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IRCP & DLMDataLoader Integration - Quick Reference

| Component | File Path | |-----------|-----------| | **IRCP Trainer** | `packages/ircp/training/icp_trainer.py` | | **IRCP Database Loader** | `packages/ircp/data/database_loader.py` | | **IRCP Base Models** | `packages/ircp/core/base_models.py` | | **DLM Data Loader** | `packages/dlm/core/data_loader.py` | | **TPO Trainer** | `packages/tpo/training/trainer.py` | | **Database Enhanced RCP** | `packages/tpo/consolidation/knowledge_base/database_enhanced_rcp.py` |

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| Component | File Path | |-----------|-----------| | **IRCP Trainer** | `packages/ircp/training/icp_trainer.py` | | **IRCP Database Loader** | `packages/ircp/data/database_loader.py` | | **IRCP Base Models** | `packages/ircp/core/base_models.py` | | **DLM Data Loader** | `packages/dlm/core/data_loader.py` | | **TPO Trainer** | `packages/tpo/training/trainer.py` | | **Database Enhanced RCP** | `packages/tpo/consolidation/knowledge_base/database_enhanced_rcp.py` | ### Coordinates | IRCP DLMCoordinates | DLM DLMCoordinate | Status | |-------|-------|--------| | x | x | Direct | | y | y | Direct | | z | z | Direct | | t | t | Direct | | depth | depth_level | Direct | | sibling_count | n_parts | Semantic map | | is_linear | (missing) | Need default | | confidence | confidence | Direct | ### ConversationNode Both have ConversationNode but: - IRCP uses: `DLMCoordinates` (from ircp/core/base_models.py) - DLM uses: `DLMCoordinate` (from dlm/core/coordinates.py) 1. **Coordinate Prediction Loss** (weight: 1.0) - MSE 2. **Embedding Consistency Loss** (weight: 0.1) - Cosine similarity 3. **Conservation Constraint Loss** (weight: 0.05) - Measure preservation 4. **Topological Consistency Loss** (weight: 0.1) - k-NN preservation 5. **L2 Regularization** (weight: 1e-5) - Parameter regularization ### IRCP Expected Schema - conversations: conversation_id, total_messages - messages: message_id, conversation_id, parent_id, content, author, create_time, token_count - **dlm_coordinates**: message_id, **x_coord, y_coord, z_coord, t_coord**, depth, sibling_order, sibling_count, is_linear - embeddings: message_id, embedding_vector

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