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app.py

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+import os
+import gradio as gr
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+from langchain_groq import ChatGroq
+from langchain.prompts import PromptTemplate
+from typing import TypedDict, List
+from typing_extensions import Annotated
+from dotenv import load_dotenv
+import numpy as np
+
+# --- SETUP ---
+load_dotenv()
+api_key = os.getenv('GROQ_API_KEY')
+
+# Define the structured output type
+class AssessmentOutput(TypedDict):
+    stress_management: Annotated[float, "Percentage score (0-100) for Stress Management KPI"]
+    motivation: Annotated[float, "Percentage score (0-100) for Motivation KPI"]
+    restless_night_score: Annotated[float, "Percentage score (0-100) for Restless Night Score KPI"]
+    anxiety_level: Annotated[float, "Percentage score (0-100) for Anxiety Level KPI"]
+    burnout_level: Annotated[float, "Percentage score (0-100) for Burnout Level KPI"]
+    physical_fitness_score: Annotated[float, "Percentage score (0-100) for Physical Fitness KPI"]
+    dietary_habit_score: Annotated[float, "Percentage score (0-100) for Diet & Nutrition KPI"]
+    focus_score: Annotated[float, "Percentage score (0-100) for Cognitive Performance and Focus KPI"]
+    overall_wellness_score: Annotated[float, "Percentage score (0-100) based on all the individual KPIs"]
+    package: Annotated[List[str], "List of recommended packages"]
+    report: Annotated[str, "A detailed summary report of the assessment results"]
+
+# Define the prompt template
+template = """
+You are an AI wellness assessment system designed to evaluate users' well-being and provide personalized insights. This assessment system analyzes responses and generates wellness reports, recommending specific services and packages from *DailyWellnessAI* to help users improve their mental and physical health. While this system itself is not called *DailyWellnessAI*, all recommendations are part of the *DailyWellnessAI* platform.
+
+Based on the user's responses to the following 15 questions, predict the following KPIs as percentages out of 100:
+- stress_management
+- motivation
+- restless_night_score
+- anxiety_level
+- burnout_level
+- physical_fitness_score
+- dietary_habit_score
+- focus_score
+- overall_wellness_score
+
+Recommendation System:
+Based on the predicted KPIs, recommend one of the following *DailyWellnessAI* packages:
+- Focus (for low concentration, motivation, or burnout)
+- Insomnia (for sleep disturbances, restlessness, or anxiety before sleep)
+- Fitness (for low physical activity, poor dietary habits, or weak physical strength)
+
+If the overall_wellness_score is greater than 90 (or 95), recommend all three packages and let the user choose among them, emphasizing that DailyWellnessAI offers holistic well-being solutions.
+
+Summary Report:
+Provide a brief wellness summary explaining the predicted KPIs and recommended package(s) based on the user's responses. Justify the recommendations by highlighting key factors affecting the user's well-being and how DailyWellnessAI can help improve them.
+
+### Assessment Questions:
+
+1. How often do you feel stressed by daily tasks?
+   Answer: {ans1}
+2. How well do you handle stress?
+   Answer: {ans2}
+3. How would you rate your current level of burnout?
+   Answer: {ans3}
+4. How well can you concentrate on your daily tasks?
+   Answer: {ans4}
+5. How often do you have trouble falling asleep?
+   Answer: {ans5}
+6. How would you rate the quality of your sleep?
+   Answer: {ans6}
+7. How often do you wake up during the night?
+   Answer: {ans7}
+8. How often do you feel anxious before sleep?
+   Answer: {ans8}
+9. How happy are you with your eating habits?
+   Answer: {ans9}
+10. How balanced is your diet?
+    Answer: {ans10}
+11. How often do you exercise or do physical activity?
+    Answer: {ans11}
+12. How would you rate your physical strength?
+    Answer: {ans12}
+13. How motivated are you to work on your wellness goals daily?
+    Answer: {ans13}
+14. How would you rate your overall health and well-being?
+    Answer: {ans14}
+15. Any more remarks about yourself that you want to add?
+    Answer: {ans15}
+"""
+
+# Initialize model once
+chat = ChatGroq(api_key=api_key, model="llama-3.3-70b-versatile", temperature=0.2)
+prompt_template = PromptTemplate(
+    input_variables=[f"ans{i}" for i in range(1, 16)],
+    template=template
+)
+
+def run_assessment(answers):
+    prompt = prompt_template.format(**answers)
+    structured_llm = chat.with_structured_output(AssessmentOutput)
+    return structured_llm.invoke(prompt)
+
+# --- VISUALIZATION FUNCTIONS ---
+
+def get_emoji(score):
+    if score < 20:
+        return "😢"
+    elif score < 40:
+        return "😞"
+    elif score < 60:
+        return "😐"
+    elif score < 80:
+        return "🙂"
+    else:
+        return "😄"
+
+def create_overall_wellness_donut(score):
+    color = '#FF5252' if score < 50 else '#FFC107' if score < 75 else '#4CAF50'
+    fig = go.Figure(go.Pie(
+        values=[score, 100 - score],
+        hole=0.7,
+        textinfo='none',
+        marker_colors=[color, '#E0E0E0'],
+        showlegend=False
+    ))
+    fig.update_layout(
+        annotations=[dict(
+            text=f"{get_emoji(score)}",
+            font_size=24,
+            showarrow=False
+        )],
+        title=dict(text="Overall Wellness", x=0.5, font=dict(size=16)),
+        margin=dict(t=20, b=20, l=20, r=20),
+        height=300
+    )
+    return fig
+
+def create_kpi_bar_chart(kpis, values):
+    colors = ['#FF5252' if v < 50 else '#FFC107' if v < 75 else '#4CAF50' for v in values]
+    fig = go.Figure(go.Bar(
+        x=kpis,
+        y=values,
+        marker_color=colors,
+        text=[f"{v}%" for v in values],
+        textposition='auto'
+    ))
+    fig.update_layout(
+        title="KPI Breakdown",
+        xaxis=dict(title="KPI"),
+        yaxis=dict(title="Score (%)", range=[0, 100]),
+        margin=dict(l=40, r=40, t=60, b=40),
+        height=400
+    )
+    return fig
+
+def create_radar_chart(data):
+    categories = [
+        'Stress Management',
+        'Motivation',
+        'Sleep Quality',
+        'Anxiety Control',
+        'Burnout Resistance',
+        'Physical Fitness',
+        'Diet & Nutrition',
+        'Focus'
+    ]
+    values = [
+        data['stress_management'],
+        data['motivation'],
+        100 - data['restless_night_score'],
+        100 - data['anxiety_level'],
+        100 - data['burnout_level'],
+        data['physical_fitness_score'],
+        data['dietary_habit_score'],
+        data['focus_score']
+    ]
+    fig = go.Figure()
+    fig.add_trace(go.Scatterpolar(
+        r=values,
+        theta=categories,
+        fill='toself',
+        fillcolor='rgba(76, 175, 80, 0.3)',
+        line=dict(color='#4CAF50', width=2),
+        name='Your Profile'
+    ))
+    fig.update_layout(
+        polar=dict(
+            radialaxis=dict(visible=True, range=[0, 100], tickfont=dict(size=10))
+        ),
+        showlegend=False,
+        margin=dict(l=40, r=40, t=20, b=20),
+        height=400
+    )
+    return fig
+
+def create_bullet_charts_combined(data):
+    # Define bullet data for 8 KPIs; for "negative" metrics, invert value.
+    bullet_data = [
+        ("Stress Management", data['stress_management']),
+        ("Motivation", data['motivation']),
+        ("Sleep Quality", 100 - data['restless_night_score']),
+        ("Anxiety Control", 100 - data['anxiety_level']),
+        ("Burnout Resistance", 100 - data['burnout_level']),
+        ("Physical Fitness", data['physical_fitness_score']),
+        ("Diet & Nutrition", data['dietary_habit_score']),
+        ("Focus", data['focus_score'])
+    ]
+    rows, cols = 2, 4
+    target = 80
+    fig = make_subplots(rows=rows, cols=cols, subplot_titles=[item[0] for item in bullet_data])
+    for i, (label, val) in enumerate(bullet_data):
+        row = i // cols + 1
+        col = i % cols + 1
+        # Add a simple horizontal bar as the bullet indicator.
+        fig.add_trace(go.Bar(
+            x=[val],
+            y=[""],
+            orientation="h",
+            marker_color='#4CAF50' if val >= target else '#FF5252',
+            text=[f"{val}%"],
+            textposition='inside',
+            showlegend=False
+        ), row=row, col=col)
+        fig.update_xaxes(range=[0, 100], row=row, col=col)
+        # Add a vertical dashed line for the target.
+        fig.add_shape(
+            type="line",
+            x0=target, x1=target,
+            y0=0, y1=1,
+            xref=f"x{i+1} domain",
+            yref=f"y{i+1} domain",
+            line=dict(color="black", width=2, dash="dash")
+        )
+    fig.update_layout(height=400, width=1000, margin=dict(l=20, r=20, t=40, b=20))
+    return fig
+
+def combine_report(results):
+    packages = results["package"]
+    rec_text = ", ".join(packages) if packages else "None"
+    final_text = f"### Report\n{results['report']}\n\n**Recommended Packages:** {rec_text}"
+    return final_text
+
+# --- GRADIO APP FUNCTION ---
+
+def gradio_assessment(
+    ans1, ans2, ans3, ans4, ans5,
+    ans6, ans7, ans8, ans9, ans10,
+    ans11, ans12, ans13, ans14, ans15
+):
+    answers = {
+        "ans1": ans1, "ans2": ans2, "ans3": ans3, "ans4": ans4, "ans5": ans5,
+        "ans6": ans6, "ans7": ans7, "ans8": ans8, "ans9": ans9, "ans10": ans10,
+        "ans11": ans11, "ans12": ans12, "ans13": ans13, "ans14": ans14,
+        "ans15": ans15 or None
+    }
+    results = run_assessment(answers)
+    overall_score = int(results["overall_wellness_score"])
+    donut_fig = create_overall_wellness_donut(overall_score)
+
+    kpis = [
+        "Stress Management", "Motivation", "Sleep Quality",
+        "Anxiety Control", "Burnout Resistance", "Physical Fitness",
+        "Diet & Nutrition", "Focus"
+    ]
+    values = [
+        results["stress_management"],
+        results["motivation"],
+        100 - results["restless_night_score"],
+        100 - results["anxiety_level"],
+        100 - results["burnout_level"],
+        results["physical_fitness_score"],
+        results["dietary_habit_score"],
+        results["focus_score"]
+    ]
+    bar_fig = create_kpi_bar_chart(kpis, values)
+    radar_fig = create_radar_chart(results)
+    bullet_fig = create_bullet_charts_combined(results)
+    report_text = combine_report(results)
+    return donut_fig, bar_fig, radar_fig, bullet_fig, report_text
+
+# --- BUILD GRADIO INTERFACE ---
+
+def build_app():
+    with gr.Blocks() as demo:
+        gr.Markdown("# 🌿 DailyWellnessAI Assessment")
+        gr.Markdown("Fill out the questionnaire below to receive personalized insights and recommendations.")
+
+        with gr.Row():
+            with gr.Column():
+                ans1 = gr.Dropdown(label="1. How often do you feel stressed by daily tasks?",
+                                   choices=["Never", "Sometimes", "Often", "Always"], value="Never")
+                ans2 = gr.Dropdown(label="2. How well do you handle stress?",
+                                   choices=["Excellent", "Good", "Fair", "Poor"], value="Good")
+                ans3 = gr.Dropdown(label="3. How would you rate your current level of burnout?",
+                                   choices=["None", "Mild", "Moderate", "Severe"], value="None")
+                ans4 = gr.Dropdown(label="4. How well can you concentrate on your daily tasks?",
+                                   choices=["Excellent", "Good", "Fair", "Poor"], value="Good")
+                ans5 = gr.Dropdown(label="5. How often do you have trouble falling asleep?",
+                                   choices=["Never", "Rarely", "Sometimes", "Always"], value="Rarely")
+                ans6 = gr.Dropdown(label="6. How would you rate the quality of your sleep?",
+                                   choices=["Excellent", "Good", "Fair", "Poor"], value="Good")
+                ans7 = gr.Dropdown(label="7. How often do you wake up during the night?",
+                                   choices=["Never", "Rarely", "Sometimes", "Often"], value="Rarely")
+                ans8 = gr.Dropdown(label="8. How often do you feel anxious before sleep?",
+                                   choices=["Never", "Rarely", "Sometimes", "Often"], value="Rarely")
+            with gr.Column():
+                ans9 = gr.Dropdown(label="9. How happy are you with your eating habits?",
+                                   choices=["Very happy", "Happy", "Unhappy", "Very unhappy"], value="Happy")
+                ans10 = gr.Dropdown(label="10. How balanced is your diet?",
+                                    choices=["Very balanced", "Balanced", "Unbalanced", "Very unbalanced"], value="Balanced")
+                ans11 = gr.Dropdown(label="11. How often do you exercise or do physical activity?",
+                                    choices=["Daily", "Several times a week", "Once a week", "Never"], value="Daily")
+                ans12 = gr.Dropdown(label="12. How would you rate your physical strength?",
+                                    choices=["Excellent", "Good", "Fair", "Poor"], value="Good")
+                ans13 = gr.Dropdown(label="13. How motivated are you to work on your wellness goals daily?",
+                                    choices=["Very motivated", "Moderately motivated", "Slightly motivated", "Not at all"], value="Very motivated")
+                ans14 = gr.Dropdown(label="14. How would you rate your overall health and well-being?",
+                                    choices=["Excellent", "Good", "Fair", "Poor"], value="Good")
+                ans15 = gr.Textbox(label="15. Any more remarks about yourself (optional):", placeholder="Optional", lines=3)
+
+        with gr.Row():
+            submit_btn = gr.Button("Submit Assessment")
+        
+        with gr.Row():
+            gr.Markdown("## Results")
+        with gr.Row():
+            donut_plot = gr.Plot(label="Overall Wellness Donut")
+            bar_plot = gr.Plot(label="KPI Bar Chart")
+        with gr.Row():
+            radar_plot = gr.Plot(label="Radar Chart")
+            bullet_plot = gr.Plot(label="Bullet Charts")
+        with gr.Row():
+            report_md = gr.Markdown(label="Assessment Report")
+
+        submit_btn.click(
+            fn=gradio_assessment,
+            inputs=[ans1, ans2, ans3, ans4, ans5, ans6, ans7, ans8, ans9, ans10, ans11, ans12, ans13, ans14, ans15],
+            outputs=[donut_plot, bar_plot, radar_plot, bullet_plot, report_md]
+        )
+    return demo
+
+if __name__ == "__main__":
+    demo_app = build_app()
+    demo_app.launch(server_name="0.0.0.0", server_port=7860, share= True)