78 lines
2.3 KiB
Python
78 lines
2.3 KiB
Python
from embedchain.config.vectordb.base import BaseVectorDbConfig
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from embedchain.embedder.base import BaseEmbedder
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from embedchain.helpers.json_serializable import JSONSerializable
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class BaseVectorDB(JSONSerializable):
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"""Base class for vector database."""
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def __init__(self, config: BaseVectorDbConfig):
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"""Initialize the database. Save the config and client as an attribute.
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:param config: Database configuration class instance.
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:type config: BaseVectorDbConfig
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"""
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self.client = self._get_or_create_db()
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self.config: BaseVectorDbConfig = config
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def _initialize(self):
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"""
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This method is needed because `embedder` attribute needs to be set externally before it can be initialized.
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So it's can't be done in __init__ in one step.
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"""
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raise NotImplementedError
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def _get_or_create_db(self):
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"""Get or create the database."""
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raise NotImplementedError
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def _get_or_create_collection(self):
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"""Get or create a named collection."""
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raise NotImplementedError
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def _set_embedder(self, embedder: BaseEmbedder):
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"""
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The database needs to access the embedder sometimes, with this method you can persistently set it.
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:param embedder: Embedder to be set as the embedder for this database.
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:type embedder: BaseEmbedder
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"""
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self.embedder = embedder
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def get(self):
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"""Get database embeddings by id."""
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raise NotImplementedError
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def add(self):
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"""Add to database"""
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raise NotImplementedError
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def query(self):
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"""Query contents from vector data base based on vector similarity"""
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raise NotImplementedError
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def count(self) -> int:
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"""
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Count number of documents/chunks embedded in the database.
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:return: number of documents
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:rtype: int
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"""
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raise NotImplementedError
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def reset(self):
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"""
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Resets the database. Deletes all embeddings irreversibly.
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"""
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raise NotImplementedError
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def set_collection_name(self, name: str):
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"""
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Set the name of the collection. A collection is an isolated space for vectors.
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:param name: Name of the collection.
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:type name: str
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"""
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raise NotImplementedError
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