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Add vector docs, provide how to you vector connector in DB-GPT. 1.chroma docs 2.milvus docs Closes #230
77 lines
2.3 KiB
Markdown
77 lines
2.3 KiB
Markdown
MilvusStore
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==================================
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MilvusStore is one implementation of the Milvus vector database in VectorConnector.
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[Tutorial on how to create a Milvus instance](https://milvus.io/docs/install_standalone-docker.md)
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inheriting the VectorStoreBase and implement similar_search(), vector_name_exists(), load_document().
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```
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class MilvusStore(VectorStoreBase):
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"""Milvus database"""
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def __init__(self, ctx: {}) -> None:
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"""init a milvus storage connection.
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Args:
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ctx ({}): MilvusStore global config.
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"""
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# self.configure(cfg)
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connect_kwargs = {}
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self.uri = CFG.MILVUS_URL
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self.port = CFG.MILVUS_PORT
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self.username = CFG.MILVUS_USERNAME
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self.password = CFG.MILVUS_PASSWORD
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self.collection_name = ctx.get("vector_store_name", None)
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self.secure = ctx.get("secure", None)
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self.embedding = ctx.get("embeddings", None)
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self.fields = []
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self.alias = "default"
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)
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```
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similar_search()
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```
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def similar_search(self, text, topk) -> None:
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"""similar_search in vector database."""
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self.col = Collection(self.collection_name)
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schema = self.col.schema
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for x in schema.fields:
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self.fields.append(x.name)
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if x.auto_id:
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self.fields.remove(x.name)
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if x.is_primary:
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self.primary_field = x.name
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if x.dtype == DataType.FLOAT_VECTOR or x.dtype == DataType.BINARY_VECTOR:
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self.vector_field = x.name
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_, docs_and_scores = self._search(text, topk)
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return [doc for doc, _, _ in docs_and_scores]
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```
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vector_name_exists()
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```
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def vector_name_exists(self):
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"""is vector store name exist."""
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return utility.has_collection(self.collection_name)
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```
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load_document()
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```
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def load_document(self, documents) -> None:
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"""load document in vector database."""
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# self.init_schema_and_load(self.collection_name, documents)
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batch_size = 500
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batched_list = [
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documents[i : i + batch_size] for i in range(0, len(documents), batch_size)
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]
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# docs = []
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for doc_batch in batched_list:
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self.init_schema_and_load(self.collection_name, doc_batch)
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```
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