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As consumers rely more and more on search engines and technical software programs to answer their questions, the demand for effective and scalable natural language processing has gone immensely up. OpenAI provides access to the GPT-3 model, which can perform several operations for NLP-related tasks such as summarization, classification, text completion, text insertion, and more. In this course, you’ll learn about the various endpoints of the OpenAI API and how they can be used to accomplish certain NLP tasks. We'll also look at examples of each endpoint to show how they work. By the time you’re done with this course, you’ll be able to work on your own projects using the OpenAI API.

Using OpenAI API for Natural Language Processing in Python

## Completion

The completions endpoint can also be used to complete unattended (incomplete) sentences. For example, if we leave a sentence half-written, the completions endpoint can complete the sentence provided that it has the appropriate context. In this case, the value of the `temperature` is usually kept low so that the completion does not disregard the previous context. 


### Example
Let’s see an example of a sentence completion:

# Completion

The completions endpoint can also be used to complete unattended (incomplete) sentences. For example, if we leave a sentence half-written, the completions endpoint can complete the sentence provided that it has the appropriate context. In this case, the value of the `temperature` is usually kept low so that the completion does not disregard the previous context. 


## Example
Let’s see an example of a sentence completion:

Learn about completing incomplete content and factual responses using the completions endpoint.

Introduction

The Completions Endpoint

Miscellaneous Endpoints

Conclusion

Appendix

Completing Incomplete Content and Factual Responses

Completion

Example