Constitutional AI governance for agents — enforce rules, audit decisions, MACI role separation, formal verification, and 18-framework compliance coverage.
Project description
ACGS-Lite: Constitutional AI Governance for Agents
The missing safety layer between your LLM and production.
acgs-lite is a deterministic governance engine for AI agents. Define rules in YAML, enforce them at runtime with MACI role separation, and prove compliance with tamper-evident audit trails. Every action is validated before it executes — violations are blocked, not just logged.
🚀 5-Line Quickstart
from acgs_lite import Constitution, GovernedAgent
constitution = Constitution.from_yaml("constitution.yaml")
agent = GovernedAgent(my_llm_agent, constitution=constitution)
result = agent.run("Process this high-risk transaction")
Rules in YAML (constitution.yaml):
constitutional_hash: "608508a9bd224290"
rules:
- id: no-pii
pattern: "SSN|social security|passport number"
severity: CRITICAL
description: Block PII exposure
- id: no-destructive
pattern: "delete|drop table|rm -rf"
severity: HIGH
description: Block destructive operations
- id: require-approval
pattern: "transfer|payment|wire"
severity: HIGH
description: Financial actions require human approval
📦 Installation
pip install acgs-lite
With framework integrations:
pip install "acgs-lite[openai]" # OpenAI
pip install "acgs-lite[anthropic]" # Anthropic Claude
pip install "acgs-lite[langchain]" # LangChain / LangGraph
pip install "acgs-lite[mcp]" # Model Context Protocol server
pip install "acgs-lite[autogen]" # AutoGen / AG2
pip install "acgs-lite[a2a]" # Google A2A protocol
pip install "acgs-lite[all]" # All integrations
🛡️ Core Concepts
Governance Engine
The GovernanceEngine sits between your agent and its tools. Every action passes through it before execution. Matching rules block or flag the action; the result is an immutable ValidationResult.
from acgs_lite import Constitution, GovernanceEngine, Rule, Severity
constitution = Constitution.from_rules([
Rule(id="no-pii", pattern=r"SSN|\bpassport\b", severity=Severity.CRITICAL),
Rule(id="no-delete", pattern=r"\bdelete\b|\bdrop\b", severity=Severity.HIGH),
])
engine = GovernanceEngine(constitution)
result = engine.validate("summarize the quarterly report", agent_id="analyst-01")
if not result.valid:
for v in result.violations:
print(f"[{v.severity}] {v.rule_id}: {v.description}")
MACI — Separation of Powers
MACI prevents a single agent from proposing, validating, and executing the same action:
from acgs_lite import MACIEnforcer, MACIRole
enforcer = MACIEnforcer()
# Assign roles
enforcer.assign(agent_id="planner", role=MACIRole.PROPOSER)
enforcer.assign(agent_id="reviewer", role=MACIRole.VALIDATOR)
enforcer.assign(agent_id="executor", role=MACIRole.EXECUTOR)
# Proposer creates; Validator checks; Executor runs — never the same agent
proposal = enforcer.propose("planner", action="deploy v2.1 to production")
approval = enforcer.validate("reviewer", proposal)
enforcer.execute("executor", approval)
Tamper-Evident Audit Trail
Every governance decision is written to an append-only, SHA-256-chained log:
from acgs_lite import AuditLog
log = AuditLog()
engine = GovernanceEngine(constitution, audit_log=log)
engine.validate("send email to user@example.com", agent_id="mailer")
for entry in log.entries():
print(entry.id, entry.valid, entry.constitutional_hash)
# Verify chain integrity
assert log.verify_chain(), "Audit log tampered!"
GovernedAgent — Drop-in Wrapper
from acgs_lite import Constitution, GovernedAgent
@GovernedAgent.decorate(constitution=constitution, agent_id="summarizer")
def summarize(text: str) -> str:
return my_llm.complete(f"Summarize: {text}")
# Raises ConstitutionalViolationError if text contains violations
result = summarize("Q4 revenue was $4.2M")
🌐 Integrations
OpenAI
from acgs_lite.integrations.openai import GovernedOpenAI
from openai import OpenAI
client = GovernedOpenAI(OpenAI(), constitution=constitution)
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Analyze the contract"}],
)
Anthropic Claude
from acgs_lite.integrations.anthropic import GovernedAnthropic
import anthropic
client = GovernedAnthropic(anthropic.Anthropic(), constitution=constitution)
message = client.messages.create(
model="claude-opus-4-5",
max_tokens=1024,
messages=[{"role": "user", "content": "Review this code"}],
)
LangChain
from acgs_lite.integrations.langchain import GovernanceRunnable
from langchain_openai import ChatOpenAI
governed_llm = GovernanceRunnable(
ChatOpenAI(model="gpt-4o"),
constitution=constitution,
)
result = governed_llm.invoke("Translate this document")
MCP Server
Start a governance server that any MCP-compatible agent can query:
acgs serve --host 0.0.0.0 --port 8080
from acgs_lite.integrations.mcp_server import create_mcp_server
app = create_mcp_server(constitution=constitution)
📋 Compliance Coverage
ACGS maps governance controls to 18 regulatory frameworks. Run acgs assess to generate a compliance report:
acgs assess --framework eu-ai-act --output report.pdf
| Framework | Coverage | Key Controls |
|---|---|---|
| EU AI Act (High-Risk) | Art. 9, 10, 13, 14, 17 | Risk management, human oversight, transparency |
| NIST AI RMF | 7 / 16 functions | Govern, Map, Measure, Manage |
| SOC 2 + AI | 10 / 16 criteria | CC6, CC7, CC9 trust service criteria |
| HIPAA + AI | 9 / 15 safeguards | PHI detection, access controls, audit controls |
| GDPR Art. 22 | 10 / 12 requirements | Automated decision-making, right to explanation |
| CCPA / CPRA | 8 / 10 rights | Opt-out, data minimisation, transparency |
| ISO 42001 | Clause 6, 8, 9, 10 | AI management system controls |
| OWASP LLM Top 10 | 9 / 10 risks | Prompt injection, insecure output, data poisoning |
🔬 Advanced: Formal Verification
For the highest-risk scenarios, ACGS supports mathematical proof of safety properties.
Z3 SMT Solver
from acgs_lite.integrations.z3_verifier import Z3ConstraintVerifier
verifier = Z3ConstraintVerifier()
result = verifier.verify(
action="transfer $50,000 to external account",
constraints=["amount <= 10000", "recipient in approved_list"],
)
print(result.satisfiable, result.counterexample)
Lean 4 Proof Certificates (Leanstral)
from acgs_lite import LeanstralVerifier
verifier = LeanstralVerifier() # requires mistralai extra
certificate = await verifier.verify(
property="∀ action : Action, action.amount ≤ 10000",
context={"action": "transfer $5,000"},
)
print(certificate.kernel_verified) # True only if Lean kernel accepted proof
print(certificate.to_audit_dict()) # attach to AuditEntry
⚡ Performance
| Operation | Latency | Notes |
|---|---|---|
| Rule validation (Python) | < 1 ms | Aho-Corasick multi-pattern |
| Rule validation (Rust) | ~560 ns | Optional Rust extension |
| Engine batch (100 rules) | ~2 ms | Parallel severity evaluation |
| Audit write (JSONL) | ~50 µs | Append-only, SHA-256 chained |
| Compliance report | < 500 ms | 18 frameworks, cached |
🖥️ CLI
# Validate a single action
acgs validate "send email to user@corp.com" --constitution rules.yaml
# Run governance status check
acgs status
# Generate compliance report
acgs assess --framework hipaa --output hipaa_report.pdf
# Audit log inspection
acgs audit --tail 20
acgs audit --verify-chain
# Start MCP governance server
acgs serve --port 8080
# EU AI Act Art. 14(3) kill switch
acgs halt --agent-id agent-01 --reason "anomalous behaviour detected"
acgs resume --agent-id agent-01
📖 Documentation
| Guide | Description |
|---|---|
| Quickstart | Up and running in 5 minutes |
| Architecture | Engine internals, MACI deep dive |
| Integrations | OpenAI, Anthropic, LangChain, MCP, A2A |
| Compliance | 18-framework regulatory mapping |
| CLI Reference | Full command reference |
| Why Governance? | The case for deterministic guardrails |
| OWASP LLM Top 10 | ACGS coverage of each risk |
| Testing Guide | Testing governed agents |
🤝 Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
git clone https://github.com/dislovelhl/acgs-lite
cd acgs-lite/packages/acgs-lite
pip install -e ".[dev]"
pytest tests/ --import-mode=importlib
📄 License
Apache-2.0. See LICENSE for details.
Commercial enterprise licences (SLA, support, air-gapped deployment) available at acgs.ai.
Constitutional Hash: 608508a9bd224290 — embedded in every validation path.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file acgs_lite-2.7.2.tar.gz.
File metadata
- Download URL: acgs_lite-2.7.2.tar.gz
- Upload date:
- Size: 987.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
da35e0de26e72d407cd0619e764468295b89814978267520f49e61f800db7e0e
|
|
| MD5 |
c2c0327221eace94f8406f8fb0ebcaf5
|
|
| BLAKE2b-256 |
7a98c04d79eee761d96446f0f3bba87ca8377471e5d19349849ebd0ffc0d7a5c
|
Provenance
The following attestation bundles were made for acgs_lite-2.7.2.tar.gz:
Publisher:
publish.yml on dislovelhl/acgs-lite
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
acgs_lite-2.7.2.tar.gz -
Subject digest:
da35e0de26e72d407cd0619e764468295b89814978267520f49e61f800db7e0e - Sigstore transparency entry: 1260563953
- Sigstore integration time:
-
Permalink:
dislovelhl/acgs-lite@cea22e90728213b63832f3699e2f0f1a81bd2498 -
Branch / Tag:
refs/tags/v2.7.2 - Owner: https://github.com/dislovelhl
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@cea22e90728213b63832f3699e2f0f1a81bd2498 -
Trigger Event:
release
-
Statement type:
File details
Details for the file acgs_lite-2.7.2-py3-none-any.whl.
File metadata
- Download URL: acgs_lite-2.7.2-py3-none-any.whl
- Upload date:
- Size: 776.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
54f42383eccad78f23f8ebd9668817babe810eae5663d8ede6bbd29eaee24673
|
|
| MD5 |
7aa0052a43e430b7b1c7f4ae653716fe
|
|
| BLAKE2b-256 |
6a8f319a63ad0b5484d3b8201a39d4472cd51f7f512c7de2f5f1173bbb3b521e
|
Provenance
The following attestation bundles were made for acgs_lite-2.7.2-py3-none-any.whl:
Publisher:
publish.yml on dislovelhl/acgs-lite
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
acgs_lite-2.7.2-py3-none-any.whl -
Subject digest:
54f42383eccad78f23f8ebd9668817babe810eae5663d8ede6bbd29eaee24673 - Sigstore transparency entry: 1260563954
- Sigstore integration time:
-
Permalink:
dislovelhl/acgs-lite@cea22e90728213b63832f3699e2f0f1a81bd2498 -
Branch / Tag:
refs/tags/v2.7.2 - Owner: https://github.com/dislovelhl
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@cea22e90728213b63832f3699e2f0f1a81bd2498 -
Trigger Event:
release
-
Statement type: