dataherald
Interact with your SQL database, Natural Language to SQL using LLMs
Stars: 3182
Dataherald is a natural language-to-SQL engine built for enterprise-level question answering over structured data. It allows you to set up an API from your database that can answer questions in plain English. You can use Dataherald to: * Allow business users to get insights from the data warehouse without going through a data analyst * Enable Q+A from your production DBs inside your SaaS application * Create a ChatGPT plug-in from your proprietary data
README:
Query your relational data in natural language.
Dataherald is a natural language-to-SQL engine built for enterprise-level question answering over relational data. It allows you to set up an API from your database that can answer questions in plain English. You can use Dataherald to:
- Allow business users to get insights from the data warehouse without going through a data analyst
- Enable Q+A from your production DBs inside your SaaS application
- Create a ChatGPT plug-in from your proprietary data
This repository contains four components under /services
which can be used together to set up an end-to-end Dataherald deployment:
- Engine: The core natural language-to-SQL engine. If you would like to use the dataherald API without users or authentication, running the engine will suffice.
- Enterprise: The application API layer which adds authentication, organizations and users, and other business logic to Dataherald.
- Admin-console: The front-end component of Dataherald which allows a GUI for configuration and observability. You will need to run both engine and enterprise for the admin-console to work.
- Slackbot: A slackbot which allows users from a slack channel to interact with dataherald. Requires both engine and enterprise to run.
For more information on each component, please take a look at their README.md
files.
Each component in the /services
directory has its own docker-compose.yml
file. To set up the environment, follow these steps:
-
Set Environment Variables:
Each service requires specific environment variables. Refer to the
.env.example
file in each service directory and create a.env
file with the necessary values.For the Next.js front-end app is
.env.local
- Run Services: You can run all the services using a single script located in the root directory. This script creates a common Docker network and runs each service in detached mode.
Run the script to start all services:
sh docker-run.sh
As an open-source project in a rapidly developing field, we are open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see here.
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