LLM helper for psql
Project description
gptsql
An LLM wrapper around your database connection. Think of it as a "smart" version of the psql cli.
Example:
python -m gptsql
> show me the schemas
thinking...
Running select query: SELECT schema_name FROM information_schema.schemata;
processing the function response...
Here are the schemas in your database:
1. pg_catalog
2. information_schema
3. analytics
4. public
5. aws_commons
6. bi_staging
7. rds_tools
> show me all the tables with 'sales' in the name
⠸ thinking... Running select query: SELECT table_name FROM information_schema.tables WHERE table_name LIKE '%%sales%%' ORDER BY table_name;
[assistant] --> The tables with 'sales' in the name are as follows:
- salesorderdetail
- salesorderheader
- salesorderheadersalesreason
- salesperson
- salespersonquotahistory
- salesreason
- salestaxrate
- salesterritory
- salesterritoryhistory
- vsalesperson
- vsalespersonsalesbyfiscalyears
- vsalespersonsalesbyfiscalyearsdata
> how many rows are in the salesperson table?
⠏ thinking... Running select query: SELECT COUNT(*) FROM sales.salesperson;
[assistant] --> The `salesperson` table contains 17 rows.
Getting started
You need credentials for your database, and you will need an OpenAI API Key from your OpenAI account.
Installation:
pip install gptsql
or download the source.
Run the CLI with:
gptsql
or use python -m gptsql
to run from source.
Project details
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