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Construct LangGraph Prior-Authorization Workflow

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

Linked challenge: Prior-Authorization Oncology Review Agent using LangChain and Llama 3.3 70B

Format
Code-aware
Lines
11
Sections
3
Linked challenge
Prior-Authorization Oncology Review Agent using LangChain and Llama 3.3 70B

Prompt source

Original prompt text with formatting preserved for inspection.

11 lines
3 sections
No variables
0 checklist items
from langgraph.graph import StateGraph, END
from langchain_community.llms import Ollama # or Llama 3.3 70B provider

# Define state schema for oncology prior authorization
class PriorAuthState(dict):
    patient_id: str
    clinical_text: str
    mutation_dosage: float
    decision: str

# Create LangGraph state nodes
workflow = StateGraph(PriorAuthState)
# Define extraction, rule check, and decision synthesis nodes

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.