feed_back_llm.py

import json
import random


# Function to read the JSON from the file
def read_json(file_path):
    with open(file_path, 'r') as json_file:
        return json.load(json_file)

# Function to add a new day's progress
def add_next_day_progress(data, next_day_progress):
    # Extract the current day count (last day in the list)
    last_day_number = int(data["daily_progress"][-1]["day"].split(" ")[1]) if data["daily_progress"] else 0
    
    # Construct the new day's entry
    next_day_number = last_day_number + 1
    next_day_name = f"Day {next_day_number}"
    
    
    # Add the next day's data with the LOINC-like identifier
    new_day_entry = {  # Unique identifier for the day
        "day": next_day_name,
        "progress": next_day_progress["progress"],
        "rest_time": next_day_progress["rest_time"],
        "workout_time": next_day_progress["workout_time"]
    }
    
    data["daily_progress"].append(new_day_entry)
    
    # Update weekly summary (rest_time and workout_time)
    total_rest_time = sum(day["rest_time"] for day in data["daily_progress"])
    total_workout_time = sum(day["workout_time"] for day in data["daily_progress"])
    
    data["weekly_summary"]["rest_time"] = total_rest_time
    data["weekly_summary"]["workout_time"] = total_workout_time

    return data

# Function to save the updated data to a file
def save_json(data, file_path):
    with open(file_path, 'w') as json_file:
        json.dump(data, json_file, indent=2)


def update_feed_back():
    # Path to the JSON file
    file_path = r'static\feedback.json'

    # Step 1: Read the existing JSON data
    data = read_json(file_path)

    # Example new day data to add (Day 8)


    # Generating random values for progress, rest_time, and workout_time
    next_day_progress = {
        "progress": random.randint(50, 100),  # Random progress between 50 and 100
        "rest_time": random.randint(4, 10),   # Random rest time between 4 and 10 hours
        "workout_time": random.randint(1, 5)  # Random workout time between 1 and 5 hours
    }

    # Step 2: Add the new day to the data and update the weekly summary
    updated_data = add_next_day_progress(data, next_day_progress)

    # Step 3: Save the updated data back to the file
    save_json(updated_data, file_path)

    print(f"Updated data saved to {file_path}")