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docs: Use cosine similarity in quickstart example #219

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docs: Use cosine similarity in quickstart example #219

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6 changes: 3 additions & 3 deletions src/components/InteractiveTutorial/MdxPages/FilteringClauses.mdx
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Expand Up @@ -21,11 +21,11 @@ Before we start to practice with filtering conditions, let's create some datapoi
1. Create a collection:

``` json withRunButton="true"
PUT collections/demo
PUT /collections/demo
{
"vectors": {
"size": 4,
"distance": "Dot"
"size": 4,
"distance": "Cosine"
}
}
```
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14 changes: 7 additions & 7 deletions src/components/InteractiveTutorial/MdxPages/Quickstart.mdx
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Expand Up @@ -8,14 +8,14 @@ In this tutorial, you will create a collection, load data into it and run a basi

## Create a collection

First, create a collection to store vector data. Let’s name it `test_collection`. This collection will use the dot product distance metric to determine similarity between vectors. Added vectors will have 4 dimensions.
First, create a collection to store vector data. Let’s name it `test_collection`. This collection will use cosine similarity to determine the distance between vectors. Added vectors will have 4 dimensions.

```json withRunButton=true
PUT collections/test_collection
PUT /collections/test_collection
{
"vectors": {
"size": 4,
"distance": "Dot"
"distance": "Cosine"
}
}
```
Expand All @@ -25,7 +25,7 @@ PUT collections/test_collection
Now, you need to add a few vectors. For each vector, you will specify a JSON payload. A payload is metadata that describes each vector, such as `city`.

```json withRunButton=true
PUT collections/test_collection/points
PUT /collections/test_collection/points
{
"points": [
{
Expand Down Expand Up @@ -71,7 +71,7 @@ We need to ask a question in vector form:
`[0.2, 0.1, 0.9, 0.7]`

```json withRunButton=true
POST collections/test_collection/points/search
POST /collections/test_collection/points/search
{
"vector": [0.2, 0.1, 0.9, 0.7],
"limit": 3,
Expand All @@ -87,7 +87,7 @@ See [payload and vector in the result](https://qdrant.tech/documentation/concept
You can narrow down the results further by setting conditions on the payload. Let's filter the closest results that include the city of "London".

```json withRunButton=true
POST collections/test_collection/points/search
POST /collections/test_collection/points/search
{
"vector": [0.2, 0.1, 0.9, 0.7],
"filter": {
Expand All @@ -107,4 +107,4 @@ That’s it! You have just performed a vector search. You loaded vectors into a

## Next steps

In the next section, you will learn how to create complex filter conditions and how to use them in your queries.
In the next section, you will learn how to create complex filter conditions and how to use them in your queries.