Create with_viz.py
Browse files- mylab/with_viz.py +170 -0
mylab/with_viz.py
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import gradio as gr
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import matplotlib.pyplot as plt
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import pandas as pd
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import numpy as np
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from datetime import datetime
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from langchain_core.messages import HumanMessage
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from tools import tools
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from agents import *
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from config import *
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from workflow import create_workflow
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# Initialize workflow
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graph = create_workflow()
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# Helper Functions
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def run_graph(input_message, history, user_details):
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try:
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# Relevant fitness-related keywords to handle irrelevant user prompts
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relevant_keywords = [
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"workout", "training", "exercise", "cardio", "strength training", "hiit (high-intensity interval training)",
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"flexibility", "yoga", "pilates", "aerobics", "crossfit", "bodybuilding", "endurance", "running",
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"cycling", "swimming", "martial arts", "stretching", "warm-up", "cool-down",
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"diet plan", "meal plan", "macronutrients", "micronutrients", "vitamins", "minerals", "protein",
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"carbohydrates", "fats", "calories", "calorie", "daily", "nutrition", "supplements", "hydration", "weightloss",
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"weight gain", "healthy eating", "health", "fitness", "intermittent fasting", "keto diet", "vegan diet", "paleo diet",
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"mediterranean diet", "gluten-free", "low-carb", "high-protein", "bmi", "calculate", "body mass index", "calculator",
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"mental health", "mindfulness", "meditation", "stress management", "anxiety relief", "depression",
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"positive thinking", "motivation", "self-care", "relaxation", "sleep hygiene", "therapy",
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"counseling", "cognitive-behavioral therapy (cbt)", "mood tracking", "mental", "emotional well-being",
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"healthy lifestyle", "fitness goals", "health routines", "daily habits", "ergonomics",
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"posture", "work-life balance", "workplace", "habit tracking", "goal setting", "personal growth",
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"injury prevention", "recovery", "rehabilitation", "physical therapy", "sports injuries",
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"pain management", "recovery techniques", "foam rolling", "stretching exercises",
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"injury management", "injuries", "apps", "health tracking", "wearable technology", "equipment",
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"home workouts", "gym routines", "outdoor activities", "sports", "wellness tips", "water", "adult", "adults",
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"child", "children", "infant", "sleep", "habit", "habits", "routine", "weight", "fruits", "vegetables", "lose", "lost weight", "weight-loss",
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"chicken", "veg", "vegetarian", "non-veg", "non-vegetarian", "plant", "plant-based", "plant based", "fat", "resources",
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"help", "cutting", "bulking", "link", "links", "website", "online", "websites", "peace", "mind", "equipments", "equipment",
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"watch", "tracker", "watch", "band", "height", "injured", "quick", "remedy", "solution", "solutions", "pain", "male", "female", "kilograms", "kg", "Pounds",
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"lbs"
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]
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greetings = ["hello", "hi", "how are you doing"]
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if any(keyword in input_message.lower() for keyword in relevant_keywords):
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response = graph.invoke({
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"messages": [HumanMessage(content=input_message)],
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"user_details": user_details # Pass user-specific data for customization
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})
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return response['messages'][1].content
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elif any(keyword in input_message.lower() for keyword in greetings):
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return "Hi there, I am FIT bot, your personal wellbeing coach! Let me know your fitness goals or questions."
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else:
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return "I'm here to assist with fitness, nutrition, mental health, and related topics. Please ask questions related to these areas."
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except Exception as e:
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return f"An error occurred while processing your request: {e}"
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def calculate_bmi(height, weight, gender):
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"""
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Calculate BMI and determine the category based on height, weight, and gender.
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"""
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try:
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height_m = height / 100
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bmi = weight / (height_m ** 2)
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if bmi < 18.5:
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status = "underweight"
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elif 18.5 <= bmi < 24.9:
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status = "normal weight"
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elif 25 <= bmi < 29.9:
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status = "overweight"
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else:
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status = "obese"
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return bmi, status
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except:
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return None, "Invalid height or weight provided."
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def visualize_bmi(bmi):
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"""
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Create a visualization for BMI, showing the user's value against standard categories.
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"""
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categories = ["Underweight", "Normal Weight", "Overweight", "Obese"]
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bmi_ranges = [18.5, 24.9, 29.9, 40]
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x_pos = np.arange(len(categories))
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user_position = min(len(bmi_ranges), sum(bmi > np.array(bmi_ranges)))
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plt.figure(figsize=(8, 4))
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plt.bar(x_pos, bmi_ranges, color=['blue', 'green', 'orange', 'red'], alpha=0.6, label="BMI Categories")
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plt.axhline(y=bmi, color='purple', linestyle='--', linewidth=2, label=f"Your BMI: {bmi:.2f}")
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plt.xticks(x_pos, categories)
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plt.ylabel("BMI Value")
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plt.title("BMI Visualization")
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plt.legend()
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plt.tight_layout()
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plt_path = "bmi_chart.png"
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plt.savefig(plt_path)
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plt.close()
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return plt_path
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def calculate_calories(age, weight, height, activity_level, gender):
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"""
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Estimate daily calorie needs based on user inputs.
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"""
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try:
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if gender.lower() == "male":
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bmr = 10 * weight + 6.25 * height - 5 * age + 5
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else:
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bmr = 10 * weight + 6.25 * height - 5 * age - 161
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activity_multipliers = {
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"Sedentary": 1.2,
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"Lightly active": 1.375,
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"Moderately active": 1.55,
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"Very active": 1.725,
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"Extra active": 1.9,
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}
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calories = bmr * activity_multipliers.get(activity_level, 1.2)
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return calories
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except Exception:
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return "Invalid inputs for calorie calculation."
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# Interface Components
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with gr.Blocks() as demo:
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gr.Markdown("<strong>FIT.AI - Your Fitness and Wellbeing Coach</strong>")
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# User Info
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with gr.Row():
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user_name = gr.Textbox(placeholder="Enter your name", label="Name")
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user_age = gr.Number(label="Age (years)", value=25, precision=0)
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user_gender = gr.Dropdown(choices=["Male", "Female"], label="Gender", value="Male")
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user_weight = gr.Number(label="Weight (kg)", value=70, precision=1)
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user_height = gr.Number(label="Height (cm)", value=170, precision=1)
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activity_level = gr.Dropdown(
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choices=["Sedentary", "Lightly active", "Moderately active", "Very active", "Extra active"],
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label="Activity Level",
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value="Moderately active"
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)
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# Outputs
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bmi_output = gr.Label(label="BMI Result")
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calorie_output = gr.Label(label="Calorie Needs")
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bmi_chart = gr.Image(label="BMI Chart")
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# Actions
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calculate_button = gr.Button("Calculate")
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+
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def calculate_metrics(age, weight, height, gender, activity_level):
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bmi, status = calculate_bmi(height, weight, gender)
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if bmi:
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bmi_path = visualize_bmi(bmi)
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calories = calculate_calories(age, weight, height, activity_level, gender)
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return f"Your BMI is {bmi:.2f}, considered {status}.", f"Daily calorie needs: {calories:.2f} kcal", bmi_path
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else:
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return "Invalid inputs.", "", ""
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calculate_button.click(
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calculate_metrics,
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inputs=[user_age, user_weight, user_height, user_gender, activity_level],
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outputs=[bmi_output, calorie_output, bmi_chart]
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)
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demo.launch(share=True)
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