Fixed SQL code formatting errors by:
- catching both single and double backslashes in the formatting
- explicitly telling LLM how to format linebreaks
Also did some changes to the UI and allowed general questions
about the database content to be asked.
Using respective credentials for both local development as well as
deployment. When deployed on azure, the app authenticates with the SQL
database via Entra ID (formerly active directory) and accesses other
credentials via key vault as a system managed identity.
Before, there was no direct description about the usage of the manual
SQL query input field. A plotly dash component was added with a more
precise description for the user.
Add the first working code logic both in terms of backend and
frontend-related tasks. Add a detailled system message for improved
results. Add several UI improvements for result display and user
information. Add text input field for direct SQL code comparison.
The implementation of the openAI backend had to be changed due to strict
rate limits of azure OpenAI free tier and was replaced with a regular
openai API key.
In order to compare the (not yet implemented) SQL query generated by
the LLM with an actual query, another text field was added that parses
the query to `pyodbc`, which connects to our database, stores the
resulting rows in a `pandas` dataframe and then visualizes it as a table
in plotly dash.
The SQL functionalities are implemented in the `sql_utils.py` module.
Additionally, some minor updates to the overall behavior and layout of
the app were implemented.
Includes the first version of a rudimentary chat app, still without the
SQL capabilities that we want later. For now, we can connect to the
Azure OpenAI source and then have the response displayed in a plotly
dash webapp.
Some styling and UI elements were also added, such as logos. UI
components are designed that the user cannot enter the same query twice
and cannot click the submit button as long as the query is running.
Setting up python project files using poetry. A basic environment
is installed including dash for the app that will be implemented
later.
Also contains several dev tools, including pre-commit hooks.
Co-authored-by: Tobias Quadfasel <tobias.loesche@studium.uni-hamburg.de>
Reviewed-on: #1
