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Adds functionality to LLMGenerator to generate novel text values for specified columns, conditioned on the values of other attribute columns, while attempting to preserve attribute distributions. Key changes: - Modified `SamplerLLM` to accept `text_generating_columns` and `conditional_columns` parameters. - Updated `generate_data` to handle conditional logic, using `be_great.impute` for non-text columns and direct LLM prompting via a new `_generate_via_prompt` helper for text columns. - Implemented novelty checks for generated text. - Added unit tests (mocked due to environment constraints for full runs) for the new functionality. - Updated README.md with documentation for the new parameters and an example. Note: Full testing was impeded by sandbox environment disk space limitations preventing complete dependency installation (primarily PyTorch and its CUDA components).
# Conflicts: # README.md
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