Skip to main content
Back to Prompt Library
implementation

LangGraph State Machine Setup

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: LangChain & All Hands AI Asset Management Compliance Suite

Format
Code-aware
Lines
13
Sections
4
Linked challenge
LangChain & All Hands AI Asset Management Compliance Suite

Prompt source

Original prompt text with formatting preserved for inspection.

13 lines
4 sections
No variables
0 checklist items
from typing import TypedDict, Annotated, List
from langgraph.graph import StateGraph, END

class AuditState(TypedDict):
    fund_data: dict
    violations: List[str]
    nodes_traversed: List[str]

def node_check_esg(state: AuditState):
    # Check ESG rules
    state['nodes_traversed'].append('check_esg')
    return state

workflow = StateGraph(AuditState)
workflow.add_node('check_esg', node_check_esg)
# Wire graph conditional edges here

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.