A Python reference implementation of the Agent Deliberation Protocol (ADP) specification — the consensus protocol that multi-agent systems use to reach calibrated, falsifiable decisions together. ADP defines proposals, weights, tallies, falsification, termination, and reversibility tiers.
This library is one of several reference implementations (TypeScript) of the same spec. The spec itself is at adp-manifest.dev and is the source of truth; this library implements what the spec says.
Zero runtime dependencies. Requires Python 3.10+.
Looking for a runnable agent? This library is the protocol core — data types, weighting math, and an in-memory orchestrator. For a full federation-ready agent runtime with HTTP endpoints, journal persistence, Ed25519 signing, signed calibration snapshots, ACB pricing, and MCP integration, install
@ai-manifests/adp-agent(TypeScript/Node).
pip install adp-manifestOr from source:
git clone https://github.com/ai-manifests/adp-ref-lib-py.git
cd adp-ref-lib-py
pip install -e .from adp_manifest import (
DeliberationOrchestrator,
DeliberationConfig,
Proposal,
Stake,
Justification,
Vote,
StakeMagnitude,
CalibrationScore,
compute_weight,
)
proposal = Proposal(
agent_id="did:adp:test-runner-v1",
domain="code.correctness",
vote=Vote.APPROVE,
confidence=0.82,
stake=Stake(magnitude=StakeMagnitude.MEDIUM, domain="code.correctness"),
justification=Justification(rationale="all tests pass", evidence_refs=[]),
dissent_conditions=[],
)
calibration = CalibrationScore(value=0.78, sample_size=42)
weight = compute_weight(proposal, calibration)
# weight ≈ 0.82 × 0.78 × stake_factor(MEDIUM) × sample_size_discount(42)All public symbols are exported from the adp_manifest package root.
Vote, ReversibilityTier, DissentConditionStatus, TerminationState, StakeMagnitude
Proposal, ProposalAction, BlastRadius, DomainClaim, Justification, Stake, DissentCondition, VoteRevision, Amendment, CalibrationScore, AgentRegistration, TallyResult
compute_weight(proposal, calibration)— canonical proposal weight per ADP §4.2compute_decay(age, half_life)— time decay of calibration evidencestake_factor(magnitude)— mapsStakeMagnitudeto its numeric factorapply_sample_size_discount(weight, n)— Wilson-interval sample-size discount
DeliberationOrchestrator— in-memory state machine that runs a deliberation through proposal → tally → falsification → termination. Takes aDeliberationConfig. Intended for prototypes, tests, and embedded-in-process use. For production distributed deliberation, see@ai-manifests/adp-agent(TypeScript/Node).
pip install -e .[dev]
pytestThis library implements the Agent Deliberation Protocol specification. Read the spec at adp-manifest.dev. If the spec and this library disagree, the spec is correct and this is a bug.
Apache-2.0 — see LICENSE for the full license text and NOTICE for attribution.