garvitg
garvitg
PostsComments
CDCloudflare Developers
Created by thousandmiles on 11/5/2024 in #vectorize
I've been browsing through messages in
Hi @thousandmiles. Thanks for reaching out! You can refer to our documentation on building a RAG pipeline using the Cloudflare development platform: https://developers.cloudflare.com/reference-architecture/diagrams/ai/ai-rag/. This tutorial should also be useful: https://developers.cloudflare.com/workers-ai/tutorials/build-a-retrieval-augmented-generation-ai/.
which I do need at a certain point because the product I am building requires global coverage.
Cloudlfare edge infrastructure seems like a great fit for your requirement. I was hoping to understand any other specific concerns or requirements that you may have around building a RAG pipeline with Workers AI and Vectorize on Cloudflare's edge network.
1 replies
CDCloudflare Developers
Created by Talljoe on 10/28/2024 in #vectorize
cloudflare
We are working with the responsible team to get the V2 changes in the TS package. It may not happen by tomorrow, but we will keep you posted.
6 replies
CDCloudflare Developers
Created by Talljoe on 10/28/2024 in #vectorize
cloudflare
Hi @Talljoe. The get-vectors and info operations were never operational for Vectorize V1 indexes and that's why the deprecated-v1 flag does not work for these Wrangler commands. Due to limitations such as this, we would recommend that you use Vectorize V2 for any new indexes that you create. You can refer to https://developers.cloudflare.com/vectorize/reference/transition-vectorize-legacy/ for more details about the transition considerations. If you absolutely need to use the get-vectors operation for a V1 index, you can use the REST endpoint: https://developers.cloudflare.com/api/operations/vectorize-(-deprecated)-get-vectors-by-id. The info operation is a V2-only operation, but the get-index Wrangler command (https://developers.cloudflare.com/workers/wrangler/commands/#get) or REST endpoint (https://developers.cloudflare.com/api/operations/vectorize-(-deprecated)-get-vectorize-index) could potentially be useful.
6 replies
CDCloudflare Developers
Created by ac on 11/1/2024 in #vectorize
I am noticing a large number of `AiError
Hi @ac. Thanks for reaching out! The error code does not look like a Vectorize error. Our friends over at #workers-ai would be able to help you better on this.
3 replies
CDCloudflare Developers
Created by yanlinw on 10/28/2024 in #vectorize
Given the limitations of the meta-
Since metadata indexing only works for primitive types right now, you wouldn't be able to create one for an object type.
6 replies
CDCloudflare Developers
Created by Rahul gangotri on 10/29/2024 in #vectorize
Quick question
We are actively working on providing a dynamic binding ability like the one you have described to reference and interact with multiple indexes!
6 replies
CDCloudflare Developers
Created by Rahul gangotri on 10/29/2024 in #vectorize
Quick question
Thank you for the additional details! As of now, a single Vectorize index cannot exceed the 5 million vectors limit. If your requirements exceed that scale, then creating multiple indexes is the way to go for now. We understand that it may not be the convenient to operate with multiple indexes, and we are working on streamlining the experience of using multiple indexes. Your feedback would be valuable for the way we implement this solution.
also i need to filter on metadata without creating indexes if that's possible for my account?
Unfortunately, this is not supported as a platform capability right now. But we can prioritize this effort and make it available for customers as soon as possible.
6 replies
CDCloudflare Developers
Created by Rahul gangotri on 10/29/2024 in #vectorize
Quick question
Hey @Rahul gangotri. Thanks for reaching out, and for sharing this feedback.
1. Why do we need to create metadata index and even if we have to create, why only 1 key at a time and upto 10 index is the limit? While upstash allows to filter on metadata normally on all metadata
As of now, Vectorize requires users to explicitly define metadata indexes for them to be used to filter query results. If you have a use case where you would need metadata filtering without explicitly created metadata indexes, we would be happy to keep your feedback under consideration! Any details that you can share around your expectations around metadata index creation or filtering (on this channel or over DM), would enable us to address your concerns better. The limit of 10 metadata indexes is a generic platform limit, and we can enhance it if they are insufficient for your use case.
2. Can we also expect glob and more type of searches operators along with eq and neq
We are actively working on enhancing the metadata filtering capabilities in Vectorize, and you can expect the support for some of these to land in the near future!
3. can we also have hybrid search like a cosine similarity search with Full text search as well for better search in future?
Hybrid search capabilities are not on the immediate roadmap, but we would be happy to record your feedback! Any details that you can share around your requirements would help us design and prioritize a solution that could best match your needs.
6 replies
CDCloudflare Developers
Created by yanlinw on 10/28/2024 in #vectorize
Given the limitations of the meta-
A metadata index on a nested field can be created using a command like: npx wrangler vectorize create-metadata-index <your-index> --property-name=pandas.nice --type=<prop-type>. Please note that filtering on the pandas.nice field would only work for the vectors that were inserted after you run this command to create the metadata index. To filter query results using a nested property, you can use a command like: npx wrangler vectorize query <your-index> --vector <input-vector> --filter '{"pandas.nice": "<your-value>"}'
However, the API documentation suggests that setting returnMetadata: "all" allows filtering without an index.
This is not accurate, and we apologize if the documentation made it confusing. The returnMetadata field is an optional parameter passed during the query operation to inform Vectorize if you'd like to receive the metadata fields as part of the query response. Passing returnMetadata=all would ensure that all of the metadata fields for a vector would be included in the query response in addition to the matching vector ids and scores. With returnMetadata=indexed, you would only receive the metadata fields that were indexed by Vectorize, and with returnMetadata=none, you would only receive the query results and scores without the presence of any metadata fields.
6 replies
CDCloudflare Developers
Created by freddw on 10/26/2024 in #vectorize
Is best practice for supporting more
Hi @freddw. Thanks for sharing the details of your use case and your feedback! We are actively working on enhancing the metadata filtering capabilities in Vectorize. Stay tuned for updates in the coming months! Thank you for sharing your suggestion on a more streamlined integration of D1 and Vectorize. We are happy to take your feedback under consideration. Please feel free to share more details of how you would envision this integration if you have any additional thoughts that you'd like us to consider!
1 replies
CDCloudflare Developers
Created by yanlinw on 10/28/2024 in #vectorize
Given the limitations of the meta-
Hi @yanlinw. Thanks for reaching out! Vectorize currently supports nested JSON objects of depth 1 (similar to { "pandas": { "nice": 42 } }). The error code 40019 typically shows up when a metadata object of depth greater than 1 is passed to Vectorize. If you are attempting to add a metadata field of depth 1 and are still encountering this error, we would be happy to help you debug this issue. Please feel to share (or DM it to me) the metadata field that you are attempting to add to a vector.
6 replies
CDCloudflare Developers
Created by Talljoe on 10/28/2024 in #vectorize
cloudflare
Hi @Talljoe. Thanks for reaching out and sharing your feedback! We are working on enabling Vectorize V2 operations on the Typescript API. It currently supports Vectorize V1 operations: https://github.com/cloudflare/cloudflare-typescript/blob/HEAD/api.md#vectorize.
I'm running into a problem where Wrangler doesn't support the --deprecated-v1 flag on certain calls.
Could you please share some additional details about the failures you are observing? We can look into any potential issues with this flag, and we can provide you with guidance or workarounds for your use case.
6 replies
CDCloudflare Developers
Created by steyblind on 8/15/2024 in #vectorize
Question about metadata indexing
As of now, metadata filtering can only be applied for vectors that are inserted after metadata indexes have been created. That's why we would recommend creating metadata indexes right after index creation, and before any vectors are inserted.
5 replies