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