more-on-local-models

docs/docs/get-started/install.mdx

@@ -83,11 +83,12 @@ For more information on virtual environments, see [uv](https://docs.astral.sh/uv
    The application opens.
 8. Select your language model and embedding model provider, and complete the required fields.
    **Your provider can only be selected once, and you must use the same provider for your language model and embedding model.
-   To change your selection, you must restart OpenRAG.**
+   To change your provider selection, you must restart OpenRAG and delete the `config.yml` file.**
+   **Your language model can be changed, but your embeddings model cannot be changed.**
 
 <Tabs groupId="Embedding provider">
   <TabItem value="OpenAI" label="OpenAI" default>
-   9. You already entered a value for `OPENAI_API_KEY` in the TUI in Step 5, so enable **Get API key from environment variable**.
+   9. If you already entered a value for `OPENAI_API_KEY` in the TUI in Step 5, enable **Get API key from environment variable**.
    10. Under **Advanced settings**, select your **Embedding Model** and **Language Model**.
    11. To load 2 sample PDFs, enable **Sample dataset**.
    This is recommended, but not required.

docs/docs/get-started/quickstart.mdx

@@ -12,7 +12,40 @@ Get started with OpenRAG by loading your knowledge, swapping out your language m
 ## Prerequisites
 
 - [Install and start OpenRAG](/install)
-- [Langflow API key](/)
+- Create a [Langflow API key](https://docs.langflow.org/api-keys-and-authentication)
+    <details>
+        <summary>Create a Langflow API key</summary>
+    
+        A Langflow API key is a user-specific token you can use with Langflow.
+        It is **only** used for sending requests to the Langflow server.
+        It does **not** access to OpenRAG.
+    
+        To create a Langflow API key, do the following:
+    
+        1. In Langflow, click your user icon, and then select **Settings**.
+        2. Click **Langflow API Keys**, and then click <Icon name="Plus" aria-hidden="true"/> **Add New**.
+        3. Name your key, and then click **Create API Key**.
+        4. Copy the API key and store it securely.
+        5. To use your Langflow API key in a request, set a `LANGFLOW_API_KEY` environment variable in your terminal, and then include an `x-api-key` header or query parameter with your request.
+        For example:
+    
+            ```bash
+            # Set variable
+            export LANGFLOW_API_KEY="sk..."
+    
+            # Send request
+            curl --request POST \
+            --url "http://LANGFLOW_SERVER_ADDRESS/api/v1/run/FLOW_ID" \
+            --header "Content-Type: application/json" \
+            --header "x-api-key: $LANGFLOW_API_KEY" \
+            --data '{
+              "output_type": "chat",
+              "input_type": "chat",
+              "input_value": "Hello"
+            }'
+            ```
+    
+    </details>
 
 ## Find your way around 
 
@@ -44,12 +77,14 @@ If you aren't getting the results you need, you can further tune the knowledge i
 To modify the knowledge ingestion or Agent behavior, click <Icon name="Settings" aria-hidden="true"/> **Settings**.
 
 In this example, you'll try a different LLM to demonstrate how the Agent's response changes.
+You can only change the **Language model**, and not the **Model provider** that you started with in OpenRAG.
+If you're using Ollama, you can swap out any model.
 
 1. To edit the Agent's behavior, click **Edit in Langflow**.
+You can more quickly access the **Language Model** and **Agent Instructions** fields in this page, but for illustration purposes, navigate to the Langflow visual builder.
 2. OpenRAG warns you that you're entering Langflow. Click **Proceed**.
 3. The OpenRAG Open Search Agent flow appears. 
-
-![OpenRAG Open Search Agent Flow](/img/opensearch-agent-flow.png)
+   ![OpenRAG Open Search Agent Flow](/img/opensearch-agent-flow.png)
 
 4. In the **Language Model** component, under **Model Provider**, select **Anthropic**.
    :::note