41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
import os
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from typing import Optional
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from vertexai.language_models import TextEmbeddingModel
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from mem0.configs.embeddings.base import BaseEmbedderConfig
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from mem0.embeddings.base import EmbeddingBase
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class VertexAI(EmbeddingBase):
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def __init__(self, config: Optional[BaseEmbedderConfig] = None):
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super().__init__(config)
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self.config.model = self.config.model or "text-embedding-004"
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self.config.embedding_dims = self.config.embedding_dims or 256
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credentials_path = self.config.vertex_credentials_json
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if credentials_path:
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os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = credentials_path
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elif not os.getenv("GOOGLE_APPLICATION_CREDENTIALS"):
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raise ValueError(
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"Google application credentials JSON is not provided. Please provide a valid JSON path or set the 'GOOGLE_APPLICATION_CREDENTIALS' environment variable."
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)
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self.model = TextEmbeddingModel.from_pretrained(self.config.model)
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def embed(self, text):
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"""
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Get the embedding for the given text using Vertex AI.
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Args:
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text (str): The text to embed.
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Returns:
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list: The embedding vector.
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"""
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embeddings = self.model.get_embeddings(texts=[text], output_dimensionality=self.config.embedding_dims)
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return embeddings[0].values
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