update pages for content and screenshots from Ingest for search section to RAG section

Author: ketkee-aryamane

solutions/_snippets/connect-local-llm-to-playground.md

@@ -1,6 +1,6 @@
 Create a connector using the public URL from ngrok.
 
-1. In Kibana, go to **Search > Playground**, and click **Connect to an LLM**.
+1. In Kibana, go to **Playground** from the left navigation menu, and select the wrench button (🔧) in the **Large Language Model (LLM)** tile to connect an LLM.
 2. Select **OpenAI** on the fly-out.
 3. Provide a name for the connector.
 4. Under **Connector settings**, select **Other (OpenAI Compatible Service)** as the OpenAI provider.

solutions/images/elasticsearch-openai-compatible-connector.png

@@ -96,7 +96,7 @@ You can create and manage synonym sets and synonym rules using the {{kib}} user
 
 To create a synonym set using the UI:
 
-1. Navigate to **Elasticsearch** > **Synonyms** or use the [global search field](/explore-analyze/query-filter/filtering.md#_finding_your_apps_and_objects).
+1. Use the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md) to find Synonyms, then select **Synonyms / Synonyms** from the results.
 2. Click **Get started**.
 3. Enter a name for your synonym set.
 4. Add your synonym rules in the editor by adding terms to match against:

solutions/images/elasticsearch-reference-ingest-pipeline-ent-search-ui.png

@@ -28,7 +28,7 @@ Currently you can only select **one field** to be provided as context to the LLM
 
 ## Edit context in UI [playground-context-ui] 
 
-Use the **Edit context** button in the Playground UI to adjust the number of documents and fields sent to the LLM.
+Use the **Playground context** section in the Playground UI to adjust the number of documents and fields sent to the LLM.
 
 If you’re hitting context length limits, try the following:
 
@@ -56,9 +56,9 @@ Refer to the following Python notebooks for examples of how to chunk your docume
 * [Website content](https://github.com/elastic/elasticsearch-labs/tree/main/notebooks/ingestion-and-chunking/website-chunking-ingest.ipynb)
 
 
-### Balancing cost/latency and result quality [playground-context-balance] 
+### Optimizing context for cost and performance [playground-context-balance] 
 
-Here are some general recommendations for balancing cost/latency and result quality with different context sizes:
+The following recommendations can help you balance cost, latency, and result quality when working with different context sizes:
 
 Optimize context length
 :   Determine the optimal context length through empirical testing. Start with a baseline and adjust incrementally to find a balance that optimizes both response quality and system performance.
@@ -69,7 +69,6 @@ Implement token pruning for ELSER model
     * [Optimizing retrieval with ELSER v2](https://www.elastic.co/search-labs/blog/introducing-elser-v2-part-2)
     * [Improving text expansion performance using token pruning](https://www.elastic.co/search-labs/blog/text-expansion-pruning)
 
-
 Monitor and adjust
 :   Continuously monitor the effects of context size changes on performance and adjust as necessary.
 

solutions/images/kibana-chat-interface.png

@@ -17,7 +17,7 @@ This functionality is in technical preview and may be changed or removed in a fu
 
 Once you’ve set up your chat interface, you can start chatting with the model. Playground will automatically generate {{es}} queries based on your questions, and retrieve the most relevant documents from your {{es}} indices. The Playground UI enables you to view and modify these queries.
 
-* Click **View query** to open the visual query editor.
+* Select the **Query** tab to open the visual query editor.
 * Modify the query by selecting fields to query per index.
 
 ::::{tip}