58 lines
2.8 KiB
Markdown
58 lines
2.8 KiB
Markdown
# Product Overview
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MiroFish is a multi-agent **swarm intelligence prediction engine**. Given seed
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material (news, policy drafts, financial signals, novel chapters, etc.) and a
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natural-language prediction question, it builds a knowledge graph, populates a
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parallel "digital sandbox" with thousands of personality-driven AI agents,
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runs a social simulation, and returns an analytical report plus an explorable
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simulated world.
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The user-facing experience is a guided **5-step workflow**: Graph Build →
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Environment Setup → Simulation → Report → Interaction. Long-running steps
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(LLM ontology extraction, graph build, profile generation, simulation, report)
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execute as background tasks the UI polls for progress.
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## Core Capabilities
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- **Knowledge graph construction** — Files (PDF, text) are parsed, an LLM
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extracts ontology, and Graphiti writes nodes/edges into Neo4j scoped per
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project (`group_id`).
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- **Persona-driven agent generation** — Entities pulled from the graph become
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OASIS agent profiles with traits, memory, and behavior priors.
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- **Dual-platform social simulation** — CAMEL-OASIS runs Twitter and Reddit
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agents in parallel rounds with a configurable action set.
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- **ReACT-loop report agent** — A reasoning agent answers the prediction
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question using graph tools (`SearchResult`, `InsightForge`, `Panorama`,
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`Interview`).
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- **Post-simulation interaction** — Users can chat with any simulated agent
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or the report agent to probe results.
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## Target Use Cases
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- **Macro decision rehearsal** — Stress-test policies, PR strategies, or
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market moves against a synthetic public before committing.
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- **Public-opinion / political forecasting** — Project how an event or
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narrative may diffuse across social platforms.
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- **Narrative and creative simulation** — Explore alternate endings,
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what-if scenarios, or fiction continuations (e.g. *Dream of the Red
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Chamber* lost-ending demo).
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- **Operator-led research** — Internal analysts upload reports and inspect
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the resulting graph + simulation rather than running ad-hoc surveys.
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## Value Proposition
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MiroFish converts a static document into a **dynamic, interrogable digital
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society**. Where traditional forecasting summarizes data, MiroFish lets
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decision-makers *watch the future play out* — observing emergent collective
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behavior, intervening from a "god view," and reading both an analytical
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report and the underlying agent interactions that produced it.
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The pipeline is deliberately **provider-agnostic** at the LLM layer (any
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OpenAI-SDK-compatible endpoint works) and **self-hosted** at the graph layer
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(Neo4j + Graphiti, no third-party graph service required), so the same
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system can run from a developer laptop to a managed deployment without
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vendor lock-in.
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---
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_Focus on patterns and purpose, not exhaustive feature lists_
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