# Help with pipeline and reindex and search using E5 embedding model

**URL:** <https://discuss.elastic.co/t/help-with-pipeline-and-reindex-and-search-using-e5-embedding-model/369359>\
**Category:** Elasticsearch\
**Tags:** elastic-stack-machine-learning\
**Created:** [October 24, 2024, 12:22pm UTC](https://discuss.elastic.co/t/help-with-pipeline-and-reindex-and-search-using-e5-embedding-model/369359 "2024-10-24T12:22:57Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![Sergio\_Fernandez\_Col](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/sergio_fernandez_col/32/138677_2.png) [@Sergio\_Fernandez\_Col](https://discuss.elastic.co/u/Sergio_Fernandez_Col)\
**Post date:** [October 24, 2024, 12:22pm UTC](https://discuss.elastic.co/t/help-with-pipeline-and-reindex-and-search-using-e5-embedding-model/369359/1 "2024-10-24T12:22:57Z")

</div>

Hi all,  
I have uploaded a tsv file with chunked information, this information is divided in this columns: "document\_name", "page\_number" and "text".  
I did this many times but using elser\_v2, now I have to use the built-in E5.  
I have been trying to create a pipeline and a correct way to reindex this file from the original index to the embedded one, also the way to RAG search using E5 and I can't find the right way to do it.

Also, I think I had achieve this reindex successfully but they way to do a search (I think I have to embed the query too, not like elser) always gives me an error

Does anyone have a similar use case?

---

<div class="post-metadata">

**Author:** ![Shell\_Dias](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/shell_dias/32/136785_2.png) [@Shell\_Dias](https://discuss.elastic.co/u/Shell_Dias)\
**Post date:** [November 7, 2024, 5:42pm UTC](https://discuss.elastic.co/t/help-with-pipeline-and-reindex-and-search-using-e5-embedding-model/369359/2 "2024-11-07T17:42:43Z")

</div>

```auto
PUT _ingest/pipeline/e5-small-ingest-pipeline
{
  "description": "e5-small",
  "processors": [
    {
      "inference": {
        "model_id": ".multilingual-e5-small_linux-x86_64",
        "input_output": [
          {
            "input_field": "name",
            "output_field": "name_embedding"
          },
          {
            "input_field": "text",
            "output_field": "text_embedding"
          }
        ]
      }
    }
  ],
  "on_failure": [
    {
      "set": {
        "description": "Index document to 'failed-<index>'",
        "field": "_index",
        "value": "failed-{{{_index}}}"
      }
    },
    {
      "set": {
        "description": "Set error message",
        "field": "ingest.failure",
        "value": "{{_ingest.on_failure_message}}"
      }
    },
    {
      "set": {
        "field": "error.pipeline",
        "value": "{{ _ingest.pipeline }}"
      }
    }
  ]
}

```