Neural search text_embedding pipeline error

Plugins Machine Learning
1

Versions (relevant - OpenSearch/Dashboard/Server OS/Browser):
2.15.0
Problem
I’m trying to implement hybrid search.
I created a connector to my own service, where the model is deployed

data_connector = {
    'name': 'proba_connector', 
    'description': 'The connector for proba_connector', 
    'version': 1, 
    'protocol': 'http', 
    'actions': [{
        "action_type": "predict", 
        "method": "POST", 
        "headers": {
            "content-type": "application/json"
        },
        "url": "http://localhost:8000/", 
        "request_body":"{ \"text\":${parameters.text}}",
        "post_process_function": "connector.post_process.default.embedding"}],
    'credential': {},
    'parameters':{
        'skip_validating_missing_parameters': True
    }
}

With output:

{"connector_id":"7IuE75QBSNMx2eSv1MRQ"}

When I make a request like this for a model

data_predict = {
  "parameters": {
      "text": ["how are you"]}
}
r = requests.post('https://localhost:9201/_plugins/_ml/models/7ouF75QBSNMx2eSvCsQ-/_predict', auth=('admin', 'admin'), verify=False, json=data_predict, headers=headers)

then it gives the following answer

{"inference_results":[{"output":[{"name":"sentence_embedding","data_type":"FLOAT32","shape":[4096],"data":[0.0110944714397192,0.019420204684138298,0.012235138565301895,0.008400695398449898,0.008350025862455368,0.009718209505081177,-0.00913007277995348,0.009152905084192753,0.02582375705242157,0.0064290789887309074,0.0084756501019001,-0.0023967644665390253,-0.004717715550214052,-0.010794127359986305,0.01587575674057007,-0.015306735411286354,0.02125721424818039,-0.0015540372114628553,-0.00030985873308964074,0.002872861921787262,0.0008000598754733801,0.014949942007660866,-0.0232723169028759,-0.008435241878032684,0.0018127607181668282,0.009296631440520287,-0.0017149467021226883,-0.005 ... 0.014812000095844269,-0.021458394825458527,0.005142853129655123]}],"status_code":200}]}

The following example request creates an ingest pipeline

body = {
    "description": "An NLP ingest pipeline",
    "processors": [
        {
            "text_embedding": {
                "model_id": "7ouF75QBSNMx2eSvCsQ-",
                "field_map": {
                    "text": "sentence_embedding"
                }
            }
        }
    ]
}

ingest_client = IngestClient(client)
ingest_client.put_pipeline(id=1, body=body)
ingest_client.get_pipeline()

Next output

{'1': {'description': 'An NLP ingest pipeline',
  'processors': [{'text_embedding': {'model_id': '7ouF75QBSNMx2eSvCsQ-',
     'field_map': {'text': 'sentence_embedding'}}}]}

Test the pipeline

body_simulate = {
    "docs": [
        {
            "_index": "run",
            "_id": "1",
            "_source": {
                "text": ["how are you"]
            }
        }
    ]
}

ingest_client.simulate(id=1, body=body_simulate)

gives the following error

{'docs': [{'error': {'root_cause': [{'type': 'illegal_argument_exception',
      'reason': 'Invalid payload: { "text":${parameters.text}}'}],
    'type': 'illegal_argument_exception',
    'reason': 'Invalid payload: { "text":${parameters.text}}'}}]}

why does this error occur? what’s wrong?