47 lines
1.5 KiB
Python
47 lines
1.5 KiB
Python
from typing import Any, Callable, Optional
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from embedchain.config.embedder.BaseEmbedderConfig import BaseEmbedderConfig
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try:
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from chromadb.api.types import Documents, Embeddings
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except RuntimeError:
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from embedchain.utils import use_pysqlite3
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use_pysqlite3()
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from chromadb.api.types import Documents, Embeddings
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class BaseEmbedder:
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"""
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Class that manages everything regarding embeddings. Including embedding function, loaders and chunkers.
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Embedding functions and vector dimensions are set based on the child class you choose.
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To manually overwrite you can use this classes `set_...` methods.
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"""
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def __init__(self, config: Optional[BaseEmbedderConfig] = FileNotFoundError):
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if config is None:
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self.config = BaseEmbedderConfig()
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else:
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self.config = config
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self.vector_dimension: int
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def set_embedding_fn(self, embedding_fn: Callable[[list[str]], list[str]]):
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if not hasattr(embedding_fn, "__call__"):
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raise ValueError("Embedding function is not a function")
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self.embedding_fn = embedding_fn
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def set_vector_dimension(self, vector_dimension: int):
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self.vector_dimension = vector_dimension
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@staticmethod
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def _langchain_default_concept(embeddings: Any):
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"""
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Langchains default function layout for embeddings.
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"""
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def embed_function(texts: Documents) -> Embeddings:
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return embeddings.embed_documents(texts)
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return embed_function
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