#17Map your components to the frameworksEasyAgentic AI
Map your components to the frameworks
Background
Everything you built from scratch has a name in production frameworks. When you open LangGraph or LangSmith, you'll recognise the parts:
| What you built | Framework equivalent |
|---|---|
LLMClient | BaseChatModel |
SearchTool | Tool |
Planner | node |
SharedMemory | state |
Critic | evaluator |
Orchestrator | StateGraph |
Tracer | LangSmith |
Problem statement
Implement framework_equivalent(component) returning the framework name for a built component.
Input
component— one of the lowercased names:"llmclient","searchtool","planner","sharedmemory","critic","orchestrator","tracer".
Output
Returns the framework equivalent string from the table above.
Examples
Input: "orchestrator" Output: "StateGraph"
Input: "sharedmemory" Output: "state"
Input: "tracer" Output: "LangSmith"
Constraints
- Map each component to its framework equivalent exactly.
Notes
- LangChain gives the parts, LangGraph wires them into a stateful loop, LangSmith traces — they package what you built.
Python
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▶ Run executes the 3 visible sample tests below in your browser. Submit runs the full suite — including hidden tests — on the server for an official verdict.
- •Reference example: orchestrator maps to StateGraph
- •Sample: sharedmemory maps to state
- •Reference: tracer maps to LangSmith