django-elasticsearch-dsl | allows indexing of django models | Functional Testing library

I am trying to call a local ES instance running on docker. I used the following instructions to setup my ES instance: https://www.elastic.co/guide/en/elasticsearch/reference/current/getting-started.html https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-dev-mode

I am able to play around with my instance on Kibana at http://0.0.0.0:5601/app/dev_tools#/console. Everything works upto here.

Now I am trying to define some sample documents using django models and index them through the library; I am following the instructions here: https://django-elasticsearch-dsl.readthedocs.io/en/latest/quickstart.html#install-and-configure

First, I add pip installed and added django_elasticsearch_dsl to INSTALLED_APPS

Next, I added in settings.py:

I have a model that uses django hashid fields for the id.

I am using django-elasticsearch-dsl library a high level client to interact with elasticsearch.

This is my Document.py file

I'm trying to implement the following Elasticsearch query using django-elasticsearch-dsl and am having some difficulty

Query

I am trying to implement search suggestions using django-elasticsearch-dsl-drf for streets.

This is documents.py:

How to make OR query (using django-elasticsearch-dsl-drf) with multiple contains statements? Query in words: Search for objects where title contains "hello" OR description contains "world"

I can't find about it in documentation: https://django-elasticsearch-dsl-drf.readthedocs.io/en/0.3.12/advanced_usage_examples.html#usage-example

I am trying to build a simple django elastice search which can search cars. But when I am trying to rebuid the indexes, it gives me the error above. I am following this doc -> quickstart elasticsearch...full traceback is given below->

I used two packages (i.e. django-elasticsearch-dsl==7.1.4 and django-elasticsearch-dsl-drf==0.20.8) to add a search engine to my Django project. The model which I indexed in elastic is:

I’m building a Django web application to store documents and their associated metadata.

The bulk of the metadata will be stored in the underlying MySQL database, with the OCR’d document text indexed in Elasticsearch to enable full-text search. I’ve incorporated django-elasticsearch-dsl to connect and synchronize my data models, as I’m also indexing (and thus, double-storing) a few other fields found in my models. I had considered using Haystack, but it lacks support for the latest Elasticsearch versions.

When a document is uploaded via the applications’s admin interface, a post_save signal automatically triggers a Celery asynchronous background task to perform the OCR and will ultimately index the extracted text into Elasticsearch.

Seeing as how I don’t have a full-text field defined in my model (and hope to avoid doing so as I don’t want to store or search against CLOB’s in the database), I’m seeking the best practice for updating my Elasticsearch documents from my tasks.py file. There doesn’t seem to be a way to do so using django-elasticseach-dsl (but maybe I’m wrong?) and so I’m wondering if I should either:

1. Try to interface with Elasticsearch via REST using the sister django-elasticsearch-dsl-drf package.

2. More loosely integrate my application with Elasticsearch by using the more vanilla elasticsearch-dsl-py package (based on elasticsearch-py). I‘d lose some “luxury” with this approach as I’d have to write a bit more integration code, at least if I want to wire up my models with signals.

Is there a best practice? Or another approach I haven’t considered?

Update 1: In trying to implement the answer from @Nielk, I'm able to persist the OCR'd text (result = "test" in tasks.py below) into ElasticSearch, but it's also persisting in the MySQL database. I'm still confused about how to essentially configure Submission.rawtext as a passthru to ElasticSearch.

models.py: