deepmodeling
- 17 skills
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- 19 hours ago last updated
- ▌ Dpdata Plugin · deepmodelingCreate and install dpdata plugins (especially custom Format readers/writers) using Format.register(...) and pyproject.toml entry_points under 'dpdata.plugins'. Use when extending dpdata with new formats or distributing plugins as separate Python packages.
- ▌ Dpdisp Submit · deepmodelingRun Shell commands as computational jobs, on local machines or HPC clusters, through Shell, Slurm, PBS, LSF, Bohrium, etc. USE WHEN the user needs to submit batch jobs to a cluster, run commands on a remote server, execute tasks via job schedulers (Slurm, PBS, LSF), or safely run long-term/background shell commands that require state tracking and auto-recovery.
- ▌ Dpgen Run · deepmodeling bundlePrepare, explain, validate, and run DP-GEN concurrent-learning workflows using param.json and machine.json.
- ▌ Dpgen Simplify · deepmodeling bundlePrepare, explain, validate, and run DP-GEN simplify workflows for reducing repeated or redundant DeepMD datasets. Use when the user wants to generate or modify `param.json` and `machine.json`, run `dpgen simplify param.json machine.json`, organize repeated simplify experiments, or inspect simplify outputs.
- ▌ Deepmd Install · deepmodeling bundleInstall DeePMD-kit with pip, conda, dp1s, an offline package, Docker, or source code. Use for PyTorch, TensorFlow, JAX, or Paddle on CPU, CUDA, or ROCm, and for backend-enabled or backend-neutral C/C++ interfaces and DeePMD-enabled LAMMPS.
- ▌ Add Descriptor · deepmodeling bundleGuides through adding a new descriptor type to deepmd-kit. Covers implementing in dpmodel (array-API-compatible), wrapping for JAX/pt_expt backends, hard-coding for PT/PD, registering arguments, and writing all required tests.
- ▌ Debug Gradient Flow · deepmodeling bundleDiagnose gradient flow issues in training, especially for compiled models (torch.compile/make_fx). Systematically isolates which loss components (energy, force, virial) contribute gradients to which parameters, and identifies where the gradient chain breaks.
- ▌ Host Node · deepmodeling bundleOperate Uni-Lab host node via REST API — create resources, test latency, test resource tree, manual confirm. Use when the user mentions host_node, creating resources, resource management, testing latency, or any host node operation.
- ▌ Add Device · deepmodelingGuide for adding new devices to Uni-Lab-OS (接入新设备). Uses @device decorator + AST auto-scanning instead of manual YAML. Walks through device category, communication protocol, driver creation with decorators, and graph file setup. Use when the user wants to add/integrate a new device, create a device driver, write a device class, or mentions 接入设备/添加设备/设备驱动/物模型.
- ▌ Add Resource · deepmodeling bundleGuide for adding new resources (materials, bottles, carriers, decks, warehouses) to Uni-Lab-OS (添加新物料/资源). Uses @resource decorator for AST auto-scanning. Covers Bottle, Carrier, Deck, WareHouse definitions. Use when the user wants to add resources, define materials, create a deck layout, add bottles/carriers/plates, or mentions 物料/资源/resource/bottle/carrier/deck/plate/warehouse.
- ▌ Add Workstation · deepmodeling bundleGuide for adding new workstations to Uni-Lab-OS (接入新工作站). Uses @device decorator + AST auto-scanning. Walks through workstation type, sub-device composition, driver creation, deck setup, and graph file. Use when the user wants to add a workstation, create a workstation driver, configure a station with sub-devices, or mentions 工作站/工站/station/workstation.
- ▌ Virtual Workbench · deepmodeling bundleOperate Virtual Workbench via REST API — prepare materials, move to heating stations, start heating, move to output, transfer resources. Use when the user mentions virtual workbench, virtual_workbench, 虚拟工作台, heating stations, material processing, or workbench operations.
- ▌ Create Device Skill · deepmodeling bundleCreate a skill for any Uni-Lab device by extracting action schemas from the device registry. Use when the user wants to create a new device skill, add device API documentation, or set up action schemas for a device.
- ▌ Submit Agent Result · deepmodeling bundleSubmit historical experiment results (agent_result) to Uni-Lab cloud platform (leap-lab) notebook — read data files, assemble JSON payload, PUT to cloud API. Use when the user wants to submit experiment results, upload agent results, report experiment data, or mentions agent_result/实验结果/历史记录/notebook结果.
- ▌ Batch Insert Reagent · deepmodelingBatch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Use when the user wants to add reagents, insert chemicals, batch register reagents, or mentions 录入试剂/添加试剂/试剂入库/reagent.
- ▌ Batch Submit Experiment · deepmodeling bundleBatch submit experiments (notebooks) to the Uni-Lab cloud platform (leap-lab) — list workflows, generate node_params from registry schemas, submit multiple rounds, check notebook status. Use when the user wants to submit experiments, create notebooks, batch run workflows, check experiment status, or mentions 提交实验/批量实验/notebook/实验轮次/实验状态.
- ▌ Filter Workflow By Tags · deepmodeling bundleQuery backend workflow list, aggregate all tags, and filter workflows by domain/scenario requirements using tags. Use when the user wants to search workflows, find workflows by tags, list available workflow tags, filter workflows by category/domain/scenario, or mentions 工作流筛选/标签查询/workflow tags/按领域查找工作流.