https://github.com/nlpie/mtap
MTAP: A framework for distributed text analysis using gRPC and microservices-based architecture.
https://github.com/nlpie/mtap
framework grpc java microservices mtap natural-language-processing nlp pipelines python text-analysis
Last synced: 11 months ago
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MTAP: A framework for distributed text analysis using gRPC and microservices-based architecture.
- Host: GitHub
- URL: https://github.com/nlpie/mtap
- Owner: nlpie
- License: apache-2.0
- Created: 2019-04-10T16:53:42.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2025-03-27T22:31:33.000Z (about 1 year ago)
- Last Synced: 2025-03-27T22:32:32.546Z (about 1 year ago)
- Topics: framework, grpc, java, microservices, mtap, natural-language-processing, nlp, pipelines, python, text-analysis
- Language: Python
- Homepage: https://nlpie.github.io/mtap
- Size: 5.94 MB
- Stars: 6
- Watchers: 5
- Forks: 2
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# MTAP
[nlpie.github.io/mtap](https://nlpie.github.io/mtap)
## Microservice Text Analysis Platform
MTAP is a framework for distributed text analysis using gRPC and microservices-based architecture.
MTAP is used to create independent, scalable, interoperable text analysis pipeline
components in either Python or Java.
## Requirements
- Operating System: We test on Ubuntu 22.04 and MacOS Big Sur, but other UNIX-like distributions should work.
- [Python 3.9+](https://www.python.org/downloads/) We test on Python 3.9 and the latest stable version of Python.
- Optional: [Java 11+](https://adoptium.net) (_If you want to create Java Processors_) We test on Java 11 and the latest stable version of Java.
- Optional: [Go 13+](https://golang.org) if you want to run the RESTful API Gateway.
## Instructions
We make getting started tutorials available on our project website for both [Python](https://nlpie.github.io/mtap/docs/tutorials/python.html) and [Java](https://nlpie.github.io/mtap/docs/tutorials/java.html).
## About Us
MTAP is developed at the University of Minnesota by the [NLP/IE Group in the Institute for Health Informatics](https://healthinformatics.umn.edu/research/nlpie-group).
## Acknowledgements
Funding for this work was provided by:
- 1 R01 LM011364-01 NIH-NLM
- 1 R01 GM102282-01A1 NIH-NIGMS
- U54 RR026066-01A2 NIH-NCRR