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생산성 및 협업 · SKILL.md

workflow-engine

workflow-engine

Operate on BiSheng's LangGraph workflow DAG engine, workflow nodes, graph state, callbacks, interruptions, and Celery workflow execution.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: workflow-engine description: "Operate on BiSheng's LangGraph workflow DAG engine, workflow nodes, graph state, callbacks, interruptions, and Celery workflow execution." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

workflow-engine

Use this sub-skill when a task touches BiSheng visual workflow execution: LangGraph DAG compilation, node registration, GraphState variable passing, conditional edges, callbacks, streaming events, input/output interruptions, workflow Celery tasks, or adding/debugging workflow nodes.

Start here

Run bundled helper commands from this sub-skill directory, or adjust the script path to this directory after import.

  1. Inspect node registration without importing the backend:
    python scripts/inspect_workflow_nodes.py --repo-root <bisheng-checkout>
    
  2. Read references/workflows.md for GraphEngine, node, callback, and worker workflows.
  3. Read references/troubleshooting.md when execution, resume, fan-in, callback, or Celery behavior is unclear.

Owned responsibilities

  • src/backend/bisheng/workflow/common/node.py node type definitions and node data schemas.
  • workflow/nodes/node_manage.py node factory and NODE_CLASS_MAP registration.
  • workflow/graph/graph_engine.py, graph_state.py, and workflow.py graph compilation and execution.
  • workflow/edges/edges.py conditional routing, fan-in, and branch handling.
  • workflow/callback/ callback events and LLM streaming bridges.
  • src/backend/bisheng/worker/workflow/tasks.py and Redis callback behavior for async execution, continuation, and stop signals.
  • Tests under src/backend/test/workflow/ and workflow-related API/service tests.

Route sibling areas instead of duplicating them

  • Use frontend-apps for React workflow canvas UI, node panels, route guards, or request wrappers.
  • Use knowledge-rag for KnowledgeRetriever, QA retriever, RAG pipeline internals, and retrieval quality.
  • Use linsight-mcp for Linsight autonomous task-mode workflows, SOP/Skill runtime, and MCP tools.
  • Use identity-permissions-tenancy for workflow app visibility, app permissions, tenant filters, and cursor list permission scans.
  • Use backend-core for route/envelope/service-layer changes not specific to workflow execution.

Non-negotiables

  • Add a workflow node by updating the enum, node class, and factory map together.
  • Preserve GraphState variable reference semantics ({node_id}.{variable_key} and indexed suffixes) when changing node outputs.
  • Respect INPUT and interactive OUTPUT interruption/resume behavior; do not bypass LangGraph checkpoints casually.
  • Keep callback event payloads compatible with frontend streaming and persisted message expectations.
  • Do not run long workflow executions, external tools, or LLM calls as verification unless the environment and credentials are explicitly approved.
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