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Add training scripts and utilities for NodeAudit and GraphReview
- Implement `train_lora.py` for LoRA training pipeline, including dataset preparation and model training. - Create `trajectory_collector.py` to collect trajectories and DPO pairs from the CodeReview environment. - Develop `training_graph.py` for visualizing training outcomes and module performance. - Introduce `inference.py` as an example inference script for LLM interactions. - Add scripts for cloning training repositories and seeding databases from the training corpus. - Implement `verify_all.py` to run verification scripts in the code-review environment.902cd29
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Add visualization and reporting features for Phase 05
- Implemented interactive graph visualization using Pyvis in visualizer/pyvis_renderer.py. - Developed report generation functionality in visualizer/report_generator.py, producing Markdown and JSON outputs. - Created tests for graph linking and reporting in test_graph_linking.py, test_phase5_reporting.py, and test_phase5_server_api.py. - Established a structured plan for Phase 05, detailing objectives, constraints, and verification frameworks in phase-05-visualization-reporting-plan.md. - Ensured all new features adhere to the existing database schema and maintain data integrity.1432cf4