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How to find support tickets by meaning, not keywords with Jev4 PG

Count and group tickets that describe a problem, using a plain-language condition in SQL.

Credentials. The setup prompt asks for your TypeSafe key, so keep it in your local configuration and do not paste it into shared logs or prompts.

Who it is forA support analyst who needs to count unresolved billing tickets by product from a CSV export, without writing keyword rules.

The problemKeyword searches miss tickets that describe the same issue in different words, so counts are unreliable.

The outcomeA grouped count per product, where each row was judged by JEV against the stated condition and uncertain rows stay visible.

What you need first

  • Python 3.11+ and Docker with Compose v2
  • A TypeSafe key or other JEV provider settings
  • A CSV export or an existing PostgreSQL table to query

Steps

  1. Run git clone --branch v0.7.0 https://github.com/Sheltercosmo/jev4pg.git and then cd jev4pg.
  2. Run python deploy/configure.py and enter your TypeSafe key when prompted.
  3. Run docker compose build and then docker compose up -d --wait.
  4. Run python deploy/configure.py --show-token, open http://127.0.0.1:8000/ask/en and connect with that token.
  5. Choose Import CSV, select your file, name the dataset, choose Preview import, then Create table, and run the SEMANTIC query in SQL mode.

Prompt for your agent

Use the jev4pg repository to set up the workspace, import the CSV at <path-to-csv> as a dataset named tickets, and run a SQL query that counts rows where SEMANTIC(body, 'The ticket describes an unresolved billing problem.') is true, grouped by product. Return the grouped counts and confirm that the decision states and any uncertain rows are reported before the counts are treated as final.

Caveat. Browser CSV imports support up to 5 MB and 10,000 rows, so larger files need a direct PostgreSQL load and an attached table.

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