Set attribute for all agents @param attr: (str) agent attribute @param obj: (object) object attribute @return: None

Reset all agent states @return: None

Get human feedback for phase output @param phase: (str) current phase @param phase_prod: (str) current phase result @

Utility function to save data as plain text.

Produce a system prompt for the mle-solver to solve ml problems @param commands: (bool) whether to use command prompt @return

Remove a directory if it exists.

Generate well-formatted code lines with line numbers @param code: (list) list of code line strings @return: (str) code lines

Loop through all research phases @return: None

Take command from language model and execute if valid @param model_resp: (str) language model output @return: (tuple) tuple c

Take command from language model and execute if valid @param model_resp: (str) language model output @return: (tuple) tuple c

Remove a directory if it exists.

Save state for phase @param phase: (str) phase string @return: None

Produce a system prompt for the paper-solver @param commands: (bool) whether to use command prompt @return: (str) system prom

Some general tips to avoid common code errors, also TF has many errors so we avoid this and ask to use pytorch @return: (str) common

Process query string to fit within MAX_QUERY_LENGTH while preserving as much information as possible

Fix minor corrections :return: (str) corrected text

Provide command descriptions @return: (str) command descriptions

Provide command descriptions @return: (str) command descriptions

Perform data preparation phase @return: (bool) whether to repeat the phase

Generate description prompt for kaggle dataset @param data_loader: (DataLoader) data loader @return: (str) description prompt

Generate well-formatted code lines with line numbers @param code: (list) list of code line strings @return: (str) code lines

Well-formatted history string @return: (str) history string

Initialize the solver and get an initial set of papers and a return @return: None

Initialize the solver and get an initial set of code and a return @return: None

Perform literature review phase @return: (bool) whether to repeat the phase

Describe system role and general tips for mle-solver @return: (str) system role

Describe system role and general tips for mle-solver @return: (str) system role

Perform plan formulation phase @return: (bool) whether to repeat the phase

Provide a reflection on produced behavior for next execution @return: (str) language model-produced reflection

Reflect on your future plans and next steps to improve the code @param reflect_prompt: (str) reflection prompt @param code_st

Perform report refinement phase @return: (bool) whether to repeat the phase

Perform report writing phase @return: (bool) whether to repeat the phase

Perform results interpretation phase @return: (bool) whether to repeat the phase

Provide results as list of results in human-readable format. :param results: (list(dict)) list of results from search :return

Retrieves the top N datasets matching the query, weighted by likes and downloads. :param query: The search query string. :par

Provide role description @return: (str) role description

Provide role description @return: (str) role description

Perform running experiments phase @return: (bool) whether to repeat the phase