langflow_agentmesh 3.2.2

Governance components for Langflow — policy enforcement, trust routing, audit logging, and compliance checking for visual AI flows

langflow-agentmesh

Governance components for Langflow — policy enforcement, trust-based routing, audit logging, and compliance checking for visual AI flows.

Part of the AgentMesh ecosystem.

What This Does

Adds governance guardrails to Langflow flows as custom components. Each component can be dropped into a flow to enforce policies, route by trust, log decisions, and validate compliance — without writing code.

Component	Purpose	Key Feature
Governance Gate	Policy enforcement	Tool allowlist/blocklist, content pattern scanning
Trust Router	Trust-based routing	Three outputs: trusted / review / blocked
Audit Logger	Tamper-evident logging	SHA-256 hash chain, JSONL export
Compliance Checker	Framework validation	EU AI Act, SOC2, HIPAA

Install

pip install langflow-agentmesh

With Langflow:

pip install langflow-agentmesh[langflow]

Quick Start

Governance Gate

from langflow_agentmesh import GovernanceComponent

gate = GovernanceComponent(
    allowed_tools=["search", "read_file"],
    blocked_patterns=[("rm -rf", "substring"), (r".*password.*=.*", "regex")],
    max_calls=10,
)

result = gate.process(
    action="search",
    parameters={"query": "python tutorials"},
    agent_id="agent-1",
)
print(result.allowed)  # True

Trust Router

from langflow_agentmesh import TrustRouter

router = TrustRouter(trusted_threshold=0.7, review_threshold=0.3)

# Build trust through successful actions
router.record_success("agent-1", dimensions=["reliability", "security"])

# Route based on trust
result = router.route("agent-1", payload={"task": "deploy"})
print(result.decision.value)  # "review" or "trusted"

# Three outputs for Langflow flow branching
trusted_data = router.get_trusted_output(result)
review_data = router.get_review_output(result)
blocked_data = router.get_blocked_output(result)

Audit Logger

from langflow_agentmesh import AuditLogger

logger = AuditLogger()
logger.log("agent-1", "search", "allowed", context={"query": "data"})
logger.log("agent-2", "delete", "blocked", context={"reason": "policy"})

# Verify chain integrity
assert logger.verify_chain()

# Export for compliance
logger.export_jsonl_to_file("audit-trail.jsonl")

Compliance Checker

from langflow_agentmesh import ComplianceChecker, ComplianceFramework

checker = ComplianceChecker(frameworks=[
    ComplianceFramework.EU_AI_ACT,
    ComplianceFramework.SOC2,
    ComplianceFramework.HIPAA,
])

result = checker.check(
    action="classify",
    parameters={"data": "patient records"},
    agent_id="agent-1",
    context={"domain": "employment", "audit_enabled": True},
)

print(result.compliance_status.value)  # "requires_review"
for action in result.required_actions:
    print(f"  → {action}")

YAML Policy

# governance-policy.yaml
max_tool_calls_per_request: 10
confidence_threshold: 0.8
allowed_tools:
  - search
  - read_file
blocked_tools:
  - delete
  - drop
blocked_patterns:
  - pattern: "rm -rf"
    type: substring
  - pattern: ".*password.*=.*"
    type: regex

from langflow_agentmesh import GovernanceComponent

gate = GovernanceComponent(policy_yaml=open("governance-policy.yaml").read())

Example Langflow Flow

┌─────────────┐     ┌──────────────────┐     ┌──────────────┐
│  LLM Agent  │────▶│ Governance Gate  │────▶│ Trust Router  │
└─────────────┘     └──────────────────┘     └──┬───┬───┬───┘
                                                 │   │   │
                          ┌──────────────────────┘   │   └──────────┐
                          ▼                          ▼              ▼
                   ┌─────────────┐         ┌──────────────┐  ┌──────────┐
                   │  Tool Exec  │         │ Human Review │  │  Blocked │
                   └──────┬──────┘         └──────────────┘  └──────────┘
                          │
                          ▼
                   ┌─────────────────┐     ┌────────────────────┐
                   │  Audit Logger   │────▶│ Compliance Checker │
                   └─────────────────┘     └────────────────────┘

Compliance Frameworks

EU AI Act

• Article 5: Blocks unacceptable-risk AI practices (social scoring, subliminal manipulation)
• Article 13: Requires transparency notices for high-risk AI systems
• Article 14: Requires human oversight for high-risk domains (employment, education, law enforcement)

SOC2

• CC6.1: Requires agent identity for logical access control
• CC7.2: Requires audit logging for system monitoring
• CC8.1: Requires change approval for sensitive actions (delete, deploy, modify)

HIPAA

• §164.502: Detects PHI (SSN, MRN, DOB, email) and requires encryption
• §164.502(b): Enforces minimum necessary data scope
• §164.312(b): Requires access logging for PHI operations

License

Apache-2.0