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Rasa Paraphraser
San Francisco, United States, with engineering in Berlin, Germany
What it is
Rasa Paraphraser is a free, MIT-licensed open-source tool for generating sentence alternatives with similar meaning and different wording or structure. Rasa primarily built it for data augmentation in Rasa Open Source, though it can serve other paraphrasing tasks. The multilingual model supports 30 languages; the README says testing has covered English, German, French, Spanish, and Russian. You can work interactively from a command line or process files in bulk. Bulk input accepts Rasa NLU training data or CSV rows with a sentence and optional label, while output can use Rasa NLU format or CSV and includes similarity scores. Options control 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 a possible quality reduction.
For and against
For
- Supports 30 languages
- Interactive and bulk generation modes
- CSV and Rasa data formats
- Similarity scores accompany outputs
- MIT-licensed and free
Against
- Requires Docker
- Testing listed for only five languages
- Model may generate offensive content
- Lightweight mode may reduce quality
The verdict
Rasa Paraphraser offers configurable, self-hosted generation for multilingual data workflows. Docker setup and the absence of offensive-content filtering require attention before deployment.
Who it suits
Rasa Paraphraser suits developers and teams needing local, Linux-based paraphrase generation, especially for Rasa training-data augmentation. It is also relevant for users comfortable running Docker and command-line workflows.
Plans and prices
Rasa Paraphraser
MIT-licensed open-source tool · requires Docker
Read 4 Oct 2026 · github.com
On the record
- Content safety
- The README warns that the model can generate offensive content and says the tool does not currently filter or detect it.github.com · read 4 Oct 2026
- Deployment
- The README instructs users to install Docker and documents CPU and GPU container builds and runs.github.com · read 4 Oct 2026
- Feedback
- The README invites users to provide feedback.github.com · read 4 Oct 2026
- Generation controls
- Command-line options control language, lexical diversity, n-gram penalization, beam search, and the number of candidate paraphrases.github.com · read 4 Oct 2026
- Input formats
- Bulk mode accepts Rasa NLU training data or CSV rows containing a sentence and optional label.github.com · read 4 Oct 2026
- Languages
- The model supports 30 languages, but the README says the tool has only been tested in English, German, French, Spanish, and Russian.github.com · read 4 Oct 2026
- License
- The repository includes an MIT license.github.com · read 4 Oct 2026
- Model
- It uses a multilingual neural machine translation model from the Prism framework with diversity-promoting decoding changes.github.com · read 4 Oct 2026
- Output formats
- Bulk output can use Rasa NLU training data format or CSV, and includes similarity scores for generated paraphrases.github.com · read 4 Oct 2026
- Purpose
- It generates paraphrases of sentences that are intended to be semantically similar but lexically and structurally different.github.com · read 4 Oct 2026
- Quality option
- A lightweight mode is described as around 2.5 times faster, with a possible negative effect on generation quality.github.com · read 4 Oct 2026
- Run modes
- The tool provides interactive command-line use and bulk generation from input files.github.com · read 4 Oct 2026
- 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.github.com · read 4 Oct 2026
