nlp_query_builder

Dependency

The model is tested in python 3.6 and pytorch 1.0. :

pip install -r requirements.txt

Download Pretrained BERT model from here as model/bert/data/annotated_wikisql_and_PyTorch_bert_param/pytorch_model_uncased_L-12_H-768_A-12.bin.

Download the database sqlite files from here as data/database.

Run SParC experiment on EditSQL

First, download SParC. Then please follow

• for training run: run_sparc_editsql.sh.
• experimental logs are saved at logs/logs_sparc_editsql. Delete args.log from there before commencing training
• The dev results can be reproduced by test_sparc_editsql.sh with the pre-trained model downloaded from here and put under logs/logs_sparc_editsql/save_31_sparc_editsql.
• The predictions are saved at logs/logs_sparc_editsql as dev_use_predicted_queries_predictions.json

Edit data/sparc/tables.json to add a new table, edit data/sparc/dev.json and data/sparc/dev_no_value.json to add new questions:

• Use https://github.com/taoyds/spider#tables and https://github.com/taoyds/spider#question-sql-and-parsed-sql as reference to understand the structure of the files.
• parsed_sql_examples.sql(https://github.com/taoyds/spider/blob/master/preprocess/parsed_sql_examples.sql) gives examples to help understand the input structure.
• In dev.json and dev_no_value.json there is no need to edit anything except the utterance and utterance_toks as per the new question that you want to ask.

Add the new database schema file (.sqlite file) at data/sparc/databases/new_schema_name/new_schema.sqlite and add the database name to the list of database names in data/sparc/dev_db_ids.txt

After adding new questions, delete the following folders if they exist:

• processed_data_sparc_removefrom
• processed_data_sparc_removefrom_test
• data/sparc_data_removefrom These folders contain vocabulary files which need to be recreated if you have edited the dev files or added a new schema

Run output.py to get a text file named output.txt with formatted results.