Enterprise-grade Agent Platform SDK built on LangGraph principles (TOON + ZAD)
Project description
LangGraph Enterprise SDK
An enterprise-grade Agent Platform SDK inspired by LangGraph, built with TOON & ZAD principles, designed for governance, security, scalability, and multi-agent systems.
๐ Overview
LangGraph Enterprise SDK is a production-ready Agent Platform SDK that provides a governed, secure, and extensible foundation for building single-agent and multi-agent systems in enterprise and regulated environments.
This SDK does not replace LangGraph.
Instead, it hardens and operationalizes agent execution, adding the layers required for real-world production use.
๐ฏ Why This SDK Exists
Most agent frameworks are optimized for:
- Prototyping
- Demos
- Experiments
They are not sufficient for:
- Governance & compliance
- Multi-tenant isolation
- Long-running agents
- Human-in-the-loop workflows
- Deterministic replay & audit
- Security boundaries
- Enterprise DevOps & SRE operations
This SDK fills that gap.
๐ง Core Design Principles
1๏ธโฃ TOON โ Tool-Oriented Orchestration Nodes
- Nodes only orchestrate
- Tools perform side effects
- LLMs perform reasoning
- Clear separation of responsibilities
2๏ธโฃ ZAD โ Zero-Action Design
- No implicit state mutation
- No hidden side effects
- Deterministic execution
- Replayable workflows
3๏ธโฃ Enterprise-First Architecture
- Security & governance are first-class
- Observability is built-in
- Persistence & recovery are mandatory
- Protocols (A2A, MCP) are standards-based
๐งฉ High-Level Architecture
Client / UI
|
Server (Control Plane)
(Auth, Tenancy, Lifecycle)
|
Execution Runtime
(GraphExecutor, Scheduler)
|
Workflows
(Planner, Supervisor)
|
Nodes (TOON)
|
LLMs (Reasoning) ---- Tools (Side Effects)
๐ฆ Key Capabilities
โ Agent Execution
- Deterministic graph execution
- Retry & cancellation support
- Lifecycle hooks
- Streaming events
โ Multi-Agent Workflows
- Planner / Supervisor model
- Explicit delegation
- A2A-ready design
โ Governance
- Approval workflows
- Audit logging
- Compliance policies
- Quotas & rate limits
โ Security
- Authentication & Authorization
- RBAC
- Tenant & execution isolation
- Secrets abstraction
โ Persistence & Durability
- Checkpointing
- Snapshots (time-travel)
- Crash recovery
- Replay & resume
โ Memory & RAG
- Postgres / Redis memory
- pgvector / OpenSearch vector stores
- Embedding abstraction
โ Knowledge Graph
- Neo4j integration
- SOP / Runbook reasoning
- Dependency & impact analysis
โ LLM Abstraction
- OpenAI
- Azure OpenAI
- Anthropic
- Ollama
- LLaMA-cpp
- Groq
- Custom / on-prem models
โ MCP (Model Context Protocol)
- Tool invocation via protocol
- HTTP / stdio / WebSocket
- Secure metadata propagation
โ Observability
- Structured logging
- Metrics (Prometheus)
- Tracing (OpenTelemetry)
- Dashboard registry
๐ Project Structure
src/
โโโ api/
โโโ execution/
โโโ workflows/
โโโ tools/
โโโ llm/
โโโ memory/
โโโ graph_store/
โโโ mcp/
โโโ a2a/
โโโ governance/
โโโ security/
โโโ persistence/
โโโ streaming/
โโโ observability/
โโโ server/
โโโ utils/
โโโ connectors/
โ๏ธ Installation
Core SDK
pip install langgraph-enterprise-sdk
Full Enterprise Install
pip install "langgraph-enterprise-sdk[enterprise]"
LLM Providers
pip install "langgraph-enterprise-sdk[all-llms]"
๐งช Testing
Enterprise-grade test strategy:
tests/
โโโ unit/
โโโ integration/
โโโ security/
โโโ durability/
โโโ load/
Run all tests:
pytest
๐ Security Model
- Zero-trust by default
- AuthN โ AuthZ โ Policy โ Isolation โ Execution
- Tools are sandboxed
- No implicit privilege escalation
- Multi-tenant safe
๐ Relation to LangGraph
| LangGraph | This SDK |
|---|---|
| Graph execution | Deterministic runtime |
| Nodes | TOON-compliant nodes |
| State | Immutable ZAD state |
| Memory | Enterprise memory + RAG |
| Tools | Sandboxed & governed |
| Agents | Multi-agent workflows |
| Server | Control plane |
| Governance | Built-in |
LangGraph can be used inside this SDK but is not exposed directly to application teams.
๐ข Who Should Use This?
โ Platform Engineering Teams
โ Enterprise AI / GenAI Teams
โ Regulated Industries (Banking, Healthcare, Telecom)
โ DevSecOps & SRE Teams
โ Organizations building agent platforms, not just agents
๐ค Contributing
See CONTRIBUTING.md
๐ License
Apache 2.0 โ see LICENSE
๐ Final Note
This repository is not a demo.
It is a platform-grade foundation for building safe, scalable, enterprise AI agents.
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