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feat: Add search template mutation #9802
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The tests only work once the embeddings are calculated, which does not happen on CI.
@@ -224,13 +258,29 @@ export const ActivityLibrary = (props: Props) => { | |||
onQueryChange, | |||
resetQuery | |||
} = useSearchFilter(templates, getTemplateDocumentValue) | |||
const [debouncedSearchQuery] = useDebounce(searchQuery, 500) |
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@tianrunhe I changed the debounced query logic. Because this is used for analytics, let me know if that's ok.
Hey @Dschoordsch, I'm getting a timeout error when using the semantic search: https://www.loom.com/share/11e27dce1ba747829b205b87f090a932 Is there any set-up required to test this one?
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LGTM metrics side
I tried to reproduce this, but had no success yet:
@nickoferrall Are you processing lots of data atm? Can you check your |
My Are these env vars the same as |
@Dschoordsch after our call, I removed everything from Docker, restarted my laptop, cleared the job queue and metadata a couple of times, but no luck, unfortunately. The embeddings service is still slow to respond so I get a timeout. We don't know whether it shouldn't be working for you, or it should be working for me, so perhaps someone else could test this PR so we can isolate the problem? Could @tianrunhe test it as you're here please? |
I encountered the same behavior as Nick. The |
Could one of you try deleting the
and the embedding data delete from "Embeddings_ember_1";
delete from "EmbeddingsMetadata";
delete from "EmbeddingsJobQueue"; and then try again? |
@nickoferrall ☝️ could you try one more time? I noticed that locally I have some issues with the embedding service not always rebuilding. |
I tried the step above, but no luck. I'm working on getting the text-embeddings-inference server install on bare metal here following this now |
I got the embedder up and running on my m1, but it’s still not working 😞 The job queue is empty as is the |
I will go ahead and merge the change. If it fails, it will just yield no results, which is safe. As embeddings work in production, I'm positive the search will work there. |
// all team ids which could have accessible templates | ||
const allTeamIds = ['aGhostTeam', ...allOrgTeams.map(({id}) => id)] | ||
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const response = await fetch('http://localhost:3040/embed', { |
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-1 this should be a env variable instead. I'm now using port 3041 for the text-embeddings-inference server because I'm running on my mac rather than Docker
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Also, no localhost
or port should be hardcoded into our code as each component can run in any port and location in other environments.
Description
Fixes #9774, #9775
Add a template search query to the User object.
Demo
https://www.loom.com/share/114efbf0a1864ba09816c0bf87a28620?sid=86867080-17c0-405a-bf6a-828a591bdfad
Testing scenarios
EmbeddingsJobQueue
is empty) and search for itFinal checklist