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Rasa Paraphraser

github.com

Free plan LinuxSelf-hosted
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Spec score 7.7 #16 of 24 in AI Paraphrasing Tools

What it is

Rasa Paraphraser is a free, MIT-licensed open-source tool for generating sentence alternatives that keep intended meaning while changing wording and structure. Rasa built it mainly for data augmentation in Rasa Open Source, with other paraphrasing uses also possible. The multilingual model supports 30 languages, although the README says testing has covered English, German, French, Spanish and Russian. It uses a Prism-framework neural machine translation model with decoding changes intended to increase diversity. Users can work interactively at the command line or generate batches from files. Bulk input accepts Rasa NLU training data or CSV rows containing a sentence and optional label; output can use either format and includes similarity scores. Controls cover language, lexical diversity, n-gram penalties, beam search and candidate count. Docker is required, with CPU and GPU container instructions. A lightweight mode is described as about 2.5 times faster, with possible quality impact.

Spec sheet

Purpose
It generates paraphrases of sentences that are intended to be semantically similar but lexically and structurally different.Read 4 Oct 2026 · github.com
Deployment
The README instructs users to install Docker and documents CPU and GPU container builds and runs.Read 4 Oct 2026 · github.com
License
The repository includes an MIT license.Read 4 Oct 2026 · github.com
Headquarters
San Francisco, United States, with engineering in Berlin, GermanyRead 28 Sep 2026 · github.com
Founded
2016Read 28 Sep 2026 · github.com
Content safety
The README warns that the model can generate offensive content and says the tool does not currently filter or detect it.Read 4 Oct 2026 · github.com
Feedback
The README invites users to provide feedback.Read 4 Oct 2026 · github.com
Generation controls
Command-line options control language, lexical diversity, n-gram penalization, beam search, and the number of candidate paraphrases.Read 4 Oct 2026 · github.com
Input formats
Bulk mode accepts Rasa NLU training data or CSV rows containing a sentence and optional label.Read 4 Oct 2026 · github.com
Languages
The model supports 30 languages, but the README says the tool has only been tested in English, German, French, Spanish, and Russian.Read 4 Oct 2026 · github.com
Model
It uses a multilingual neural machine translation model from the Prism framework with diversity-promoting decoding changes.Read 4 Oct 2026 · github.com
Output formats
Bulk output can use Rasa NLU training data format or CSV, and includes similarity scores for generated paraphrases.Read 4 Oct 2026 · github.com
Quality option
A lightweight mode is described as around 2.5 times faster, with a possible negative effect on generation quality.Read 4 Oct 2026 · github.com
Run modes
The tool provides interactive command-line use and bulk generation from input files.Read 4 Oct 2026 · github.com
Use case
Rasa says it was primarily built for data augmentation inside the Rasa Open Source framework and can also be used for other paraphrasing needs.Read 4 Oct 2026 · github.com

Plans and prices

Rasa Paraphraser Free MIT-licensed open-source tool · requires Docker Read 4 Oct 2026 · github.com

Every Rasa Paraphraser plan and price →

Strong points and limits

Strong points

  • Supports 30 languages
  • Interactive and bulk generation
  • Rasa NLU and CSV formats
  • Similarity scores in bulk output
  • MIT-licensed and free

Limits

  • Requires Docker
  • Testing listed for five languages
  • May generate offensive content
  • Lightweight mode may reduce quality

Who it suits

It suits developers needing local or self-hosted paraphrase generation, especially for Rasa data augmentation. Users should be comfortable with Docker and command-line workflows.

Verdict

Rasa Paraphraser offers configurable command-line and batch generation with multilingual output and similarity scoring. Its Docker requirement and unfiltered offensive-content warning are important deployment considerations.

Where Specifiction places it

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