven by LLMs
- you want to inject variables and observe emergent collective behavior in simulation
- you need a general-purpose prediction engine that accepts natural-language goals and seed documents

## When to avoid
- you need deterministic, statistically validated forecasting rather than LLM-driven simulation
- you lack the compute budget for thousands of concurrent LLM agents
- you need a lightweight single-agent chatbot or simple automation tool

## Facets
- artifact type: framework
- maturity: active
- function: agent-framework, machine-learning, simulation, llm-inference, data-science
- domain: artificial-intelligence, large-language-models, simulation, data-science
- platform: python, cross-platform
- tags: multi-agent-simulation, swarm-intelligence, prediction-engine, social-simulation, financial-forecasting, knowledge-graph, agent-memory, digital-twin, llm-agents, ai-agents, docker, web-server

## Member repositories
- 666ghj/MiroFish (main) score 70

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:21.035758+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:16:22.577084+00:00, confidence not recorded.
  - readme: https://github.com/666ghj/MiroFish (fetched 2026-08-28T04:12:21.035758+00:00, sha 8fe49f707be7)
  - homepage: https://mirofish.ai (fetched 2026-08-28T17:50:25.541977+00:00, sha a5a0000824f9)
- Data as of 2026-08-30T08:39:29.467469+00:00.