from __future__ import annotations

import gc
import inspect
import os
import time
from collections import OrderedDict
from concurrent.futures import ThreadPoolExecutor
from functools import partial
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
from unittest.mock import MagicMock, Mock, patch

import dill as pickle
import numpy as np
import pytest
import supervision as sv
from fastapi import BackgroundTasks
from inference.core.active_learning.entities import (ImageDimensions,
                                                     StrategyLimit,
                                                     StrategyLimitType)
from inference.core.cache.base import BaseCache
from inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1 import (
    execute_registration, generate_batch_name, get_workspace_name,
    register_datapoint, register_datapoint_at_roboflow)
from inference.core.workflows.execution_engine.entities.base import (
    ImageParentMetadata, WorkflowImageData)


def codeflash_wrap(codeflash_wrapped, codeflash_test_module_name, codeflash_test_class_name, codeflash_test_name, codeflash_function_name, codeflash_line_id, codeflash_loop_index, *args, **kwargs):
    test_id = f'{codeflash_test_module_name}:{codeflash_test_class_name}:{codeflash_test_name}:{codeflash_line_id}:{codeflash_loop_index}'
    if not hasattr(codeflash_wrap, 'index'):
        codeflash_wrap.index = {}
    if test_id in codeflash_wrap.index:
        codeflash_wrap.index[test_id] += 1
    else:
        codeflash_wrap.index[test_id] = 0
    codeflash_test_index = codeflash_wrap.index[test_id]
    invocation_id = f'{codeflash_line_id}_{codeflash_test_index}'
    test_stdout_tag = f"{codeflash_test_module_name}:{(codeflash_test_class_name + '.' if codeflash_test_class_name else '')}{codeflash_test_name}:{codeflash_function_name}:{codeflash_loop_index}:{invocation_id}"
    print(f'!$######{test_stdout_tag}######$!')
    exception = None
    gc.disable()
    try:
        counter = time.perf_counter_ns()
        return_value = codeflash_wrapped(*args, **kwargs)
        codeflash_duration = time.perf_counter_ns() - counter
    except Exception as e:
        codeflash_duration = time.perf_counter_ns() - counter
        exception = e
    gc.enable()
    print(f'!######{test_stdout_tag}######!')
    iteration = os.environ['CODEFLASH_TEST_ITERATION']
    with Path('{codeflash_run_tmp_dir_client_side}', f'test_return_values_{iteration}.bin').open('ab') as f:
        pickled_values = pickle.dumps((args, kwargs, exception)) if exception else pickle.dumps((args, kwargs, return_value))
        _test_name = f"{codeflash_test_module_name}:{(codeflash_test_class_name + '.' if codeflash_test_class_name else '')}{codeflash_test_name}:{codeflash_function_name}:{codeflash_line_id}".encode('ascii')
        f.write(len(_test_name).to_bytes(4, byteorder='big'))
        f.write(_test_name)
        f.write(codeflash_duration.to_bytes(8, byteorder='big'))
        f.write(len(pickled_values).to_bytes(4, byteorder='big'))
        f.write(pickled_values)
        f.write(codeflash_loop_index.to_bytes(8, byteorder='big'))
        f.write(len(invocation_id).to_bytes(4, byteorder='big'))
        f.write(invocation_id.encode('ascii'))
    if exception:
        raise exception
    return return_value

def test_register_datapoint_at_roboflow_with_fire_and_forget_false_calls_execute_registration():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that when fire_and_forget is False, execute_registration is called directly.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_fire_and_forget_false_calls_execute_registration', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_fire_and_forget_true_and_background_tasks():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that when fire_and_forget=True and background_tasks provided, task is added to background.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = True
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = BackgroundTasks()
    thread_pool_executor = None
    api_key = 'test_api_key'
    _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_fire_and_forget_true_and_background_tasks', 'register_datapoint_at_roboflow', '20', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_register_datapoint_at_roboflow_with_fire_and_forget_true_and_thread_pool():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that when fire_and_forget=True and thread_pool provided, task is submitted to pool.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = True
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    mock_thread_pool = Mock(spec=ThreadPoolExecutor)
    api_key = 'test_api_key'
    _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=mock_thread_pool, api_key=api_key)
    _call__bound__arguments.apply_defaults()
    codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_fire_and_forget_true_and_thread_pool', 'register_datapoint_at_roboflow', '20', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
    codeflash_output = codeflash_return_value
    result = codeflash_output

def test_register_datapoint_at_roboflow_with_image_name_parameter():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that image_name parameter is passed through when provided.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    custom_image_name = 'my_custom_image_name'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, image_name=custom_image_name)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_image_name_parameter', 'register_datapoint_at_roboflow', '21_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_metadata_parameter():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test that metadata parameter is passed through when provided.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    custom_metadata = {'key1': 'value1', 'key2': 'value2'}
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, metadata=custom_metadata)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_metadata_parameter', 'register_datapoint_at_roboflow', '21_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_generate_batch_name_with_never_frequency():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    "Test generate_batch_name returns prefix when frequency is 'never'."
    prefix = 'my_batch'
    result = generate_batch_name(labeling_batch_prefix=prefix, new_labeling_batch_frequency='never')

def test_generate_batch_name_with_daily_frequency():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    "Test generate_batch_name includes timestamp for 'daily' frequency."
    prefix = 'my_batch'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.generate_today_timestamp') as mock_timestamp:
        mock_timestamp.return_value = '2024_01_15'
        result = generate_batch_name(labeling_batch_prefix=prefix, new_labeling_batch_frequency='daily')

def test_generate_batch_name_with_weekly_frequency():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    "Test generate_batch_name includes timestamp for 'weekly' frequency."
    prefix = 'my_batch'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.generate_start_timestamp_for_this_week') as mock_timestamp:
        mock_timestamp.return_value = '2024_01_10'
        result = generate_batch_name(labeling_batch_prefix=prefix, new_labeling_batch_frequency='weekly')

def test_generate_batch_name_with_monthly_frequency():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    "Test generate_batch_name includes timestamp for 'monthly' frequency."
    prefix = 'my_batch'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.generate_start_timestamp_for_this_month') as mock_timestamp:
        mock_timestamp.return_value = '2024_01_01'
        result = generate_batch_name(labeling_batch_prefix=prefix, new_labeling_batch_frequency='monthly')

def test_get_workspace_name_returns_cached_value_if_available():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test get_workspace_name returns cached workspace name when available.'
    api_key = 'test_api_key'
    cached_workspace = 'cached_workspace_name'
    mock_cache = Mock(spec=BaseCache)
    mock_cache.get.return_value = cached_workspace
    result = get_workspace_name(api_key=api_key, cache=mock_cache)

def test_get_workspace_name_fetches_and_caches_when_not_cached():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test get_workspace_name fetches from API and caches when not in cache.'
    api_key = 'test_api_key'
    workspace_from_api = 'api_workspace_name'
    mock_cache = Mock(spec=BaseCache)
    mock_cache.get.return_value = None
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.get_roboflow_workspace') as mock_get_ws:
        mock_get_ws.return_value = workspace_from_api
        result = get_workspace_name(api_key=api_key, cache=mock_cache)

def test_register_datapoint_at_roboflow_with_empty_registration_tags():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles empty registration tags list.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = []
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_empty_registration_tags', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_zero_usage_limits():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles zero usage limits.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 0
    hourly_usage_limit = 0
    daily_usage_limit = 0
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_zero_usage_limits', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_very_small_max_image_size():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles very small max_image_size.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (1, 1)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_very_small_max_image_size', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_very_large_max_image_size():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles very large max_image_size.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (10000, 10000)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_very_large_max_image_size', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_min_compression_level():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles minimum compression level (0).'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 0
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_min_compression_level', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_max_compression_level():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles maximum compression level (100).'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 100
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_max_compression_level', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_none_prediction():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles None prediction.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=None, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_none_prediction', 'register_datapoint_at_roboflow', '19_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_dict_prediction():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles dict prediction.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    dict_prediction = {'detections': [], 'confidence': []}
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = True
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=dict_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_dict_prediction', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_sv_detections_prediction():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles sv.Detections prediction.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    sv_prediction = sv.Detections.empty()
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = True
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=sv_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_sv_detections_prediction', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_empty_string_image_name():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles empty string image_name.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, image_name='')
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_empty_string_image_name', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_with_none_metadata():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles None metadata.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, metadata=None)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_none_metadata', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_empty_metadata():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles empty metadata dictionary.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, metadata={})
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_empty_metadata', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_special_characters_in_target_project():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles special characters in target_project.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test-project_123!@#'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_special_characters_in_target_project', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_special_characters_in_labeling_batch_prefix():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function handles special characters in labeling_batch_prefix.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch-prefix_123!@#'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_special_characters_in_labeling_batch_prefix', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_get_workspace_name_with_api_key_containing_special_chars():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test get_workspace_name handles API key with special characters.'
    api_key = 'test_api_key!@#$%^&*()'
    workspace_from_api = 'workspace_name'
    mock_cache = Mock(spec=BaseCache)
    mock_cache.get.return_value = None
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.get_roboflow_workspace') as mock_get_ws:
        mock_get_ws.return_value = workspace_from_api
        result = get_workspace_name(api_key=api_key, cache=mock_cache)

def test_get_workspace_name_with_very_long_api_key():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test get_workspace_name handles very long API key.'
    api_key = 'a' * 1000
    workspace_from_api = 'workspace_name'
    mock_cache = Mock(spec=BaseCache)
    mock_cache.get.return_value = None
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.get_roboflow_workspace') as mock_get_ws:
        mock_get_ws.return_value = workspace_from_api
        result = get_workspace_name(api_key=api_key, cache=mock_cache)

def test_register_datapoint_at_roboflow_persist_predictions_true():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function with persist_predictions set to True.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = True
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_persist_predictions_true', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_persist_predictions_false():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function with persist_predictions set to False.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_persist_predictions_false', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_many_registration_tags():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function with large number of registration tags.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = [f'tag_{i}' for i in range(100)]
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_many_registration_tags', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_large_metadata():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function with large metadata dictionary.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    large_metadata = {f'key_{i}': f'value_{i}' for i in range(500)}
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key, metadata=large_metadata)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_large_metadata', 'register_datapoint_at_roboflow', '21_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output
        call_kwargs = mock_execute.call_args[1]

def test_register_datapoint_at_roboflow_with_large_image():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test function with large image data.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((2000, 2000, 3), dtype=np.uint8)
    mock_prediction = None
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = False
    labeling_batch_prefix = 'batch'
    new_labeling_batch_frequency = 'never'
    mock_cache = Mock(spec=BaseCache)
    background_tasks = None
    thread_pool_executor = None
    api_key = 'test_api_key'
    with patch('inference.core.workflows.core_steps.sinks.roboflow.dataset_upload.v1.execute_registration') as mock_execute:
        mock_execute.return_value = (True, 'Test message')
        _call__bound__arguments = inspect.signature(register_datapoint_at_roboflow).bind(image=mock_image, prediction=mock_prediction, target_project=target_project, usage_quota_name=usage_quota_name, persist_predictions=persist_predictions, minutely_usage_limit=minutely_usage_limit, hourly_usage_limit=hourly_usage_limit, daily_usage_limit=daily_usage_limit, max_image_size=max_image_size, compression_level=compression_level, registration_tags=registration_tags, fire_and_forget=fire_and_forget, labeling_batch_prefix=labeling_batch_prefix, new_labeling_batch_frequency=new_labeling_batch_frequency, cache=mock_cache, background_tasks=background_tasks, thread_pool_executor=thread_pool_executor, api_key=api_key)
        _call__bound__arguments.apply_defaults()
        codeflash_return_value = codeflash_wrap(register_datapoint_at_roboflow, 'tests.inference.unit_tests.test_register_datapoint_at_roboflow__unit_test_1', None, 'test_register_datapoint_at_roboflow_with_large_image', 'register_datapoint_at_roboflow', '20_1', codeflash_loop_index, *_call__bound__arguments.args, **_call__bound__arguments.kwargs)
        codeflash_output = codeflash_return_value
        result = codeflash_output

def test_register_datapoint_at_roboflow_multiple_calls_with_background_tasks():
    np.random.seed(42)
    codeflash_loop_index = int(os.environ['CODEFLASH_LOOP_INDEX'])
    'Test multiple calls with background_tasks accumulate tasks.'
    mock_image = Mock(spec=WorkflowImageData)
    mock_image.numpy_image = np.zeros((100, 100, 3), dtype=np.uint8)
    target_project = 'test_project'
    usage_quota_name = 'default_quota'
    persist_predictions = False
    minutely_usage_limit = 10
    hourly_usage_limit = 100
    daily_usage_limit = 1000
    max_image_size = (640, 480)
    compression_level = 95
    registration_tags = ['test']
    fire_and_forget = True
    lab