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Type: Bug
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Resolution: Unresolved
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Priority: Major - P3
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None
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Affects Version/s: None
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Component/s: None
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Query Integration
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ALL
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Hide
In order to reproduce this you need a mongoDB collection with vectors and vector search index. In this case I am referring to a collection where the embeddings are computed using https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2.
You should be able to reproduce it even with a "fake" vector search collection.
This is the pipeline I used:
[
{ queryVector: [ 0.36474791169166565, 0.2787139117717743, 0.037420038133859634, -0.11489459872245789, 0.011614377610385418, 0.07989057898521423, 0.3743008077144623, 0.3031100928783417, -0.053919192403554916, -0.22758670151233673, 0.35668912529945374, 0.19494308531284332, 0.23027025163173676, -0.13939541578292847, -0.07496068626642227, 0.24313263595104218, 0.09207076579332352, 0.13547749817371368, 0.14529556035995483, -0.4175901710987091, 0.09342092275619507, -0.06883081793785095, -0.015943696722388268, -0.22336186468601227, -0.36722221970558167, 0.16170752048492432, -0.17376397550106049, 0.2820833921432495, -0.21961534023284912, -0.29807227849960327, -0.22774584591388702, -0.046463266015052795, 0.38292327523231506, 0.6705532073974609, -0.0011250475654378533, -0.4374222457408905, 0.0059357210993766785, -0.2868773639202118, 0.33803629875183105, -0.4322603940963745, -0.30203333497047424, -0.3678397834300995, -0.12692205607891083, 0.11778966337442398, 0.6134411096572876, 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{
$vectorSearch:},
{ $meta: "vectorSearchScore" }
{
$addFields: {
score:}
{ $gt: 0.7 }
},
{
$match: {
score:}
}
]Attaching also a screenshot from compass showing the computed view.
ShowIn order to reproduce this you need a mongoDB collection with vectors and vector search index. In this case I am referring to a collection where the embeddings are computed using https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2. You should be able to reproduce it even with a "fake" vector search collection. This is the pipeline I used: [ { $vectorSearch: { queryVector: [ 0.36474791169166565, 0.2787139117717743, 0.037420038133859634, -0.11489459872245789, 0.011614377610385418, 0.07989057898521423, 0.3743008077144623, 0.3031100928783417, -0.053919192403554916, -0.22758670151233673, 0.35668912529945374, 0.19494308531284332, 0.23027025163173676, -0.13939541578292847, -0.07496068626642227, 0.24313263595104218, 0.09207076579332352, 0.13547749817371368, 0.14529556035995483, -0.4175901710987091, 0.09342092275619507, -0.06883081793785095, -0.015943696722388268, -0.22336186468601227, -0.36722221970558167, 0.16170752048492432, -0.17376397550106049, 0.2820833921432495, -0.21961534023284912, -0.29807227849960327, -0.22774584591388702, -0.046463266015052795, 0.38292327523231506, 0.6705532073974609, -0.0011250475654378533, -0.4374222457408905, 0.0059357210993766785, -0.2868773639202118, 0.33803629875183105, -0.4322603940963745, -0.30203333497047424, -0.3678397834300995, -0.12692205607891083, 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Hi team, in the Atlas doc page on $vectorSearch, in the limitations section we say:
$vectorSearch can’t be used in view definition and the following pipeline stages:$lookup sub-pipeline […]
but if I try to create a view using $vectorSearch in the view definition I am able to create the view.
Original Slack thread: https://mongodb.slack.com/archives/C061L7P3FK4/p1708334467026529