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implementation
Construct LangChain and Agno Clinical Workflow Agent
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Postpartum Psychiatric Risk Monitoring Agent using LangChain and Agno
Format
Code-aware
Lines
8
Sections
2
Linked challenge
Postpartum Psychiatric Risk Monitoring Agent using LangChain and Agno
Prompt source
Original prompt text with formatting preserved for inspection.
8 lines
2 sections
No variables
0 checklist items
from langchain.chains import SequentialChain
from agno.agent import Agent
# Initialize Agno clinical safety agent embedded in LangChain structure
clinical_agent = Agent(
name='PostpartumPsychiatryMonitor',
role='Clinical Safety Monitor',
instructions='Analyze clinical notes for psychotropic polypharmacy and flag risk factors.'
)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.