Generate GSQL from human sentences.
Currently a prototype. Built for the Tigergraph Graphathon challenge https://tigergraph2020.devpost.com/
Tigergraph GSQL generation based on human input text. Open source, and deployed version available.
Built for improving accessibility and build tools for Tigergraph.
Note this project currently isn't a complete representation of the GSQL language. Sentences are expected to have one subject and possible multiple direct objects or actions. Tiger NLP will currently identify the following constructs:
Vertices
Directed edges
Undirected edges
Vertex properties
Edge properties
Graph
An item is considered a property if it is not used in a vertex capacity. i.e. for elements that are defined using 'has a', they would be considered a vertex if we could derive an edge from it but a property otherwise.
The client is the user-facing website.
From the tiger-nlp client directory:
yarn
yarn start
The backend runs a flask server that serves the model for generating GSQL from english sentences.
From the ./server directory:
pip install -r requirements.txt
python3 -m spacy download en_core_web_sm
flask run
- Get started with Tigergraph: https://docs.tigergraph.com/start/get-started-with-tigergraph
- Get started with spaCy: https://spacy.io/
- Tigergraph GSQL language spec: https://docs-beta.tigergraph.com/dev/gsql-ref/querying/appendix-query/complete-formal-syntax-for-query-language
- Define the schema: https://docs.tigergraph.com/start/gsql-102/define-the-schema