Released: 29 Jul 2026
AIDB 7.5.0 includes the following enhancements and bug fixes:
| Type | Description |
|---|---|
| Enhancement | Model validation on creation: aidb.create_model() now validates a model by default, running a small probe inference — downloading and loading local models, or sending a test request to external providers — so configuration and credential problems surface at creation time instead of on first use. Pass validate => false to skip it, or use the new aidb.validate_model() to check an existing model. See Integrating models. |
| Enhancement | Local LLM inference with llama.cpp: AIDB can now run GGUF-format models locally through the new llamacpp_generate and llamacpp_embeddings providers, alongside the existing Candle-based local models. Ships with 7 pre-registered default models (5 for embeddings, 2 for generation). See Local models. |
| Enhancement | Requeuing failed pipeline records: The new aidb.requeue_pipeline_errors() function marks record-level error log entries dirty for reprocessing on the pipeline's next run, without needing to touch source data. See Requeuing failed records. |
| Enhancement | Live-tunable model thread limit: The new aidb.max_threads parameter caps CPU threads used for local model inference (Candle and llama.cpp), and can be changed live without a restart. See Threading limits. |
| Enhancement | I/O thread pool control: The new aidb.max_io_threads parameter caps the async I/O thread pool used for remote-model HTTP calls and volume/object-store access, live-tunable without a restart. See Threading limits. |
| Enhancement | llama.cpp native log control: The new aidb.enable_llamacpp_logs parameter turns on llama.cpp's own diagnostic logging in the server log, for troubleshooting model loading and inference issues. Off by default; requires a restart to take effect. See Local models — Troubleshooting. |
| Enhancement | Clearer error for pipeline column/step type mismatches: aidb.create_pipeline() now rejects a source column whose SQL type doesn't match its configured step (for example, a text column feeding a KnowledgeBase(Image) step) with a specific error at creation time, instead of failing later with an opaque internal error. |
| Change | Metrics collector is now opt-in: The background worker that materializes pipeline metrics into aidb.pipeline_metrics_collection is disabled by default. Enable it with the new aidb.enable_background_metrics_collector setting, instance-wide or per database. See Materialized metrics. |
| Change | topk must be a positive integer: aidb.retrieve_key() and aidb.retrieve_text() now reject topk values less than 1 with a clear error, instead of silently clamping to 1. |
| Bug fix | Error log functions and Empty-source pipelines: aidb.get_error_logs(), aidb.get_error_log_summary(), and aidb.get_all_error_summaries() no longer raise an error for pipelines with an Empty source (such as Semantic KB) — they return empty results instead, and no longer abort results for other pipelines in the same call. |