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Hi, are there plan to increase the topk

Hi, are there plan to increase the topk limit of 20 with metadata filtering? With chunked data a limit of 20 is severely limiting, especially for paginated search experiences.

can the vectorize http api docs be

can the vectorize http api docs be updated? I basically had to try random things then give up and searched in this channel before i saw somebody with the correct format

Are there any plans to increase the

Are there any plans to increase the current dimension limit? OpenAI’s latest embedding model is over 3000, and while it’s possible to lower it, if you want more accuracy then it simply won’t be possible to use Vectorize

Cf vector queue

Hi @EndiM, is there a thread on dev community or detailed query you posted earlier? Can you share the link please?

I attempted to record a video on how to

I attempted to record a video on how to use Vectorize but I failed at the following: - figuring out binding VECTORIZE The documentation needs work in these areas....

Can we also expect

Can we also expect 1. Metadata filters without creating indexes for each 2. Create dynamic vector indexes programatically without the manual bindings...

hi, I am evaluating Vectorize as the

hi, I am evaluating Vectorize as the data store for an AI RAG application I am building for work. I noticed the metadata filtering does not implement $gte and $lte matching. Are those operators on the roadmap?

is it possible to load stuff into a prod

is it possible to load stuff into a prod vectorize index from the local machine? or is the data running in the miniflare / simulator only?

Hi @garvitg , I got question regarding

Hi @garvitg , I got question regarding the workers ai and vectorize, I have an app running Resnet50 to vectorize image, I'm planning to switch over to cloudflare since you guys support Resnet50, however, I saw the limitiations of the Vectorize it says it has maximum dimensions per vector 1536 dimensions, which is not high enough for my app since it generate 2048 dimensions using Resnet50, any idea how can I reduce the dimensions that is generated from Resnet50? I'm really new to this field, so any help would be awesome, thanks!...

Hello, Quick question, I get really slow

Hello, Quick question, I get really slow response times in Vectorise. Like seconds of response time. My code is very simple, so nothing else should be slowing it down. I am in Greece btw, so not sure if that plays a role. I get the same speeds when deploying the worker. ```typescript }), async (c) => {...

Are there any tips and tricks to improve

Are there any tips and tricks to improve query performance against Vectorize? We make use of (per-project) namespaces for limiting the scope of similarity searches, and are seeing very slow performance on initial query against a namespace, and subsequent queries are much faster. One example has roughly 100 vectors and is taking ~3s for first query vs ~150ms for subsequent queries. Are cold-starts a thing with Vectorize?...

How can I see what vectors I have in my

How can I see what vectors I have in my index? I checked the commands I could run, and none mentioned showing the vectors I got in my index. I want to be able to delete and test stuff before I run the actual thing. Any guidance would be appreciated.

Is supporting arrays with metadata

Is supporting arrays with metadata filtering on the roadmap? I'm migrating a v1 index to v2, and looking at adding a metadata index while I'm at it, but my metadata has string array properties. According to the docs this isn't possible now, but will it be in the near future? If not, I'll need to rethink how my metadata is stored before the migration.

Hi, is Cloudflare Vectorize now support

Hi, is Cloudflare Vectorize now support $in metadata filter ?

I've been browsing through messages in

I've been browsing through messages in the past and documentations on vectorize, looks like now it's a great time to jump in, considering the beta release of workflow as well. though my concern is full RAG pipeline still needs a long way to go, so I'd prefer develop locally using llamaindex+chromadb(or equivalent)+litellm(embedding, inference, rerank, whisper, etc) first, before switching to cloudflare edge side completely, which I do need at a certain point because the product I am building requires global coverage. may I ask guy who already had previous experiences here, that, is this a viable plan, or anything I should keep in mind for choosing tech stack or develop or doing gitops? thanks a million!...

I am noticing a large number of `AiError

I am noticing a large number of AiError: 3001: Unknown internal error s when doing some Vectorize queries. Is there any way to get more insight into what these are? I have no clue if it's not finding a vector by ID, if I'm getting rate limited, or if it's something I can't control

api idea - It would be great to have

api idea - It would be great to have method for get/delete (all)vectors by namespace mainly delete use-case would be very helpful - in my case I have namespace for every "project" and I would like an easy way to clean-up.

Vector index issue

Nothing should have caused such issues, let me check with the team, it could be delayed as most of the team is in US time zone.

Is there a way to dynamically add

Is there a way to dynamically add Vectorize bindings programatically?