i am performing a translation over a vtt file.

i receive those errors:
ValueError: Expected 5 translations but got 4.
Assistant's response: ["Ti darò alcune nozioni di base sulla\npiattaforma.", "Quindi quando accediamo a Canvas, il tuo\nschermo sarà diverso dal mio se vuoi accedere.", "Se vuoi seguirmi,\ninserirò il link nella chat", "dove potrai accedere."]

this is my code:

import os
import openai
import json
import re
from tqdm import tqdm

# Set up your OpenAI API key
openai.api_key = '<TRUFFLEHOG_REDACTED_OPENAI>'

def read_vtt_file(file_path):
    """
    Reads a VTT file and parses it into a list of cues.
    Each cue is a dictionary containing 'id', 'timestamp', and 'text'.
    """
    cues = []
    with open(file_path, 'r', encoding='utf-8') as f:
        lines = f.readlines()

    idx = 0
    while idx < len(lines):
        line = lines[idx].strip()

        # Skip header
        if line == 'WEBVTT' or line == '':
            idx +=1
            continue

        cue = {'id': '', 'timestamp': '', 'text': ''}

        # Check if line is an ID
        if '-->' not in line:
            cue['id'] = line
            idx +=1
            line = lines[idx].strip()

        # Line must be timestamp now
        cue['timestamp'] = line
        idx +=1

        # Collect text (could be multiple lines)
        text_lines = []
        while idx < len(lines) and lines[idx].strip() != '':
            text_lines.append(lines[idx].strip())
            idx +=1
        cue['text'] = '\n'.join(text_lines)

        cues.append(cue)
        idx +=1  # Skip the empty line

    return cues

def write_vtt_file(cues, output_path):
    """
    Writes the list of cues back to a VTT file.
    """
    with open(output_path, 'w', encoding='utf-8') as f:
        f.write('WEBVTT\n\n')
        for cue in cues:
            if cue['id']:
                f.write(f"{cue['id']}\n")
            f.write(f"{cue['timestamp']}\n")
            f.write(f"{cue['text']}\n\n")

def split_long_lines(text, max_line_length=42):
    """
    Splits long lines of text into multiple lines without breaking words.
    """
    lines = []
    for paragraph in text.strip().split('\n'):
        words = paragraph.split()
        line = ''
        for word in words:
            # If the word itself is longer than max_line_length, split it
            while len(word) > max_line_length:
                lines.append(word[:max_line_length])
                word = word[max_line_length:]
            if len(line) + len(word) + 1 <= max_line_length:
                if line:
                    line += ' ' + word
                else:
                    line = word
            else:
                lines.append(line)
                line = word
        if line:
            lines.append(line)
    return '\n'.join(lines)

def batch_translate(texts, source_lang='English', target_lang='Italian'):
    """
    Translates a list of texts using OpenAI's API in batches.
    """
    translated_texts = []
    batch_size = 5  # Adjusted to 5 for better compliance.

    for i in tqdm(range(0, len(texts), batch_size), desc="Translating"):
        batch = texts[i:i+batch_size]
        # Create a JSON array of texts
        batch_json = json.dumps(batch)
        # Construct the message for the assistant
        system_prompt = (
            f"You are a translation assistant that translates texts from {source_lang} to {target_lang}. "
            f"You will be provided with a JSON array of texts in {source_lang}. "
            f"The array may contain empty strings. "
            f"Translate each text into {target_lang}, preserving the order and including empty strings where appropriate. "
            f"Do not combine or split texts. "
            f"Return the translations as a JSON array with the same number of items as the input array. "
            f"Do not include any additional text, explanations, or formatting in your response. "
            f"Ensure the output is valid JSON.\n\n"
            f"For example, if you receive:\n"
            f'["Hello", "", "Thank you"]\n'
            f"You should return:\n"
            f'["Ciao", "", "Grazie"]'
        )
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": f"Translate the following texts:\n{batch_json}"}
        ]
        # Call the OpenAI API
        try:
            response = openai.ChatCompletion.create(
                model="gpt-3.5-turbo",
                messages=messages,
                temperature=0.0,
            )
            assistant_reply = response['choices'][0]['message']['content'].strip()
            # Extract JSON array from the assistant's response
            json_pattern = r'\[.*\]'
            json_match = re.search(json_pattern, assistant_reply, re.DOTALL)
            if json_match:
                json_str = json_match.group(0)
                try:
                    translated_batch = json.loads(json_str)
                    if not isinstance(translated_batch, list):
                        raise ValueError("Assistant did not return a JSON array.")
                    if len(translated_batch) != len(batch):
                        raise ValueError(f"Expected {len(batch)} translations but got {len(translated_batch)}.")
                    translated_texts.extend(translated_batch)
                except json.JSONDecodeError:
                    print(f"Error: Could not decode JSON response from assistant at batch index {i}.")
                    print(f"Assistant's response: {assistant_reply}")
                    translated_texts.extend([''] * len(batch))
                except ValueError as ve:
                    print(f"ValueError: {ve}")
                    print(f"Assistant's response: {assistant_reply}")
                    translated_texts.extend([''] * len(batch))
            else:
                print(f"Error: Could not find JSON array in assistant's response at batch index {i}")
                print(f"Assistant's response: {assistant_reply}")
                translated_texts.extend([''] * len(batch))
        except Exception as e:
            print(f"An error occurred during translation at batch index {i}: {e}")
            translated_texts.extend([''] * len(batch))
    return translated_texts

def main():
    input_file = 'reduced_GMT20240906-080857_Recording_gallery_1760x900-en-GB copy.vtt'
    output_file = 'openai_translated_GMT20240906-080857_Recording_gallery_1760x900-it-IT.vtt'

    # Step 1: Read the VTT file
    cues = read_vtt_file(input_file)

    # Step 2: Extract texts for translation
    texts = [cue['text'] for cue in cues]

    # Step 3: Translate texts
    translated_texts = batch_translate(texts, source_lang='English', target_lang='Italian')

    # Step 4: Process translated texts (split long lines)
    processed_translations = []
    for translated_text in translated_texts:
        processed_text = split_long_lines(translated_text, max_line_length=42)
        processed_translations.append(processed_text)

    # Step 5: Assign processed translations back to cues
    for idx, cue in enumerate(cues):
        try:
            cue['text'] = processed_translations[idx]
        except IndexError:
            print(f"Error: No translation available for cue at index {idx}.")
            cue['text'] = ''

    # Step 6: Write the translated cues to a new VTT file
    write_vtt_file(cues, output_file)
    print(f"Translation complete. Translated file saved as '{output_file}'.")

if __name__ == "__main__":
    main()