v8.1.0
neuml/txtaiv8.1.0Dec 10, 2024by davidmezzetti
AI Summary
This release adds Docling integration, Embeddings context managers, and significant database component enhancements.
Key Highlights
- Add text extraction with Docling
- Add Embeddings context manager
- Support for halfvec and bit vector types with PGVector ANN
- Persist embeddings components to specified schema
New Features
- Docling text extraction
- Embeddings context manager
- PGVector support (halfvec/bit)
- Schema persistence for embeddings
Full Release Notes
**This release adds Docling integration, Embeddings context managers and significant database component enhancements** See below for full details on the new features, improvements and bug fixes. New Features -------------------------- - Add text extraction with Docling (#814) - Add Embeddings context manager (#832) - Add support for halfvec and bit vector types with PGVector ANN (#839) - Persist embeddings components to specified schema (#829) - Add example notebook that analyzes the Hugging Face Posts dataset (#817) - Add an example notebook for autonomous agents (#820) Improvements -------------------------- - Cloud storage improvements (#821) - Autodetect Model2Vec model paths (#822) - Add parameter to disable text cleaning in Segmentation pipeline (#823) - Refactor vectors package (#826) - Refactor Textractor pipeline into multiple pipelines (#828) - RDBMS graph.delete tests and upgrade graph dependency (#837) - Bound ANN hamming scores between 0.0 and 1.0 (#838) Bug Fixes -------------------------- - Fix error with inferring function parameters in agents (#816) - Add programmatic workaround for Faiss + macOS (#818) Thank you @yukiman76! - docs: update 49_External_database_integration.ipynb (#819) Thank you @eltociear! - Fix memory issue with llama.cpp LLM pipeline (#824) - Fix issue with calling cached_file for local directories (#825) - Fix resource issues with embeddings indexing components backed by databases (#831) - Fix bug with NetworkX.hasedge method (#834)