Update chain_recommendations.py

chain_recommendations.py

@@ -1,25 +1,32 @@
-# chain_recommendations.py
 import json
 from typing import Dict
 from langchain import PromptTemplate, LLMChain
 from models import chat_model
 
+# Enhanced Prompt Template
 recommend_prompt_template = PromptTemplate(
     input_variables=["problems"],
     template=(
-        "Given the following problem severity percentages:\n"
+        "You are a helpful wellness recommendation system. Given the following problem severity percentages:\n"
         "{problems}\n\n"
-        "Using these rules:\n"
+        "Based on these strict rules:\n"
         "- If sleep_problem > 70: Recommend Sleep Improvement Package\n"
         "- If stress_problem > 70: Recommend Stress Reduction Package\n"
         "- If exercise_problem > 70: Recommend Exercise Enhancement Package\n"
         "- If all problems are between 30 and 70: Recommend Balanced Wellness Package\n"
         "- If no severe problems: Recommend General Wellness Package\n\n"
-        "What are the recommended wellness packages?"
+        "List the recommended wellness packages separated by commas. "
+        "Do not include any additional text or explanation."
     )
 )
+
 recommend_chain = LLMChain(llm=chat_model, prompt=recommend_prompt_template)
 
 def generate_recommendations(problems: Dict[str, float]) -> str:
+    """
+    Generates wellness package recommendations based on problem severity percentages.
+    The function accepts a dictionary of problem severities and returns a 
+    comma-separated string of recommended packages based on predefined rules.
+    """
     recommendations = recommend_chain.run(problems=json.dumps(problems))
     return recommendations.strip()