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Docs: Feedback for Vector Collection #1235
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Jet bindings for vector collection are documented under Jet:
See the original PR: #1125 There are no links from data structure description, but we do not have such links to Jet docs also for IMap or other data structure. |
This feels more like a tutorial. Basic search invocation from pipeline is shown in https://docs.hazelcast.com/hazelcast/6.0-snapshot/integrate/vector-collection-connector#searching-in-vector-collection
I do not know of any easy way to send input from HZ client directly to a Jet pipeline. At least that is a situation if you think about streaming pipeline. For batch pipeline this can be organized differently, but you would have to submit the job many times (eg. once for each query) which is doable but IMO inconvenient and inefficient.
We had examples of embedding creation in Jet pipelines as part of demos. I did not check yet if they ended in published tutorials. |
Then we should add cross-references, and the restructuring I suggested in
Slack. There are use cases for both methods of ingestion and that should be
discussed under the data structure itself. The way its set up now, you
don't even know using Jet is an option... Except for in the tutorial.
…On Fri, Aug 2, 2024, 7:11 AM Krzysztof Jamróz ***@***.***> wrote:
Jet bindings for vector collection are documented under Jet:
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https://docs.hazelcast.com/hazelcast/6.0-snapshot/integrate/vector-collection-connector
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https://docs.hazelcast.com/hazelcast/6.0-snapshot/integrate/legacy-file-connector#fvecs-and-ivecs
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https://docs.hazelcast.com/hazelcast/6.0-snapshot/integrate/file-connector#fvecs-and-ivecs
See the original PR: #1125
<#1125>
There are no links from data structure description, but we do not have
such links to Jet docs also for IMap or other data structure.
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I agree that currently discovering that you can use vector collections in Jet is not easy |
Hi, I have some feedback about this page
Using a vector collection within a pipeline is not included in the documentation. We need to add the following examples:
Using a pipeline to create/update a VectorCollection. This is in the vector search tutorial, but we also need an example of it on this page as well.
Using a pipeline for the similarity search. In this example, the client can be any HZ client. The search string is ingested into the pipeline, which does the embedding, the subsequent similarity search, any LLM interactions, and returns the results to the client. This opens up vector search to any HZ client - all the ML/AI work is done within the cluster.
Happy to do the editing/review once the code is in place...
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