Feb 15, 2024 · Feb 15, 2024
diff --git a/pgml-cms/blog/using-postgresml-with-django-and-embedding-search.md b/pgml-cms/blog/using-postgresml-with-django-and-embedding-search.md

 Before going forward, make sure you have the app running either locally or in a cloud provider of your choice. If hosting it somewhere, replace `localhost:8000` with the URL and port of your service.

 The simplest way to interact with it is to use cURL oranHTTP client of your preference. If running in debug mode locally, the Rest Framework provides a nice web UI which you can access on [http://localhost:8000/api/todos/](http://localhost:8000/api/todo/) using a browser.
 The simplest way to interact with it is to use cURL oryour preferredHTTP client. If running in debug mode locally, the Rest Framework provides a nice web UI which you can access on [http://localhost:8000/api/todo/](http://localhost:8000/api/todo/) using a browser.

 To create a to-do item with cURL, you can just run this:


 The embedding contains 384 floating point numbers; we removed most of them in this blog post to make sure it fits on the page.

 You can try creating multiple to-do items for fun and profit. If the description is changed, so will the embedding, demonstrating how the `intfloat/e5-small` modelis understanding the semantic meaning of your text.
 You can try creating multiple to-do items for fun and profit. If the description is changed, so will the embedding, demonstrating how the `intfloat/e5-small` modelunderstands the semantic meaning of your text.

 ### Searching

 Once you have a few embeddings and to-dos stored in your database, the fun part of searching can begin. In a typical search example with PostgreSQL, you'd now be using `tsvector` to keyword match your to-dos to the search query with term frequency. That's a good technique, but semantic search is better.

 We've created a simplesearch endpointthataccepts a query, a completed to-do filter, and a limit. To use it, you can justdo this:
 Oursearch endpoint accepts a query, a completed to-do filter, and a limit. To use it, you can justrun this:

 ```bash
 curl \
 If you've created a bunch of different to-do items, you should get only one search result back, and exactly the one you were expecting:

 ```json
 "Make a New Year resolution list"
 "Make a New Year resolution"
 ```

 You can increase the `limit` to something larger and you should get more documents, in decreasing order of relevance.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -88,7 +88,7 @@ All of this happens inside PostgresML. Our Django app doesn't need to implement

		Before going forward, make sure you have the app running either locally or in a cloud provider of your choice. If hosting it somewhere, replace `localhost:8000` with the URL and port of your service.

		The simplest way to interact with it is to use cURL oranHTTP client of your preference. If running in debug mode locally, the Rest Framework provides a nice web UI which you can access on [http://localhost:8000/api/todos/](http://localhost:8000/api/todo/) using a browser.
		The simplest way to interact with it is to use cURL oryour preferredHTTP client. If running in debug mode locally, the Rest Framework provides a nice web UI which you can access on [http://localhost:8000/api/todo/](http://localhost:8000/api/todo/) using a browser.

		To create a to-do item with cURL, you can just run this:

Expand All		@@ -115,13 +115,13 @@ In return, you'll get your to-do item alongside the embedding of the `descriptio

		The embedding contains 384 floating point numbers; we removed most of them in this blog post to make sure it fits on the page.

		You can try creating multiple to-do items for fun and profit. If the description is changed, so will the embedding, demonstrating how the `intfloat/e5-small` modelis understanding the semantic meaning of your text.
		You can try creating multiple to-do items for fun and profit. If the description is changed, so will the embedding, demonstrating how the `intfloat/e5-small` modelunderstands the semantic meaning of your text.

		### Searching

		Once you have a few embeddings and to-dos stored in your database, the fun part of searching can begin. In a typical search example with PostgreSQL, you'd now be using `tsvector` to keyword match your to-dos to the search query with term frequency. That's a good technique, but semantic search is better.

		We've created a simplesearch endpointthataccepts a query, a completed to-do filter, and a limit. To use it, you can justdo this:
		Oursearch endpoint accepts a query, a completed to-do filter, and a limit. To use it, you can justrun this:

		```bash
		curl \
Expand All		@@ -134,7 +134,7 @@ curl \
		If you've created a bunch of different to-do items, you should get only one search result back, and exactly the one you were expecting:

		```json
		"Make a New Year resolution list"
		"Make a New Year resolution"
		```

		You can increase the `limit` to something larger and you should get more documents, in decreasing order of relevance.
Expand Down