Update chain_recommendations.py

chain_recommendations.py

@@ -9,6 +9,13 @@ improved_recommend_prompt_template = PromptTemplate(
     template=(
         "You are a wellness recommendation assistant. Given the following problem severity percentages:\n"
         "{problems}\n\n"
+        "Based on these percentages and the available wellness packages:\n"
+        "1. Fitness & Mobility | Tagline: 'Enhance Mobility. Boost Fitness.'\n"
+        "2. No More Insomnia | Deep Rest | Tagline: 'Reclaim Your Sleep. Restore Your Mind.'\n"
+        "3. Focus Flow | Clarity Boost | Tagline: 'Stay Focused. Stay Productive.'\n"
+        "4. Boost Energy | Tagline: 'Fuel Your Day. Boost Your Energy.'\n"
+        "5. Chronic Care | Chronic Support | Tagline: 'Ongoing Support for Chronic Wellness.'\n"
+        "6. Mental Wellness | Calm Mind | Tagline: 'Find Peace of Mind, Every Day.'\n\n"
         "Carefully analyze these percentages and consider nuanced differences between the areas. "
         "Your goal is to recommend the most appropriate wellness packages based on a detailed assessment of these numbers, "
         "not just fixed thresholds. Consider the following guidelines:\n\n"
@@ -17,11 +24,12 @@ improved_recommend_prompt_template = PromptTemplate(
         "- If all areas are moderate (between 30 and 70), recommend a balanced wellness package that addresses overall health.\n"
         "- If all areas are low, a general wellness package might be sufficient.\n"
         "- Consider borderline cases and recommend packages that address both current issues and preventive measures.\n\n"
-        "Return the recommended wellness packages in a JSON array format."
+        "Return the recommended wellness packages in a JSON array format. "
+        "Each item should be exactly one of the following package names: "
+        "\"Fitness & Mobility\", \"No More Insomnia\", \"Focus Flow\", \"Boost Energy\", \"Chronic Care\", \"Mental Wellness\"."
     )
 )
 
-# Initialize the improved recommendation chain
 recommend_chain = LLMChain(llm=chat_model, prompt=improved_recommend_prompt_template)
 
 def generate_recommendations(problems: Dict[str, float]) -> str: