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