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* Add code for data filtering llm judge * Ignore log file created on root (mainly for synthetic_data_generation.log) * Fix metadata API compatibility issues by commenting out metadata tags in LLM API calls - Commented out metadata.tags parameters in all LLM API calls across the codebase - This fixes compatibility issues with custom LLM providers that don't support metadata - Affects shades generation, topics generation, wiki generation, bio QA, and question generation - Preserves the original code structure for future re-enabling if needed * feat: add data filtering pipeline with Ollama integration - Add MergedDataJudge class for intelligent data filtering using Ollama Gemma - Integrate automatic Ollama CLI installation into project setup process - Add DATA_FILTERING step to training pipeline with concurrent processing - Include testing for MergedDataJudge in its local main() function - Add Ollama dependency to pyproject.toml * feat: add automatic Ollama model cleanup after data filtering * Add logging for outputting data filtering parameters * fix: adjust error handling for MergedDataJudge: - Keep original merged.json unchanged when any error occurs - Exit filtering process immediately on errors instead of continuing with defaults - Ensure training pipeline continues safely even if data filtering fails * Add frontend for data filtering pipeline * resolve data filtering quality_level error by commenting out problematic fields, change TrainProcessService back to original class definition * fix: quote unquoted shade icons to prevent JSON parsing errors * Fixed wiki_res.json missing due to no database connection at wiki/base.py module import * Added scoring reasoning as part of the merged data * fix: filter ANSI escape sequences from Ollama logs in data filtering step * fix: Add data filtering steps to cloud training to resolve KeyError - Added 'Data Filtering' step to cloud training progress holder - Added data filtering step execution in cloud training service - Added data filtering parameters to cloud training routes - Updated frontend to send data filtering parameters - Fixed missing except clause in cloud training service This resolves the KeyError: 'data_filtering' when switching from cloud to local training. |
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| .. | ||
| generate_no_notes_questions.py | ||
| generate_notes_questions.py | ||