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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.
+