Cloudflare Developers•12mo ago

Hey guys, checked but couldn't find. What is the best approach to update metadata? Should we use ups

Hey guys, checked but couldn't find. What is the best approach to update metadata? Should we use upsert for that?

Mmakrdev Hey guys, checked but couldn't find. What is the best approach to update metadat...

yevgen•1/13/25, 1:50 PM

correct.

Utkarsh Saxena•1/15/25, 12:25 PM

Hi, I am having issue in inserting vector with correct vector format, anyone else experiencing same issue, there is no error but it is returning null. Any idea

Paige•1/15/25, 5:21 PM

Hello, I'm wondering one thing before getting into cloudflare vectorize, it seems many vector databases charge based on how much data there is to scan through, but I don't find the documentation for vectorize clear, does "queried dimensions" refer to that same thing, or only to the actual dimensions of the vector you're searching by (please ping when responding

)

daguang•1/16/25, 1:56 AM

Vectorize If I filter using Metadata filter, will I be billed for the quantity before filtering or after filtering?

daguang•1/16/25, 1:56 AM

I went through all the documentation but couldn't find a corresponding description

Bob•1/17/25, 6:55 PM

Hello

Is there no UI option to create vector index? I am getting this screen. the UI comes for a split second and goes away

Bob•1/17/25, 6:58 PM

ok. I can create via cli. please ignore my question. :blob_sweat:

Bob•1/19/25, 1:08 PM

Hi. I found this in the vectorize docs. I have 2 questions -

How long do I need to wait before sending next 5000embeddings after 1st batch so that I don't get rate limited. I am trying to insert and later query via HTTP API.
The global limit says 1200req/5min which is too low. It means, on avg only 4 queries can be done on the vectorize index per second right? This limit seems too low or I am not understanding it properly. If I query the index via worker, does this limit not apply in that case?

Bob•1/19/25, 2:38 PM

thanks @Leo ya I also thought so at the end

Bob•1/19/25, 2:39 PM

I have to offload the vector insert/query part to a worker, because I want to write the main backend in go

BBob Hi. I found this in the vectorize docs. I have 2 questions - 1. How long do I n...

garvitg•1/20/25, 10:38 PM

Hi @Bob. Thank you for reaching out!

You can batch upto 5000 vectors in a single request to Vectorize if you would like to insert a large number of vectors quickly. And you will not be rate-limited as long as you stay within the limit of 1200 requests (each request can contain 5k vectors) per 5 minutes if you are using the HTTP API.
If you are concerned about the rate-limiting over HTTP API for Vectorize queries, and if you do not wish to use Vectorize bindings via Workers/Pages for your use case, could you please DM me and describe your requirements in greater detail. We will do our best to figure out a solution for you.

Noam•1/23/25, 12:49 AM

Hello,

I am thinking of using CF Vectorize databases but can't find the docs for max queries/requests per second per namespace/globally. Do you know where I can get this information?

We need to be able to handle at least 10,000 queries/second, and want to make sure that CF can support that.

Thanks!

tornado•1/23/25, 5:24 PM

Is it possible to create vectorize database dynamically? I want to create a platform where my customers get their own vectorize database, the 5 million vector limit might become a problem if I use one index with difference namespaces. Is there a way to create and get indexes dynamically similar to DOs.

Ttornado Is it possible to create vectorize database dynamically? I want to create a plat...

Ashley•1/23/25, 6:28 PM

You can use the REST API rather than a binding, as one option ( https://developers.cloudflare.com/api/resources/vectorize/subresources/indexes/methods/create/ )

Cloudflare API | Vectorize › Indexes › Create Vectorize Index

Interact with Cloudflare's products and services via the Cloudflare API

Jorgo•1/24/25, 2:54 PM

Hello anyone can help me with a vectorise problem VECTOR_QUERY_ERROR (code = 50111)
the weird thing is that with this payload below it works as expected
{
"search_prompt": "i saw that users wanted our company phone number, and couldnt find it.",
"function_type": "search",
"access_level": "internal",
"vector_search": true,
"filter": "kaizens",
"db_source": "vector"
}

but with this search prompt it throws the error
{
"search_prompt": "i saw .",
"function_type": "search",
"access_level": "internal",
"vector_search": true,
"filter": "kaizens",
"db_source": "vector"
}

i also need to mention this only happends on the kaizens filter and the weird behaviour does not have a pattern or something we can explain. for example it sometimes works with 3 words on the search_prompt and sometimes it doesn't.From what we can tell it is totally random and we have no clue why "heythere" works and "hey there" does not work. I would appreciate any feedback. Thanks!

crunchy•1/25/25, 9:08 PM

Hi, I'm hitting the Vectorise Upsert limit, appears to around 1000 requests per min. Does that sound about right? I couldn't find any documenation on it but was hopping to do considerably more. "Error: VECTOR_UPSERT_ERROR (code = 971): Please wait and consider throttling your request speed". If i was to request an increase, is there a upper bound for what can be supported?

crunchy•1/25/25, 11:45 PM

I'm also getting very high latency on 30s to get a response back from env.VECTORIZE.upsert(vectors); with a batch of 100 vectors of 768 size. I understood that this api was only queuing the work? and it's eventually consistent So why so high to call the add api?

Ccrunchy I'm also getting very high latency on 30s to get a response back from env.VECTOR...

crunchy•1/25/25, 11:59 PM

Ah I'm underestimating the JSON payload size of these vectors and the RPC overhead. I've if i limit the decimal places then I can get 20k rpm at batches of 100.

Rezigco•1/28/25, 1:14 PM

I've been reading and for my use case, I'm wondering if I'll need to combine both workers and the cloudflare api: I want each of my users to have their own index but I want the users of my users to be able to query my user's index and it could exceed the cloudflare api limit so I would like the queries/inserting to be done via cloudflare workers, but how can I dynamically pass in the name of the index

Utkarsh Saxena•1/30/25, 9:16 AM

Hi, I wanted to know about pricing of vectorization:
There are some confusing things in vectorization:

This is for a month:
Let's say I am making 10 queries of some documents where vector stored amount is: 10k and there are 100 those documents. and dimension is 376.
Then how will the queried vector dimension will be calculated:

if we calculate queried vector dimension of 10 queries for one document then: it will be: (10,000+ 10)376 = 3763760
Now for 100 documents it will be: 3763760100 = 376376000

but now it consider whole 100 documents queries at one level:
total queries will be: (100 ) (10) = 1000
Queries dimension for all 100 : (10,000+1000)*376 = 4136000

Which one is correct ?

garff•1/31/25, 2:59 PM

Hi, I have a worker deployed utilizing vectorize. It's deployed bound to a certain index but when I do my searches it also returns results from another index. Is this normal behaviour? Or what's up? Anyone had any troubles like that?

garff•1/31/25, 2:59 PM

Bindings in the settings looking under the dashboard says "Vectorize index
VECTORIZE
bge-large-en"

garff•1/31/25, 2:59 PM

And in swagger I get

garff•1/31/25, 2:59 PM

{
"success": true,
"embeddings": {
"count": 3,
"matches": [
{
"id": "15",
"score": 0.86592543,
"namespace": "findu-job-desc-test1",

garff•1/31/25, 3:00 PM

I feel certain that only the index you are currently utilizing should return results. Not other indexes. Or am I mistaken?

garff•1/31/25, 3:01 PM

And I'm trying to delete the index now - takes aaaages..

Mitya•1/31/25, 3:13 PM

Trying to get info on an index, as per the docs, via the following command:

npx wrangler vectorize info tmpdb

npx wrangler vectorize info tmpdb

But this gives:

Unknown arguments: info, tmpdb

crunchy•2/1/25, 10:36 PM

works for me

may be check your wrangler version and than the correct program is being triggered

crunchy•2/1/25, 10:38 PM

Is there any significance to the mutationIds? i.e. c0e522b1-3541-4aa8-a298-32c5c5fbf5b9. All i want to know is if there are in any kind of order. It's great seeing the latest one in status but which ones came inbetween? Similiar vector databases return a mutation number in a sequence]

RRafal is there anyone else running into `Error: VECTOR_QUERY_ERROR (code = 10000): Aut...

Bob•2/4/25, 4:21 PM

same for me too

RRafal is there anyone else running into `Error: VECTOR_QUERY_ERROR (code = 10000): Aut...

ggu•2/4/25, 4:41 PM

Hi Rafal, can you share your worker code with me so I can help debug it?

ggu•2/4/25, 4:41 PM

Also share the command you're using to launch it locally

RRafal Sure, here it is: https://gist.github.com/RafalWilinski/274d51bcd0b999eb161b00c3...

ggu•2/4/25, 4:59 PM

This code is running at the top-level, which seems strange to me. If you put the code within a fetch handler does the issue persist?

Thomas Ankcorn•2/4/25, 5:03 PM

Looks like something weird with getPlatformProxy. @Edmund Hung might know

Samko•2/4/25, 7:14 PM

I'm experiencing same issue with Error: VECTOR_GET_ERROR (code = 10000): Authentication errorError: VECTOR_GET_ERROR (code = 10000): Authentication error although it worked before. Already tried to upgrade to latest wrangler. I'm also getting:

✘ [ERROR] Error storing embeddings for undefined

  Error: VECTOR_UPSERT_ERROR (code = 999): vectorize.upstream_timeout
      at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:164:23)
      at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21)
      at async Object.queue
  (file:///Users/samko/Documents/Web/vecrio-api/workers/queue/src/index.ts:220:11) {
    [cause]: Error: vectorize.upstream_timeout
        at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:167:28)
        at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21)
        at async Object.queue

✘ [ERROR] Error storing embeddings for undefined

  Error: VECTOR_UPSERT_ERROR (code = 999): vectorize.upstream_timeout
      at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:164:23)
      at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21)
      at async Object.queue
  (file:///Users/samko/Documents/Web/vecrio-api/workers/queue/src/index.ts:220:11) {
    [cause]: Error: vectorize.upstream_timeout
        at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:167:28)
        at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21)
        at async Object.queue

Eric•2/6/25, 8:24 AM

https://developers.cloudflare.com/api/resources/vectorize/subresources/indexes/methods/list/ can anyone fix this link?

Eric•2/6/25, 8:25 AM

Perhaps this too? https://developers.cloudflare.com/api/resources/durable_objects/subresources/namespaces/methods/list/

Jerome•2/6/25, 9:20 AM

The service experienced an elevated rate of errors last 30 minutes, due to an R2 incident. It is now recovering and error rate is nominal. https://www.cloudflarestatus.com/incidents/pgz7g5xlpxzr

Cloudflare R2 Availability Issues

crunchy•2/6/25, 6:53 PM

Does vectorize have rate limits when called via workers? I'm unclear if the global limits only apply to the rest api? I'm luck getting those limits increased if i'm not an enterprise size customer. It's tricky to plan with the uncertainity

UUtkarsh Saxena Hi, I wanted to know about pricing of vectorization: There are some confusing th...

Utkarsh Saxena•2/7/25, 9:00 AM

Anyone knows about this?

dandoen•2/7/25, 11:43 AM

hi cloudflare team, are there any short term plans to support the multilingual BAAI/bge-m3 embedding model? the current BGE ones are english only. if it's not coming soon, i won't be able to use vectorize but if it's coming up then i can live with EN for now only!

Marco Aleixo•2/8/25, 9:35 PM

What is the roadmap for vectorize?
Do you plan to support multi dense vector like the ones from colpali?

RRafal is there anyone else running into `Error: VECTOR_QUERY_ERROR (code = 10000): Aut...

shoo•2/9/25, 5:30 PM

Facing the same issue - not sure what's causing it. query fails. Error: VECTOR_QUERY_ERROR (code = 10000): Authentication error

Bob•2/9/25, 7:27 PM

Hello, I have a question. It seems the indexing process takes few seconds. When we insert data, we get a mutation id. Is there any way to check against the mutation id if that batch got indexed or not?

beingmudit [WePlayDOS]•2/9/25, 8:42 PM

Damn! @Bob I joined this discord just to ask the same questions. Interesting that this is not just me experienceing indexing latency.

beingmudit [WePlayDOS]•2/9/25, 8:43 PM

Hey CF team!

We're building with Vectorize and noticed some interesting behavior around indexing latency and consistency. Here's what we're observing:

Indexing Latency:
Create index -> Success (immediate)
Add 2 vectors -> Success (immediate)
Search vectors -> No results for ~9 seconds
Search attempt timeline:
- 0s: No results
- 3s: No results
- 6s: No results
- 9s: Finally get results
Deletion Consistency:
After vectors are searchable
Delete vector "vec1" -> Success
Immediate search still returns both vectors including the deleted one
Subsequent searches also return the deleted vector

Test Case Details:

Index dimension: 32
Two simple test vectors:
- vec1: Array(32).fill(0.1)
- vec2: Array(32).fill(0.2)
Query vector: Array(32).fill(0.15)

Questions:

Is this expected latency for indexing?
Are there any best practices for handling the indexing delay?
Should deleted vectors remain searchable? If not, is there a known delay before deletions are reflected?
Are there any configuration options we should be using to optimize this?

Full test code available if needed. Thanks for any insights/help/

✘ [ERROR] Error storing embeddings for undefined Error: VECTOR_UPSERT_ERROR (code = 999): vectorize.upstream_timeout at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:164:23) at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21) at async Object.queue (file:///Users/samko/Documents/Web/vecrio-api/workers/queue/src/index.ts:220:11) { [cause]: Error: vectorize.upstream_timeout at VectorizeIndexImpl._send (cloudflare-internal:vectorize-api:167:28) at async VectorizeIndexImpl.upsert (cloudflare-internal:vectorize-api:117:21) at async Object.queue

Hey guys, checked but couldn't find. What is the best approach to update metadata? Should we use ups

Similar Threads

Similar Threads

Similar Threads