Is ColBERT model provide the right result for query and document vector embedding and rerank?

Nobody has claimed this yet.

### System Info

docker
docker.io/michaelf34/infinity:0.0.75

not set gpu

Model: ```jinaai/jina-colbert-v2```

### Information

- [ ] Docker + cli
- [ ] pip + cli
- [ ] pip + usage of Python interface

### Tasks

- [ ] An officially supported CLI command
- [ ] My own modifications

### Reproduction

# Reference
https://jina.ai/news/jina-colbert-v2-multilingual-late-interaction-retriever-for-embedding-and-reranking/

# Embeddings
It said that there is an ```input_type``` params (query|document) return different Embeddings.

But i found that ```input_type``` is useless here. dimensions size return by token size
And ```dimensions``` set a big size for small token size will return error

and the shape is always [f(token.size), 1028], if set ```dimensions``` returns shape [dimensions,1028]

However I have try the jina api:
```https://jina.ai/api-dashboard/embedding```
and make test here (replace below):
It returns shape [f(token.size),dimensions] for document, and [32,dimensions] for query.

[document-64.json](https://github.com/user-attachments/files/19290498/document-64.json)
```bash
curl 'https://api.jina.ai/v1/multi-vector' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer ' \
-d '{
"model": "jina-colbert-v2",
"dimensions": 64,
"input_type": "document",
"embedding_type": "float",
"input": [
"Your document text string goes here",
"You can send multiple texts",
"Each text can be up to 8192 tokens long"
]}' > document-64.json
```
[document-128.json](https://github.com/user-attachments/files/19290496/document-128.json)
```bash
curl 'https://api.jina.ai/v1/multi-vector' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer ' \
-d '{
"model": "jina-colbert-v2",
"dimensions": 128,
"input_type": "document",
"embedding_type": "float",
"input": [
"Your document text string goes here",
"You can send multiple texts",
"Each text can be up to 8192 tokens long"
]}' > document-128.json
```
[query-128.json](https://github.com/user-attachments/files/19290497/query-128.json)
```bash
curl 'https://api.jina.ai/v1/multi-vector' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer ' \
-d '{
"model": "jina-colbert-v2",
"dimensions": 128,
"input_type": "query",
"embedding_type": "float",
"input": [
"Your document text string goes here",
"You can send multiple texts",
"Each text can be up to 8192 tokens long"
]}' > query-128.json
```

Take a look into [query-128.json](https://github.com/user-attachments/files/19290497/query-128.json) and [document-128.json](https://github.com/user-attachments/files/19290496/document-128.json). The same text has different vector.
This behavior is different from ```infinity``` implementation. ```infinity``` return the same vector.

# Rerank
And jina-colbert-v2 also has ```/rerank``` api, but swagger ui returns:
```json
{
"error": {
"message": "ModelNotDeployedError: model=`jinaai/jina-colbert-v2` does not support `rerank`. Reason: the loaded moded cannot fullyfill `rerank`. Options are {'embed'}.",
"type": null,
"param": null,
"code": 400
}
}
```

here is jina result:
[rank.json](https://github.com/user-attachments/files/19290495/rank.json)

```bash
curl 'https://api.jina.ai/v1/rerank' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer ' \
-d '{
"model": "jina-colbert-v2",
"query": "document text",
"top_n": 3,
"documents": [
"Your document text string goes here",
"You can send multiple texts",
"Each text can be up to 8192 tokens long"
]
}' > rank.json
```

Start by reproducing the reported behavior with the Docker image and the provided curl requests for jinaai/jina-colbert-v2. Compare input_type, dimensions, embedding shapes, and rerank support with the linked Jina API results. Done means the implementation's behavior is corrected or clearly documented, including whether reranking is supported.

Written by the indexing model from the issue text.