Crisis BFT consensus protocol — Go PoC, Python recorder, and CrisisViz: a native macOS scrubbable curriculum visualizer (10 chapters, ~18 minutes at 1×, signed-speed slider with reverse playback).
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saymrwulf 0976239ebd crisis_agents: drop the wall-clock, drive asynchronously to quiescence
The previous driver imposed a synchronous turn-counted clock that the
Crisis paper explicitly forbids — Crisis is supposed to work in
asynchronous P2P networks, with any synchronicity being virtual and
derived inside the consensus algorithm from the DAG structure, not
imposed externally by a coordinator. This commit removes the wall clock.

What changed in the engine:

  - `Mothership.run_crisis_phase(num_turns, gossip_rounds_per_turn)`
    is replaced by `run_until_quiescent(max_steps=200)`. The loop
    interleaves three concerns on each iteration — emissions, gossip,
    and alarm emissions — until none make progress. Termination is by
    quiescence, not by a fixed turn count. `max_steps` is a safety
    bound (loop-iteration cap), not an exposed clock.

  - `Mothership.run_closed_phase(num_turns)` becomes
    `run_closed_phase(max_steps=50)`. Same quiescence model — the
    closed-phase conversation runs until no agent has more to say.

  - Agents grew `pending_alarm_claims()`: each agent checks its own
    graph for un-alarmed mutations and produces AlarmClaims directly.
    The driver loop calls this every iteration, so alarms emit and
    propagate in the same loop as regular emissions and gossip — no
    separate "alarm phase."

  - `Mothership.emit_alarms_from_detectors()` and the explicit
    `run_gossip_round()` step are no longer needed by callers; both
    are subsumed by the async loop. `run_gossip_round()` stays as a
    helper but tests no longer call it externally.

What changed in the agent interface:

  - `CrisisAgent.next_turn(turn, received_claims)` becomes
    `try_emit()` — no arguments. Agents in an async network don't see
    a global tick. They decide based on their own internal state.

  - `CrisisAgent.observe(claim)` is the new optional callback the
    closed-phase loop uses to feed context into agents that care
    (overridden by LiveClaudeAgent to populate its prompt buffer).

  - `pending_alarm_claims()` is idempotent: an internal
    `_already_alarmed` set tracks claims this agent has emitted, so
    the loop calls it every step without flooding the network with
    duplicate alarms.

What changed in the dataclass schema:

  - `AlarmClaim.detected_at_turn` -> `emitted_at_step`. The word
    "turn" implies a global clock; "step" is a per-agent sequence
    number used only for log ordering — local, not networked.

  - `ClosedPhaseEntry.turn` and `CrisisPhaseEntry.turn` -> `step`.
    Same rename, same reasoning.

  - `Scenario.closed_phase_turns` and `Scenario.crisis_phase_turns`
    are gone. The scenario no longer prescribes how many turns; it
    just provides agents and lets the async loop run them out.

What changed in the CLI:

  - Phase 3 reports "drove to quiescence in N step(s)" with a
    breakdown of regular emissions / gossip transfers / alarm
    emissions, instead of "ran N turns".

  - `QuiescenceReport` (new dataclass) carries the run statistics
    back from `run_until_quiescent`/`run_closed_phase` — steps taken,
    emissions made, gossip transfers, alarm claims emitted, plus
    whether termination was via quiescence or max-step cap.

New regression tests (`test_async_quiescence.py`):

  - `test_run_until_quiescent_terminates`: the loop must exit.
  - `test_two_runs_produce_identical_final_state`: determinism check —
    if anything in the loop depended on real wall time, this would
    fail.
  - `test_max_steps_bound_caps_runtime`: setting max_steps=1 exits
    immediately and `QuiescenceReport.reached_quiescence` reflects
    reality.
  - `test_no_turn_argument_exposed_to_agents`: introspects
    `CrisisAgent.try_emit` signature; fails if anyone re-adds a
    `turn` parameter.
  - `test_no_turn_field_on_alarmclaim`: introspects the dataclass
    fields; fails if `detected_at_turn` reappears.
  - `test_alarms_propagate_through_async_loop_alone`: the loop alone
    (no manual emit_alarms / run_gossip_round) ratifies an alarm.
  - `test_quiescence_report_counts_match_logs`: sanity check that
    the report's emission count equals the crisis log length.

Suite: 163 -> 170 tests, all green in 0.79s.

Behavioral end-state is identical to the previous (synchronous)
version: same fact-check scenario, same byzantine equivocation, same
proof JSON shape, same three signers, same quorum-met outcome. The
difference is structural: the protocol now matches the paper's async
shape, and a future port to actual TCP gossip + concurrent agents
needs no change to this engine.

CrisisViz: still untouched. The `crisis_data.json` pipeline that
drives the visualizer is orthogonal.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-14 22:06:56 +02:00
CrisisViz Add CrisisViz/package-dmg.sh — distributable DMG installer 2026-05-14 15:52:14 +02:00
src crisis_agents: drop the wall-clock, drive asynchronously to quiescence 2026-05-14 22:06:56 +02:00
tests crisis_agents: drop the wall-clock, drive asynchronously to quiescence 2026-05-14 22:06:56 +02:00
.gitignore Add macOS .app bundle with native Dock icon and activation policy 2026-04-30 20:21:18 +02:00
Crisis.mirco-richter-2019.pdf Initial implementation of the Crisis protocol (Richter, 2019) 2026-04-23 13:20:30 +02:00
crisis_data.json Add JSON export pipeline + event recorder for visualization 2026-04-30 20:06:21 +02:00
INSTALL.md Add INSTALL.md — clone-to-running on a fresh macOS box 2026-05-14 15:51:39 +02:00
LICENSE Add MIT LICENSE; align pyproject.toml accordingly 2026-05-14 15:51:19 +02:00
pyproject.toml Add crisis_agents — Crisis as a coordination layer for AI agent teams 2026-05-14 16:38:11 +02:00
README.md Rewrite parent README — five-layer architecture + audience-shaped quick start 2026-05-14 15:51:31 +02:00

crisis

A proof-of-concept and educational artifact for Mirco Richter's Crisis paper — 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/, 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: cast intro, gossip mechanics, partition, round derivation, virtual voting, leader election, total order, the data-availability problem, erasure-coded recovery, and Byzantine fork detection.

Everything in the visualizer is in extreme slow motion and serialized for didactic clarity. A signed speed slider scrubs the 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

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

    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

    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

    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 rec fill:#cfe2f3,stroke:#2c5f8f,color:#062b4d
    classDef viz fill:#ead1dc,stroke:#741b47,color:#3d0a26
    class Paper paper
    class Algos pure
    class RealRT real
    class SimRT sim
    class Rec,Export rec
    class Viz viz

Key architectural fact — the recording pipeline that feeds CrisisViz only exercises the SimulatedNode path (in-process, deterministic, in-memory message passing). The CrisisNode TCP runtime is a separately developed PoC of how a real network deployment would look; it is not what produces crisis_data.json. The two runtimes are siblings, not layers.


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
├── tests/                                     pytest suite
│
└── 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

There are three audiences. Pick the one that matches what you want to do.

🧮 Verify the protocol — pytest

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

Runs the algorithm unit tests (crypto, graph, rounds, weight, message, order, voting, recorder, simulation). Should be green in under a second.

🧪 Run a deterministic simulation — Python CLI

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:

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

🎬 Watch the visualizer — Swift / macOS

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.


  • INSTALL.md — clone-to-running on a fresh macOS box. Prerequisites, Python venv setup, Swift toolchain, regenerating sim data, troubleshooting.
  • CrisisViz/README.md — Swift-side guide: serial-timeline pattern, testbed outputs, controls, cast convention.
  • CrisisViz/HANDOFF.md — engineering log for the next coding agent: current state, architecture pointers, hard-won rules.

License

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