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738511c5f2
@PrashantDixit0 --------- Co-authored-by: Chang She <759245+changhiskhan@users.noreply.github.com>
76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
# Copyright (c) 2023. LanceDB Developers
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from functools import cached_property
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from typing import List, Optional, Union
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import numpy as np
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from .base import TextEmbeddingFunction
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from .registry import register
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from .utils import api_key_not_found_help
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@register("openai")
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class OpenAIEmbeddings(TextEmbeddingFunction):
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"""
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An embedding function that uses the OpenAI API
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https://platform.openai.com/docs/guides/embeddings
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"""
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name: str = "text-embedding-ada-002"
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dim: Optional[int] = None
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def ndims(self):
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return self._ndims
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@cached_property
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def _ndims(self):
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if self.name == "text-embedding-ada-002":
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return 1536
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elif self.name == "text-embedding-3-large":
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return self.dim or 3072
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elif self.name == "text-embedding-3-small":
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return self.dim or 1536
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else:
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raise ValueError(f"Unknown model name {self.name}")
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def generate_embeddings(
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self, texts: Union[List[str], np.ndarray]
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) -> List[np.array]:
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"""
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Get the embeddings for the given texts
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Parameters
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----------
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texts: list[str] or np.ndarray (of str)
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The texts to embed
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"""
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# TODO retry, rate limit, token limit
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if self.name == "text-embedding-ada-002":
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rs = self._openai_client.embeddings.create(input=texts, model=self.name)
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else:
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rs = self._openai_client.embeddings.create(
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input=texts, model=self.name, dimensions=self.ndims()
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)
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return [v.embedding for v in rs.data]
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@cached_property
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def _openai_client(self):
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openai = self.safe_import("openai")
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if not os.environ.get("OPENAI_API_KEY"):
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api_key_not_found_help("openai")
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return openai.OpenAI()
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