addressed comment

Signed-off-by: Dhrubo Saha <[email protected]>
opensearch-project · Nov 19, 2024 · d9dc2a6 · d9dc2a6
1 parent ad64153
commit d9dc2a6
Showing 1 changed file with 6 additions and 6 deletions.
diff --git a/docs/remote_inference_blueprints/cohere_connector_image_embedding_blueprint.md b/docs/remote_inference_blueprints/cohere_connector_image_embedding_blueprint.md
@@ -173,7 +173,7 @@ PUT /_ingest/pipeline/cohere-ingest-pipeline
       "text_embedding": {
         "model_id": "<MODEL_ID>",
         "field_map": {
-          "passage_text": "passage_embedding"
+          "image_base64": "image_embedding"
         }
       }
     }
@@ -206,7 +206,7 @@ PUT /cohere-nlp-index
       "id": {
       "type": "text"
       },
-      "passage_embedding": {
+      "image_embedding": {
         "type": "knn_vector",
         "dimension": 1024,
         "method": {
@@ -216,7 +216,7 @@ PUT /cohere-nlp-index
           "parameters": {}
         }
       },
-      "passage_text": {
+      "image_base64": {
         "type": "text"
       }
     }
@@ -240,7 +240,7 @@ First, you can insert a record:
 ```json
 PUT /cohere-nlp-index/_doc/1
 {
-  "passage_text": "data:image/png;base64,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",
+  "image_base64": "data:image/png;base64,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",
   "id": "c1"
 }
 ```
@@ -299,8 +299,8 @@ Sample response:
         "_id": "1",
         "_score": 1,
         "_source": {
-          "passage_text": "Hi - Cohere Embeddings are cool!",
-          "passage_embedding": [
+          "image_base64": 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