Create chain_recommendations.py

chain_recommendations.py

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+# chain_recommendations.py
+import json
+from typing import Dict
+from langchain import PromptTemplate, LLMChain
+from models import chat_model
+
+recommend_prompt_template = PromptTemplate(
+    input_variables=["problems"],
+    template=(
+        "Given the following problem severity percentages:\n"
+        "{problems}\n\n"
+        "Using these 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?"
+    )
+)
+recommend_chain = LLMChain(llm=chat_model, prompt=recommend_prompt_template)
+
+def generate_recommendations(problems: Dict[str, float]) -> str:
+    recommendations = recommend_chain.run(problems=json.dumps(problems))
+    return recommendations.strip()