openai
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# openai |
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# Sentence Embedding with OpenAI |
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*author: Junjie, Jael* |
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<br /> |
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## Description |
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A sentence embedding operator generates one embedding vector in ndarray for each input text. |
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The embedding represents the semantic information of the whole input text as one vector. |
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This operator is implemented with embedding models from [OpenAI](https://platform.openai.com/docs/guides/embeddings). |
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Please note you need an [OpenAI API key](https://platform.openai.com/account/api-keys) to access OpenAI. |
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<br /> |
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## Code Example |
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Use the pre-trained model '' |
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to generate an embedding for the sentence "Hello, world.". |
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*Write a pipeline with explicit inputs/outputs name specifications:* |
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```python |
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from towhee.dc2 import pipe, ops, DataCollection |
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p = ( |
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pipe.input('text') |
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.map('text', 'vec', |
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ops.sentence_embedding.openai(model_name='text-embedding-ada-002', api_key=OPENAI_API_KEY)) |
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.output('text', 'vec') |
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) |
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DataCollection(p('Hello, world.')).show() |
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``` |
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<br /> |
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## Factory Constructor |
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Create the operator via the following factory method: |
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***sentence_embedding.openai(model_name='text-embedding-ada-002')*** |
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**Parameters:** |
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***model_name***: *str* |
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The model name in string, defaults to 'text-embedding-ada-002'. Supported model names: |
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- text-embedding-ada-002 |
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- text-similarity-davinci-001 |
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- text-similarity-curie-001 |
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- text-similarity-babbage-001 |
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- text-similarity-ada-001 |
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***api_key***: *str=None* |
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The OpenAI API key in string, defaults to None. |
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<br /> |
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## Interface |
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The operator takes a piece of text in string as input. |
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It returns a text emabedding in numpy.ndarray. |
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***\_\_call\_\_(txt)*** |
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**Parameters:** |
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***text***: *str* |
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The text in string. |
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**Returns**: |
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*numpy.ndarray or list* |
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The text embedding extracted by model. |
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<br /> |
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***supported_model_names()*** |
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Get a list of supported model names. |
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