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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(29) | [
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] | p | So our first criteria were performances. | [
"tags",
"tags/semantic-search"
] | 12,600 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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[
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[
"Semantic Search - Qdrant",
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] | p | As I said before, we cannot do a KnN search, brute force search each time. | [
"tags",
"tags/semantic-search"
] | 12,604 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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] | p | And so we have to find a way to approximate but to be close enough and to be good enough on these points. | [
"tags",
"tags/semantic-search"
] | 12,605 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(30) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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] | p | You can just have a three step process and do filtering, semantic search and then ranking, or do semantic search, filtering and then ranking. | [
"tags",
"tags/semantic-search"
] | 12,611 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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"tags",
"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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] | p | And if you do that, you will have, in fact, to flag each freelancers before asking the vector database and performing a search, you will have to flag each freelancer whether there could be selected or not. | [
"tags",
"tags/semantic-search"
] | 12,616 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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"tags",
"tags/semantic-search"
] | 12,617 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(31) | [
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"tags",
"tags/semantic-search"
] | 12,618 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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] | p | Nicolas Mauti: | [
"tags",
"tags/semantic-search"
] | 12,619 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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"tags",
"tags/semantic-search"
] | 12,620 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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"tags",
"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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] | p | And also you will have another problem. | [
"tags",
"tags/semantic-search"
] | 12,622 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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] | p | A lot of vector database and Qdrants is one of them using hash NSW algorithm to do your inn search. | [
"tags",
"tags/semantic-search"
] | 12,623 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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] | p | And this kind of algorithm is based on graph. | [
"tags",
"tags/semantic-search"
] | 12,624 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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"tags",
"tags/semantic-search"
] | 12,625 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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"tags",
"tags/semantic-search"
] | 12,626 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(32) | [
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] | p | So it’s definitely not a good idea to apply prefiltering. | [
"tags",
"tags/semantic-search"
] | 12,627 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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[
"Semantic Search - Qdrant",
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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] | p | You will have this kind of architecture. | [
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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] | p | And so, in fact, if you do that, you will have to retrieve a lot of freelancer for your vector database. | [
"tags",
"tags/semantic-search"
] | 12,631 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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] | p | If you apply some very aggressive filtering and you exclude a lot of freelancer with your filtering, you will have to ask for a lot of freelancer in your vector database and so your performances will be impacted. | [
"tags",
"tags/semantic-search"
] | 12,632 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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"tags",
"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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"tags",
"tags/semantic-search"
] | 12,634 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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] | p | So we had to find a database that do filtering and matching and semantic matching and search at the same time. | [
"tags",
"tags/semantic-search"
] | 12,635 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(33) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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] | p | And this filter is the geospatial filtering and a few of databases under this filtering, and I think Qdrant is one of them that supports it. | [
"tags",
"tags/semantic-search"
] | 12,639 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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] | p | But there is not a lot of databases that support them. | [
"tags",
"tags/semantic-search"
] | 12,640 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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[
"Semantic Search - Qdrant",
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] | p | We had elasticsearch PG vector, that is an extension of PostgreSQL and Qdrants. | [
"tags",
"tags/semantic-search"
] | 12,643 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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] | p | And on this slide you can see Pycon for example, and Pycon was excluded because of the lack of geospatial filtering. | [
"tags",
"tags/semantic-search"
] | 12,644 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(34) | [
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] | p | And so we benchmark them regarding the qps. | [
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[
"Semantic Search - Qdrant",
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[
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[
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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] | p | So this one is for performance, and you can see that quadron was far from the others, and we also benchmark it regarding the precision, how we computed the precision, for the precision we used a corpus that it’s called textmax, and Textmax corpus provide 1 million vectors and 1000 queries. | [
"tags",
"tags/semantic-search"
] | 12,648 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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"tags",
"tags/semantic-search"
] | 12,649 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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] | p | They used brute force knn for that. | [
"tags",
"tags/semantic-search"
] | 12,650 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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] | p | And so we stored this vector in our databases, we run the query and we check how many vectors we found that were in the ground truth. | [
"tags",
"tags/semantic-search"
] | 12,651 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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] | p | And so they give you a measure of your precision of your inn algorithm. | [
"tags",
"tags/semantic-search"
] | 12,652 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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] | p | For this metric, you could see that elasticsearch was a little bit better than Qdrants, but in fact we were able to tune a little bit the parameter of the AsHNSW algorithm and indexes. | [
"tags",
"tags/semantic-search"
] | 12,653 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(35) | [
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"tags",
"tags/semantic-search"
] | 12,654 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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] | p | Nicolas Mauti: | [
"tags",
"tags/semantic-search"
] | 12,655 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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] | p | So at the end we decided to go with Qdrant. | [
"tags",
"tags/semantic-search"
] | 12,656 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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[
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] | p | I will talk about it a little bit because I think it’s interesting and it’s also part of my job as a development engineer. | [
"tags",
"tags/semantic-search"
] | 12,659 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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] | p | So regarding the deployment, first we decided to deploy a Qdrant in a cluster configuration. | [
"tags",
"tags/semantic-search"
] | 12,660 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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] | p | We decided to start with three nodes and so we decided to get our collection. | [
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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"tags",
"tags/semantic-search"
] | 12,662 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(36) | [
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] | p | And so we decided to split our collection between three nodes. | [
"tags",
"tags/semantic-search"
] | 12,663 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | Nicolas Mauti: | [
"tags",
"tags/semantic-search"
] | 12,664 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | So it’s what we call shards. | [
"tags",
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | So you have a shard of a collection on each node, and then for each shard you have one replica. | [
"tags",
"tags/semantic-search"
] | 12,666 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | So the replica is basically a copy of a shard that is living on another node than the primary shard. | [
"tags",
"tags/semantic-search"
] | 12,667 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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"tags",
"tags/semantic-search"
] | 12,668 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | And so this way if we operate normal conditions, your query will be split across your three nodes, and so you will have your response accordingly. | [
"tags",
"tags/semantic-search"
] | 12,669 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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"tags",
"tags/semantic-search"
] | 12,670 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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] | p | And so this configuration is very robust and so we are very happy with it. | [
"tags",
"tags/semantic-search"
] | 12,671 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(37) | [
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"tags",
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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] | p | Nicolas Mauti: | [
"tags",
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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] | p | So as I said, we deployed it in kubernetes. | [
"tags",
"tags/semantic-search"
] | 12,674 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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] | p | So we use the Qdrant M chart, the official M chart provided by Qdrants. | [
"tags",
"tags/semantic-search"
] | 12,675 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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[
"Semantic Search - Qdrant",
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] | p | And when you have that at malt we are using what we called a GitHub’s approach. | [
"tags",
"tags/semantic-search"
] | 12,678 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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] | p | And so GitHub’s approach is basic idea that your git repository is your groom truth regarding what you must have in your Kubernetes clusters. | [
"tags",
"tags/semantic-search"
] | 12,679 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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] | p | And so we store these files and these M charts in git, and then we have a tool that is called Argo CD that will pull our git repository at some time and it will check the differences between what we have in git and what we have in our cluster and what is living in our cluster. | [
"tags",
"tags/semantic-search"
] | 12,680 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(38) | [
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[
"Semantic Search - Qdrant",
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] | p | So this is a very good approach to collaborate and to be sure that what we have in git is what you have in your cluster. | [
"tags",
"tags/semantic-search"
] | 12,683 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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"tags/semantic-search"
] | 12,684 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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] | p | And I think that’s pretty all I have one last slide, I think that will interest you. | [
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"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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] | p | We built this architecture with our first phase with Qdrants that do the semantic matching and that apply all the filtering we have. | [
"tags",
"tags/semantic-search"
] | 12,687 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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] | p | And in the second part we keep our all drunking system. | [
"tags",
"tags/semantic-search"
] | 12,688 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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] | p | And so if we look at the latency of our apps, at the P 50 latency of our apps, so it’s a wall app with the two steps and with the filters, the semantic matching and the ranking. | [
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[
"Semantic Search - Qdrant",
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] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(39) | [
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[
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] | p | Nicolas Mauti: | [
"tags",
"tags/semantic-search"
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | And so we already saw a huge drop in the application and we decided to go full in December and we can see another big drop. | [
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[
"Semantic Search - Qdrant",
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] | p | And so we were around 10 seconds and now we are around 1 second and alpha. | [
"tags",
"tags/semantic-search"
] | 12,694 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | So we divided the latency of more than five times. | [
"tags",
"tags/semantic-search"
] | 12,695 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | And so it’s a very good news for us because first it’s more scalable because the retriever is very scalable and with the cluster deployment of Qdrants, if we need, we can add more nodes and we will be able to scale this phase. | [
"tags",
"tags/semantic-search"
] | 12,696 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | And after that we have a fixed number of freelancers that go into the matching part. | [
"tags",
"tags/semantic-search"
] | 12,697 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | And so the matching part doesn’t have to scale. | [
"tags",
"tags/semantic-search"
] | 12,698 |
[
"Semantic Search - Qdrant",
"Transcript:"
] | /tags/semantic-search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(40) | [
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] | p | No. | [
"tags",
"tags/semantic-search"
] | 12,699 |
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