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.