chenmoshushi / mlsql Goto Github PK

Infer SQL queries from plain-text questions and table headers.

Requirements:

• install docker
• install curl
• Make sure docker allows at least 3GB of RAM (see Docker>Preferences>Advanced or equivalent)

This wraps up a published pretrained model for Sqlova (https://github.com/naver/sqlova/).

Fetch and start sqlova running as an api server on port 5050:

docker run --name sqlova -d -p 5050:5050 paulfitz/sqlova

Be patient, the image is about 4.2GB. Once it is running, it'll take a few seconds to load models and then you can start asking questions about CSV tables. For example:

curl -F "[email protected]" -F "q=how long is throgs neck" localhost:5050
# {"answer":[1800],"params":["throgs neck"],"sql":"SELECT (length) FROM bridges WHERE bridge = ?"}

This is using the sample bridges.csv included in this repo.

Here are some examples of the answers and sql inferred for plain-text questions about this table:

With the players.csv sample from WikiSQL:

Some questions about iris.csv:

There are plenty of types of questions this model cannot answer (and that aren't covered in the dataset it is trained on, or in the sql it is permitted to generate). I hope to track research in the area and substitute in models as they become available:

• WikiSQL leaderboard
• Spider leaderboard
• Code/models coming soon hopefully: IRNet, Spider Schema GNN
• Is there any code for X-SQL?
• SyntaxSQL