Updated Agent Orchestrator Plan Recommender

insucompass/core/agent_orchestrator.py

@@ -1,6 +1,7 @@
 import logging
 import json
 import uuid
+import datetime
 import sqlite3
 from typing import List, Dict, Any
 from typing_extensions import TypedDict
@@ -80,17 +81,50 @@ def plan_recommender_node(state: AgentState) -> Dict[str, Any]:
     logger.info("---NODE: PLAN RECOMMENDER---")
     user_profile = state["user_profile"]
     
-    # Formulate a generic query to retrieve a broad set of plan documents
-    initial_plan_query = f"Find general health insurance plan options available in {user_profile.get('state', 'the US')} suitable for a {user_profile.get('age')}-year-old."
+    # # Formulate a generic query to retrieve a broad set of plan documents
+    # initial_plan_query = f"Find general health insurance plan options available in {user_profile.get('state', 'the US')} suitable for a {user_profile.get('age')}-year-old."
     
-    # Retrieve documents
-    documents = transformer.transform_and_retrieve(initial_plan_query)
+    # # Retrieve documents
+    # documents = transformer.transform_and_retrieve(initial_plan_query)
+
+    # # Generate structured recommendations
+    # recommendations = planner.generate_recommendations(user_profile, documents)
+    
+    # 1. Formulate a search query to find up-to-date plans
+
+
+    # ------------ 1) Capture today's date in a friendly format ------------
+    current_date = datetime.date.today().strftime("%B %d %Y")  # e.g., "July 21 2025"
+
+    # ------------ 2) Tavern / Tavily search-query template ------------
+    query_template = (
+        '"Individual health-insurance plans" '
+        '"{county} County {state} {zip_code}" "{current_date}" '
+        '"{age}-year-old" "household size {household_size}" "income {income}" '
+        '"employment {employment_status}" "citizenship {citizenship}" '
+        '"coverage for {medical_history}" "formulary {medications}" "{special_cases}" '
+        '"ACA marketplace OR Healthcare.gov OR CMS Landscape File" '
+        '"off-exchange OR private health insurance OR direct-to-consumer plan OR short-term medical" '
+        '"premium" "deductible" "out-of-pocket max" "metal tier bronze silver gold platinum" '
+        '"network HMO PPO EPO" "Summary of Benefits and Coverage" "CMS 2025 final rate filings"'
+    )
+
+    # ------------ 3) Inject user-specific values ------------
+    search_query = query_template.format(current_date=current_date, **user_profile)
+    logger.info(f"Plan Recommender search query: '{search_query}'")
+    
+    # 2. Use the SearchAgent to get live, up-to-date information
+    documents = searcher.search(search_query)
+    
+    # Optional: Ingest these newly found documents for future reference
+    if documents:
+        ingestor.ingest_documents(documents)
     
-    # Generate structured recommendations
-    recommendations = planner.generate_recommendations(user_profile, documents)
+    # 3. Generate structured recommendations from the live search results
+    recommendations = searcher.generate_recommendations(user_profile, documents)
     
     # Create a human-friendly message to present the plans
-    generation_message = "Thank you! I've completed your profile and based on your information, here are a few initial plan recommendations for you to consider. You can ask me more detailed questions about them."
+    generation_message = "Great, your profile is all set! I've prepared a few initial plan recommendations just for you. \n Ask me anything about these plans or any questions you have related to Health Insurance!"
     
     history = state["conversation_history"]
     # history.append(f"Agent: {generation_message}")