Release 0.14.0

[khoroshevskyi]

Changes:

• Updated qdrant and encoder model initialization. (One connection for qdrant and one initialized object per model)
• Added hybrid semantic search.(dense + sparse search)

TODO:

• Version of pepdbagent updated in __version__.py file
• Changelog updated

[Copilot]

Pull request overview

This PR updates the project to version 0.14.0, introducing hybrid semantic search capabilities that combine dense and sparse embeddings for improved search accuracy. The key architectural change is the refactoring of Qdrant and encoder model initialization to use a single Qdrant connection and initialized encoder objects that are reused throughout the application.

Key Changes:

• Refactored Qdrant client initialization to use a single shared QdrantClient instance
• Added hybrid search functionality combining dense (semantic) and sparse (keyword-based) retrieval
• Updated encoder initialization to create persistent instances (dense, sparse, r2v, umap) for reuse
• Updated Python version support from 3.9-3.12 to 3.10-3.13 in CI workflows

Reviewed changes

Copilot reviewed 16 out of 16 changed files in this pull request and generated 16 comments.

Show a summary per file

File	Description
bbconf/_version.py	Version bumped to 0.14.0
bbconf/config_parser/const.py	Added sparse model constant and renamed Qdrant collection constants for clarity
bbconf/config_parser/models.py	Updated model paths and Qdrant collection names to match new constants
bbconf/config_parser/bedbaseconfig.py	Major refactoring: single Qdrant client initialization, separate encoder instances, new hybrid collection setup
bbconf/modules/bedfiles.py	Updated to use new encoder properties, added hybrid_search method, refactored semantic search
requirements/requirements-all.txt	Updated geniml dependency from 0.7.1 to 0.8.2
tests/config_test.yaml	Updated region2vec model name to use new naming convention
.github/workflows/*.yml	Updated Python versions and GitHub Actions versions
Import organization files	Reorganized imports alphabetically for consistency

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