LangChain and LangGraph
LangChain is an open-source ecosystem for composing model calls, prompts, retrievers, tools, and output processing. LangGraph provides graph-based orchestration for stateful workflows and agents. Their APIs evolve quickly, so examples should be checked against the current official documentation.
Different Roles
LangChain offers integrations and reusable components. LangGraph represents a process as nodes, state, and transitions, including conditional and cyclic flows. A graph makes control flow explicit, but it does not automatically make an agent safe or reliable.
Design Guidance
- keep domain data models independent of framework-specific objects;
- define state fields and reducers deliberately;
- separate pure computation from side-effecting tools;
- bound loops and retries;
- make checkpoints and resume semantics explicit;
- test nodes and transitions without requiring a live model when possible;
- retain application-level authorization around tool execution.
Framework abstractions are useful when they reduce repeated integration work or make state transitions easier to inspect. A small direct implementation can be clearer for a short fixed pipeline. Select a framework after defining the control flow, not as a substitute for defining it.
Evaluation and Observability
Trace node inputs, typed outputs, tool results, errors, and final outcomes while redacting sensitive data. Evaluate the graph with simulated failures and deterministic test doubles. A successful node execution is not necessarily a successful user outcome.