How to connect vector search pipeline to RAG stack (with langchain)?

[Vishnu_Satis]

@Vishnu_Satis

{
  "fields": [
    {
      "numDimensions": 1536,
      "path": "embeddings",
      "similarity": "euclidean",
      "type": "vector"
    },
    {
      "path": "businessAccount",
      "type": "filter"
    },
    {
      "path": "_id",
      "type": "filter"
    }
  ]
}

Which index should I use ?
{
“fields”: [
{
“numDimensions”: 1536,
“path”: “embeddings”,
“similarity”: “euclidean”,
“type”: “vector”
},
{
“path”: “businessAccount”,
“type”: “filter”
},
{
“path”: “_id”,
“type”: “filter”
}
]
}

or the other one. Most documentation mention this as the right one, here the path already specifies which to use and it has ?path: embeddings"