update pages for content and screenshots for 9.2 nav

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/search/full-text/search-with-synonyms.md

@@ -96,13 +96,13 @@ 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).
-2. Click **Get started**.
+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. Select **Get started**.
 3. Enter a name for your synonym set.
 4. Add your synonym rules in the editor by adding terms to match against:
    - Add **Equivalent rules** by adding multiple equivalent terms. For example: `ipod, i-pod, i pod`
    - Add **Explicit rules** by adding multiple terms that map to a single term. For example: `i-pod, i pod => ipod`
-5. Click **Save** to save your rules.
+5. Select **Save** to save your rules.
 
 The UI supports the same synonym rule formats as the file-based approach. Changes made through the UI will automatically reload the associated analyzers.
 
@@ -123,7 +123,7 @@ You can store your synonyms set in a file.
 
 Make sure you upload a synonyms set file for all your cluster nodes, to the configuration directory for your {{es}} distribution. If you're using {{ech}}, you can upload synonyms files using [custom bundles](../../../deploy-manage/deploy/elastic-cloud/upload-custom-plugins-bundles.md).
 
-An example synonyms file:
+An example of a synonyms file:
 
 ```markdown
 # Blank lines and lines starting with pound are comments.

solutions/search/get-started/keyword-search-python.md

@@ -36,10 +36,12 @@ To learn about role-based access control, go to [](/deploy-manage/users-roles/cl
 ::::{step} Create an index
 
 An index is a collection of documents uniquely identified by a name or an alias.
-To create an index, go to **{{es}} > Home**, select keyword search, and follow the guided workflow.
+To create an index:
+1. Go to  **Index Management** in the management page using the navigation menu or the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md).
+2. Select **Create index**, select **Keyword Search**, and follow the guided workflow.
 
 To enable your client to talk to your project, you must also create an API key.
-Click **Create API Key** and use the default values, which are sufficient for this quickstart.
+Select **Create an API Key** and use the default values, which are sufficient for this quickstart.
 
 :::{tip}
 For more information about indices and API keys, go to [](/manage-data/data-store/index-basics.md) and [](/deploy-manage/api-keys/serverless-project-api-keys.md).
@@ -50,7 +52,7 @@ For more information about indices and API keys, go to [](/manage-data/data-stor
 Select your preferred language in the keyword search workflow.
 For this quickstart, use Python.
 
-![Client installation step in the keyword search workflow](https://images.contentstack.io/v3/assets/bltefdd0b53724fa2ce/bltbf810f73fd4082fb/67c21c06304ea9790b82ee4d/screenshot-my-index.png)
+![Client installation step in the keyword search workflow](/solutions/images/search-quickstart-install-python-client.png)
 
 The {{es}} client library is a Python package that is installed with `pip`:
 
@@ -132,7 +134,7 @@ For more details about bulker helpers, refer to [Client helpers](elasticsearch-p
 
 You should now be able to see the documents in the guided workflow:
 
-![Viewing data in the guided workflow](https://images.contentstack.io/v3/assets/bltefdd0b53724fa2ce/blt0ac36402cde2a645/67d0a443b8764e72b9e8e1f3/view_docs_in_elasticsearch.png)
+![Viewing data in the guided workflow](/solutions/images/search-quickstart-view-data-python-keywordsearch.png)
 
 Optionally open [Discover](/explore-analyze/discover.md) from the navigation menu or the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md) to familiarize yourself with this data set.
 

solutions/search/get-started/semantic-search.md

@@ -42,8 +42,9 @@ This guide uses the [semantic text field type](elasticsearch://reference/elastic
 An index is a collection of documents uniquely identified by a name or an alias.
 You can follow the guided index workflow:
 
-- If you're using {{es-serverless}}, go to **{{es}} > Home**, select the semantic search workflow, and click **Create a semantic optimized index**.
-- If you're using {{ech}} or running {{es}} locally, go to **{{es}} > Home** and click **Create API index**. Select the semantic search workflow.
+- If you're using {{es-serverless}}, {{ech}}, or running {{es}} locally:
+  1. Go to  **Index Management** in the management page using the navigation menu or the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md).
+  2. Select **Create index**, select **Semantic Search**, and follow the guided workflow.
 
 When you complete the workflow, you will have sample data and can skip to the steps related to exploring and searching it.
 Alternatively, run the following API request in [Console](/explore-analyze/query-filter/tools/console.md):

solutions/search/query-rules-ui.md

@@ -38,7 +38,7 @@ For full access to the Query Rules UI, you need the following privileges:
 
 ## Accessing the Query Rules UI
 
-Go to your deployment and select **Query Rules** from the left navigation menu under **Relevance**. If the option does not appear, contact your administrator to review your privileges.
+Go to **Query Rules** in the management page using the navigation menu or the [global search field](/explore-analyze/find-and-organize/find-apps-and-objects.md). If the option does not appear, contact your administrator to review your privileges.
 
 :::{image} /solutions/images/elasticsearch-query-rules-ui-home.png
 :alt: Landing page for Query Rules UI.

solutions/search/rag/playground-context.md

@@ -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/search/rag/playground-query.md

@@ -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}

solutions/search/rag/playground-troubleshooting.md

@@ -23,7 +23,7 @@ Context length error
 :   You’ll need to adjust the size of the context you’re sending to the model. Refer to [Optimize model context](playground-context.md).
 
 LLM credentials not working
-:   Under **Model settings**, use the wrench button (🔧) to edit your GenAI connector settings.
+:   Under **LLM settings**, use the wrench button (🔧) to edit your GenAI connector settings.
 
 Poor answer quality
 :   Check the retrieved documents to see if they are valid. Adjust your {{es}} queries to improve the relevance of the documents retrieved. Refer to [View and modify queries](playground-query.md).

solutions/search/rag/playground.md

@@ -61,7 +61,7 @@ Here’s a simpified overview of how Playground works:
 
 ## Availability and prerequisites [playground-availability-prerequisites]
 
-For Elastic Cloud and self-managed deployments Playground is available in the **Search** space in {{kib}}, under **Content** > **Playground**.
+For Elastic Cloud and self-managed deployments, select **Playground** from the left navigation menu.
 
 For Elastic Serverless, Playground is available in your {{es}} project UI.
 
@@ -114,11 +114,11 @@ You can also use locally hosted LLMs that are compatible with the OpenAI SDK. On
 
 ### Connect to LLM provider [playground-getting-started-connect]
 
-To get started with Playground, you need to create a [connector](../../../deploy-manage/manage-connectors.md) for your LLM provider. You can also connect to [locally hosted LLMs](playground.md#playground-local-llms) which are compatible with the OpenAI API, by using the OpenAI connector.
+To get started with Playground, you need to create a [connector](../../../deploy-manage/manage-connectors.md) for your LLM provider. By default, an Elastic Managed LLM is connected. You can also connect to [locally hosted LLMs](playground.md#playground-local-llms) which are compatible with the OpenAI API, by using the OpenAI connector.
 
-To connect to an LLM provider, follow these steps on the Playground landing page:
+To connect to an LLM provider, use the following steps on the Playground landing page:
 
-1. Under **Connect to an LLM**, click **Create connector**.
+1. Select **New Playground**. Select the wrench button (🔧) in the **Large Language Model (LLM)** tile to connect an LLM.
 2. Select your **LLM provider**.
 3. **Name** your connector.
 4. Select a **URL endpoint** (or use the default).
@@ -170,7 +170,7 @@ We’ve also provided some Jupyter notebooks to easily ingest sample data into {
 
 Once you’ve connected to your LLM provider, it’s time to choose the data you want to search.
 
-1. Click **Add data sources**.
+1. Select **Add data sources**.
 2. Select one or more {{es}} indices.
 3. Click **Save and continue** to launch the chat interface.
 
@@ -219,9 +219,9 @@ Learn more about the underlying {{es}} queries used to search your data in [View
 
 You can start chatting with your data immediately, but you might want to tweak some defaults first.
 
-You can adjust the following under **Model settings**:
+You can adjust the following under **LLM settings**:
 
-* **Model**. The model used for generating responses.
+* **AI Connector**. The model used for generating responses.
 * **Instructions**. Also known as the *system prompt*, these initial instructions and guidelines define the behavior of the model throughout the conversation. Be **clear and specific** for best results.
 * **Include citations**. A toggle to include citations from the relevant {{es}} documents in responses.
 
@@ -240,12 +240,12 @@ Click **⟳ Clear chat** to clear chat history and start a new conversation.
 
 ### View and download Python code [playground-getting-started-view-code]
 
-Use the **View code** button to see the Python code that powers the chat interface. You can integrate it into your own application, modifying as needed. We currently support two implementation options:
+Use the **Export** button to see the Python code that powers the chat interface. You can integrate it into your own application, modifying as needed. We currently support two implementation options:
 
 * {{es}} Python Client + LLM provider
 * LangChain + LLM provider
 
-:::{image} /solutions/images/kibana-view-code-button.png
+:::{image} /solutions/images/kibana-view-python-code.png
 :alt: view code button
 :screenshot:
 :width: 150px

solutions/search/search-connection-details.md

@@ -79,15 +79,16 @@ The **Cloud ID** is also available in the **Connection Details** section. Toggle
 ### Create an API key [create-an-api-key-serverless]
 
 1. Go to the serverless project’s home page.
-2. In the **Connect to Elasticsearch** section, select **Create API key**.
+2. Select the settings icon in the **Elasticsearch endpoint** section.
+3. On the **API keys** page, select **Create API key**.
 
     :::{image} /solutions/images/kibana-serverless-create-an-api-key.png
     :alt: serverless create an api key
     :screenshot:
     :::
 
-3. Enter the API key details, and select **Create API key**.
-4. Copy and securely store the API key, since it won't appear again.
+4. Enter the API key details, and select **Create API key**.
+5. Copy and securely store the API key, since it won't appear again.
 
 ### Test connection [elasticsearch-get-started-test-connection]