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[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Question Answering on biomedical data" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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[ "articles", "articles/qa-with-cohere-and-qdrant" ]
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[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Question Answering on biomedical data" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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Our system is going to be fed with the embeddings generated by
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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p
co.embed API and we’ll load them to Qdrant.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,675
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Question Answering on biomedical data" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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p
Using Qdrant Cloud vs your own instance does not matter much here.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,676
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Question Answering on biomedical data" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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p
There is a subtle difference in how to connect to the cloud instance, but all the other operations are executed
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,677
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Question Answering on biomedical data" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(12)
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p
in the same way.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,678
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(2)
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h3
Using Cohere and Qdrant to build the answers database
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,679
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
In order to start generating the embeddings, you need to create a Cohere account.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,680
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
That will start your trial period, so you’ll be able to vectorize the texts for free.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,681
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
Once logged in, your default API key will
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,682
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
be available in Settings.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,683
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(13)
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p
We’ll need it to call the co.embed API. with the official python package.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,684
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(14)
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p
Let’s connect to the Qdrant instance first and create a collection with the proper configuration, so we can put some embeddings into it later on.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,685
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
Now we’re able to vectorize all the answers.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,686
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
They are going to form our collection, so we can also put them already into Qdrant, along with the
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,687
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
payloads and identifiers.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,688
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(15)
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p
That will make our dataset easily searchable.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,689
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
And that’s it.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,690
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
Without even setting up a single server on our own, we created a system that might be easily asked a question.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,691
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
I don’t want to call
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,692
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Using Cohere and Qdrant to build the answers database" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(16)
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p
it serverless, as this term is already taken, but co.embed API with Qdrant Cloud makes everything way easier to maintain.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,693
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(3)
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h3
Answering the questions with semantic search — the quality
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,694
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
It’s high time to query our database with some questions.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,695
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
It might be interesting to somehow measure the quality of the system in general.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,696
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
In those kinds of problems we typically use top-k accuracy.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,697
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
We assume the prediction of the system was correct if the correct answer
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,698
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(17)
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p
was present in the first k results.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,699
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(18)
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p
Saved answer positions allow us to calculate the metric for different k values.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,700
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(19)
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p
Here are the values of the top-k accuracy for different values of k:
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,701
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20)
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p
It seems like our system worked pretty well even if we consider just the first result, with the lowest distance.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,702
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20)
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p
We failed with around 12% of questions.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,703
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20)
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p
But numbers become better with the higher values of k.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,704
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20)
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p
It might be also
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,705
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(20)
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p
valuable to check out what questions our system failed to answer, their perfect match and our guesses.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,706
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
We managed to implement a working Question Answering system within just a few lines of code.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,707
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
If you are fine
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,708
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
with the results achieved, then you can start using it right away.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,709
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
Still, if you feel you need a slight improvement,
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,710
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
then fine-tuning the model is a way to go.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,711
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
If you want to check out the full source code,
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,712
[ "Question Answering as a Service with Cohere and Qdrant - Qdrant", "Answering the questions with semantic search — the quality" ]
/articles/qa-with-cohere-and-qdrant/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(21)
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p
it is available on Google Colab.
[ "articles", "articles/qa-with-cohere-and-qdrant" ]
3,713
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
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3,715
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul > li:nth-of-type(3)
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3,716
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > ul > li:nth-of-type(2)
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li
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[ "articles", "articles/qdrant-1.2.x" ]
3,717
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
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li
Introducing Qdrant 1.2.x
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3,718
[ "Introducing Qdrant 1.2.x - Qdrant" ]
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h1
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h1
Introducing Qdrant 1.2.x
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3,719
[ "Introducing Qdrant 1.2.x - Qdrant", "Introducing Qdrant 1.2.x" ]
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
A brand-new Qdrant 1.2 release comes packed with a plethora of new features, some of which
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3,720
[ "Introducing Qdrant 1.2.x - Qdrant", "Introducing Qdrant 1.2.x" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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were highly requested by our users.
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3,721
[ "Introducing Qdrant 1.2.x - Qdrant", "Introducing Qdrant 1.2.x" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
If you want to shape the development of the Qdrant vector
[ "articles", "articles/qdrant-1.2.x" ]
3,722
[ "Introducing Qdrant 1.2.x - Qdrant", "Introducing Qdrant 1.2.x" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
database, please join our Discord community and let us know
[ "articles", "articles/qdrant-1.2.x" ]
3,723
[ "Introducing Qdrant 1.2.x - Qdrant", "Introducing Qdrant 1.2.x" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(1)
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p
how you use it!
[ "articles", "articles/qdrant-1.2.x" ]
3,724
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h2:nth-of-type(1)
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h2
New features
[ "articles", "articles/qdrant-1.2.x" ]
3,725
[ "Introducing Qdrant 1.2.x - Qdrant", "New features" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(2)
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p
As usual, a minor version update of Qdrant brings some interesting new features.
[ "articles", "articles/qdrant-1.2.x" ]
3,726
[ "Introducing Qdrant 1.2.x - Qdrant", "New features" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(2)
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p
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[ "articles", "articles/qdrant-1.2.x" ]
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[ "Introducing Qdrant 1.2.x - Qdrant", "New features" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(2)
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p
feedback, and we tried to include the features most requested by our community.
[ "articles", "articles/qdrant-1.2.x" ]
3,728
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(1)
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h3
Product Quantization
[ "articles", "articles/qdrant-1.2.x" ]
3,729
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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The primary focus of Qdrant was always performance.
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3,730
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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That’s why we built it in Rust, but we were
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3,731
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
always concerned about making vector search affordable.
[ "articles", "articles/qdrant-1.2.x" ]
3,732
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
From the very beginning, Qdrant offered
[ "articles", "articles/qdrant-1.2.x" ]
3,733
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
support for disk-stored collections, as storage space is way cheaper than memory.
[ "articles", "articles/qdrant-1.2.x" ]
3,734
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
That’s also
[ "articles", "articles/qdrant-1.2.x" ]
3,735
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
why we have introduced the Scalar Quantization mechanism recently,
[ "articles", "articles/qdrant-1.2.x" ]
3,736
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(3)
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p
which makes it possible to reduce the memory requirements by up to four times.
[ "articles", "articles/qdrant-1.2.x" ]
3,737
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
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p
Today, we are bringing a new quantization mechanism to life.
[ "articles", "articles/qdrant-1.2.x" ]
3,738
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
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p
A separate article on Product
[ "articles", "articles/qdrant-1.2.x" ]
3,739
[ "Introducing Qdrant 1.2.x - Qdrant", "Product Quantization" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
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Quantization will describe that feature in more
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3,740
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
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3,741
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/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(4)
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p
In a nutshell, you can reduce the memory requirements by up to 64 times!
[ "articles", "articles/qdrant-1.2.x" ]
3,742
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(2)
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h3
Optional named vectors
[ "articles", "articles/qdrant-1.2.x" ]
3,743
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
Qdrant has been supporting multiple named vectors per point for quite a long time.
[ "articles", "articles/qdrant-1.2.x" ]
3,744
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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Those may have
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
Having multiple
[ "articles", "articles/qdrant-1.2.x" ]
3,747
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
embeddings per item is an essential real-world scenario.
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html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
For example, you might be encoding textual
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3,749
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/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
and visual data using different models.
[ "articles", "articles/qdrant-1.2.x" ]
3,750
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
Or you might be experimenting with different models but
[ "articles", "articles/qdrant-1.2.x" ]
3,751
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(5)
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p
don’t want to make your payloads redundant by keeping them in separate collections.
[ "articles", "articles/qdrant-1.2.x" ]
3,752
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
However, up to the previous version, we requested that you provide all the vectors for each point.
[ "articles", "articles/qdrant-1.2.x" ]
3,753
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
There
[ "articles", "articles/qdrant-1.2.x" ]
3,754
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
have been many requests to allow nullable vectors, as sometimes you cannot generate an embedding or
[ "articles", "articles/qdrant-1.2.x" ]
3,755
[ "Introducing Qdrant 1.2.x - Qdrant", "Optional named vectors" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(7)
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p
simply don’t want to for reasons we don’t need to know.
[ "articles", "articles/qdrant-1.2.x" ]
3,756
[ "Introducing Qdrant 1.2.x - Qdrant" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > h3:nth-of-type(3)
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h3
Grouping requests
[ "articles", "articles/qdrant-1.2.x" ]
3,757
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
Having a summary of a book may sound attractive, but in reality, we
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3,760
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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divide it into paragraphs or some different parts to have higher granularity.
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3,761
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
That pays off when we
[ "articles", "articles/qdrant-1.2.x" ]
3,762
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
perform the semantic search, as we can return the relevant pieces only.
[ "articles", "articles/qdrant-1.2.x" ]
3,763
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
That’s also how modern tools
[ "articles", "articles/qdrant-1.2.x" ]
3,764
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
like Langchain process the data.
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3,765
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
The typical way is to encode some smaller parts of the document and
[ "articles", "articles/qdrant-1.2.x" ]
3,766
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(8)
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p
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[ "articles", "articles/qdrant-1.2.x" ]
3,767
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
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p
There are cases where we want to find relevant parts, but only up to a specific number of results
[ "articles", "articles/qdrant-1.2.x" ]
3,768
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
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p
per document (for example, only a single one).
[ "articles", "articles/qdrant-1.2.x" ]
3,769
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
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p
Up till now, we had to implement such a mechanism
[ "articles", "articles/qdrant-1.2.x" ]
3,770
[ "Introducing Qdrant 1.2.x - Qdrant", "Grouping requests" ]
/articles/qdrant-1.2.x/
html > body > div:nth-of-type(1) > div:nth-of-type(1) > div > section > article > p:nth-of-type(10)
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p
on the client side and send several calls to the Qdrant engine.
[ "articles", "articles/qdrant-1.2.x" ]
3,771