Create with_viz4.py

mylab/with_viz4.py

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