aws textract couldn't recognize some tables and convert them into csv

I am trying to take all the tables from pdf with aws Textract and convert to CSV file each of them but when I try it doesn't recognize some of them. I tried the demo version of Textract and it is working fine so I think I have some mistake in my code and I couldn't find it. this is lambda function:

def lambda_handler(event, context):
    s3_client = boto3.client("s3")
    textract = boto3.client("textract")

    if event:
        file_obj = event["Records"][0]
        bucket_name = str(file_obj["s3"]["bucket"]["name"])
        s3_key = unquote_plus(str(file_obj["s3"]["object"]["key"]))
        file_name = s3_key.split('/')[-1].split('.')[0]  # Extracting file name without extension
        unique_folder = f"{file_name}_{uuid.uuid4().hex}"
        output_prefix = f"analyze-output/{unique_folder}"

        try:
            response = textract.start_document_analysis(
                DocumentLocation={'S3Object': {'Bucket': bucket_name, 'Name': s3_key}},
                FeatureTypes=["TABLES"]
            )
            job_id = response['JobId']
            logging.info(f"Started Textract job with Job ID: {job_id}")

            status = ""
            while True:
                response = textract.get_document_analysis(JobId=job_id)
                status = response['JobStatus']
                if status in ["SUCCEEDED", "FAILED"]:
                    break
                time.sleep(5)

            if status == "SUCCEEDED":
                finished = False
                nextToken = None
                while not finished:
                    response = textract.get_document_analysis(JobId=job_id, NextToken=nextToken) if nextToken else textract.get_document_analysis(JobId=job_id)
                    
                    logging.info(f"Processing response batch for file: {output_prefix}")
                    process_textract_response(s3_client, response, output_prefix, bucket_name)

                    nextToken = response.get('NextToken')
                    finished = nextToken is None

            else:
                logging.error("Textract job failed")
                return {
                    "statusCode": 500,
                    "body": json.dumps("Textract job failed"),
                }

        except Exception as e:
            logging.error(f"Error processing file: {e}")
            return {
                "statusCode": 500,
                "body": json.dumps("Error in processing PDF"),
            }

    return {"statusCode": 200, "body": json.dumps("Hello")}

if __name__ == "__main__":
    lambda_handler(None, None)

this is helper function:

def get_rows_columns_map(table_result, blocks_map):
    rows = {}
    for relationship in table_result['Relationships']:
        if relationship['Type'] == 'CHILD':
            for child_id in relationship['Ids']:
                cell = blocks_map[child_id]
                if cell['BlockType'] == 'CELL':
                    row_index = cell['RowIndex']
                    col_index = cell['ColumnIndex']
                    if row_index not in rows:
                        rows[row_index] = {}
                    rows[row_index][col_index] = get_text(cell, blocks_map)
    return rows

def get_text(result, blocks_map):
    text = ''
    if 'Relationships' in result:
        for relationship in result['Relationships']:
            if relationship['Type'] == 'CHILD':
                for child_id in relationship['Ids']:
                    word = blocks_map[child_id]
                    if word['BlockType'] == 'WORD':
                        text += word['Text'] + ' '
                    elif word['BlockType'] == 'SELECTION_ELEMENT':
                        if word['SelectionStatus'] == 'SELECTED':
                            text += 'X '
    return text.strip()

def upload_to_s3(s3_client, file_path, bucket_name, s3_key):
    try:
        s3_client.upload_file(file_path, bucket_name, s3_key)
        logging.info(f"File {file_path} uploaded to {bucket_name}/{s3_key}")
    except Exception as e:
        logging.error(f"Error uploading file to S3: {e}")

def process_textract_response(s3_client, response, file_name, bucket_name):
    blocks_map = {}
    page_tables = {}

    logging.info(f"Starting to process response for file: {file_name}")

    for block in response['Blocks']:
        blocks_map[block['Id']] = block
        if block['BlockType'] == "TABLE":
            page_number = block.get('Page', 1)
            if page_number not in page_tables:
                page_tables[page_number] = []
            page_tables[page_number].append(block)

    if not page_tables:
        logging.info("No tables found")
        return

    output_dir = f"/tmp/{file_name}"
    os.makedirs(output_dir, exist_ok=True)

    for page_number, tables in page_tables.items():
        for index, table in enumerate(tables):
            try:
                csv_content = generate_table_csv(table, blocks_map)
                output_file = f"{output_dir}/table_page_{page_number}_index_{index}.csv"
                
                with open(output_file, "w") as f:
                    f.write(csv_content)
                logging.info(f"Table {index} on Page {page_number} saved to {output_file}")

                s3_key = f"{file_name}/table_page_{page_number}_index_{index}.csv"
                upload_to_s3(s3_client, output_file, bucket_name, s3_key)
            except Exception as e:
                logging.error(f"Error processing table on page {page_number}, index {index}: {e}")

    logging.info(f"Completed processing for file: {file_name}")

def generate_table_csv(table_result, blocks_map):
    rows = get_rows_columns_map(table_result, blocks_map)
    csv = ''
    for row_index, cols in sorted(rows.items()):
        for col_index, text in sorted(cols.items()):
            csv += f'"{text}",'
        csv = csv[:-1] + '\n'
    return csv

the error I am getting: