The Governance-First Framework for Agentic AI
Project description
govAgent: Enterprise-Grade AI Governance Framework
The Governance-First Framework for Production-Grade Autonomous Systems.
GovAgent provides a high-abstraction Control Plane for agentic AI. With a clear chain of accountability, this lightweight framework helps move autonomous systems from experimental sandboxes into governed, production environments.
The v0.4.3 "Sovereign Swarm" update introduces Recursive Fiscal Control and Cloud SOC Integration, allowing for the deployment of multi-agent swarms with penny-accurate cost tracking and immutable forensic audit trails.
⚡ 60-Second Quickstart: Institutional Sovereignty
Achieve Article 12 and 14 compliance in three commands. This setup orchestrates a containerized environment with native support for AWS CloudWatch, Pydantic V2 validation, and Recursive TCO tracking.
- Initialize the Control Plane Ensure your .env file contains your OPENAI_API_KEY and Slack credentials in the root directory.
# Clone the Sovereign Repository
git clone https://github.com/thekakodkar/govagent.git
cd govagent
# Launch the Governed Container Stack
docker-compose up -d
- Verify the Governance Loop Execute the Institutional Demo to witness real-time PII redaction and fiscal gating.
docker-compose exec govagent-demo python examples/demo.py
🏗️ Core Pillars: The Chain of Accountability
GovAgent replaces "Black Box" reasoning with a transparent, governed loop:
- Policy (The Law): Declarative boundaries and "Rules of Engagement" defined by stakeholders in
policy.yaml. - Guards (The Enforcement): Real-time circuit breakers that intercept agent intent before API execution to prevent budget or security breaches.
- HITL (The Judiciary): Synchronous Human-in-the-Loop escalation. High-risk actions are physically blocked until an explicit "Approve" or "Reject" signal is received via Slack or CLI.
- Telemetry (The Evidence): Forensic-grade audit trails providing an immutable ledger of compliance and real-world ROI.
⚖️ Comparative Analysis: Governance Superiority
In an institutional setting, "State Management" is insufficient—you need Sovereignty. GovAgent is engineered to meet the specific requirements of Big 4 audit and compliance, transforming "Black Box" reasoning into a transparent, governed lifecycle.
| Feature | GovAgent | LangGraph | CrewAI |
|---|---|---|---|
| Policy Enforcement | ✅ Deterministic Enforcement | ⚠️ Partial / Manual | ❌ None |
| Audit Trails | ✅ Cloud SOC (AWS/Azure) | ⚠️ Local / LangSmith | ❌ Console Logs |
| Human Approval Gates | ✅ Synchronous & Blocking | ⚠️ Manual Interrupts | ❌ Optional |
| Recursive TCO Tracking | ✅ Aggregated Swarm Cost | ❌ Per-run only | ❌ None |
| Enterprise Governance | ✅ EU AI Act Ready | ❌ Experimental | ❌ Experimental |
Strategic Directive: While LangGraph and CrewAI focus on agent capability and roleplay, GovAgent operates as the Institutional Control Plane that ensures every action is legislated, evaluated, and forensically recorded.
⚖️ Regulatory Compliance: EU AI Act (Regulation 2024/1689)
GovAgent satisfies key transparency and oversight mandates for High-Risk AI Systems:
- Article 9: Risk Management & Privacy Automated PII redaction (Stage 0) and policy-driven intent interception.
- Article 12: Record-Keeping & Traceability Immutable Forensic Telemetry with native cloud exporters and recursive
parent_trace_idtracking. - Article 14: Human Oversight Physical gating of high-risk actions through synchronous human authorization.
🛠️ Key Capabilities (v0.4.0)
- 💸 Recursive Fiscal Ceilings: Aggregate TCO (Total Cost of Operation) tracking across parent and sub-agents to prevent budget fragmentation.
- ☁️ Cloud-Native SOC: Native telemetry exporters for AWS CloudWatch and Azure Monitor.
- 🛡️ Article 9 Privacy Guard: Stage 0 PII scrubbing before tasks reach the LLM.
- 📐 Type-Safe Intent: Pydantic-hardened tool parameters for deterministic integrity.
📖 Advanced Usage: High-Abstraction Governance
In an enterprise environment, GovAgent acts as your digital "Control Plane" for high-stakes workflows like healthcare claim processing.
1. Define a Governed tool (Pillars 2 & 3)
from govagent import tool
@tool(name="execute_financial_transaction", guards=["fiscal", "judiciary"], risk_level="high")
async def process_payment(amount: float, reference_id: str):
"""
Executes a financial disbursement.
Injected guards handle Recursive TCO and Judiciary gating automatically.
"""
return f"SUCCESS: Paid ${amount} for Ref: {reference_id}"
2. The Institutional session (Pillars 1, 4 & Cloud SOC)
import asyncio
import os
from langchain_openai import ChatOpenAI
from govagent import ExecutiveAgent
from govagent.exporters.cloudwatch import CloudWatchExporter
async def run_governed_session():
# 1. Load Policy (Pillar 1) & Initialize Session
agent = ExecutiveAgent.bootstrap(
policy_path="policies/finance_policy.yaml",
llm=ChatOpenAI(model="gpt-4o"),
slack_channel="C12345" # Synchronous Judiciary Link
)
# 2. Enroll Cloud SOC (Pillar 4 - Phase 3)
# Dispatches forensic evidence to AWS CloudWatch in real-time
agent.telemetry.add_exporter(CloudWatchExporter(log_group="/aws/govagent/audit"))
# 3. Execution (Stage 0 Privacy & Stage 2 Fiscal)
task = "Process a reimbursement for John Doe in the amount of $1200."
report = await agent.execute(task)
# 4. Institutional Audit Report
print(f"🏁 Session Status: {report.status.upper()}")
print(f"💰 Recursive Swarm TCO: ${report.recursive_tco_usd:.4f}")
print(f"🆔 Global Trace ID: {report.trace_id}")
📊 Forensic Telemetry: Article 12 Readiness
Every session generates an immutable snapshot dispatched to your enrolled cloud SOC or stored locally in /logs/audit_trail.jsonl.
{
"timestamp": "2026-05-07T15:30:00Z",
"trace_id": "exec-882-9934",
"parent_trace_id": "director-main-771",
"persona": "Healthcare Finance Director",
"task": "Process claim #882 for $1200.00",
"status": "SUCCESS: TRANSACTION FINALIZED",
"guards_evaluated": ["privacy", "fiscal", "policy", "judiciary"],
"metrics": {
"tokens": 850,
"individual_cost_usd": 0.012,
"recursive_tco_usd": 0.045,
"pii_entities_redacted": 2
},
"judiciary_audit": {
"approver": "U12345 (Slack)",
"decision": "APPROVED",
"timestamp": "2026-05-07T15:28:45Z"
}
}
🗺️ Strategic Roadmap
✅ v0.4.0: The Sovereign Swarm (Current)
- Cloud Exporters: AWS/Azure telemetry sinks.
- Recursive TCO: Shared fiscal context for multi-agent swarms.
- Privacy Guard: Stage 0 PII redaction.
🚀 v0.5.0: The Federated Judiciary (Next)
- Multi-Party Approval: M-of-N consensus for ultra-high-risk financial moves.
- Semantic Policy Alignment: Vector-based guardrails for qualitative boundaries.
- Self-Healing Telemetry: Automated retry logic for failed cloud SOC dispatches.
⚙️ Installation
GovAgent is designed to be lightweight and modular. You can install the core framework or include specific integrations as needed.
1. Core Installation (Lightweight)
Recommended for users building custom agents or those who only require the Judiciary and Policy layers.
pip install govagent
2. Full Integration (With LangChain)
Includes all dependencies required to run governed LangChain sessions, including the langchain_tool wrappers and OpenAI clients.
pip install "govagent[langchain]"
3. Development Installation
If you are contributing to the framework or running the examples in this repository, install in editable mode:
git clone [https://github.com/thekakodkar/govagent.git](https://github.com/thekakodkar/govagent.git)
cd govagent
pip install -e ".[langchain]"
🚀 Quick Setup
Ensure your .env file is configured with the necessary tokens for the Judiciary Layer to function:
Code snippet
Slack Credentials (Socket Mode)
SLACK_BOT_TOKEN=xoxb-your-token SLACK_APP_TOKEN=xapp-your-token SLACK_CHANNEL_ID=C12345678
Model Provider
OPENAI_API_KEY=sk-your-key
"Governance is not a constraint; it is the catalyst for enterprise AI adoption."
Author Stamp
- Framework: GovAgent v0.4.3 (Stable)
- Status: Active / Open-Source Standard
- Compliance: Designed for Enterprise-Grade Accountability
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 govagent-0.4.3.tar.gz.
File metadata
- Download URL: govagent-0.4.3.tar.gz
- Upload date:
- Size: 50.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4b186932b1e6cfa7de5ec35cf6da50362fb11c3a7d1f3e73dbdad047b984f07e
|
|
| MD5 |
90eb99366b0b0b897ae04d5852bbc27d
|
|
| BLAKE2b-256 |
bc7d738459f854a22858334c4bd3dadfac4311ef30cca4f63d5a0ad9ec0f6189
|
File details
Details for the file govagent-0.4.3-py3-none-any.whl.
File metadata
- Download URL: govagent-0.4.3-py3-none-any.whl
- Upload date:
- Size: 23.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.11.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8b179091a20411085f3cb137100e057ac901e2aa3f093656cb30279d5c89ecd9
|
|
| MD5 |
0a3308311342795e9f2d37862abc5f02
|
|
| BLAKE2b-256 |
73537ba5b15d129b9804eaceb393fc94e7c5d62a62b2574128cc1d57203c49d4
|