Changelog

See https://keepachangelog.com/en/1.0.0/ for a description of the changelog format.

[0.2.0] - 2025-01-18

Command line interface botex to initialize oTree sessions and start bots from the command line
Added LLM API throttling to deal with LLM rate limits
botex now explicitly checks for oTree validation checks and provides this feedback to LLM bots to trigger corrected responses
oTree pages with multiple buttons but no next button are now handled correctly
Option to use an already existing llama.cpp endpoint
Parsing of botex environment file by calling load_botex_env() function
Convenience functions start_otree_server() and stop_otree_server() to facilitate starting oTree server from within Python
Function export_otree_data() to export oTree wide multi-app data via the oTree web frontend
Function normalize_otree_data() to normalize oTree wide multi-app data to a normalized set of list-of-dicts that is convenient for downstream analysis. This function is based on some educated guesses on the oTree data format and will likely need adjustment for different oTree experiment setups.

Communication with LLMs is now based on structured outputs, requiring the use of LLM endpoints that support this feature (making gpt-4o-2024-08-06 the new standard model).
For those models that don't support structured outputs via LiteLLM, there is a largely untested fallback using the instructor package. This is experimental and will likely be removed as soon as LiteLLM supports Ollama's structured output feature.
Prompting has been improved by streamlining language and adjusting it to the usage of structured outputs.
The API of the main functions has been standardized and moved closer to the API of LiteLLM.
run_bots_on_session() and run_single_bot() now return the resulting thread object(s) if wait is set to False.
botex now logs to its own logger.