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/Tutorials/tutorials-math-agent.md

@@ -0,0 +1,56 @@
+---
+title: Math agent
+slug: /tutorials-math-agent
+---
+
+import Icon from "@site/src/components/icon";
+
+Build a **Math Agent** flow for an agentic application using the **Tool-calling agent** component.
+
+In this flow, the **Tool-calling agent** reasons using an **Open AI** LLM to solve math problems.
+It selects the **Calculator** tool for simpler math and the **Python REPL** tool (with the Python `math` library) for more complex problems.
+
+## Prerequisites
+
+To use this flow, you need an OpenAI API key.
+
+## Open Langflow and start a new flow
+
+Click **New Flow**, and then select the **Math Agent** flow.
+
+This opens a starter flow with the necessary components to run an agentic application using the Tool-calling agent.
+
+## Math Agent flow
+
+![](/img/starter-flow-simple-agent-repl.png)
+
+The **Math Agent** flow consists of these components:
+
+* The **Tool calling agent** component uses the connected LLM to reason through the user's input and select among the connected tools to complete its task.
+* The **Python REPL tool** component executes Python code in a REPL (Read-Evaluate-Print Loop) interpreter.
+* The **Calculator** component performs basic arithmetic operations.
+* The **Chat Input** component accepts user input to the chat.
+* The **Prompt** component combines the user input with a user-defined prompt.
+* The **Chat Output** component prints the flow's output to the chat.
+* The **OpenAI** model component sends the user input and prompt to the OpenAI API and receives a response.
+
+## Run the Math Agent flow
+
+1. Add your credentials to the Open AI component.
+2. Click **Playground** to start a chat session.
+3. Enter a simple math problem, like `2 + 2`, and then make sure the bot responds with the correct answer.
+4. To confirm the REPL interpreter is working, prompt the `math` library directly with `math.sqrt(4)` and see if the bot responds with `4`.
+5. The agent will also reason through more complex word problems. For example, prompt the agent with the following math problem:
+
+```plain
+The equation 24x2+25x−47ax−2=−8x−3−53ax−2 is true for all values of x≠2a, where a is a constant.
+What is the value of a?
+A) -16
+B) -3
+C) 3
+D) 16
+```
+
+The agent should respond with `B`.
+
+Now that your query has completed the journey from **Chat input** to **Chat output**, you have completed the **Math Agent** flow.