Repository Analysis

microsoft/RD-Agent

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report

24.3 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of microsoft/RD-Agent, a Python project with 13,879 GitHub stars. SynthScan v2.0 examined 113,373 lines of code across 790 source files, recording 1444 pattern matches distributed across 23 syntactic categories. The overall adjusted score of 24.3 places this repository in the Moderate AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

24.3
Adjusted Score
24.3
Raw Score
100%
Time Factor
2026-06-15
Last Push
13.9K
Stars
Python
Language
113.4K
Lines of Code
790
Files
1.4K
Pattern Hits
2026-07-14
Scan Date
0.29
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 227MEDIUM 176LOW 1041

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 1444 distinct pattern matches across 23 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Cross-File Repetition212 hits · 1060 pts
SeverityFileLineSnippetContext
HIGHrdagent/core/interactor.py0interact with the user to get feedback or confirmation. responsibilities: - present the current state of the experiment STRING
HIGHrdagent/scenarios/data_science/interactor/__init__.py0interact with the user to get feedback or confirmation. responsibilities: - present the current state of the experiment STRING
HIGHrdagent/components/interactor/__init__.py0interact with the user to get feedback or confirmation. responsibilities: - present the current state of the experiment STRING
HIGHrdagent/app/qlib_rd_loop/model.py0auto r&d evolving loop for fintech factors. you can continue running session by .. code-block:: python dotenv run -- pytSTRING
HIGHrdagent/app/qlib_rd_loop/factor.py0auto r&d evolving loop for fintech factors. you can continue running session by .. code-block:: python dotenv run -- pytSTRING
HIGHrdagent/app/qlib_rd_loop/quant.py0auto r&d evolving loop for fintech factors. you can continue running session by .. code-block:: python dotenv run -- pytSTRING
HIGH…ent/components/coder/data_science/ensemble/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGH…ent/components/coder/data_science/pipeline/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGH…ent/components/coder/data_science/workflow/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGHrdagent/components/coder/data_science/model/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGH…gent/components/coder/data_science/feature/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGH…ponents/coder/data_science/raw_data_loader/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGHrdagent/scenarios/data_science/dev/runner/__init__.py0assign the code list to the evolving item. the code list is aligned with the evolving item's sub-tasks. if a task is notSTRING
HIGH…ent/spaceship-titanic_template/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…mplates/playground-series-s4e8/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…/templates/meta_tpl_deprecated/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…lar-playground-series-dec-2021/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…york-city-taxi-fare-prediction/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…plates/playground-series-s3e26/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…/experiment/templates/sf-crime/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…s/forest-cover-type-prediction/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…nt/templates/spaceship-titanic/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…ent/templates/digit-recognizer/fea_share_preprocess.py0this method loads the data, drops the unnecessary columns, and splits it into train and validation sets.STRING
HIGH…ent/spaceship-titanic_template/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…mplates/playground-series-s4e8/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…/templates/meta_tpl_deprecated/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…plates/playground-series-s3e26/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…/experiment/templates/sf-crime/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…nt/templates/spaceship-titanic/fea_share_preprocess.py0fits the preprocessor on the training data and returns the fitted preprocessor.STRING
HIGH…ent/spaceship-titanic_template/fea_share_preprocess.py0transforms the given dataframe using the fitted preprocessor. ensures the processed data has consistent features across STRING
HIGH…/templates/meta_tpl_deprecated/fea_share_preprocess.py0transforms the given dataframe using the fitted preprocessor. ensures the processed data has consistent features across STRING
HIGH…nt/templates/spaceship-titanic/fea_share_preprocess.py0transforms the given dataframe using the fitted preprocessor. ensures the processed data has consistent features across STRING
HIGH…ent/spaceship-titanic_template/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…mplates/playground-series-s4e8/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…plates/playground-series-s3e14/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…/templates/meta_tpl_deprecated/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…ventilator-pressure-prediction/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…lar-playground-series-dec-2021/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…york-city-taxi-fare-prediction/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…plates/playground-series-s3e11/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…plates/playground-series-s3e16/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…plates/playground-series-s3e26/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…rize-english-language-learning/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…/experiment/templates/sf-crime/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…s/forest-cover-type-prediction/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…lar-playground-series-may-2022/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…nt/templates/spaceship-titanic/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…l-iceberg-classifier-challenge/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…ent/templates/digit-recognizer/fea_share_preprocess.py0this method applies the preprocessing steps to the training, validation, and test datasets.STRING
HIGH…paceship-titanic_template/model/select_randomforest.py0select relevant features. to be used in fit & predict function.STRING
HIGH…periment/spaceship-titanic_template/model/select_nn.py0select relevant features. to be used in fit & predict function.STRING
HIGH…nt/spaceship-titanic_template/model/select_lightgbm.py0select relevant features. to be used in fit & predict function.STRING
HIGH…ent/spaceship-titanic_template/model/select_xgboost.py0select relevant features. to be used in fit & predict function.STRING
HIGH…es/playground-series-s4e9/model/select_randomforest.py0select relevant features. to be used in fit & predict function.STRING
HIGH…nt/templates/playground-series-s4e9/model/select_nn.py0select relevant features. to be used in fit & predict function.STRING
HIGH…plates/playground-series-s4e9/model/select_lightgbm.py0select relevant features. to be used in fit & predict function.STRING
HIGH…mplates/playground-series-s4e9/model/select_xgboost.py0select relevant features. to be used in fit & predict function.STRING
HIGH…es/playground-series-s4e8/model/select_randomforest.py0select relevant features. to be used in fit & predict function.STRING
HIGH…nt/templates/playground-series-s4e8/model/select_nn.py0select relevant features. to be used in fit & predict function.STRING
HIGH…plates/playground-series-s4e8/model/select_lightgbm.py0select relevant features. to be used in fit & predict function.STRING
152 more matches not shown…
Unused Imports310 hits · 306 pts
SeverityFileLineSnippetContext
LOWtest/utils/test_conf.py4CODE
LOWtest/utils/test_env.py1CODE
LOWtest/utils/test_import.py2CODE
LOWtest/utils/env_tpl/read_exp.py2CODE
LOWtest/utils/env_tpl/read_exp.py3CODE
LOWtest/finetune/test_benchmark_tablebench.py6CODE
LOWtest/finetune/test_benchmark.py10CODE
LOWtest/finetune/test_benchmark_api.py10CODE
LOWtest/oai/test_advanced.py7CODE
LOWtest/oai/test_base.py1CODE
LOWtest/oai/test_completion.py3CODE
LOWtest/notebook/testfiles/main2.py5CODE
LOWtest/notebook/testfiles/main2.py14CODE
LOWtest/notebook/testfiles/main2.py16CODE
LOWrdagent/core/evolving_agent.py1CODE
LOWrdagent/core/conf.py1CODE
LOWrdagent/core/evolving_framework.py1CODE
LOWrdagent/core/proposal.py3CODE
LOWrdagent/core/experiment.py1CODE
LOWrdagent/core/utils.py1CODE
LOWrdagent/core/developer.py1CODE
LOWrdagent/core/interactor.py1CODE
LOWrdagent/app/cli.py9CODE
LOWrdagent/app/benchmark/factor/analysis.py9CODE
LOWrdagent/app/benchmark/model/eval.py14CODE
LOWrdagent/app/CI/run.py1CODE
LOWrdagent/app/utils/ws.py1CODE
LOWrdagent/app/utils/health_check.py6CODE
LOWrdagent/app/utils/info.py4CODE
LOWrdagent/app/utils/info.py9CODE
LOWrdagent/app/utils/ws_ft.py1CODE
LOWrdagent/app/utils/ws_ft.py5CODE
LOWrdagent/app/utils/ws_ft.py7CODE
LOWrdagent/app/finetune/data_science/scen.py4CODE
LOWrdagent/app/finetune/data_science/scen.py5CODE
LOWrdagent/app/finetune/data_science/scen.py8CODE
LOWrdagent/app/finetune/data_science/loop.py8CODE
LOWrdagent/app/finetune/data_science/loop.py9CODE
LOWrdagent/app/qlib_rd_loop/factor_from_report.py4CODE
LOWrdagent/app/qlib_rd_loop/factor_from_report.py15CODE
LOWrdagent/app/rl/ui/data_loader.py17CODE
LOWrdagent/utils/env.py14CODE
LOWrdagent/utils/env.py45CODE
LOWrdagent/utils/__init__.py21CODE
LOWrdagent/utils/agent/apply_patch.py9CODE
LOWrdagent/utils/agent/__init__.py1CODE
LOWrdagent/utils/agent/workflow.py2CODE
LOWrdagent/utils/agent/workflow.py2CODE
LOWrdagent/utils/workflow/__init__.py1CODE
LOWrdagent/utils/workflow/__init__.py1CODE
LOWrdagent/utils/workflow/__init__.py2CODE
LOWrdagent/utils/workflow/__init__.py3CODE
LOWrdagent/utils/workflow/loop.py21CODE
LOWrdagent/utils/workflow/tracking.py18CODE
LOWrdagent/utils/repo/repo_utils.py2CODE
LOWrdagent/oai/llm_utils.py1CODE
LOWrdagent/oai/llm_utils.py10CODE
LOWrdagent/oai/llm_conf.py1CODE
LOWrdagent/oai/backend/deprec.py2CODE
LOWrdagent/oai/backend/deprec.py4CODE
250 more matches not shown…
Excessive Try-Catch Wrapping193 hits · 242 pts
SeverityFileLineSnippetContext
LOWtest/utils/test_import.py56 except Exception as e:CODE
MEDIUMtest/finetune/test_benchmark_tablebench.py122 print(f"Error: {result.stdout[-2000:] if result.stdout else 'No output'}")CODE
MEDIUMtest/finetune/test_benchmark.py125 print(f"Error: {result.stdout[-2000:] if result.stdout else 'No output'}")CODE
MEDIUMtest/finetune/test_benchmark_api.py296 print(f"Error: {result.stdout[-2000:] if result.stdout else 'No output'}")CODE
LOWtest/oai/test_llm_connectivity.py42 except Exception as e:CODE
LOWtest/notebook/test_util.py1475except Exception as e:CODE
LOWtest/notebook/test_util.py1483except Exception as e:CODE
MEDIUMtest/notebook/testfiles/main2.py56 print(f"Error loading train.csv: {e}")CODE
MEDIUMtest/notebook/testfiles/main2.py62 print(f"Error listing train dir: {e}")CODE
MEDIUMtest/notebook/testfiles/main2.py68 print(f"Error listing test dir: {e}")CODE
MEDIUMtest/notebook/testfiles/main2.py79 print(f"Error reading sample_submission.csv: {e}")CODE
MEDIUMtest/notebook/testfiles/main2.py127 print(f"Error reading {filepath}: {e}")CODE
MEDIUMtest/notebook/testfiles/main2.py372 print("Error computing log_loss on val:", ex)CODE
MEDIUMtest/notebook/testfiles/main2.py420 print("Error computing log_loss on validation:", ex)CODE
MEDIUMtest/notebook/testfiles/main2.py117def load_img_as_numpy_with_mask(filepath):CODE
LOWtest/notebook/testfiles/main2.py55 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py61 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py67 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py78 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py126 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py198 except Exception as e:CODE
LOWtest/notebook/testfiles/main2.py370 except Exception as ex:CODE
LOWtest/notebook/testfiles/main2.py418 except Exception as ex:CODE
LOWtest/notebook/testfiles/main2.py446 except Exception:CODE
LOWtest/notebook/testfiles/main_missing_sections.py303 except Exception as e:CODE
LOWtest/notebook/testfiles/main_missing_sections.py311 except Exception as e:CODE
MEDIUMtest/notebook/testfiles/main_missing_sections.py300def main():CODE
LOWtest/notebook/testfiles/main_missing_main_fn.py303except Exception as e:CODE
LOWtest/notebook/testfiles/main_missing_main_fn.py311except Exception as e:CODE
LOWtest/notebook/testfiles/main.py305 except Exception as e:CODE
LOWtest/notebook/testfiles/main.py313 except Exception as e:CODE
LOWrdagent/app/kaggle/loop.py86 except Exception as e:CODE
LOWrdagent/app/kaggle/loop.py106 except Exception as e:CODE
LOWrdagent/app/utils/health_check.py73 except Exception as e:CODE
LOWrdagent/app/utils/health_check.py89 except Exception as e:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py55 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py96 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py139 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py181 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py452 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py485 except Exception:CODE
LOWrdagent/app/finetune/llm/ui/components.py225 except Exception:CODE
LOWrdagent/app/rl/ui/rl_summary.py45 except Exception:CODE
MEDIUMrdagent/utils/env.py948def prepare(self) -> None:CODE
MEDIUMrdagent/utils/env.py994def prepare(self) -> None:CODE
LOWrdagent/utils/env.py110 except Exception as cleanup_error:CODE
LOWrdagent/utils/env.py346 except Exception as e:CODE
LOWrdagent/utils/env.py863 except Exception as e:CODE
LOWrdagent/utils/env.py887 except Exception as exc: # pragma: no cover - best-effort helperCODE
LOWrdagent/utils/env.py971 except Exception as e:CODE
LOWrdagent/utils/env.py1005 except Exception as e:CODE
LOWrdagent/utils/env.py1405 except Exception:CODE
LOWrdagent/utils/__init__.py83 except Exception as e:CODE
LOWrdagent/utils/__init__.py172 except Exception as e:CODE
LOWrdagent/utils/__init__.py181 except Exception as e:CODE
LOWrdagent/utils/agent/workflow.py53 except Exception as e:CODE
LOWrdagent/utils/workflow/misc.py40 except Exception as e:CODE
MEDIUMrdagent/utils/workflow/misc.py41 print(f"Error: {e}")CODE
LOWrdagent/utils/workflow/loop.py247 except Exception as e:CODE
LOWrdagent/utils/workflow/loop.py556 except Exception as ex:CODE
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Hyper-Verbose Identifiers199 hits · 202 pts
SeverityFileLineSnippetContext
LOWtest/qlib/test_model_factor_proposal.py42def test_model_proposal_import():CODE
LOWtest/qlib/test_model_factor_proposal.py46def test_factor_proposal_import():CODE
LOWtest/utils/test_env.py146 def test_cleanup_container_import(self):CODE
LOWtest/utils/test_import.py17 def import_all_modules_from_directory(directory):CODE
LOWtest/utils/test_ws.py27 def test_checkpoint_roundtrip(self) -> None:CODE
LOWtest/utils/test_kaggle.py12 def test_competition_template(self):CODE
LOWtest/oai/test_embedding_and_similarity.py22 def test_embedding_similarity(self) -> None:CODE
LOWtest/oai/test_embedding_and_similarity.py29 def test_embedding_long_text_truncation(self) -> None:CODE
LOWtest/oai/test_advanced.py24 def test_chat_cache_multiprocess(self) -> None:CODE
LOWtest/oai/test_completion.py29 def test_chat_completion_json_mode(self) -> None:CODE
LOWtest/oai/test_completion.py41 def test_build_messages_and_calculate_token(self) -> None:CODE
LOWtest/oai/test_completion.py48 def test_json_mode_with_specific_target_type(self) -> None:CODE
LOWtest/oai/test_completion.py68 def test_response_format_with_basemodel(self) -> None:CODE
LOWtest/notebook/test_util.py143 def test_happy_path_no_header(self):CODE
LOWtest/notebook/test_util.py268 def test_ignores_indented_calls(self):CODE
LOWtest/notebook/test_util.py356 def test_happy_path_no_header(self):CODE
LOWtest/notebook/test_util.py477 def test_ignore_unknown_section(self):CODE
LOWtest/notebook/test_util.py548 def test_happy_path_multiline(self):CODE
LOWtest/notebook/test_util.py600 def test_arbitrary_print_happy_path(self):CODE
LOWtest/notebook/test_util.py695 def test_happy_path_with_args(self):CODE
LOWtest/notebook/test_util.py703 def test_happy_path_with_args_multiline(self):CODE
LOWtest/notebook/test_util.py740 def test_function_does_not_exist(self):CODE
LOWtest/notebook/test_util.py807 def test_happy_path_arbitrary_content(self):CODE
LOWtest/notebook/test_util.py820 def test_block_does_not_exist(self):CODE
LOWtest/notebook/test_notebook_converter.py10def normalize_nb_json_for_comparison(nb_json_str):CODE
LOWtest/notebook/test_notebook_converter.py30 def test_validation_missing_main_fn(self):CODE
LOWtest/notebook/test_notebook_converter.py39 def test_validation_missing_sections(self):CODE
LOWtest/notebook/test_notebook_converter.py96 def test_argparse_with_dupe_sys(self):CODE
LOWtest/notebook/testfiles/main2.py117 def load_img_as_numpy_with_mask(filepath):CODE
LOWrdagent/core/conf.py16 def settings_customise_sources(CODE
LOWrdagent/core/evolving_framework.py148 def load_or_init_knowledge_base(CODE
LOWrdagent/core/evolving_framework.py183 def load_dumped_knowledge_base(self, *args: Any, **kwargs: Any) -> None:CODE
LOWrdagent/core/proposal.py178 def get_sota_hypothesis_and_experiment(self) -> tuple[Hypothesis | None, Experiment | None]:CODE
LOWrdagent/core/experiment.py209 def link_all_files_in_folder_to_workspace(data_path: Path, workspace_path: Path) -> None:CODE
LOWrdagent/core/experiment.py275 def inject_code_from_file_dict(self, workspace: FBWorkspace) -> None:CODE
LOWrdagent/app/utils/health_check.py37def check_and_list_free_ports(start_port=19899, max_ports=10) -> None:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py457def extract_baseline_full_benchmark(task_path: Path, split: str = "validation") -> dict | None:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py490def get_task_full_benchmark_df(task_path: Path, split: str) -> pd.DataFrame:CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py554def render_task_detail_selector(job_path: Path) -> None:CODE
LOWrdagent/app/finetune/llm/ui/components.py17def convert_latex_for_streamlit(text: str) -> str:CODE
LOWrdagent/app/finetune/data_science/scen.py14 def _get_data_folder_description(self) -> str:CODE
LOWrdagent/app/general_model/general_model.py14def extract_models_and_implement(report_file_path: str) -> None:CODE
LOWrdagent/app/qlib_rd_loop/factor_from_report.py61def extract_hypothesis_and_exp_from_reports(report_file_path: str) -> QlibFactorExperiment | None:CODE
LOWrdagent/utils/env.py69def extract_dir_name_from_path_config(path_str: str) -> str:CODE
LOWrdagent/utils/env.py172 def get_workspace_content_for_hash(self, local_path: str | Path) -> list[list[str]]:CODE
LOWrdagent/utils/env.py275 def unzip_a_file_into_a_folder(CODE
LOWrdagent/utils/env.py537 def dump_python_code_run_and_get_results(CODE
LOWrdagent/utils/env.py811 def populate_exclude_chmod_paths(self) -> "DockerConf":CODE
LOWrdagent/utils/env.py877def _sync_conda_cache_with_real_envs() -> None:CODE
LOWrdagent/utils/env.py1117 def get_workspace_content_for_hash(self, local_path: str | Path) -> list[list[str]]:CODE
LOWrdagent/utils/__init__.py28def get_module_by_module_path(module_path: Union[str, ModuleType]) -> ModuleType:CODE
LOWrdagent/utils/__init__.py193def remove_path_info_from_str(base_path: Path, target_string: str) -> str:CODE
LOWrdagent/utils/agent/workflow.py10def build_cls_from_json_with_retry(CODE
LOWrdagent/utils/workflow/loop.py172 def _check_exit_conditions_on_step(self, loop_id: Optional[int] = None, step_id: Optional[int] = None) -> None:CODE
LOWrdagent/oai/llm_utils.py13def calculate_embedding_distance_between_str_list(CODE
LOWrdagent/oai/backend/deprec.py273 def _create_embedding_inner_function(self, input_content_list: list[str]) -> list[list[float]]:CODE
LOWrdagent/oai/backend/deprec.py294 def _create_chat_completion_inner_function( # type: ignore[no-untyped-def] # noqa: C901, PLR0912, PLR0915CODE
LOWrdagent/oai/backend/deprec.py467 def _calculate_token_from_messages(self, messages: list[dict[str, Any]]) -> int:CODE
LOWrdagent/oai/backend/litellm.py60 def _calculate_token_from_messages(self, messages: list[dict[str, Any]]) -> int:CODE
LOWrdagent/oai/backend/litellm.py71 def _create_embedding_inner_function(self, input_content_list: list[str]) -> list[list[float]]:CODE
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Decorative Section Separators66 hits · 197 pts
SeverityFileLineSnippetContext
MEDIUMrdagent/utils/__init__.py108 \d+/\d+\s+[━]+\s+\d+s?\s+\d+ms/step.*?\u0008+ | # e.g. "10/100 ━━━━━━ 3s 50ms/step"CODE
MEDIUMrdagent/utils/__init__.py109 \d+/\d+\s+[━]+\s+\d+s?\s+\d+ms/step | # e.g. "10/100 ━━━━━━ 3s 50ms/step" (no backspaces)CODE
MEDIUM…arios/data_science/proposal/exp_gen/trace_scheduler.py134# ======================================================================================COMMENT
MEDIUM…arios/data_science/proposal/exp_gen/trace_scheduler.py136# ======================================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py38# ==============================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py40# ==============================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py516# ==============================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py518# ==============================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py634# ==============================================================================COMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py636# ==============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/default.py17# ============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/default.py19# ============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/default.py203# ============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/default.py205# ============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml1# =============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml3# =============================================================================COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml18 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml20 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml163 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml165 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml223 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/finetune/proposal/prompts.yaml225 # ═══════════════════════════════════════════════════════════════════════════COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/server.py356# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/server.py358# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py83# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py85# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py98# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py100# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py173# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py175# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py238# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py240# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py272# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py274# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py346# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py348# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py386# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/utils.py388# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/evaluator.py16# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/evaluator.py18# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/evaluator.py49# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/core/evaluator.py51# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py35# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py37# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py228# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py230# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py313# ============================================================COMMENT
MEDIUMrdagent/scenarios/rl/autorl_bench/test/test_fixes.py315# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py67# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py69# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py121# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py123# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py212# ============================================================COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py214# ============================================================COMMENT
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py56# ============================================================COMMENT
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py58# ============================================================COMMENT
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py148# ============================================================COMMENT
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py150# ============================================================COMMENT
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py261# ============================================================STRING
MEDIUM…t/scenarios/rl/autorl_bench/benchmarks/webshop/eval.py263# ============================================================STRING
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Deep Nesting178 hits · 168 pts
SeverityFileLineSnippetContext
LOWtest/notebook/testfiles/main2.py37CODE
LOWrdagent/core/evolving_agent.py140CODE
LOWrdagent/core/experiment.py324CODE
LOWrdagent/core/experiment.py350CODE
LOWrdagent/app/CI/run.py182CODE
LOWrdagent/app/CI/run.py432CODE
LOWrdagent/app/CI/run.py185CODE
LOWrdagent/app/finetune/llm/ui/data_loader.py98CODE
LOWrdagent/app/finetune/llm/ui/data_loader.py365CODE
LOWrdagent/app/finetune/llm/ui/data_loader.py423CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py27CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py73CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py101CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py224CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py429CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py457CODE
LOWrdagent/app/finetune/llm/ui/ft_summary.py490CODE
LOWrdagent/app/finetune/llm/ui/app.py28CODE
LOWrdagent/app/finetune/llm/ui/app.py66CODE
LOWrdagent/app/finetune/llm/ui/components.py42CODE
LOWrdagent/app/finetune/llm/ui/components.py58CODE
LOWrdagent/app/finetune/llm/ui/components.py208CODE
LOWrdagent/app/finetune/llm/ui/components.py313CODE
LOWrdagent/app/finetune/llm/ui/components.py461CODE
LOWrdagent/app/finetune/llm/ui/components.py602CODE
LOWrdagent/app/finetune/llm/ui/components.py665CODE
LOWrdagent/app/finetune/llm/ui/benchmarks/bioprobench.py21CODE
LOWrdagent/app/finetune/llm/ui/benchmarks/__init__.py22CODE
LOWrdagent/app/finetune/llm/ui/benchmarks/chemcotbench.py47CODE
LOWrdagent/app/qlib_rd_loop/factor_from_report.py112CODE
LOWrdagent/app/rl/ui/data_loader.py237CODE
LOWrdagent/app/rl/ui/data_loader.py285CODE
LOWrdagent/app/rl/ui/rl_summary.py74CODE
LOWrdagent/app/rl/ui/app.py46CODE
LOWrdagent/app/rl/ui/app.py75CODE
LOWrdagent/app/rl/ui/components.py24CODE
LOWrdagent/app/rl/ui/components.py38CODE
LOWrdagent/app/rl/ui/components.py211CODE
LOWrdagent/utils/env.py139CODE
LOWrdagent/utils/env.py275CODE
LOWrdagent/utils/env.py593CODE
LOWrdagent/utils/env.py1162CODE
LOWrdagent/utils/env.py1308CODE
LOWrdagent/utils/env.py617CODE
LOWrdagent/utils/__init__.py100CODE
LOWrdagent/utils/agent/apply_patch.py275CODE
LOWrdagent/utils/agent/apply_patch.py385CODE
LOWrdagent/utils/agent/apply_patch.py457CODE
LOWrdagent/utils/agent/apply_patch.py173CODE
LOWrdagent/utils/agent/tpl.py33CODE
LOWrdagent/utils/workflow/loop.py194CODE
LOWrdagent/utils/workflow/loop.py313CODE
LOWrdagent/oai/backend/deprec.py109CODE
LOWrdagent/oai/backend/deprec.py294CODE
LOWrdagent/oai/backend/litellm.py95CODE
LOWrdagent/oai/backend/litellm.py127CODE
LOWrdagent/oai/backend/base.py520CODE
LOWrdagent/components/benchmark/eval_method.py200CODE
LOWrdagent/components/knowledge_management/graph.py197CODE
LOWrdagent/components/workflow/rd_loop.py75CODE
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Verbosity Indicators41 hits · 85 pts
SeverityFileLineSnippetContext
LOWrdagent/utils/env.py955 # Step 1: Install base dependencies (torch, llamafactory, etc.)COMMENT
LOWrdagent/utils/env.py959 # Step 2: Install flash-attn (requires torch first, uses --no-build-isolation)COMMENT
LOWrdagent/utils/agent/ret.py97 # Step 1: extract patch by patternCOMMENT
LOWrdagent/utils/agent/ret.py103 # Step 2: apply the patch, this will modify the file in placeCOMMENT
LOW…nt/components/coder/data_science/pipeline/prompts.yaml302 ### Step 6: Similar Successful Implementations to help Code ImprovementCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py70 # Step 1: Parameter filteringCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py73 # Step 2: Inject required parameters for multi-task environmentsCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py76 # Step 3: Micro-batch testing (validates everything at runtime)COMMENT
LOWrdagent/components/coder/finetune/prompts.yaml87 # Step 1: Run complete sampling/filtering (fast, no LLM) - runs in BOTH modesCOMMENT
LOWrdagent/components/coder/finetune/prompts.yaml90 # Step 2: Limit LLM processing in debug mode onlyCOMMENT
LOWrdagent/components/coder/finetune/prompts.yaml96 # Step 3: Show the actual number of sampled items (Do not estimate; count the exact number of samples that will be pCOMMENT
LOWrdagent/components/coder/finetune/eval.py68 # Step 1: Check script existsCOMMENT
LOWrdagent/components/coder/finetune/eval.py82 # Step 3: Execute script in DEBUG mode (generates ~10 samples for fast validation)COMMENT
LOWrdagent/components/coder/finetune/eval.py101 # Step 4: Validate outputCOMMENT
LOWrdagent/components/coder/finetune/eval.py111 # Step 5: Load data if validCOMMENT
LOWrdagent/components/coder/finetune/eval.py120 # Step 6: Generate LLM feedbackCOMMENT
LOW…cenarios/data_science/proposal/exp_gen/prompts_v2.yaml803 ### Step 2: **Workflow Update** :COMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py401 # Step 2: Generate the rest of the hypothesis & taskCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1458 # Step 3: Select the best hypothesisCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py347 # Step 1: Generate componentCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1367 # Step 1: Identify problemsCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1391 # Step 2: Propose hypothesis based on the identified problems (and sampled ideas)COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py205 # Step 1: If we have fewer traces than our target, start a new one.COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py210 # Step 2: Probabilistically select a leaf to expand.COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py359 # Step 1: keep same policy to reach target number of parallel tracesCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py364 # Step 2: consider only available leaves (not being expanded)COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py369 # Step 3: compute priors (P) from potentials via softmaxCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py377 # Step 4: score each leaf using PUCT-like rule: Q + UCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py391 # # Step 5: optimistic visit update on selection; value update deferred to observe_feedbackCOMMENT
LOW…data_science/proposal/exp_gen/draft/prompts_draft.yaml220 # Step 2: Workflow UpdateCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py246 # Step 0: PrepareCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py271 # Step 1: Retrieve KnowledgeCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py274 # Step 2: Generate Hypothesis based on General KnowledgeCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py282 # Step 3: Design TaskCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml12 ## Step 0: Pre-definitionCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml17 ## Step 1: Benchmark Metrics Evaluation (HIGHEST PRIORITY)COMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml30 ## Step 2: Code Quality AssessmentCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml34 ## Step 3: Final Decision (Acceptance as SOTA)COMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml190 ## Step 1: Error ClassificationCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml197 ## Step 2: Root Cause AnalysisCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml202 ## Step 3: Actionable SuggestionsCOMMENT
Structural Annotation Overuse40 hits · 83 pts
SeverityFileLineSnippetContext
LOWrdagent/utils/env.py955 # Step 1: Install base dependencies (torch, llamafactory, etc.)COMMENT
LOWrdagent/utils/env.py959 # Step 2: Install flash-attn (requires torch first, uses --no-build-isolation)COMMENT
LOWrdagent/utils/agent/ret.py97 # Step 1: extract patch by patternCOMMENT
LOWrdagent/utils/agent/ret.py103 # Step 2: apply the patch, this will modify the file in placeCOMMENT
LOW…nt/components/coder/data_science/pipeline/prompts.yaml302 ### Step 6: Similar Successful Implementations to help Code ImprovementCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py70 # Step 1: Parameter filteringCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py73 # Step 2: Inject required parameters for multi-task environmentsCOMMENT
LOWrdagent/components/coder/finetune/unified_validator.py76 # Step 3: Micro-batch testing (validates everything at runtime)COMMENT
LOWrdagent/components/coder/finetune/prompts.yaml87 # Step 1: Run complete sampling/filtering (fast, no LLM) - runs in BOTH modesCOMMENT
LOWrdagent/components/coder/finetune/prompts.yaml90 # Step 2: Limit LLM processing in debug mode onlyCOMMENT
LOWrdagent/components/coder/finetune/prompts.yaml96 # Step 3: Show the actual number of sampled items (Do not estimate; count the exact number of samples that will be pCOMMENT
LOWrdagent/components/coder/finetune/eval.py68 # Step 1: Check script existsCOMMENT
LOWrdagent/components/coder/finetune/eval.py82 # Step 3: Execute script in DEBUG mode (generates ~10 samples for fast validation)COMMENT
LOWrdagent/components/coder/finetune/eval.py101 # Step 4: Validate outputCOMMENT
LOWrdagent/components/coder/finetune/eval.py111 # Step 5: Load data if validCOMMENT
LOWrdagent/components/coder/finetune/eval.py120 # Step 6: Generate LLM feedbackCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py401 # Step 2: Generate the rest of the hypothesis & taskCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1458 # Step 3: Select the best hypothesisCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py347 # Step 1: Generate componentCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1367 # Step 1: Identify problemsCOMMENT
LOW…nt/scenarios/data_science/proposal/exp_gen/proposal.py1391 # Step 2: Propose hypothesis based on the identified problems (and sampled ideas)COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py205 # Step 1: If we have fewer traces than our target, start a new one.COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py210 # Step 2: Probabilistically select a leaf to expand.COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py359 # Step 1: keep same policy to reach target number of parallel tracesCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py364 # Step 2: consider only available leaves (not being expanded)COMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py369 # Step 3: compute priors (P) from potentials via softmaxCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py377 # Step 4: score each leaf using PUCT-like rule: Q + UCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py391 # # Step 5: optimistic visit update on selection; value update deferred to observe_feedbackCOMMENT
LOW…data_science/proposal/exp_gen/draft/prompts_draft.yaml220 # Step 2: Workflow UpdateCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py246 # Step 0: PrepareCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py271 # Step 1: Retrieve KnowledgeCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py274 # Step 2: Generate Hypothesis based on General KnowledgeCOMMENT
LOW…scenarios/data_science/proposal/exp_gen/draft/draft.py282 # Step 3: Design TaskCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml12 ## Step 0: Pre-definitionCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml17 ## Step 1: Benchmark Metrics Evaluation (HIGHEST PRIORITY)COMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml30 ## Step 2: Code Quality AssessmentCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml34 ## Step 3: Final Decision (Acceptance as SOTA)COMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml190 ## Step 1: Error ClassificationCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml197 ## Step 2: Root Cause AnalysisCOMMENT
LOWrdagent/scenarios/finetune/dev/prompts.yaml202 ## Step 3: Actionable SuggestionsCOMMENT
Self-Referential Comments24 hits · 69 pts
SeverityFileLineSnippetContext
MEDIUMtest/utils/coder/test_finetune_coder.py14 # Create the ensemble task with actual data context and specificationCOMMENT
MEDIUMtest/oai/test_embedding_and_similarity.py31 # Create a very long text that will definitely exceed embedding token limitsCOMMENT
MEDIUMrdagent/app/CI/run.py773 # Create a table to display the counts and ratiosCOMMENT
MEDIUMrdagent/utils/agent/apply_patch.py2# The following code is modified from https://cookbook.openai.com/examples/gpt4-1_prompting_guideCOMMENT
MEDIUMrdagent/utils/workflow/tracking.py22# Define a placeholder for mlflow if it's not availableCOMMENT
MEDIUMrdagent/components/proposal/__init__.py22 # The following methods are scenario related so they should be implemented in the subclassCOMMENT
MEDIUMrdagent/components/coder/factor_coder/evaluators.py21 """This class is the v1 version of evaluator for a single factor implementation.STRING
MEDIUMrdagent/components/coder/factor_coder/eva_utils.py399 # Initialize result variablesCOMMENT
MEDIUMrdagent/components/coder/CoSTEER/evaluators.py126 """This class is a base class for all code generator feedback to single implementation"""STRING
MEDIUMrdagent/components/coder/data_science/ensemble/test.py39 # Create the ensemble task with actual data context and specificationCOMMENT
MEDIUMrdagent/components/coder/data_science/model/test.py23 # Create the taskCOMMENT
MEDIUMrdagent/components/coder/data_science/feature/test.py22 # Create the experimentCOMMENT
MEDIUM…/components/coder/data_science/raw_data_loader/test.py19 # Create the experimentCOMMENT
MEDIUMrdagent/components/coder/data_science/share/notebook.py89 # Create a markdown cell for the section name and commentsCOMMENT
MEDIUMrdagent/components/coder/data_science/share/notebook.py98 # Create a code cell for the section code and outputCOMMENT
MEDIUMrdagent/scenarios/kaggle/experiment/prompts.yaml241 # Define the forward passCOMMENT
MEDIUM…xperiment/templates/digit-recognizer/model/model_nn.py11# Define the neural network model with Batch NormalizationCOMMENT
MEDIUM…nt/scenarios/data_science/proposal/exp_gen/proposal.py918 # Create a random but reproducible integerCOMMENT
MEDIUM…enarios/data_science/proposal/exp_gen/select/submit.py452 # Create a temporary workspace to test the generated scriptCOMMENT
MEDIUMrdagent/scenarios/data_science/debug/data.py365 # Create a sampled subsetCOMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/benchmark.py183 # Create a temporary environment for merging (use FT env as it has peft/transformers)COMMENT
MEDIUMrdagent/log/ui/ds_trace.py917 # Create a color map for different root nodes - using colors that work well in both light and dark modesCOMMENT
MEDIUMrdagent/log/ui/app.py1038 # Create a results tableSTRING
MEDIUMrdagent/log/utils/__init__.py40 # This method is called too frequently, which is not good.COMMENT
Redundant / Tautological Comments37 hits · 57 pts
SeverityFileLineSnippetContext
LOWrdagent/app/finetune/llm/ui/ft_summary.py338 # Check if it's a numeric score (with optional "/" separator)COMMENT
LOWrdagent/app/finetune/llm/ui/app.py44 # Check if standalone task (has __session__ directly)COMMENT
LOWrdagent/app/finetune/llm/ui/app.py47 # Check if job directory (subdirs have __session__)COMMENT
LOWrdagent/app/finetune/llm/ui/components.py322 # Check if markdown rendering is enabledCOMMENT
LOWrdagent/utils/env.py1250 # Check if specific GPUs are requested via CUDA_VISIBLE_DEVICESCOMMENT
LOWrdagent/components/coder/factor_coder/eva_utils.py407 # Check if both dataframe has only one columns Mute this since factor task might generate more than one columns COMMENT
LOWrdagent/components/coder/factor_coder/eva_utils.py422 # Check if the index of the dataframe is ("datetime", "instrument")COMMENT
LOWrdagent/components/coder/data_science/pipeline/eval.py78 # Check if error_message contains Context7 documentation resultsCOMMENT
LOWrdagent/components/coder/data_science/pipeline/eval.py242 # Check if scores contain NaN (values)COMMENT
LOWrdagent/components/coder/data_science/workflow/eval.py113 # Check if scores contain NaN (values)COMMENT
LOWrdagent/components/coder/data_science/share/eval.py126 # Check if scores contain NaN (values)COMMENT
LOWrdagent/components/coder/data_science/share/eval.py167 # Check if the content has changedCOMMENT
LOWrdagent/components/coder/finetune/__init__.py71 # Check if proposal decided to skip data processing (reuse SOTA's data processing script)COMMENT
LOWrdagent/components/coder/model_coder/benchmark/eval.py69 # Check if it is not a good evaluation!!COMMENT
LOW…narios/qlib/experiment/factor_template/read_exp_res.py31 # Check if the recorder has a valid end timeCOMMENT
LOW…narios/qlib/experiment/factor_template/read_exp_res.py40# Check if the latest recorder is foundCOMMENT
LOW…enarios/qlib/experiment/model_template/read_exp_res.py31 # Check if the recorder has a valid end timeCOMMENT
LOW…enarios/qlib/experiment/model_template/read_exp_res.py40# Check if the latest recorder is foundCOMMENT
LOWrdagent/scenarios/kaggle/developer/feedback.py59 # Check if there are any based experimentsCOMMENT
LOWrdagent/scenarios/kaggle/experiment/prompts.yaml164 params = ... # Set parameters to XGBoost modelCODE
LOW…riment/templates/meta_tpl_deprecated/model/model_nn.py8# Check if a GPU is availableCOMMENT
LOW…a_science/example/eval/playground-series-s4e9/valid.py3# Check if our submission file existsCOMMENT
LOW…nce/example/eval/arf-12-hours-prediction-task/valid.py3# Check if our submission file existsCOMMENT
LOW…arios/data_science/proposal/exp_gen/trace_scheduler.py292 # Check if this experiment was successful (decision=True)COMMENT
LOW…enarios/data_science/proposal/exp_gen/select/expand.py83 # Check if we've reached the maximum number of tracesCOMMENT
LOW…enarios/data_science/proposal/exp_gen/select/expand.py131 # Check if we've reached the maximum number of tracesCOMMENT
LOW…enarios/data_science/proposal/exp_gen/select/expand.py191 # Check if we've reached the maximum number of traces before creating a new oneCOMMENT
LOWrdagent/scenarios/data_science/debug/data.py403 # Check if each file is in the "used" listCOMMENT
LOWrdagent/scenarios/finetune/scen/utils.py558 # Check if tokenizer supports <think> token for CoT trainingCOMMENT
LOWrdagent/scenarios/finetune/scen/scenario.py246 # Check if already configuredCOMMENT
LOWrdagent/scenarios/finetune/benchmark/benchmark.py179 # Check if we need to merge the model (e.g. vLLM doesn't support LoRA with modules_to_save)COMMENT
LOWrdagent/scenarios/finetune/benchmark/benchmark.py253 # Check if results already exist (skip re-running if cached)COMMENT
LOWrdagent/scenarios/finetune/benchmark/data/default.py87 # Check if it's conversation formatCOMMENT
LOWrdagent/scenarios/finetune/train/eval.py97 # Check if FT_YAML_FILE_NAME existsCOMMENT
LOWrdagent/log/ui/utils.py912 # Check if G is a path (a single line)COMMENT
LOWrdagent/log/ui/app.py588 # # Check if metric series exists and has the matching roundCOMMENT
LOWrdagent/log/ui/app.py912 # Display resultsSTRING
Slop Phrases25 hits · 48 pts
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MEDIUMrdagent/components/coder/factor_coder/factor.py144 # TODO you can change the name of the data folder for a better understandingCOMMENT
MEDIUMrdagent/scenarios/kaggle/experiment/prompts.yaml247 optimizer = torch.optim.Adam(model.parameters(), lr=0.01) # Example optimizer, you can use any optimizerCODE
MEDIUMrdagent/scenarios/kaggle/experiment/prompts.yaml248 criterion = torch.nn.CrossEntropyLoss() # Example loss function, you can use any loss functionCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json1036 "output_1":"Escargot is a classic French delicacy made from cooked land snails. It is often served as an appetizer iCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json1037 "output_2":"Making escargot is a delightful culinary experience, and it involves a few key steps. Here\u2019s a basiCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json17 "output_2":"The names of the states in the United States are derived from various historical and cultural factors, bCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json125 "output_2":"As an AI language model, I don't have personal experiences or emotions, but I can provide you with some CODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json148 "output_1":"Certainly! Canjeero, also known as Anjero, Laxoox or Somali pancake, is a traditional Somali dish similaCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json149 "output_2":"Certainly! Canjeero is a traditional Somali dish that is known for its rich, flavorful broth and hearty CODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json197 "output_2":"As an AI language model, I don't have personal experiences or beliefs, but I can provide you with some gCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json221 "output_2":"As an AI language model, I don't have the ability to perceive or feel physical sensations, including theCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json281 "output_2":"As an AI language model, I don't have a physical form or a personal experience, so I don't become an autCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json436 "output_1":"Escargot is a classic French delicacy made from cooked land snails. It is often served as an appetizer iCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json473 "output_2":"As an AI language model, I don't have personal experiences or emotions, but I can provide some general iCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json497 "output_2":"As an AI language model, I don't have the ability to physically use a phone, but I can provide you with CODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json533 "output_2":"As an AI language model, I don't have personal beliefs or emotions, but I can provide some general inforCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json557 "output_2":"As an AI language model, I don't have personal beliefs or opinions, but I can provide some general inforCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json568 "output_1":"Certainly! Mine Frite, which means \"fried noodles\" in English, is a popular street food dish in MauritCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json748 "output_1":"Certainly! Canjeero, also known as Anjero, Laxoox or Somali pancake, is a traditional Somali dish similaCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json1061 "output_2":"Of course! Tahini is a delicious and versatile ingredient that can be used in many dishes. Here's a simpCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json1168 "output_1":"Certainly! Mine Frite, which means \"fried noodles\" in English, is a popular street food dish in MauritCODE
LOW…val/annotators_gpt52_fn/annotations_seed0_configs.json1036 "output_1":"Escargot is a classic French delicacy made from cooked land snails. It is often served as an appetizer iCODE
LOW…val/annotators_gpt52_fn/annotations_seed0_configs.json232 "output_1":"Roasting a whole pig is a traditional and festive way to celebrate for many cultures, and it can be an eCODE
LOW…val/annotators_gpt52_fn/annotations_seed0_configs.json436 "output_1":"Escargot is a classic French delicacy made from cooked land snails. It is often served as an appetizer iCODE
LOW…val/annotators_gpt52_fn/annotations_seed0_configs.json832 "output_1":"Roasting a whole pig is a traditional and festive way to celebrate for many cultures, and it can be an eCODE
Modern AI Meta-Vocabulary15 hits · 48 pts
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MEDIUMREADME.md233 # EMBEDDING MODEL: Using SiliconFlow for embedding since deepseek has no embedding model.COMMENT
MEDIUMtest/finetune/test_benchmark.py194 # PANORAMA - Patent Analysis (zero-shot)COMMENT
MEDIUMtest/finetune/test_benchmark_api.py145 # Limit few-shot examples to avoid index out of rangeCOMMENT
MEDIUMtest/finetune/test_benchmark_api.py441 # PANORAMA - Patent Analysis (zero-shot)COMMENT
MEDIUMrdagent/core/evolving_agent.py147 # 1. RAGCOMMENT
MEDIUMrdagent/app/kaggle/conf.py54 # Conditionally set the knowledge_base based on the use of graph RAGCOMMENT
MEDIUMrdagent/app/data_science/conf.py146 # constrains the number of SOTA experiments to retrieve, otherwise too many SOTA experiments to retrieve will cause COMMENT
MEDIUMrdagent/oai/utils/embedding.py12# Common embedding model token limitsCOMMENT
MEDIUM…nt/scenarios/data_science/proposal/exp_gen/proposal.py399 # - after we know the selected component, we can use RAG.COMMENT
MEDIUM…nt/scenarios/data_science/proposal/exp_gen/proposal.py334 # - Extra RAGCOMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/default.py92 # Multi-turn few-shot: format with ChatML-style markersCOMMENT
MEDIUMrdagent/scenarios/finetune/benchmark/data/adaptor.py56 # PANORAMA - Patent Analysis Benchmarks (zero-shot)COMMENT
MEDIUMrdagent/scenarios/finetune/datasets/financeiq/split.py35 # FinanceIQ specific: 'dev' folder is small and used for few-shot.COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py71# 任务类型 → few-shot prompt key 的映射COMMENT
MEDIUM…/scenarios/rl/autorl_bench/benchmarks/alfworld/eval.py279 # --- 加载 ReAct few-shot prompts ---COMMENT
Cross-Language Confusion6 hits · 38 pts
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HIGHrdagent/components/agent/context7/conf.py10 bun i && bun run buildSTRING
HIGHrdagent/scenarios/qlib/developer/utils.py54 if all(first_values.equals(values) for values in candidate_values[1:]):CODE
HIGHrdagent/scenarios/shared/get_runtime_info.py22 strace_check = implementation.execute(env=env, entry="which strace || echo MISSING").strip()CODE
HIGHrdagent/scenarios/shared/get_runtime_info.py27 coverage_check = implementation.execute(env=env, entry="python -m coverage --version || echo MISSING").strip()CODE
HIGHrdagent/log/mle_summary.py226# "score": null,COMMENT
HIGHrdagent/log/ui/st_fixed_container.py34let lastBackgroundColor = null;CODE
Docstring Block Structure6 hits · 30 pts
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HIGHrdagent/utils/env.py70 Extract the first directory component from a relative path string. This is used to get the basename from path STRING
HIGHrdagent/components/coder/CoSTEER/evaluators.py56 Validates and converts the 'final_decision' field in the given data dictionary. Args: dataSTRING
HIGH…/kaggle/tpl_ex/aerial-cactus-identification/feature.py11 Perform feature engineering on the input data. Parameters: - X: np.ndarray The input data to be trSTRING
HIGHrdagent/scenarios/data_science/scen/utils.py339 Generate a tree structure of files in a directory. Args: path: Target directory path STRING
HIGHrdagent/scenarios/finetune/scen/utils.py831Scan datasets directory and return top-level dataset names not yet in existing_config. Only scans first-level direcSTRING
HIGHrdagent/scenarios/rl/autorl_bench/core/server.py114 提交模型评测 Args: model_path: 模型路径 gpu: 指定 GPU(如 "0", "1", "0,1"),必须是 CUDA_VISIBLE_STRING
AI Slop Vocabulary10 hits · 27 pts
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MEDIUMtest/notebook/test_util.py1667 # Defensive import; fallback to the most robust method for v1.4.15COMMENT
MEDIUMtest/notebook/testfiles/main_missing_sections.py89 # Defensive import; fallback to the most robust method for v1.4.15COMMENT
MEDIUMtest/notebook/testfiles/main_missing_main_fn.py89 # Defensive import; fallback to the most robust method for v1.4.15COMMENT
MEDIUMtest/notebook/testfiles/main.py89 # Defensive import; fallback to the most robust method for v1.4.15COMMENT
MEDIUMrdagent/scenarios/data_science/loop.py72 # rsync is more robust choice, but it is not installed in some docker images.COMMENT
MEDIUMrdagent/scenarios/finetune/train/eval.py153 # Combine data processing and training stdout for comprehensive feedbackCOMMENT
MEDIUMrdagent/scenarios/finetune/train/eval.py214 # Build comprehensive result with training metrics and benchmark resultsCOMMENT
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json460 "output_1":"Certainly! Tahini is a paste made from sesame seeds and is quite easy to make at home. You just need sesCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json845 "output_2":"Certainly! When choosing an electric saw, it's important to consider factors such as the type of saw youCODE
MEDIUM…val/annotators_gpt52_fn/annotations_seed0_configs.json1060 "output_1":"Certainly! Tahini is a paste made from sesame seeds and is quite easy to make at home. You just need sesCODE
Over-Commented Block25 hits · 25 pts
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LOWtest/finetune/test_benchmark.py181 results_summary = {}COMMENT
LOWweb/src/utils/snap.svg-min.js1// Snap.svg 0.5.0COMMENT
LOWweb/src/router/index.ts41 // },COMMENT
LOWweb/src/router/index.ts61// query: { redirect: to.fullPath }COMMENT
LOWrdagent/app/finetune/llm/job/run_ft_job.sh1#!/bin/bashCOMMENT
LOWrdagent/components/loader/task_loader.py21 # self.json_uri = json_uriCOMMENT
LOWrdagent/components/loader/task_loader.py41COMMENT
LOW…agent/components/coder/CoSTEER/knowledge_management.py781 constraint_labels=["task_trace"],COMMENT
LOWrdagent/components/coder/CoSTEER/evaluators.py21# 2. If it proves to be useful, relocate it to a more general location.COMMENT
LOWrdagent/components/coder/CoSTEER/evaluators.py301 task_li_feedback_li.append(multi_implementation_feedback)COMMENT
LOWrdagent/components/coder/data_science/ensemble/conf.py1# Configuration file for ensemble componentCOMMENT
LOWrdagent/scenarios/kaggle/kaggle_crawler.py401 "statoil-iceberg-classifier-challenge",COMMENT
LOWrdagent/scenarios/data_science/scen/utils.py361 except Exception as e:COMMENT
LOWrdagent/scenarios/data_science/scen/utils.py381 #COMMENT
LOW…rios/data_science/proposal/exp_gen/planner/__init__.py41 # elif DS_RD_SETTING.merge_hours > 0:COMMENT
LOW…/rl/autorl_bench/benchmarks/humaneval/requirements.txt1# HumanEval benchmark 额外依赖COMMENT
LOW…os/rl/autorl_bench/benchmarks/webshop/requirements.txt1# WebShop benchmark 依赖COMMENT
LOW…narios/rl/autorl_bench/benchmarks/deepsearchqa/eval.py201 # for step in range(max_steps):COMMENT
LOW…narios/rl/autorl_bench/benchmarks/deepsearchqa/eval.py221 # observation = search_fn(action_content)COMMENT
LOWrdagent/log/mle_summary.py221 pd.to_pickle(stat, save_p)COMMENT
LOWrdagent/log/ui/llm_st.py121COMMENT
LOWrdagent/log/ui/llm_st.py141# st.json(cxt)COMMENT
LOWrdagent/log/ui/llm_st.py161# rdict.pop("spec")COMMENT
LOWrdagent/log/ui/app.py581 if mem := state.msgs[0]["load_experiment"]:COMMENT
LOWrdagent/log/ui/app.py601 # 'Sharpe': float(f"{metric['1day.excess_return_with_cost.annualized_return'] / abs(metric['1day.excCOMMENT
Modern Structural Boilerplate22 hits · 22 pts
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LOWrdagent/core/proposal.py200 def set_current_selection(self, selection: tuple[int, ...]) -> None:CODE
LOWrdagent/core/experiment.py446 def set_user_instructions(self, user_instructions: UserInstructions | None) -> None:CODE
LOWrdagent/core/utils.py104 def set_seed(self, seed: int) -> None:CODE
LOWrdagent/app/finetune/llm/ui/benchmarks/__init__.py62__all__ = [CODE
LOWrdagent/utils/env.py229 def update_stdout(self, stdout: str) -> None:CODE
LOWrdagent/utils/env.py747 def _update_bin_path(self) -> None:CODE
LOWrdagent/utils/agent/__init__.py3__all__ = ["build_cls_from_json_with_retry"]CODE
LOWrdagent/utils/workflow/__init__.py5__all__ = ["LoopBase", "LoopMeta", "WorkflowTracker", "wait_retry"]CODE
LOWrdagent/components/benchmark/utils.py10logger = logging.getLogger(__name__)CODE
LOWrdagent/scenarios/kaggle/proposal/proposal.py200 def update_reward_estimates(self, trace: Trace) -> None:STRING
LOW…nt/scenarios/data_science/proposal/exp_gen/__init__.py3__all__ = ["DSTrace"]CODE
LOW…t/scenarios/data_science/proposal/exp_gen/idea_pool.py182 def update_pickled_problem(self, problems: Dict, pickled_problem_name: str) -> None:CODE
LOWrdagent/scenarios/data_science/proposal/exp_gen/base.py88 def set_sota_exp_to_submit(self, exp: DSExperiment) -> None:CODE
LOWrdagent/scenarios/data_science/experiment/experiment.py42 def set_local_selection(self, local_selection: tuple[int, ...]) -> None:CODE
LOWrdagent/scenarios/finetune/benchmark/__init__.py3__all__ = ["get_benchmark_ranges", "run_benchmark"]CODE
LOWrdagent/scenarios/rl/autorl_bench/core/__init__.py63__all__ = [CODE
LOWrdagent/scenarios/rl/autorl_bench/agents/__init__.py3__all__ = ["get_agent", "list_agents"]CODE
LOW…scenarios/rl/autorl_bench/benchmarks/smith/__init__.py16logger = logging.getLogger(__name__)CODE
LOW…enarios/rl/autorl_bench/benchmarks/webshop/__init__.py6__all__ = ["WebShopEvaluator", "download_train_data"]CODE
LOWrdagent/log/timer.py63 def update_remain_time(self) -> None:CODE
LOWrdagent/log/conf.py22 def set_ui_server_port(self, port: int | None) -> None:CODE
LOWrdagent/log/logger.py106 def set_storages_path(self, path: str | Path) -> None:CODE
AI Structural Patterns15 hits · 15 pts
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LOWtest/finetune/test_benchmark_api.py94CODE
LOWtest/finetune/test_benchmark_api.py180CODE
LOWrdagent/app/cli.py150CODE
LOWrdagent/app/data_science/loop.py13CODE
LOWrdagent/app/finetune/llm/loop.py17CODE
LOWrdagent/oai/backend/base.py625CODE
LOWrdagent/components/coder/CoSTEER/evaluators.py128CODE
LOW…mponents/coder/model_coder/benchmark/gt_code/visnet.py752CODE
LOW…mponents/coder/model_coder/benchmark/gt_code/visnet.py1077CODE
LOW…ponents/coder/model_coder/benchmark/gt_code/gpsconv.py59CODE
LOWrdagent/scenarios/kaggle/kaggle_crawler.py284CODE
LOW…t/scenarios/kaggle/knowledge_management/vector_base.py21CODE
LOW…t/scenarios/kaggle/knowledge_management/vector_base.py280CODE
LOWrdagent/scenarios/data_science/proposal/exp_gen/base.py14CODE
LOWrdagent/scenarios/finetune/train/eval.py330CODE
Dead Code7 hits · 14 pts
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MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py185CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py227CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py228CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py229CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py231CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py232CODE
MEDIUM…agent/components/coder/CoSTEER/knowledge_management.py278CODE
Magic Placeholder Names3 hits · 12 pts
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HIGHrdagent/app/finetune/llm/README.md58OPENAI_API_KEY=<your_api_key>CODE
HIGHrdagent/scenarios/finetune/benchmark/benchmark.py11FT_JUDGE_API_KEY="<your_api_key>"STRING
HIGHrdagent/scenarios/rl/autorl_bench/README.md69OPENAI_API_KEY=your_api_keyCODE
Overly Generic Function Names7 hits · 7 pts
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LOWtest/notebook/test_util.py997 "def process_data(data):",CODE
LOWtest/notebook/test_util.py1071 "def process_data(data):",CODE
LOWtest/notebook/test_util.py1155 "def process_data(data):",CODE
LOWtest/notebook/test_util.py1216 "def process_data(data):",CODE
LOWtest/notebook/test_util.py1240 "def process_data(data):",CODE
LOWtest/notebook/test_util.py1326 "def process_data(data):",CODE
LOW…l-iceberg-classifier-challenge/fea_share_preprocess.py20 def process_data(df):CODE
Example Usage Blocks2 hits · 2 pts
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LOWrdagent/app/utils/ape.py22# Example usageCOMMENT
LOWrdagent/log/base.py29 # Usage:STRING
TODO Padding1 hit · 2 pts
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LOW…enarios/data_science/proposal/exp_gen/select/expand.py244# TODO: implement these selectors and moreCOMMENT