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- Simplified package-data patterns in pyproject.toml - Added MANIFEST.in for explicit binary file inclusion - Ensures _bin/ and lib/ directories are always included in wheels - Verified: wheel now contains all platform binaries (toondb-bulk, toondb-grpc-server, toondb-server, libtoondb_storage.dylib)
Previously sdist was built without any binaries, making it incomplete. Changes: - sdist now downloads binaries from all 3 platforms (Linux, macOS, Windows) - Copies binaries to src/toondb/_bin/ and src/toondb/lib/ before building sdist - Ensures sdist contains all platform binaries for cross-platform compatibility - Only builds sdist once (using Linux target as trigger) to avoid duplicates This ensures 'pip install toondb-client' from source will work with embedded FFI mode.
Features
========
- Add create_index() method to Database class for easy vector index creation
- Add insert_vectors() method for batch vector insertion
- Add search() method for k-NN vector search
- Vector indices now accessible directly from Database without VectorIndex class
API Improvements
================
Before (required separate VectorIndex):
from toondb.vector import VectorIndex
index = VectorIndex(dimension=384)
index.insert_batch(ids, vectors)
results = index.search(query, k=5)
After (convenience methods on Database):
db = Database.open('./mydb')
db.create_index('embeddings', dimension=384)
db.insert_vectors('embeddings', ids, vectors)
results = db.search('embeddings', query, k=5)
Implementation
==============
- Indices managed internally as _vector_indices dict
- Metadata stored in database under _indices/{name}/meta
- Lazy loading of indices from metadata
- Full compatibility with existing VectorIndex class
Testing
=======
- Vector index creation: ✅
- Batch vector insertion: ✅
- k-NN search: ✅
- All operations working with tokio-optional architecture
Packaging
=========
- Remove MANIFEST.in (not needed with modern pyproject.toml)
- Update version to 0.3.5
Documentation Updates
=====================
- Add 'What's New in 0.3.5' section
- Document new vector operations on Database class
- Show simplified API compared to separate VectorIndex class
- Add code examples for create_index(), insert_vectors(), search()
- Document tokio-optional compatibility
API Examples
============
Before (0.3.4):
from toondb.vector import VectorIndex
index = VectorIndex(dimension=384)
After (0.3.5):
db = Database.open('./mydb')
db.create_index('embeddings', dimension=384)
Benefits
========
- Simpler API - all operations on Database class
- No need to manage separate VectorIndex instances
- Index metadata stored in database
- Backwards compatible with VectorIndex class
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