Add redirects from old links to ML documentation (opensearch-project#5707)

* Add redirects from old links to ML documentation

Signed-off-by: Fanit Kolchina <[email protected]>

* Rename links

Signed-off-by: Fanit Kolchina <[email protected]>

---------

Signed-off-by: Fanit Kolchina <[email protected]>

Author: kolchfa-aws

_ingest-pipelines/processors/text-image-embedding.md

@@ -134,6 +134,6 @@ The response confirms that in addition to the `image_description` and `image_bin
 ## Next steps
 
 - To learn how to use the `neural` query for a multimodal search, see [Neural query]({{site.url}}{{site.baseurl}}/query-dsl/specialized/neural/).
-- To learn more about multimodal neural search, see [Multimodal search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/multimodal-search/).
+- To learn more about multimodal neural search, see [Multimodal search]({{site.url}}{{site.baseurl}}/search-plugins/multimodal-search/).
 To learn more about using models in OpenSearch, see [Choosing a model]({{site.url}}{{site.baseurl}}/ml-commons-plugin/integrating-ml-models/#choosing-a-model).
 - For a comprehensive example, see [Neural search tutorial]({{site.url}}{{site.baseurl}}/search-plugins/neural-search-tutorial/).

_ml-commons-plugin/pretrained-models.md

@@ -266,9 +266,9 @@ The response contains the tokens and weights:
 
 ## Step 5: Use the model for search
 
-To learn how to set up a vector index and use text embedding models for search, see [Semantic search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/semantic-search/).
+To learn how to set up a vector index and use text embedding models for search, see [Semantic search]({{site.url}}{{site.baseurl}}/search-plugins/semantic-search/).
 
-To learn how to set up a vector index and use sparse encoding models for search, see [Sparse search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/sparse-search/).
+To learn how to set up a vector index and use sparse encoding models for search, see [Sparse search]({{site.url}}{{site.baseurl}}/search-plugins/sparse-search/).
 
 
 ## Supported pretrained models

_ml-commons-plugin/remote-models/blueprints.md

@@ -6,7 +6,7 @@ nav_order: 65
 parent: Connecting to remote models 
 grand_parent: Integrating ML models
 redirect_from: 
-  - ml-commons-plugin/remote-models/blueprints/
+  - ml-commons-plugin/extensibility/blueprints/
 ---
 
 # Connector blueprints

_ml-commons-plugin/remote-models/connectors.md

@@ -7,7 +7,7 @@ nav_order: 61
 parent: Connecting to remote models 
 grand_parent: Integrating ML models
 redirect_from: 
-  - ml-commons-plugin/remote-models/connectors/
+  - ml-commons-plugin/extensibility/connectors/
 ---
 
 # Creating connectors for third-party ML platforms

_ml-commons-plugin/remote-models/index.md

@@ -6,7 +6,7 @@ has_children: true
 has_toc: false
 nav_order: 60
 redirect_from: 
-  - ml-commons-plugin/remote-models/index/
+  - ml-commons-plugin/extensibility/index/
 ---
 
 # Connecting to remote models

_ml-commons-plugin/using-ml-models.md

@@ -6,7 +6,7 @@ has_children: true
 nav_order: 50
 redirect_from:
    - /ml-commons-plugin/model-serving-framework/
-   - /ml-commons-plugin/using-ml-models/
+   - /ml-commons-plugin/ml-framework/
 ---
 
 # Using ML models within OpenSearch

_search-plugins/conversational-search.md

@@ -5,7 +5,6 @@ has_children: false
 nav_order: 70
 redirect_from:
   - /ml-commons-plugin/conversational-search/
-  - /search-plugins/search-methods/conversational-search/
 ---
 
 This is an experimental feature and is not recommended for use in a production environment. For updates on the progress of the feature or if you want to leave feedback, see the associated [GitHub issue](https://forum.opensearch.org/t/feedback-conversational-search-and-retrieval-augmented-generation-using-search-pipeline-experimental-release/16073). 

_search-plugins/hybrid-search.md

@@ -3,8 +3,6 @@ layout: default
 title: Hybrid search
 has_children: false
 nav_order: 40
-redirect_from:
-  - /search-plugins/search-methods/hybrid-search/
 ---
 
 # Hybrid search

_search-plugins/keyword-search.md

@@ -3,8 +3,6 @@ layout: default
 title: Keyword search
 has_children: false
 nav_order: 10
-redirect_from:
-  - /search-plugins/search-methods/keyword-search/
 ---
 
 # Keyword search

_search-plugins/multimodal-search.md

@@ -5,7 +5,6 @@ nav_order: 60
 has_children: false
 redirect_from:
   - /search-plugins/neural-multimodal-search/
-  - /search-plugins/search-methods/multimodal-search/
 ---
 
 # Multimodal search

_search-plugins/neural-search.md

@@ -39,16 +39,16 @@ Semantic search uses dense retrieval based on text embedding models to search te
 
 ### Hybrid search
 
-Hybrid search combines keyword and neural search to improve search relevance. For detailed setup instructions, see [Hybrid search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/hybrid-search/).
+Hybrid search combines keyword and neural search to improve search relevance. For detailed setup instructions, see [Hybrid search]({{site.url}}{{site.baseurl}}/search-plugins/hybrid-search/).
 
 ### Multimodal search
 
-Multimodal search uses neural search with multimodal embedding models to search text and image data. For detailed setup instructions, see [Multimodal search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/multimodal-search/).
+Multimodal search uses neural search with multimodal embedding models to search text and image data. For detailed setup instructions, see [Multimodal search]({{site.url}}{{site.baseurl}}/search-plugins/multimodal-search/).
 
 ### Sparse search
 
 Sparse search uses neural search with sparse retrieval based on sparse embedding models to search text data. For detailed setup instructions, see [Sparse search]({{site.url}}{{site.baseurl}}/search-plugins/neural-sparse-search/).
 
 ### Conversational search
 
-With conversational search, you can ask questions in natural language, receive a text response, and ask additional clarifying questions. For detailed setup instructions, see [Conversational search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/conversational-search/).
+With conversational search, you can ask questions in natural language, receive a text response, and ask additional clarifying questions. For detailed setup instructions, see [Conversational search]({{site.url}}{{site.baseurl}}/search-plugins/conversational-search/).

_search-plugins/semantic-search.md

@@ -5,7 +5,6 @@ nav_order: 35
 has_children: false
 redirect_from:
   - /search-plugins/neural-text-search/
-  - /search-plugins/search-methods/semantic-search/
 ---
 
 # Semantic search

_search-plugins/sparse-search.md

@@ -6,14 +6,13 @@ nav_order: 50
 has_children: false
 redirect_from:
   - /search-plugins/neural-sparse-search/
-  - /search-plugins/search-methods/sparse-search/
 ---
 
 # Sparse search
 Introduced 2.11
 {: .label .label-purple }
 
-[Semantic search]({{site.url}}{{site.baseurl}}/search-plugins/search-methods/semantic-search/) relies on dense retrieval that is based on text embedding models. However, dense methods use k-NN search, which consumes a large amount of memory and CPU resources. An alternative to semantic search, sparse search is implemented using an inverted index and is thus as efficient as BM25. Sparse search is facilitated by sparse embedding models. When you perform a sparse search, it creates a sparse vector (a list of `token: weight` key-value pairs representing an entry and its weight) and ingests data into a rank features index.
+[Semantic search]({{site.url}}{{site.baseurl}}/search-plugins/semantic-search/) relies on dense retrieval that is based on text embedding models. However, dense methods use k-NN search, which consumes a large amount of memory and CPU resources. An alternative to semantic search, sparse search is implemented using an inverted index and is thus as efficient as BM25. Sparse search is facilitated by sparse embedding models. When you perform a sparse search, it creates a sparse vector (a list of `token: weight` key-value pairs representing an entry and its weight) and ingests data into a rank features index.
 
 When selecting a model, choose one of the following options: