Deployment patterns from local execution to autonomous systems
We provide here example code that implements a set of agentic capabilities of increasing sophistication, from local execution to governed, autonomous scientific systems.
The code makes use of two agent frameworks, packages that provide abstractions and runtime support to simplify the development and use of agents:
LangGraph offers structured, reproducible workflows for LLM-driven reasoning and tool execution. Good for managing interactions with LLMs and for implementing structured or auditable reasoning pipelines.
Academy provides persistent, secure, and scalable execution across HPC systems, instruments, and data services. Good for agents that must run continuously or securely on HPC systems, laboratory robots, data platforms, or other parts of federated DOE infrastructure.
See these slides for a brief review of these two systems, and one more, Microsoft Agent Framework.
LangGraph, Academy
Your on-ramp to CAF. Run persistent, stateful agents on a laptop or workstation—no federation required.
Status: Mature
LangGraph + Academy
Cross-institutional agent execution under federated identity and policy.
Status: Mature
LangGraph, Aegis
Fan out thousands of LLM requests in parallel on HPC.
Status: Prototype
Academy governance
Invoke expensive, stateful, or dangerous tools under proactive policy enforcement.
Status: WIP
Shared state + policy + budgets
Many agents under shared governance—within one institution or across many.
Status: Emerging
Lifecycle management
Agents that persist for days to months, maintaining state, memory, and goals.
Status: Emerging
Dynamic workflow construction
Agents dynamically construct, adapt, and execute scientific workflows.
Status: Early
| Level | Meaning |
|---|---|
| Mature | Documented with working examples on this site |
| Prototype | Demonstrated on DOE systems; documentation in progress |
| WIP | Work in progress |
| Emerging | Active development; early adopters welcome |
| Early | Early stage; design and prototyping |
| Stage | Capability | What you can do | CAF Components | Where it runs | Scale | Status |
|---|---|---|---|---|---|---|
| 1 | Local Agent Execution | Run persistent, stateful agents | LangGraph | Laptop, workstation, VM | Single agent | Mature |
| 2 | Federated Agent Execution | Invoke tools under federated identity | LangGraph + Academy | DOE HPC | Multi-resource | Mature |
| 3 | Parallel Agent Inference | Fan out thousands of LLM requests | LangGraph + FIRST | HPC accelerators | O(10³–10⁴) streams | Prototype |
| 4 | Governed Tool Use | Invoke tools under policy enforcement | Academy governance | DOE HPC | O(10²–10³) tools | WIP |
| 5 | Multi-Agent Coordination | Coordinate agents under shared governance | Shared state + policy | Distributed | O(10²–10³) agents | Emerging |
| 6 | Long-Lived Agents | Persistent agents with memory and goals | Lifecycle management | Any | Days–months | Emerging |
| 7 | Agent Workflows | Dynamic workflow construction | Workflow integration | DOE infrastructure | Varies | Early |