docs: v1.1.2 (#5850)

* docs:add-changelog-to-nav

* docs: add OpenRouter component documentation with detailed inputs and outputs

* docs: add Outputs section to components-models documentation for Cohere and Ollama

* docs: update references from configuration-objects to concepts-objects across multiple components and documentation files

* feat: Add DataFrame operations section to components-processing documentation

* title-case-in-nav

* fix-memories-tab-in-chat-memory

* tool-calling-agent-update

* feat: enhance documentation with icon imports and improved instructions for OpenAI component

* material-icon

* fix: update documentation for tool mode input connection in agent component

* add-loop-component

* add-img-for-loop-summary

* feat: add documentation for using logic components in a flow with examples

* fix: enhance documentation for Loop component with detailed data flow explanation

* redirect-for-config-objects-page

* fix: improve error handling in data processing module

* fix: update documentation for Data objects in Loop component and add import statement in memory chatbot tutorial

* quickstart-screenshots

* docs: update starter flow images

* update-agent-screenshots

* move-repl-agent

* docs: enhance global variables documentation and clarify prerequisites for vector store RAG flow

* docs: update Simple Agent to use URL component

* docs: enhance memory chatbot tutorial with example conversation and clarify session ID terminology

* docs: update visibility icon description in concepts-components.md

* Apply suggestions from code review

Co-authored-by: brian-f <brian.fisher@datastax.com>

* correct-playground-sequence-and-typo

---------

Co-authored-by: brian-f <brian.fisher@datastax.com>

docs/docs/Get-Started/get-started-quickstart.md

@@ -3,14 +3,15 @@ title: Quickstart
 slug: /get-started-quickstart
 ---
 
+import Icon from "@site/src/components/icon";
+
 Get to know Langflow by building an OpenAI-powered chatbot application. After you've constructed a chatbot, add Retrieval Augmented Generation (RAG) to chat with your own data.
 
 ## Prerequisites
 
 * [An OpenAI API key](https://platform.openai.com/)
 * [An Astra DB vector database](https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html) with:
-	* AstraDB application token
-	* API endpoint
+	* An AstraDB application token
 	* [A collection in Astra](https://docs.datastax.com/en/astra-db-serverless/databases/manage-collections.html#create-collection)
 
 ## Open Langflow and start a new project
@@ -48,7 +49,7 @@ You should now have a flow that looks like this:
 ![](/img/quickstart-basic-prompt-no-connections.png)
 
 With no connections between them, the components won't interact with each other.
-You want data to flow from **Chat Input** to **Chat Output** via the connectors between the components.
+You want data to flow from **Chat Input** to **Chat Output** through the connections between the components.
 Each component accepts inputs on its left side, and sends outputs on its right side.
 Hover over the connection ports to see the data types that the component accepts.
 For more on component inputs and outputs, see [Components overview](/concepts-components).
@@ -67,7 +68,7 @@ Add your OpenAI API key to the OpenAI model component, and add a prompt to the P
 
 1. Add your credentials to the OpenAI component. The fastest way to complete these fields is with Langflow’s [Global Variables](/configuration-global-variables).
 
-	1. In the OpenAI component’s OpenAI API Key field, click the language Globe icon, and then click **Add New Variable**. 
+	1. In the OpenAI component’s OpenAI API Key field, click the <Icon name="Globe" aria-label="Globe" /> **Globe** button, and then click **Add New Variable**. 
 	Alternatively, click your username in the top right corner, and then click **Settings**, **Global Variables**, and then **Add New**.
 	2. Name your variable. Paste your OpenAI API key (sk-…​) in the Value field.
 	3. In the **Apply To Fields** field, select the OpenAI API Key field to apply this variable to all OpenAI Embeddings components.
@@ -131,9 +132,12 @@ The [OpenAI Embeddings](/components-embedding-models#openai-embeddings) componen
 
 8. Configure the **Astra DB** component.
 	1. In the **Astra DB Application Token** field, add your **Astra DB** application token.
-	2. In the **API Endpoint** field, add your **Astra DB** API endpoint. This value is found in your [Astra DB deployment](https://astra.datastax.com) and looks similar to `https://ASTRA_DB_ID-ASTRA_DB_REGION.apps.astra.datastax.com`.
-	3. In the **Collection** field, enter your Astra DB collection's name. Collections are created in your [Astra DB deployment](https://astra.datastax.com) for storing vector data. The collection’s **Dimensions** value must match the dimensions of the **OpenAI Embeddings Model**. If you’re unsure, enter `1536` and select the `text-embedding-ada-002` model in the OpenAI Embeddings component. For more on collections, see the [DataStax Astra DB Serverless documentation](https://docs.datastax.com/en/astra-db-serverless/databases/manage-collections.html#create-collection).
+	The component connects to your database and populates the menus with existing databases and collections.
+	2. Select your **Database**.
+	3. Select your **Collection**. Collections are created in your [Astra DB deployment](https://astra.datastax.com) for storing vector data.
+	If you don't have a collection, see the [DataStax Astra DB Serverless documentation](https://docs.datastax.com/en/astra-db-serverless/databases/manage-collections.html#create-collection).
 	4. Select **Embedding Model** to bring your own embeddings model, which is the connected **OpenAI Embeddings** component.
+	The **Dimensions** value must match the dimensions of your collection. This value can be found in your **Collection** in your [Astra DB deployment](https://astra.datastax.com).
 
 If you used Langflow's **Global Variables** feature, the RAG application flow components are already configured with the necessary credentials.