aialenti

	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]}

	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}

	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: