Lubu Labs
Official@lubu-labs · Poland
Offers architectural patterns and diagnostic frameworks for managing stateful multi-agent graph deployments and lifecycle governance.
Agent Skills by Lubu Labs
Showing 7 vetted skills indexed across 1 GitHub repositories.
Lubu-Labslanggraph-agent-patterns
Build and validate LangGraph multi-agent graphs with supervisor, router, orchestrator-worker, and handoff patterns.
Lubu-Labslanggraph-error-handling
Automate LangGraph error handling with RetryPolicy, ToolNode, and HITL interrupts.
Lubu-Labslangsmith-deployment
Deploy LangGraph agents via LangSmith Deployment across cloud, hybrid, and standalone environments.
Lubu-Labslanggraph-project-setup
Generate LangGraph project scaffolds with configuration and environment templates.
Lubu-Labsskill-creator
Create modular skills with SKILL.md frontmatter and starter resource directories.
Lubu-Labslanggraph-state-management
Design LangGraph state schemas, reducers, and persistence with TypedDict and MessagesState.
Lubu-Labslangsmith-trace-analyzer
Analyze LangSmith traces to generate Markdown or JSON diagnostics reports.
Frequently Asked Questions About Lubu Labs
FAQPage SchemaWhat specific architectural patterns does Lubu Labs support for graph construction?▼
Lubu Labs supports the implementation of supervisor, router, orchestrator-worker, and handoff patterns. These structures allow for the creation of complex, modular graph architectures that manage inter-node communication and task delegation effectively within stateful environments.
How does the organization handle runtime failures and human intervention?▼
Runtime failures are managed through RetryPolicy configurations and ToolNode integration. The framework supports HITL (Human-in-the-loop) interrupts, allowing developers to pause execution, inspect state, and manually intervene before resuming the graph execution flow.
What are the prerequisites for deploying these graph structures?▼
Deployment requires a configured environment using the provided project scaffolds and templates. Users must define state schemas using TypedDict and MessagesState to ensure compatibility with persistence layers and LangSmith deployment targets across cloud, hybrid, or standalone infrastructure.