v0.0.13

✨ What's New

• Make pytidb compatible with TiDB v8.5 #171 by @Mini256

• EmbeddingFunction support dimensions config for server-side embedding #184 by @Mini256

  embed_fn = EmbeddingFunction(model_name="text-embedding-3-small", dimensions=1024)

  You can use this parameter to reduce the dimensionality of the vectors generated by the embedding model, which can reduce the storage consumption and improve the query efficiency of the vector search to some extent.

• table.search() API and support returning Relationship Field #180 by @Mini256

  For example:

  class Entity(TableModel):
      __tablename__ = "entities"
      id: int = Field(primary_key=True)
      name: str = Field()
  
   entity_table = db.create_table(schema=Entity, if_exists="skip")
  
    class Relation(TableModel):
        __tablename__ = "relations"
        id: int = Field(primary_key=True)
        description: str = Field()
        source_entity_id: int = Field(foreign_key="entities.id")
        target_entity_id: int = Field(foreign_key="entities.id")
        embedding: list[float] = text_embed.VectorField(source_field="description")
        source_entity: Entity = Relationship(
            sa_relationship_kwargs={ "primaryjoin": "Relation.source_entity_id == Entity.id", "lazy": "joined" },
        )
        target_entity: Entity = Relationship(
            sa_relationship_kwargs={ "primaryjoin": "Relation.target_entity_id == Entity.id", "lazy": "joined" },
        )
  
  relation_table = db.create_table(schema=Relation, if_exists="skip")

  Now, relation_table.search("xxxx").limit(1).to_pydantic(); will return the source_entity, and target_entity field, it will help you build GraphRAG application with fewer lines of code.

📝 Documentation & Examples

• Rename "Serverless" to "Starter" #179 by @sykp241095
• Add auto embedding example for multiple model providers #181 by @Mini256
• Add custom embedding function example #167 by @Icemap

🧰 Refactor

• Move table creation logic out of Table constructor #169 by @Mini256
  Init table = Table(schema=TableModel) will no create the table in database, using table.create() or db.create_table(schema=TableModel) instead.

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🔗 Full Changelog: v0.0.12...v0.0.13