Vector Search for Python: Objectbox 4.0.0

• ObjectBox now supports vector search ("vector database") to enable efficient similarity searches.
  This is particularly useful for AI/ML/RAG applications, e.g. image, audio, or text similarity.
  Other use cases include sematic search or recommendation engines.
  See https://docs.objectbox.io/ann-vector-search for details.
• The definition of entities (aka the data model) is now greatly simplified
  • Type-specific property classes, e.g. name: String, count: Int64, score: Float32
  • Automatic ID/UID and model management (i.e. add/remove/rename of entities and properties)
  • Automatic discovery of @entity classes
• Queries: property-based conditions, e.g. box.query(City.name.starts_with("Be"))
• Queries: logical operators, e.g. box.query(City.name == "Berlin" | City.name == "Munich")
• Convenient "Store" API (deprecates ObjectBox and Builder API)
• New examples added, illustrating an VectorSearch and AI/RAG application
• Stable flat public API provided by single top-level module objectbox
• Dependency flatbuffers: Updated to 24.3.50
• Adjusting the version number to match the core version (4.0); we will be aligning on major versions from now on.