用七角色协作自动构建化学流程模型，准确率达91.5%。
CRAFTS: Collaborative Role-Adaptive Fine-Tuning of LLM Agents for Chemical Process Simulation
- 分角色协作+确定性工程门控，逐阶段生成可执行流程模型。
- 在450例数据集上完成91.5%的验证与执行，连接准确率超78%。
- 适合自动化化学流程设计、仿真工程师及工业建模开发者。
构建可执行的化学流程模型仍高度依赖人工。工程师需将模糊需求转化为单元操作、热力学、流股、约束、自由度、初始化、求解修复和优化等耦合决策，任一错误即导致模型失效。CRAFTS 模拟化工工程师的分步工作流，将仿真构建分解为七个有边界的角色任务，并通过确定性的 IDAES/Pyomo 门控连接各阶段。给定自然语言请求、流程图（PFD）证据和工程知识库，输入理解与意图模块恢复需求、约束与过程语义；视觉、拓扑和规格专家将其转化为带类型标记的模拟器合约；调试与优化模块支持有限范围内的修复与合法优化。对三个关键角色（视觉、拓扑、规格）进行微调，其余角色使用未微调的 Qwen。生成的 VisualGraphIR、TopologyIR、SpecIR、BuildPlan 与 SolveReport 明确表达单元、端口、热力学、数值与执行决策。仅当语义产物通过工程门控后，才附加兼容构造器、物性包与运行器。引入 OpenIDAES-450，一个包含450个案例的IDAES流程仿真数据集，在其冻结的82例保留测试集上评估完整七角色 LangChain/LangGraph 工作流。CRAFTS 在91.5%的案例中完成预定验证与执行合同，单位、流股与有向连接的F1分数分别为0.815、0.791和0.782。结果证明角色专业化、类型化中间表示与确定性工程门控在可靠自动化流程建模中的有效性。
原文摘要 · Abstract (English)
Constructing an executable chemical-process model remains manually intensive. Chemical engineers translate underspecified requests into coupled decisions about unit operations, thermodynamics, streams, specifications, degrees of freedom (DoF), initialization, solver repair, and optimization; one error can invalidate the model. CRAFTS mirrors the staged workflow of chemical engineers by decomposing simulation building into bounded subtasks assigned to seven bounded roles, with deterministic IDAES/Pyomo gates between stages. Given a natural-language request, process flowsheet diagram (PFD) evidence, and curated chemical-engineering knowledge, Input Understanding and Intent recover requirements, constraints, and process semantics; visual, topology, and specification specialists translate them into typed simulator contracts; and Debug and Optimization support bounded repair and eligible optimization. Fine-tuning is applied to the three schema-critical visual, topology, and specification roles, while the remaining roles use untuned Qwen. The resulting VisualGraphIR, TopologyIR, SpecIR, BuildPlan, and SolveReport expose unit, port, thermodynamic, numerical, and execution decisions. Compatible constructors, property packages, and runners are attached only after semantic artifacts pass engineering gates. We introduce OpenIDAES-450, a 450-case IDAES process- simulation dataset, and evaluate the complete seven-role LangChain/LangGraph workflow through solve and eligible optimization on its frozen 82-case held-out split. CRAFTS completes the prescribed validation and execution contract for for 91.5% of cases and achieves unit, stream, and directed-connection F1 scores of 0.815, 0.791, and 0.782. These results demonstrate the effectiveness of role specialization, typed intermediate representations, and deterministic engineering gates for reliable automated process-model construction.
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