# chain_reports.py
from typing import Dict
from langchain import PromptTemplate, LLMChain
from models import chat_model

report_prompt_template = PromptTemplate(
    input_variables=["qa_summary"],
    template=(
        "You are a wellness assistant. The user provided the following answers:\n\n"
        "{qa_summary}\n\n"
        "Based on these answers, provide a brief, actionable wellness report. "
        "Include simple suggestions to improve their sleep, exercise, stress management, and diet. "
        "Consider recommending wellness packages if applicable based on the user's needs, for instance:\n"
        "- Fitness & Mobility for exercise-related concerns\n"
        "- No More Insomnia for sleep issues\n"
        "- Focus Flow for productivity issues\n"
        "- Boost Energy for low energy\n"
        "- Chronic Care for long-term chronic conditions\n"
        "- Mental Wellness for stress and anxiety reduction\n\n"
        "Also consider aspects of therapy, maintaining a balanced weight, addressing restless nights, "
        "overcoming lack of motivation, improving gut health, managing anxiety, and preventing burnout. "
        "Be concise and helpful.\n\n"
        "Report:"
    )
)
report_chain = LLMChain(llm=chat_model, prompt=report_prompt_template)

def generate_short_report_for_session(responses: Dict[str, str]) -> str:
    qa_summary = "\n".join(f"{q}: {a}" for q, a in responses.items())
    raw_report = report_chain.run(qa_summary=qa_summary)
    return raw_report.replace("*", "").replace("**", "")