zensols.amrspring 0.0.1

A client and server that generates AMR graphs from natural language sentences.

A Spring AMR service and client

A client and server that generates AMR graphs from natural language sentences. This repository has a Docker that compiles the [AMR SPRING parser] using the original settings of the authors.

The Docker image was created because this parser has a very particular set of Python dependencies that do not compile under some platforms. Specifically tokenizers==0.7.0 fails to compile from source on a pip install because of a Rust (version) compiler misconfiguration.

The Docker image provides a very simple service written in [Flask] that uses the SPRING model for inferencing and returns the parsed AMRs.

Features:

• Parse natural language sentence (batched) into AMRs.
• Results cached in memory or an SQLite database.
• Both a command line and Pythonic object oriented client API.

Installing

First install the client:

pip3 install zensols.amrspring

Server

There is a script to build a local server, but there is also a docker image.

To build a local server:

1. Clone this repo: git clone https://github.com/plandes/amrspring
2. Working directory: cd amrspring
3. Build out the server: src/bin/build-server.sh <python installation directory>
4. Start it ( cd server ; ./serverctl start )
5. Test it ( cd server ; ./serverctl test-server )
6. Stop it ( cd server ; ./serverctl top )

Docker

To build the Docker image:

1. Download the model(s) from the [AMR SPRING parser] repository.
2. Build the image: cd docker ; make build
3. Check for errors.
4. Start the image: make up
5. Test using a method from usage.

Of course, the server code can be run without docker by cloning the [AMR SPRING parser] repository and adding the server code. See the Dockerfile for more information on how to do that.

Usage

The package can be used from the command line or directly via a Python API.

You can use a combination UNIX tools to POST directly to it:

wget -q -O - --post-data='{"sents": ["Obama was the 44th president."]}' \
  --header='Content-Type:application/json' \
  'http://localhost:8080/parse' | jq -r '.amrs."0"."graph"'
# ::snt Obama was the 44th president.
(z0 / person
    :ord (z1 / ordinal-entity
             :value 44)
    :ARG0-of (z2 / have-org-role-91
                 :ARG2 (z3 / president))
    :domain (z4 / person
                :name (z5 / name
                          :op1 "Obama")))

It also offers a command line:

$ amrspring --level warn parse 'Obama was the president.'
sent: Obama was the president.
graph:
    # ::snt Obama was the president.
    (z0 / person
        :ARG0-of (z1 / have-org-role-91
                     :ARG2 (z2 / president))
        :domain (z3 / person
                    :name (z4 / name
                              :op1 "Obama")))

The Python API is very straight forward as well:

>>> from zensols.amrspring import AmrPrediction, ApplicationFactory
>>> client = ApplicationFactory.get_client()
>>> pred = tuple(client.parse(['Obama was the president.']))[0]
2024-02-19 19:41:03,659 parsed 1 sentences in 3ms
>>> print(pred.graph)
# ::snt Obama was the president.
(z0 / person
    :ARG0-of (z1 / have-org-role-91
                 :ARG2 (z2 / president))
    :domain (z3 / person
                :name (z4 / name
                          :op1 "Obama")))

Documentation

See the full documentation. The API reference is also available.

Changelog

An extensive changelog is available here.

Community

Please star this repository and let me know how and where you use this API. Contributions as pull requests, feedback and any input is welcome.

License

MIT License

Copyright (c) 2024 Paul Landes

[AMR SPRING parser]: git clone https://github.com/SapienzaNLP/spring