# ACGS-Lite: Constitutional AI Governance for Agents

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**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

```python
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`):

```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

```bash
pip install acgs-lite
```

With framework integrations:

```bash
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`.

```python
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:

```python
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:

```python
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

```python
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

```python
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

```python
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

```python
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:

```bash
acgs serve --host 0.0.0.0 --port 8080
```

```python
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:

```bash
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

```python
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)

```python
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

```bash
# 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](https://acgs.ai/docs/quickstart) | Up and running in 5 minutes |
| [Architecture](https://acgs.ai/docs/architecture) | Engine internals, MACI deep dive |
| [Integrations](https://acgs.ai/docs/integrations) | OpenAI, Anthropic, LangChain, MCP, A2A |
| [Compliance](https://acgs.ai/docs/compliance-2026) | 18-framework regulatory mapping |
| [CLI Reference](https://acgs.ai/docs/cli) | Full command reference |
| [Why Governance?](https://acgs.ai/docs/why-governance) | The case for deterministic guardrails |
| [OWASP LLM Top 10](https://acgs.ai/docs/owasp-2026) | ACGS coverage of each risk |
| [Testing Guide](https://acgs.ai/docs/testing-governance) | Testing governed agents |

---

## 🤝 Contributing

We welcome contributions! See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

```bash
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](LICENSE) for details.

Commercial enterprise licences (SLA, support, air-gapped deployment) available at [acgs.ai](https://acgs.ai).

---

*Constitutional Hash: `608508a9bd224290` — embedded in every validation path.*
