You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


import copy
import json
import logging
import os
import sys
import traceback
from typing import List

from golem.task.taskbase import Task
from tests.apps.blender.task.test_blenderintegration import \
    TestBlenderIntegration
from tests.golem.verifier.test_utils.helpers import \
    find_crop_files_in_path, \
    are_pixels_equal, find_fragments_in_path

logger = logging.getLogger(__name__)
logging.disable(logging.CRITICAL)


class Report:

    def __init__(self):
        self.failed_params: List[dict] = list()
        self.success_params: List[dict] = list()
        self.all_params: List[dict] = list()

    def success(self, params: dict) -> None:
        self.success_params.append(params)
        self.all_params.append(params)

    def fail(self, params: dict, reason: dict) -> None:
        params['fail_reason'] = reason

        self.failed_params.append(params)
        self.all_params.append(params)

    def update(self, report: 'Report') -> None:
        self.failed_params = self.failed_params + report.failed_params
        self.success_params = self.success_params + report.success_params
        self.all_params = self.all_params + report.all_params

    # Merge reports with the same parameters but different crops.
    # Note: This function doesn't check if reports have the same parameters.
    def merge_reports_content(self):
        if self.failed_params:
            self.failed_params = [self.merge_report(self.failed_params)]
        if self.all_params:
            self.all_params = [self.merge_report(self.all_params)]
        if self.success_params:
            self.success_params = [self.merge_report(self.success_params)]

    def merge_report(self, report: List[dict]):
        if report:
            # Choose one report and copy common part.
            report_params = copy.deepcopy(report[0])

            # Delete parameters and replace it with empty dict.
            # It will be updated below.
            del report_params['crops_params']
            report_params['crops_params'] = dict()
            report_params['fails'] = list()

            for subtasks in report:
                crops_params = subtasks["crops_params"]

                # Probably there's only one subtask
                # but we can iterate over whole list.
                for subtask_num, crop in crops_params.items():

                    report_params['crops_params'][subtask_num] = crop

                    # Copy fail if it existed.
                    if subtasks.get('fail_reason') is not None:
                        report_params['fails'][subtask_num].append(
                            subtasks['fail_reason'])

            return report_params
        return report

    def to_file(self, directory: str, part: int):
        os.makedirs(directory, exist_ok=True)

        all_path = os.path.join(directory, 'all_tests{}.json'.format(part))
        with open(all_path, 'w') as outfile:
            json.dump(self.all_params, outfile, indent=4, sort_keys=False)

        failed_path = os.path.join(directory,
                                   'failed_tests{}.json'.format(part))
        with open(failed_path, 'w') as outfile:
            json.dump(self.failed_params, outfile, indent=4, sort_keys=False)

        success_path = os.path.join(directory,
                                    'success_tests{}.json'.format(part))
        with open(success_path, 'w') as outfile:
            json.dump(self.success_params, outfile, indent=4, sort_keys=False)

    def clear_reports(self):
        self.failed_params: List[dict] = list()
        self.success_params: List[dict] = list()
        self.all_params: List[dict] = list()


class ExtendedVerifierTestEnv:

    def __init__(self):
        self.report = Report()

    def run(self):

        ExtendedVerifierTest.setUpClass()

        try:
            parameters_sets = self._generate_parameters()
            self.run_for_params(parameters_sets)
        except (Exception, RuntimeError) as e:
            print("Script error ocured: {}".format(repr(e)))
        finally:
            ExtendedVerifierTest.tearDownClass()

    def _run_parameters_set(self, parameters):
        try:
            tester = ExtendedVerifierTest()

            tester.setUp()
            tester.run_for_parameters_set(parameters)

        except (Exception, RuntimeError) as e:
            _, _, tb = sys.exc_info()
            message = traceback.format_exc()
            tb_info = traceback.extract_tb(tb)
            filename, line, function, _ = tb_info[-1]

            reason = {
                'exception': repr(e),
                'line': line,
                'filename': filename,
                'function': function,
                'stacktrace': message,
                'tmp_dir': tester.tempdir
            }

            self.report.fail(parameters, reason)
        else:
            report = tester.report
            report.merge_reports_content()

            self.report.update(report)
        finally:
            tester.tearDown()

    def run_for_params(self, parameters_sets: List[dict]):
        logger.info("Parameters {}".format(str(parameters_sets)))

        num_sets = len(parameters_sets)
        print("Running {} parameters sets.".format(num_sets))

        counter = 0
        max_sets_in_batch = 100
        part = 0

        for parameters_set in parameters_sets:
            try:
                self._run_parameters_set(parameters_set)
            except (Exception, RuntimeError) as e:
                print("Saving to file partial results.")
                self._reports_to_files(part)
                raise e

            self._progress()

            # Reports consume to much space to keep them in memory
            # all the time.
            counter += 1
            if counter >= max_sets_in_batch:
                counter = 0
                self._reports_to_files(part)
                self.report.clear_reports()
                part += 1

        # Add newline on end.
        print("")
        self._print_fails()
        self._reports_to_files(part)

    def _print_fails(self):
        print("Printing failed tests:")
        print(json.dumps(self.report.failed_params, indent=4, sort_keys=False))

    def _progress(self):
        # Print dot for each test to indicate progress like in pytest.
        print(".", end='')
        sys.stdout.flush()

    def _reports_to_files(self, part):
        self.report.to_file("reports", part)

    def _generate_parameters(self):
        # resolutions_list = [[400, 400]]
        # subtasks_num_list = range(1, 4)
        # num_frames = [list(range(1, 2))]
        resolutions_list = [[400, 400]]
        subtasks_num_list = list(range(1, 40))
        num_frames = self._generate_num_frames(1, 2)

        return self._generate_combinations(resolutions_list, subtasks_num_list,
                                           num_frames)

    def _generate_num_frames(self, min_num_frames: int, max_num_frames: int):
        return [
            list(range(1, i + 1))
            for i in range(min_num_frames, max_num_frames + 1)
        ]

    @classmethod
    def _generate_combinations(cls, resolutions_list: List[List[int]],
                               subtasks_num_list: List[int],
                               frames_list: List[List[int]]):
        parameters_set = []

        for resolution in resolutions_list:
            for subtasks_num in subtasks_num_list:
                for frames in frames_list:
                    params = ExtendedVerifierTest._build_params(
                        resolution, subtasks_num, frames, {})
                    parameters_set.append(params)
        return parameters_set


# pylint: disable=too-many-ancestors
class ExtendedVerifierTest(TestBlenderIntegration):

    def __init__(self):
        super().__init__()
        self.report: Report = Report()

    def run_for_parameters_set(self, parameters_set: dict):

        resolution = parameters_set['resolution']
        subtasks = parameters_set['subtasks_count']
        frames = parameters_set['frames']

        # TODO: Use these parameters to test chosen crops.
        # crops_params = parameters_set['crops_params']

        task_def = self._task_dictionary(
            scene_file=self._get_chessboard_scene(),
            resolution=resolution,
            subtasks_count=subtasks,
            frames=frames)

        task: Task = self.start_task(task_def)

        for i in range(task.task_definition.subtasks_count):
            result, subtask_id, _ = self.compute_next_subtask(task, i)

            try:
                result = self.verify_subtask(task, subtask_id, result)
                self._assert_crops_match(task.task_definition.task_id)

                if not result:
                    raise RuntimeError("Verification (decision tree) resulted "
                                       "in negative response.")

            except (Exception, RuntimeError):
                parameters_set_copy = self._add_crop_params(
                    parameters_set, task, i)

                reason = {
                    'exception': "Crops don't match.",
                    'tmp_dir': self.tempdir
                }

                self.report.fail(parameters_set_copy, reason)
            else:
                self.report.success(
                    self._add_crop_params(parameters_set, task, i))

        result = task.task_definition.output_file
        for file in result:
            if not os.path.isfile(file):
                raise RuntimeError("Result file [{}] doesn't exist.".format(
                    file))

    def _add_crop_params(self, parameters_set: dict, task: Task,
                         subtask_num: int):
        parameters_set_copy = copy.deepcopy(parameters_set)
        crops = self._deduce_crop_parameters(task.task_definition.task_id)

        parameters_set_copy['crops_params'] = dict()
        parameters_set_copy['crops_params'][subtask_num] = crops['crops']

        return parameters_set_copy

    def _assert_crops_match(self, task_id: str) -> None:
        task_dir = os.path.join(self.tempdir, task_id)

        try:
            crops_paths = find_crop_files_in_path(
                os.path.join(task_dir, 'output'))
            fragments_paths = find_fragments_in_path(
                os.path.join(task_dir, "work"))
        except Exception:
            raise Exception(
                "Can't find crop files in output or work directory.")

        assert crops_paths, "There were no crops produced!"
        assert len(crops_paths) == len(
            fragments_paths
        ), "Amount of rendered crops != amount of image fragments!"
        for crop_path, fragment_path in zip(
                crops_paths,
                fragments_paths,
        ):
            assert are_pixels_equal(
                crop_path,
                fragment_path,
            ), f"crop: {crop_path} doesn't match: {fragment_path}"

    def _deduce_crop_parameters(self, task_id: str) -> dict:
        task_dir = os.path.join(self.tempdir, task_id)
        params_file = os.path.join(task_dir, 'work',
                                   'blender_render_params.json')

        with open(params_file, "r") as file:
            return json.load(file)

    @classmethod
    def _build_params(cls, resolution: List[int], subtasks: int,
                      frames: List[int], crops_params: dict):
        return {
            'resolution': resolution,
            'subtasks_count': subtasks,
            'frames': frames,
            'crops_params': crops_params
        }


def run_script():
    test_env = ExtendedVerifierTestEnv()
    test_env.run()


if __name__ == "__main__":
    run_script()