All 17 Dependencies
Every package MiroFish depends on, ranked by repo health score.
MiroFish is an open-source multi-agent prediction platform that turns raw seed information — news articles, policy drafts, financial signals, literary texts — into a high-fidelity parallel digital world populated by thousands of AI agents with distinct personalities, long-term memory, and behavioral logic. Rather than extrapolating trends from historical data alone, it lets agents interact freely and undergo social evolution, surfacing emergent outcomes that statistical models miss.
The platform follows a four-stage pipeline: knowledge graph construction from uploaded seed materials, environment setup where entities from the graph are converted into OASIS agent profiles, dual-platform parallel simulation across Twitter-style and Reddit-style social environments, and finally ReportAgent-driven analysis that lets users interrogate the simulated world through natural language. Each stage exposes an API, making MiroFish composable with existing analytical pipelines.
At the infrastructure layer, MiroFish relies on Zep Cloud's GraphRAG memory system to give agents persistent long-term memory and relationship awareness across simulation rounds. The OASIS simulation engine (from CAMEL-AI) drives the social interaction mechanics, while any OpenAI-compatible LLM API handles reasoning and generation — meaning users can plug in Alibaba Qwen, GPT-4o, or local models without changing application code.
Use cases span from decision-maker rehearsal laboratories (stress-testing public relations strategies or policy proposals at zero real-world cost) to creative sandboxes (predicting alternate endings for literary works). The project is incubated by Shanda Group and has rapidly grown to over 66,000 stars, reflecting strong interest in emergent-behavior prediction as a complement to traditional forecasting.
