aialenti

## chat.py
import requests
from termcolor import colored
from garmin_get_prompt import get_prompt

def get_prompt():
    # Assemble a comprehensive prompt with various components and a detailed report.
    # Note that these variables have to be populated with the data I shared in the article

    return f"""
       {PERSONA_PROMPT}

## prompt_generator.py
MAX_WEIGHTS = {
    'Dumbbell Row': 45.0,
    'Bench Press': 77.5,
    'Stretch Lying Abduction': 0,
    'Squat': 65.0,
    'Romanian Deadlift': 95.0,
    'Goblet Squat': 32.0,
    'Pull-up': 0,
    'Incline Barbell Bench Press': 65.0,
    'Weighted Dip': 15.0,

## min.py
initial_weights = {
    'Dumbbell Row': 22.5,
    'Stretch Lying Abduction': 0,
    'Bench Press': 50,
    'Squat': 25.0,
    'Romanian Deadlift': 25.0,
    'Goblet Squat': 16.0,
    'Pull-up': 0,
    'Incline Barbell Bench Press': 57.5,
    'Weighted Dip': 0,

## medians.py
MEDIAN_TOTAL_KCAL = 2687.0
MEDIAN_ACTIVE_KAL = 407.0
MEDIAN_RESTING_HR = 47.0
MEDIAN_SLEEP_SECONDS = 25140.0

## max_weights.py
max_weigts = {
    'Dumbbell Row': 45.0,
    'Bench Press': 77.5,
    'Stretch Lying Abduction': 0,
    'Squat': 65.0,
    'Romanian Deadlift': 95.0,
    'Goblet Squat': 32.0,
    'Pull-up': 0,
    'Incline Barbell Bench Press': 65.0,
    'Weighted Dip': 15.0,

## data2.py
exercise_trend_indicators = {
    'Dumbbell Row': 'increasing',
    'Stretch Lying Abduction': 'stable',
    'Squat': 'increasing',
    'Romanian Deadlift': 'stable',
    'Goblet Squat': 'increasing',
    'Pull-up': 'stable',
    'Incline Barbell Bench Press': 'increasing',
    'Weighted Dip': 'increasing',
    'Triceps Press-down': 'decreasing',

## data1.py
activity_aggregates = {
    'Back and Biceps': {
        'Average Moving Duration': 1978.67802734375,
        'Moving Duration/Duration Ratio': 0.4498125551450178,
        'Average HR': 98.6,
        'Average Calories': 456.4,
        'Average Total Sets': 19.0,
        'Average Total Reps': 102.8,
        'Total Sessions': 5,
        'Frequency per Week': 1.206896551724138

## file.py
import pandas as pd
import ast
from datetime import datetime
import numpy as np

def read_dataframes():
    """
    Reads the activity weights and details CSV files into Pandas dataframes.

    Returns:

## raw_weights.csv

          
            activityId
            wkt_step_weights

            
              14263566875
              {'Military Press': [0.0, 0.0, 0.0, 32.5, 35.0, 35.0], 'Bent-over Lateral Raise': [11.0, 11.0, 11.0], 'Front Raise': [13.5, 13.5], 'Stretch Lying Abduction': [0.0]}

            
              14295640408
              {'Squat': [55.0, 55.0, 55.0], 'Goblet Squat': [32.0, 32.0, 32.0], 'Romanian Deadlift': [0.0, 85.0, 90.0]}

            
              14310618451
              {'Romanian Deadlift': [0.0, 0.0, 0.0, 90.0, 90.0, 90.0], 'Barbell Row': [62.5, 62.5, 65.0], 'Lat Pull-down': [60.0, 65.0, 60.0], 'Barbell Biceps Curl': [15.0, 17.5, 17.5]}

## daily.csv

          
            totalKilocalories
            activeKilocalories
            restingHeartRate
            sleepingSeconds

            
              2629.0
              407.0
              49
              27960

            
              2710.0
              488.0
              47
              27600

            
              2759.0
              449.0
              51
              23340

            
              2912.0
              612.0
              47
              26760
	import requests
	from termcolor import colored
	from garmin_get_prompt import get_prompt

	def get_prompt():
	# Assemble a comprehensive prompt with various components and a detailed report.
	# Note that these variables have to be populated with the data I shared in the article

	return f"""
	{PERSONA_PROMPT}
	MAX_WEIGHTS = {
	'Dumbbell Row': 45.0,
	'Bench Press': 77.5,
	'Stretch Lying Abduction': 0,
	'Squat': 65.0,
	'Romanian Deadlift': 95.0,
	'Goblet Squat': 32.0,
	'Pull-up': 0,
	'Incline Barbell Bench Press': 65.0,
	'Weighted Dip': 15.0,
	initial_weights = {
	'Dumbbell Row': 22.5,
	'Stretch Lying Abduction': 0,
	'Bench Press': 50,
	'Squat': 25.0,
	'Romanian Deadlift': 25.0,
	'Goblet Squat': 16.0,
	'Pull-up': 0,
	'Incline Barbell Bench Press': 57.5,
	'Weighted Dip': 0,
	MEDIAN_TOTAL_KCAL = 2687.0
	MEDIAN_ACTIVE_KAL = 407.0
	MEDIAN_RESTING_HR = 47.0
	MEDIAN_SLEEP_SECONDS = 25140.0
	max_weigts = {
	'Dumbbell Row': 45.0,
	'Bench Press': 77.5,
	'Stretch Lying Abduction': 0,
	'Squat': 65.0,
	'Romanian Deadlift': 95.0,
	'Goblet Squat': 32.0,
	'Pull-up': 0,
	'Incline Barbell Bench Press': 65.0,
	'Weighted Dip': 15.0,
	exercise_trend_indicators = {
	'Dumbbell Row': 'increasing',
	'Stretch Lying Abduction': 'stable',
	'Squat': 'increasing',
	'Romanian Deadlift': 'stable',
	'Goblet Squat': 'increasing',
	'Pull-up': 'stable',
	'Incline Barbell Bench Press': 'increasing',
	'Weighted Dip': 'increasing',
	'Triceps Press-down': 'decreasing',
	activity_aggregates = {
	'Back and Biceps': {
	'Average Moving Duration': 1978.67802734375,
	'Moving Duration/Duration Ratio': 0.4498125551450178,
	'Average HR': 98.6,
	'Average Calories': 456.4,
	'Average Total Sets': 19.0,
	'Average Total Reps': 102.8,
	'Total Sessions': 5,
	'Frequency per Week': 1.206896551724138
	import pandas as pd
	import ast
	from datetime import datetime
	import numpy as np

	def read_dataframes():
	"""
	Reads the activity weights and details CSV files into Pandas dataframes.

	Returns:
	activityId	wkt_step_weights
	14263566875	{'Military Press': [0.0, 0.0, 0.0, 32.5, 35.0, 35.0], 'Bent-over Lateral Raise': [11.0, 11.0, 11.0], 'Front Raise': [13.5, 13.5], 'Stretch Lying Abduction': [0.0]}
	14295640408	{'Squat': [55.0, 55.0, 55.0], 'Goblet Squat': [32.0, 32.0, 32.0], 'Romanian Deadlift': [0.0, 85.0, 90.0]}
	14310618451	{'Romanian Deadlift': [0.0, 0.0, 0.0, 90.0, 90.0, 90.0], 'Barbell Row': [62.5, 62.5, 65.0], 'Lat Pull-down': [60.0, 65.0, 60.0], 'Barbell Biceps Curl': [15.0, 17.5, 17.5]}
totalKilocalories	activeKilocalories	restingHeartRate	sleepingSeconds
2629.0	407.0	49	27960
2710.0	488.0	47	27600
2759.0	449.0	51	23340
2912.0	612.0	47	26760