mindnet/app
Lars 7cb8fd6602 Enhance logging in ingestion_processor.py for improved change detection diagnostics
Add detailed debug and warning logs to the change detection process, providing insights into hash comparisons and artifact checks. This update aims to facilitate better traceability and debugging during ingestion, particularly when handling hash changes and missing hashes. The changes ensure that the ingestion workflow is more transparent and easier to troubleshoot.
2026-01-12 08:08:29 +01:00
..
core Enhance logging in ingestion_processor.py for improved change detection diagnostics 2026-01-12 08:08:29 +01:00
frontend bug fix 2025-12-29 11:00:00 +01:00
models Update EdgeDTO to support extended provenance values and modify explanation building in retriever.py to accommodate new provenance types. This enhances the handling of edge data for improved accuracy in retrieval processes. 2026-01-11 17:54:33 +01:00
routers Integrate symmetric edge logic and discovery API: Update ingestion processor and validation to support automatic inverse edge generation. Enhance edge registry for dual vocabulary and schema management. Introduce new discovery endpoint for proactive edge suggestions, improving graph topology and edge validation processes. 2026-01-09 13:57:10 +01:00
services Update type_registry, graph_utils, ingestion_note_payload, and discovery services for dynamic edge handling: Integrate EdgeRegistry for improved edge defaults and topology management (WP-24c). Enhance type loading and edge resolution logic to ensure backward compatibility while transitioning to a more robust architecture. Version bumps to 1.1.0 for type_registry, 1.1.0 for graph_utils, 2.5.0 for ingestion_note_payload, and 1.1.0 for discovery service. 2026-01-09 15:20:12 +01:00
__init__.py code header 2025-12-15 15:40:39 +01:00
config.py anpassung an variable Kontextgrenzen für Ollama 2025-12-26 11:15:13 +01:00
embeddings.py wiederhergstellt 2025-12-15 15:45:36 +01:00
main.py Update FastAPI application and related services for WP-25a: Enhance lifespan management with Mixture of Experts (MoE) integrity checks, improve logging and error handling in LLMService, and integrate profile-driven orchestration across components. Bump versions for main application, ingestion services, and LLM profiles to reflect new features and optimizations. 2026-01-02 08:57:29 +01:00