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mirofish

mirofish

Use MiroFish's Flask and Vue social-simulation engine to build Zep graphs from documents, prepare OASIS simulations, run them, and generate interactive reports.

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Skill-Dokumentation

GitHub

name: mirofish description: "Use MiroFish's Flask and Vue social-simulation engine to build Zep graphs from documents, prepare OASIS simulations, run them, and generate interactive reports." disable-model-invocation: true metadata: disco-role: operating license: AGPL 3.0

MiroFish

Use this repo skill when a task names MiroFish or asks for a document-to-graph-to-social-simulation workflow with Zep Cloud graph memory, OASIS/CAMEL agents, Twitter/Reddit-style simulations, generated prediction reports, or report-agent interaction.

MiroFish is a full-stack app, not a small library call. The normal operating sequence is:

  1. Build a Zep graph from seed PDFs, Markdown, or text.
  2. Prepare simulation artifacts from graph entities.
  3. Run and monitor a parallel/Twitter/Reddit OASIS simulation.
  4. Generate a report and interact with the Report Agent.

Route by task

  • Use sub-skills/graph-build/SKILL.md for seed-file upload, ontology generation, Zep graph build, graph data inspection, project/task state, graph reset, and graph deletion.
  • Use sub-skills/simulation-setup/SKILL.md for simulation creation, entity filtering, profile/persona generation, simulation_config.json, setup status, setup downloads, and setup-format validation.
  • Use sub-skills/simulation-run/SKILL.md for start/stop/close-env, run status, timelines, actions, posts, comments, agent stats, interviews, IPC, and graph-memory updater finalization.
  • Use sub-skills/reporting/SKILL.md for report generation, progress/section/log polling, download/delete, Report Agent chat, and report-side graph tools.

Read or run the root material

  • Read references/overview-and-setup.md before installing, starting, containerizing, or configuring a MiroFish deployment.
  • Read references/architecture-and-state.md to understand the backend services, frontend steps, local artifact directories, state transitions, and handoffs between sub-skills.
  • Read references/troubleshooting.md for cross-cutting install/import, API key, port, provider, Zep Cloud, Docker, and frontend/backend issues.
  • Read references/repo-provenance.md to see the source revision and evidence baseline used to build this skill.
  • Read references/repo-routing-metadata.json only when updating managed repo-skill router metadata.
  • Run python scripts/mirofish_config_check.py --help to inspect the bundled environment and service-health checker; run it with --env-file .env or --base-url http://localhost:5001 from a deployment workspace.

Minimal deployment check

cp .env.example .env
# fill LLM_API_KEY and ZEP_API_KEY
npm run setup:all
npm run dev

Expected local service URLs:

  • Frontend: http://localhost:3000
  • Backend API: http://localhost:5001
  • Health check: GET /health returns {"status":"ok","service":"MiroFish Backend"}

For Docker deployment, create .env first and then run docker compose up -d; the image exposes the same frontend/backend ports and persists backend uploads under the bind-mounted upload directory.

Configuration essentials

Required:

  • LLM_API_KEY: OpenAI-compatible LLM provider key.
  • ZEP_API_KEY: Zep Cloud key.

Common optional settings:

  • LLM_BASE_URL and LLM_MODEL_NAME: default to OpenAI-compatible behavior when omitted.
  • LLM_BOOST_*: optional faster model for selected expensive paths; omit the variables entirely when unused.
  • FLASK_HOST, FLASK_PORT, FLASK_DEBUG: backend server behavior.
  • OASIS_DEFAULT_MAX_ROUNDS: default runtime round count.
  • REPORT_AGENT_MAX_TOOL_CALLS, REPORT_AGENT_MAX_REFLECTION_ROUNDS, REPORT_AGENT_TEMPERATURE: Report Agent limits.

Do not set ZEP_API_URL; MiroFish intentionally supports Zep Cloud only and rejects self-hosted Zep URL overrides.

Operating guardrails

  • Keep live Zep Cloud validation manual. Credentialed graph validation can create/delete cloud graphs and is not part of normal skill smoke checks.
  • Treat GPU availability as optional for this skill. The selected automated verification scope is CPU-only because MiroFish's public workflows are service/API orchestration, not required CUDA kernels.
  • Do not run long OASIS launchers as casual smoke tests. Use setup checks and short unit/native candidates first; start simulations only when the user explicitly wants runtime execution.
  • Do not edit generated report or simulation artifact files while the backend is running unless the referenced sub-skill says the artifact is safe to inspect or regenerate.
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