LevelFish combines a number of AI NLG inference engines combined to generate the most relevant alternative phrasing. This is filtered through a set of quality filters to provide a high quality paraphrase set. Some of these engines are designed to focus on word use, while others are designed to focus on originality of rephrasing.

To use any of the LevelFish APIs you will require:

• an account and an API token. Contact sales@levelfish.com if you don’t have these.

• An API identifier - this is the name of the paraphrase engine you will use to generate your paraphrases.

Adding your API Token to your request headers will authorise the transaction. Any requests to the LevelFish services using your API Token will be attributed to your contract, allowance or costs. If you feel the API Token may have been compromised, please request a replacement as soon as possible.

To generate paraphrases we have several alternative methods:
 

For demonstrations and simple use:

1. Synchronous, Single/Multiple-phrase, simple results

For production implementation:

1. Synchronous, Single/Multiple-phrase, detailed results

2. Asynchronous, Single/Multiple-phrase, detailed results

With an additional feedback loop

1. Synchronous, Single/Multiple-phrase, detailed results with feedback (RECOMMENDED)

2. Asynchronous, Single/Multiple-phrase, detailed results with feedback

This is ideal for testing or demonstrating paraphrase examples. 

This is not recommended for a production implementation as it cannot be used alongside the feedback API. This API call requires the API authentication token

This is ideal for a simple implementation and gives information about the source of all the Engines used to generate the paraphrases, an indication of what has been removed by filters and provides the itemIDs needed for a feedback API implementation at some later date.

This is ideal for batch processing paraphrase requests. If you wish to send more than 5 phrases at a time it may be better to batch those requests and asynchronously pick up the results.

This method is the recommended implementation as it is a synchronous request which makes the reaction real-time.In addition, it provides the ItemIDs needed to be able to give feedback which paraphrases the user has selected.

This method can be used for batch processing tasks as above, but with the added feedback call.