# MiroFish — Universal Swarm Intelligence Prediction Engine

> An open-source swarm intelligence engine that uses multi-agent simulation and knowledge graphs to predict trends in social, financial, and public opinion domains.

## Install

Save as a script file and run:

# MiroFish — Universal Swarm Intelligence Prediction Engine

## Quick Use
```bash
git clone https://github.com/666ghj/MiroFish.git
cd MiroFish
pip install -r requirements.txt
python main.py --task "predict tech trends Q3 2025"
```

## Introduction
MiroFish is an open-source swarm intelligence engine that coordinates multiple LLM agents to analyze data, build knowledge graphs, and generate predictions. It applies multi-agent simulation to domains like financial forecasting, public opinion analysis, and trend prediction.

## What MiroFish Does
- Coordinates swarms of specialized agents to collaboratively analyze complex datasets
- Builds and queries knowledge graphs to surface relationships in unstructured data
- Generates predictions for financial markets, social trends, and public opinion shifts
- Provides structured reports with confidence scores and supporting evidence
- Supports custom prediction tasks defined through natural language prompts

## Architecture Overview
MiroFish uses a multi-agent architecture where specialized agents (data collector, analyst, predictor, critic) communicate through a shared knowledge graph. The orchestration layer distributes tasks, aggregates agent outputs using swarm consensus algorithms, and produces a final prediction with a confidence interval. The system uses LLM backends for reasoning and Python for data processing.

## Self-Hosting & Configuration
- Install via pip with Python 3.9+ and configure LLM API keys in environment variables
- Supports OpenAI, Anthropic, and local model backends through a unified adapter
- Knowledge graph storage defaults to a local SQLite database; PostgreSQL optional for scale
- Custom data connectors can be added for proprietary data sources
- GPU not required for inference; training custom agents is optional

## Key Features
- Swarm consensus mechanism aggregates diverse agent perspectives into robust predictions
- Dynamic knowledge graph construction from unstructured text and structured data
- Multi-domain support covering finance, social media, public policy, and technology trends
- Confidence scoring with explainable reasoning chains for each prediction
- Agent memory enables learning from past prediction accuracy across sessions

## Comparison with Similar Tools
- **TradingAgents** — focused on financial trading; MiroFish handles broader prediction domains
- **CrewAI** — general multi-agent orchestration; MiroFish adds swarm consensus and knowledge graphs
- **AutoGen** — multi-agent conversations; MiroFish specializes in structured prediction workflows
- **LangGraph** — agent graph framework; MiroFish provides a complete prediction application on top

## FAQ
**Q: What types of predictions can MiroFish make?**
A: Financial trends, social media sentiment shifts, technology adoption curves, and custom domains.

**Q: Does it require real-time data feeds?**
A: No. MiroFish works with both historical datasets and real-time data connectors.

**Q: How does swarm consensus differ from a single agent?**
A: Multiple agents analyze independently, then consensus algorithms weight and merge their outputs for higher accuracy.

**Q: Can I add custom agent types?**
A: Yes. The plugin system supports custom agent roles with specialized prompts and tools.

## Sources
- https://github.com/666ghj/MiroFish

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Source: https://tokrepo.com/en/workflows/asset-7368bde3
Author: Script Depot