syndisco package

Subpackages

Submodules

syndisco.experiments module

SynDisco: Automated experiment creation and execution using only LLM agents Copyright (C) 2025 Dimitris Tsirmpas

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

You may contact the author at tsirbasdim@gmail.com

class syndisco.experiments.AnnotationExperiment(annotators: list[LLMActor], history_ctx_len: int = 3, include_mod_comments: bool = True)

Bases: object

An Experiment where multiple synthetic discussions are annotated by LLM-based annotators.

begin(discussions_dir: Path, output_dir: Path) → None

Begin the annotation experiment by generating and executing annotation jobs. The results will be written as JSON files in the specified output directory.

class syndisco.experiments.DiscussionExperiment(users: list[LLMActor], seed_opinions: list[str] = [], moderator: LLMActor | None = None, next_turn_manager: TurnManager | None = None, history_ctx_len: int = 3, num_turns: int = 10, num_active_users: int = 2, num_discussions: int = 5)

Bases: object

An Experiment which creates, manages and executes multiple synthetic discussions.

begin(discussions_output_dir: Path = PosixPath('output')) → None

Begin the experiment by generating and executing a set of discussions. The results will be written as JSON files at the specified output directory

syndisco.jobs module

SynDisco: Automated experiment creation and execution using only LLM agents Copyright (C) 2025 Dimitris Tsirmpas

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

You may contact the author at tsirbasdim@gmail.com

class syndisco.jobs.Annotation(annotator: LLMActor, conv_logs_path: str | Path, include_moderator_comments: bool, history_ctx_len: int = 2)

Bases: object

An annotation job modelled as a discussion between the system writing the logs of a finished discussion, and the LLM Annotator.

begin(verbose=True) → None

Begin the conversation-modelled annotation job.

Parameters:

verbose (bool, optional) – whether to print the results of the annotation to the console, defaults to True

to_dict(timestamp_format: str = '%y-%m-%d-%H-%M') → dict[str, Any]

Get a dictionary view of the data and metadata contained in the annotation.

Parameters:

timestamp_format (str, optional) – the format for the conversation’s creation time, defaults to “%y-%m-%d-%H-%M”

Returns:

a dict representing the conversation

Return type:

dict[str, Any]

to_json_file(output_path: str | Path) → None

Export the data and metadata of the conversation as a json file.

Parameters:

output_path (str) – the path for the exported file

class syndisco.jobs.Discussion(next_turn_manager: TurnManager, users: list[LLMActor], moderator: LLMActor | None = None, history_context_len: int = 5, conv_len: int = 5, seed_opinion: str = '', seed_opinion_user: str = '')

Bases: object

A job conducting a discussion between different actors (actors.Actor).

begin(verbose: bool = True) → None

Begin the discussion between the actors.

Parameters:

verbose (bool, optional) – whether to print the messages on the screen as they are generated, defaults to True

Raises:

RuntimeError – if the object has already been used to generate a conversation

to_dict(timestamp_format: str = '%y-%m-%d-%H-%M') → dict[str, Any]

Get a dictionary view of the data and metadata contained in the discussion.

Parameters:

timestamp_format (str, optional) – the format for the conversation’s creation time, defaults to “%y-%m-%d-%H-%M”

Returns:

a dict representing the conversation

Return type:

dict[str, Any]

to_json_file(output_path: str | Path) → None

Export the data and metadata of the conversation as a json file.

Parameters:

output_path (str) – the path for the exported file

syndisco.postprocessing module

SynDisco: Automated experiment creation and execution using only LLM agents Copyright (C) 2025 Dimitris Tsirmpas

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

You may contact the author at tsirbasdim@gmail.com

syndisco.postprocessing.import_annotations(annot_dir: str | Path) → DataFrame

Import annotation data from JSON files in a directory and process it into a DataFrame.

This function reads JSON files containing annotation data, processes the data to standardize columns, and optionally includes SDB information for annotators.

Parameters:

annot_dir (str | Path) – Directory containing JSON files with annotation data.

Returns:

A DataFrame containing processed annotation data.

Return type:

pd.DataFrame

syndisco.postprocessing.import_discussions(conv_dir: Path) → DataFrame
Import discussion output (logs) from JSON files in a directory and process

it into a DataFrame.

This function reads JSON files containing conversation data, processes the

data to

standardize columns, and adds derived attributes such as user traits and

prompts.

Parameters:

conv_dir (str | Path) – Directory containing JSON files with conversation data.

Returns:

A DataFrame containing processed conversation data.

Return type:

pd.DataFrame

Module contents