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from dotenv import load_dotenv |
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from openai import AsyncOpenAI, OpenAI |
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import openai |
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from typing import List |
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import os |
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import asyncio |
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class EmbeddingModel: |
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def __init__(self, embeddings_model_name: str = "text-embedding-3-small"): |
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load_dotenv() |
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self.openai_api_key = os.getenv("OPENAI_API_KEY") |
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self.async_client = AsyncOpenAI() |
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self.client = OpenAI() |
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if self.openai_api_key is None: |
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raise ValueError( |
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"OPENAI_API_KEY environment variable is not set. Please set it to your OpenAI API key." |
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) |
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openai.api_key = self.openai_api_key |
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self.embeddings_model_name = embeddings_model_name |
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async def async_get_embeddings(self, list_of_text: List[str]) -> List[List[float]]: |
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embedding_response = await self.async_client.embeddings.create( |
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input=list_of_text, model=self.embeddings_model_name |
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) |
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return [embeddings.embedding for embeddings in embedding_response.data] |
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async def async_get_embedding(self, text: str) -> List[float]: |
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embedding = await self.async_client.embeddings.create( |
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input=text, model=self.embeddings_model_name |
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) |
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return embedding.data[0].embedding |
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def get_embeddings(self, list_of_text: List[str]) -> List[List[float]]: |
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embedding_response = self.client.embeddings.create( |
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input=list_of_text, model=self.embeddings_model_name |
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) |
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return [embeddings.embedding for embeddings in embedding_response.data] |
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def get_embedding(self, text: str) -> List[float]: |
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embedding = self.client.embeddings.create( |
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input=text, model=self.embeddings_model_name |
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) |
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return embedding.data[0].embedding |
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if __name__ == "__main__": |
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embedding_model = EmbeddingModel() |
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print(asyncio.run(embedding_model.async_get_embedding("Hello, world!"))) |
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print( |
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asyncio.run( |
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embedding_model.async_get_embeddings(["Hello, world!", "Goodbye, world!"]) |
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) |
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) |
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