Vector datasets catalog and downloader (#7446)

## Summary

Tracking issue: #7297

We will want to add vector benchmarking soon (see
#7399 for a draft).

This adds a simple catalog for the vector datasets hosted by
`https://assets.zilliz.com/benchmark` for
[VectorDBBench](https://github.com/zilliztech/vectordbbench), which both
describes the shape of the datasets (are things partitioned, randomly
shuffled, are there neighbors lists for top k, etc).

Also handles downloading everything.

I had to verify that all of this stuff was correct by looking at the S3
buckets themselves:

```sh
aws s3 ls s3://assets.zilliz.com/benchmark/ --region us-west-2 --no-sign-request
```

<details>

```sh
for d in bioasq_large_10m bioasq_medium_1m cohere_large_10m cohere_medium_1m \
         cohere_small_100k gist_medium_1m gist_small_100k glove_medium_1m \
         glove_small_100k laion_large_100m  \
         openai_large_5m openai_medium_500k openai_small_50k \
         sift_large_50m sift_medium_5m sift_small_500k; do
  echo "=== $d ==="
  aws s3 ls s3://assets.zilliz.com/benchmark/$d/ --region us-west-2 --no-sign-request
done
```

</details>

And this script from the main repo helped too:
https://github.com/zilliztech/VectorDBBench/blob/main/vectordb_bench/backend/dataset.py

---

Things that are not implemented that I would like to add:

- Is the dataset pre-normalized for cosine similarity? This is not so
obvious to me without actually working with the datasets, so I will do
this later.
- Some datasets have scalar labels for all vectors that help mimic
similarity + filter by some other column. Some of them also have
neighbor lists for these specific filtered queries. So that is something
we'll probably want to add in the future.

## Testing

N/A

Signed-off-by: Connor Tsui <connor.tsui20@gmail.com>

Author: connortsui20

vortex-bench/src/lib.rs

@@ -53,6 +53,7 @@ pub mod statpopgen;
 pub mod tpcds;
 pub mod tpch;
 pub mod utils;
+pub mod vector_dataset;
 
 pub use benchmark::Benchmark;
 pub use benchmark::TableSpec;