[BUG] Dynamic template for vectorized output fields

What is the bug?

I want to use dynamic templates to create vectorized output fields. In the ingest processor I want to create the configuration only once, without having to configure again in the index mapping.

This is not working, because I am getting the following error:

"error": {
                    "type": "mapper_parsing_exception",
                    "reason": "failed to parse field [Body_vector] of type [knn_vector] in document with id '9'. Preview of field's value: '-0.083671086'",
                    "caused_by": {
                        "type": "illegal_argument_exception",
                        "reason": "Vector dimension mismatch. Expected: 384, Given: 1"
                    }
                }

I have a field called Body that consists of text, and the neural Ingest pipeline will create an output field called Body_vector. The dimension has already been set to 384 but it sets it to 1 or parses it as 1.

How can one reproduce the bug?

Steps to reproduce the behavior.

Follow the Neural Search plugin tutorial created by Sease, but create an index with a dynamic template like this:

"dynamic_templates": [
      {
        "vectorized": {
          "match_mapping_type": "double",
          "match_pattern": "regex",
          "path_match": ".*_vector.*",
          "mapping": {
            "type": "knn_vector",
            "dimension": 384,
            "method": {
              "name": "hnsw",
              "engine": "lucene"
            }
          }
        }
      }
]

Index documents and see that you get above exception thrown.

What is the expected behavior?

A clear and concise description of what you expected to happen.

The expected behavior is that the dynamic template should create the vectorized output fields as configured in the mapping and index without errors.

What is your host/environment?

Operating system, version.

Mac 13.3, but running OpenSearch in Docker with Ubuntu.

Do you have any screenshots?

If applicable, add screenshots to help explain your problem.

N/A

Do you have any additional context?

Add any other context about the problem.

I am happy to contribute to a solution.

opensearch-project / neural-search