Multi vector database support for DB-GPT

[Aries-ckt]

VectorConnector is a vector database connection adapter that allows you to connect different vector databases and abstracts away implementation differences and underlying details of different vector data. For example, it can be used to connect to databases such as Milvus, Chroma, Weaviate, (Elasticsearch, FAISS, PGVector...)
how to integrate: reference

connector = {"Chroma": ChromaStore, "Milvus": MilvusStore, "Weaviate": WeaviateStore}


class VectorStoreConnector:
    """VectorStoreConnector, can connect different vector db provided load document api_v1 and similar search api_v1.
    1.load_document:knowledge document source into vector store.(Chroma, Milvus, Weaviate)
    2.similar_search: similarity search from vector_store
    how to use reference:https://db-gpt.readthedocs.io/en/latest/modules/vector.html
    how to integrate:https://db-gpt.readthedocs.io/en/latest/modules/vector/milvus/milvus.html

    """

    def __init__(self, vector_store_type, ctx: {}) -> None:
        """initialize vector store connector."""
        self.ctx = ctx
        self.connector_class = connector[vector_store_type]
        self.client = self.connector_class(ctx)

    def load_document(self, docs):
        """load document in vector database."""
        return self.client.load_document(docs)

    def similar_search(self, docs, topk):
        """similar search in vector database."""
        return self.client.similar_search(docs, topk)

    def vector_name_exists(self):
        """is vector store name exist."""
        return self.client.vector_name_exists()

    def delete_by_ids(self, ids):
        self.client.delete_by_ids(ids=ids)