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Version: PromptQL

AI Assistant on CSV Files

Supports importing multiple CSV files, each with their own schema.

Prerequisites​

Install the DDN CLI

Minimum version requirements

To use this guide, ensure you've installed/updated your CLI to at least v2.28.0.

Simply run the installer script in your terminal:

curl -L https://graphql-engine-cdn.hasura.io/ddn/cli/v4/get.sh | bash
ARM-based Linux Machines

Currently, the CLI does not support installation on ARM-based Linux systems.

Install Docker

The Docker-based workflow helps you iterate and develop locally without deploying any changes to Hasura DDN, making the development experience faster and your feedback loops shorter. You'll need Docker Compose v2.20 or later.

Validate the installation

You can verify that the DDN CLI is installed correctly by running:

ddn doctor

Import your CSV Files​

Step 1: Clone the project

git clone [email protected]:hasura/csv-promptql.git
cd csv-promptql

Step 2: Configure CSV file(s)

Place your CSV file(s) inside app/connector/csv/csv_files directory.

cd app/connector/csv/csv_files

Add your CSV files here.

Step 3: Introspect the Connector

ddn connector introspect csv

Note: Depending on how big the dataset is, it should take sometime to fully import the data. The schema will be initialized quickly and the data import happens in the background, so you can proceed to follow the steps below.

Step 4: Add Models

Based on the dataset imported, a SQL schema would be generated. Let's track all the models to get started quickly.

ddn model add csv "*"

Build your PromptQL app​

Now, let's set up the Hasura DDN project with PromptQL to start exploring the data in natural language!

  • Set up the Hasura DDN project already scaffolded in the repo:

In the root directory of the repo, run the following commands:

ddn supergraph build local
ddn project init
  • Start the DDN project

Let's start the DDN project by executing the following command:

ddn run docker-start
  • Open the local DDN Console to start exploring:
ddn console --local

This should open up your browser (or print a browser URL) for displaying the Hasura Console. It’ll typically be something like: https://console.hasura.io/local?engine=localhost:3280&promptql=localhost:3282

Ask questions about your dataset​

The app will have metadata about the dataset that you just imported above. You should be able to ask domain specific questions and play around with the data.

Here's a sample of what you can ask to get started.

  • Hi, what can you do?

Depending on the dataset schema, PromptQL will tell you what it can answer and you can go from there.

Clean up and restart your app​

If you want to reset the data and start from scratch:

Modify or delete the csv files in the app/connector/csv/csv_files directory

You can stop the ddn run docker-start command, whereever it is running and you can execute the following in the root directory of the repo:

docker compose down -v && ddn run docker-start