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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,300 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 filtering is a problem. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,301 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 cannot do pre filtering or post filtering. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,302 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,303 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,304 |
[
"Retriever-Ranker Architecture - Qdrant",
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[
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"tags",
"tags/retriever-ranker-architecture"
] | 12,306 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,307 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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"tags",
"tags/retriever-ranker-architecture"
] | 12,308 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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"tags",
"tags/retriever-ranker-architecture"
] | 12,309 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 now that I said all of that, we had three candidates that we tested and we benchmarked them. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,310 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | We had elasticsearch PG vector, that is an extension of PostgreSQL and Qdrants. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,311 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,312 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,313 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 | Nicolas Mauti: | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,314 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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[
"Retriever-Ranker Architecture - Qdrant",
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] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,316 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 for each queries you have your grown truth of the closest vectors. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,317 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,318 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,319 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,320 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,321 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | And at the end we found a better trade off, and we found a trade off between performance and precision in Qdrants that were better for us than what we can found on elasticsearch. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,322 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | So we have, I think all know we have our model and we have our tool to operate them, to operate our model. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,325 |
[
"Retriever-Ranker Architecture - Qdrant",
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] | /tags/retriever-ranker-architecture/ | 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 a final part of this presentation will be about the deployment. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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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/retriever-ranker-architecture"
] | 12,327 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,328 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,329 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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"tags",
"tags/retriever-ranker-architecture"
] | 12,330 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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] | /tags/retriever-ranker-architecture/ | 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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[
"Retriever-Ranker Architecture - Qdrant",
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] | p | So it’s what we call shards. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,333 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,334 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,335 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 this way you have a copy on another node. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,336 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,337 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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"tags",
"tags/retriever-ranker-architecture"
] | 12,338 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,339 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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"tags",
"tags/retriever-ranker-architecture"
] | 12,341 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,342 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,343 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 | In fact we subcharted it because we needed some additional components in your clusters and some custom configuration. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,344 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | So I didn’t talk about this, but M chart are just a bunch of file of Yaml files that will describe the Kubernetes object you will need in your cluster to operate your databases in your case, and it’s collection of file and templates to do that. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - 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/retriever-ranker-architecture"
] | 12,346 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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"tags",
"tags/retriever-ranker-architecture"
] | 12,347 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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"tags",
"tags/retriever-ranker-architecture"
] | 12,348 |
[
"Retriever-Ranker Architecture - Qdrant",
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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[
"Retriever-Ranker Architecture - 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/retriever-ranker-architecture"
] | 12,351 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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",
"tags/retriever-ranker-architecture"
] | 12,352 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 | It’s about the outcome of the project, because we did that at malt. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,354 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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",
"tags/retriever-ranker-architecture"
] | 12,355 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,356 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,357 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 | As you can see, we started in a debate test in mid October. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,358 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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 | Nicolas Mauti: | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,359 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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"tags",
"tags/retriever-ranker-architecture"
] | 12,360 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | And so we were around 10 seconds and now we are around 1 second and alpha. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,362 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,363 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,364 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | And after that we have a fixed number of freelancers that go into the matching part. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,365 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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/retriever-ranker-architecture"
] | 12,366 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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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"tags",
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(41) | [
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[
"Retriever-Ranker Architecture - Qdrant",
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] | p | And the other good news is that now that we are able to scale and we have a fixed size, after our first parts, we are able to build more complex and better matching model and we will be able to improve the quality of our matching because now we are able to scale and to be able to handle more freelancers. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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"tags",
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(42) | [
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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[
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(43) | [
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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] | p | And so that’s all. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,375 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(43) | [
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] | p | And so maybe you have plenty of question and maybe we can go with that. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,376 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(44) | [
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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] | p | All right, first off, I want to give a shout out in case there are freelancers that are watching this or looking at this, now is a great time to just join Malt, I think. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,378 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(44) | [
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(44) | [
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"tags/retriever-ranker-architecture"
] | 12,380 |
[
"Retriever-Ranker Architecture - Qdrant",
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] | p | What’s happening, Luis? | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,381 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(44) | [
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] | p | He’s asking what library or service were you using for Ann before considering Qdrant, in fact. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,382 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(45) | [
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] | p | Nicolas Mauti: | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,383 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(45) | [
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] | p | So before that we didn’t add any library or service or we were not doing any inn search or semantic search in the way we are doing it right now. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,384 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(45) | [
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] | p | We just had one model when we passed the freelancers and the project at the same time in the model, and we got relevancy scoring at the end. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,385 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(45) | [
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] | p | And so that’s why it was also so slow because you had to constrict each pair and send each pair to your model. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,386 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(45) | [
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] | p | And so right now we don’t have to do that and so it’s much better. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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] | p | Yeah, that makes sense. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,389 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(46) | [
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] | p | One question from my side is it took you, I think you said in October you started with the A B test and then in December you rolled it out. | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,390 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | What was that last slide that you had? | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,391 |
[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(47) | [
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"tags",
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(47) | [
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] | p | Yeah, that’s exactly that. | [
"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
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"tags",
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(48) | [
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"tags",
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(48) | [
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[
"Retriever-Ranker Architecture - Qdrant",
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
] | /tags/retriever-ranker-architecture/ | 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(48) | [
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"tags",
"tags/retriever-ranker-architecture"
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[
"Retriever-Ranker Architecture - Qdrant",
"Transcript:"
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] | p | Nicolas Mauti: | [
"tags",
"tags/retriever-ranker-architecture"
] | 12,399 |
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