# crisis

A proof-of-concept and educational artifact for Mirco Richter's [_Crisis_ paper](Crisis.mirco-richter-2019.pdf) — a DAG-based BFT consensus protocol that achieves total order on messages in fully open, unstructured peer-to-peer networks through **virtual voting**: votes are never sent explicitly but are deduced from the causal relationships encoded in Lamport graphs.

This repository contains:

- a **Python implementation** of the protocol (`src/crisis/`, `tests/`),
- an **event recorder** that exports a deterministic simulation run to JSON,
- **CrisisViz** — a native macOS / SwiftUI curriculum visualizer that walks the protocol end-to-end across ten chapters,
- **crisis_agents** — a coordination layer that lifts the protocol from "consensus between machines" to "consensus between AI agents," with a decentralized async event-driven engine and quorum-ratified byzantine alarms.

Everything in the visualizer is in extreme slow motion and serialized for didactic clarity. A signed speed slider scrubs each chapter forward and backward at any rate from $-16\times$ to $+16\times$; narration is bound to whichever beat the playhead is on.

---

## Architecture at a glance

```mermaid
flowchart TD
    Paper["📄 <b>Paper — the spec</b><br/>Crisis.mirco-richter-2019.pdf"]
    Paper --> Algos

    subgraph Algos["🧮 Pure protocol algorithms — <code>src/crisis/</code>"]
        direction LR
        Crypto["crypto.py"]
        Msg["message.py"]
        Graph["graph.py"]
        Weight["weight.py"]
        Rounds["rounds.py"]
        Voting["voting.py"]
        Order["order.py"]
    end

    Algos --> RealRT
    Algos --> SimRT
    Algos --> AgentLayer

    subgraph RealRT["🌐 <b>Real runtime — <code>node.py</code> + <code>gossip.py</code></b><br/><i>scalable, deployable</i>"]
        Node["CrisisNode<br/>asyncio · TCP push/pull gossip<br/>3 concurrent loops<br/>CLI: <code>crisis-node</code>"]
    end

    subgraph SimRT["🧪 <b>In-process toy runtime — <code>demo.py</code></b><br/><i>deterministic, recordable</i>"]
        SimNode["SimulatedNode<br/>direct in-memory message passing<br/>NetworkParams: delays / drops / silences"]
        SimCtl["Simulation controller<br/>spins up N honest + K byzantine<br/>CLI: <code>crisis-demo</code>"]
        SimNode --- SimCtl
    end

    subgraph AgentLayer["🤖 <b>Crisis-Agents — <code>src/crisis_agents/</code></b><br/><i>decentralized, asynchronous</i>"]
        Agent["CrisisAgent ×N<br/>owns own LamportGraph<br/>emit · receive · gossip · detect"]
        Mom["Mothership<br/>bootstrap + event-loop driver<br/>no clock · no privileged state<br/>CLI: <code>crisis-agents</code>"]
        Agent --- Mom
    end

    SimRT --> Rec
    Rec["📼 <b>Recorder — <code>recorder.py</code></b><br/>instruments every algorithm call<br/>captures events + per-step snapshots"]
    Rec --> Export
    Export["📦 <b>JSON exporter — <code>export_json.py</code></b><br/>writes <code>crisis_data.json</code>"]
    Export --> Viz

    AgentLayer --> ProofJSON["🧾 <b>proof_*.json</b><br/>multi-signer byzantine proof<br/>schema_version=2"]

    subgraph Viz["🎬 <b>CrisisViz — native macOS / SwiftUI</b>"]
        Player["Keynote-style player<br/>10 chapters · ~18 min @ 1×<br/>scrubbable −16× to +16×"]
        Testbed["Testbed harness<br/>invariants · source audit<br/>PNG sweep · 36 MP4 clips"]
    end

    classDef paper fill:#fdf6e3,stroke:#586e75,color:#073642
    classDef pure fill:#eee8d5,stroke:#586e75,color:#073642
    classDef real fill:#fce5cd,stroke:#cc4125,color:#660000
    classDef sim fill:#d9ead3,stroke:#38761d,color:#0b3d0b
    classDef agents fill:#fff2cc,stroke:#bf9000,color:#3d2e00
    classDef rec fill:#cfe2f3,stroke:#2c5f8f,color:#062b4d
    classDef viz fill:#ead1dc,stroke:#741b47,color:#3d0a26
    classDef proof fill:#fce5e8,stroke:#a64d59,color:#3d0014
    class Paper paper
    class Algos pure
    class RealRT real
    class SimRT sim
    class AgentLayer agents
    class Rec,Export rec
    class Viz viz
    class ProofJSON proof
```

**Three independent consumers of the protocol.** `src/crisis/` provides the pure algorithms (Lamport graphs, virtual voting, total order, mutation detection). Three sibling layers sit on top:

- **`CrisisNode`** — a deployable distributed runtime (TCP gossip, three concurrent asyncio loops). Has no consumers in this repo; meant as a reference for how a real network deployment would look.
- **`SimulatedNode`** — an in-process deterministic simulator whose recording becomes `crisis_data.json`, the file CrisisViz visualizes.
- **`crisis_agents`** — agent-coordination layer. Each AI agent participates as a Crisis node; the network catches byzantine equivocation through decentralized detection + quorum voting. The engine is asynchronous and event-driven — no global clock, no privileged observer.

The three are **siblings, not layers**: refactoring one doesn't break the others. CrisisViz and crisis_agents don't know each other exists.

---

## Repository layout

```
crisis/                                          ← git root
├── Crisis.mirco-richter-2019.pdf                the paper
├── README.md                                     this file
├── INSTALL.md                                    fresh-macOS install guide
├── LICENSE                                       MIT (code only; paper is CC-BY-4.0)
├── pyproject.toml                                Python ≥3.11, networkx, pytest
├── crisis_data.json                              simulation export (source of truth)
│
├── src/crisis/                                   ── PROTOCOL PoC (Python) ──
│   ├── crypto.py, message.py                     random-oracle hash + Message/Vertex
│   ├── graph.py, weight.py, rounds.py            Lamport DAG + PoW weight + round derivation
│   ├── voting.py, order.py                       BBA virtual voting + total order
│   ├── gossip.py, node.py                        real TCP runtime (CrisisNode)
│   ├── demo.py                                   in-process simulation harness
│   ├── recorder.py                               event instrumentation
│   └── export_json.py                            JSON exporter for CrisisViz
│
├── src/crisis_agents/                            ── AGENT COORDINATION (Python) ──
│   ├── README.md                                 architecture & walkthrough
│   ├── agent.py                                  CrisisAgent + MockAgent + MockByzantineAgent
│   ├── live_agent.py                             LiveClaudeAgent (Anthropic SDK)
│   ├── boundary.py                               trust-set + open() trigger
│   ├── mothership.py                             bootstrap + async event-loop driver
│   ├── claim.py                                  ClaimMessage payload
│   ├── alarm.py                                  decentralized detection
│   ├── vote.py                                   AlarmClaim + quorum tally
│   ├── proof.py                                  multi-signer ProofDocument
│   ├── cli.py                                    crisis-agents CLI entry point
│   └── scenarios/fact_check.py                   the canonical demo
│
├── tests/                                        pytest suite (170 tests, ~0.8s)
│
└── CrisisViz/                                    ── VISUALIZER (Swift / macOS 26) ──
    ├── Package.swift, bundle.sh, package-dmg.sh
    ├── Sources/CrisisViz/                        App, Engine, Model, Chapters, Views, Glass, Testbed, Canvas
    ├── README.md                                 Swift-side human guide
    └── HANDOFF.md                                agent-to-agent engineering log
```

---

## Quick start

Four audiences. Pick the one that matches what you want to do.

### 🧮 Verify the protocol — pytest

```sh
cd crisis
source .venv/bin/activate    # set up per INSTALL.md if first time
pytest -q
```

Runs all 170 tests across the protocol algorithms and the crisis_agents layer. Should be green in under a second.

### 🧪 Run a deterministic protocol simulation — Python CLI

```sh
python -m crisis.demo --nodes 4 --byzantine 1 --rounds 10
```

Spins up four honest + one byzantine `SimulatedNode`, runs ten consensus rounds in-process with a deterministic seed, prints the resulting total order. To export a fresh `crisis_data.json` for CrisisViz:

```sh
python -m crisis.export_json --steps 80 -o crisis_data.json
cp crisis_data.json CrisisViz/Sources/CrisisViz/crisis_data.json
```

### 🤖 Run the AI-agent coordination demo — Python CLI

```sh
crisis-agents demo
```

Walks a six-phase scenario: a closed honest team, a byzantine joiner who equivocates on a fact-check statement, an asynchronous gossip + detection event loop, and a quorum-ratified proof. Output ends with a `proof_*.json` document that any third party can self-verify. See **[src/crisis_agents/README.md](src/crisis_agents/README.md)** for the architecture.

For real Claude sub-agents instead of scripted mocks:

```sh
pip install -e ".[live]"           # adds anthropic SDK
export ANTHROPIC_API_KEY=...
crisis-agents demo --live
```

### 🎬 Watch the protocol visualizer — Swift / macOS

```sh
cd CrisisViz
./bundle.sh          # builds CrisisViz.app and opens it
# or:
./package-dmg.sh     # builds CrisisViz.dmg for distribution
```

Then arrow keys ←/→ to navigate, **Space** to play/pause, the bottom slider to scrub at any signed speed from $-16\times$ to $+16\times$.

---

## Where to read next

- **[INSTALL.md](INSTALL.md)** — clone-to-running on a fresh macOS box. Prerequisites, Python venv setup, Swift toolchain, regenerating sim data, running the agents demo, troubleshooting.
- **[src/crisis_agents/README.md](src/crisis_agents/README.md)** — the AI-agent coordination layer: architecture, six-phase walkthrough, decentralization principles, async event loop, quorum formula, live Claude mode, proof JSON shape.
- **[CrisisViz/README.md](CrisisViz/README.md)** — Swift-side guide: serial-timeline pattern, testbed outputs, controls, cast convention.
- **[CrisisViz/HANDOFF.md](CrisisViz/HANDOFF.md)** — engineering log for the next coding agent.

---

## License

- **Code** (`src/`, `tests/`, `CrisisViz/`) is licensed under the [MIT License](LICENSE).
- **Paper** (`Crisis.mirco-richter-2019.pdf`) by Mirco Richter is a separately licensed artifact under CC-BY-4.0.