Medica_DecisionSupportAI / scenario_planner.py
Rajan Sharma
Create scenario_planner.py
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import json
from schemas import ScenarioPlan
from settings import HEALTHCARE_SYSTEM_PROMPT
from llm_router import generate_with_fallback
PLAN_INSTRUCTIONS = """
Return ONLY valid JSON. Schema:
{
"tasks": [
{
"title": "string",
"data_key": "string|null",
"format": "table|list|comparison|map|narrative|chart",
"filter": "expr|null",
"derive": ["col=expr"]|null,
"group_by": ["col"]|null,
"agg": ["sum(col)","avg(col)",...]|null,
"pivot": {"index":"a","columns":"b","values":"c"}|null,
"join": [{"right_key":"ds","left_on":"x","right_on":"y","how":"left"}]|null,
"sort_by": "col|null",
"sort_dir": "asc|desc",
"top": int|null,
"fields": ["col"]|null,
"chart": "bar|line|area|point|tick|rule"|null,
"x": "col|null", "y": "col|null", "color":"col|null", "column":"col|null"
}
],
"narrative_required": true,
"notes": "optional"
}
"""
def build_prompt(scenario: str, catalog: dict) -> str:
catalog_str = "\n".join([f"- {k}: {', '.join(v)}" for k,v in catalog.items()])
return f"{HEALTHCARE_SYSTEM_PROMPT}\n\nDATASETS:\n{catalog_str}\n\n{PLAN_INSTRUCTIONS}\n\nSCENARIO:\n{scenario}\n\nJSON:"
def plan_from_llm(scenario: str, catalog: dict) -> ScenarioPlan:
prompt = build_prompt(scenario, catalog)
raw = generate_with_fallback(prompt)
start, end = raw.find("{"), raw.rfind("}")
data = json.loads(raw[start:end+1])
return ScenarioPlan.model_validate(data)