CAX-Agent: Lightweight Agent Harness for Reliable APDL Automation
A recent publication on arXiv (2605.15218) presents CAX-Agent, a streamlined agent framework aimed at enhancing the dependability of MAPDL finite-element simulations through the use of large language models. This system tackles frequent failures stemming from unstructured execution by integrating domain-specific orchestration middleware that oversees tool lifecycles, workflow states, and fault recovery processes. CAX-Agent structures execution into three tiers: LLM service, agent harness, and solver backend. A recovery ladder progresses from deterministic rule adjustments to model-driven regeneration, context enrichment, and human intervention. The research assesses three recovery approaches—no_recovery, rule_only, and model_only—across 50 standard structural challenges.
Key facts
- CAX-Agent is a lightweight agent harness for MAPDL automation.
- It addresses reliability challenges in LLM-based finite-element simulations.
- The system uses a three-layer architecture: LLM service, agent harness, solver backend.
- A recovery ladder includes rule patching, model-driven regeneration, context enrichment, and human intervention.
- Three recovery strategies were evaluated: no_recovery, rule_only, and model_only.
- Evaluation was performed on 50 standard structural problems.
- The paper is available on arXiv with ID 2605.15218.
- The approach inserts domain-specific orchestration middleware.
Entities
Institutions
- arXiv