Added instructions on embedding agent or assistant into a third-party webpage (#4369)

### What problem does this PR solve?


### Type of change

- [x] Documentation Update

docs/guides/agent/embed_agent_into_webpage.md

@@ -0,0 +1,16 @@
+---
+sidebar_position: 3
+slug: /embed_agent_into_webpage
+---
+
+# Embed agent into a webpage
+
+You can use iframe to embed an agent into a third-party webpage.
+
+1. Before proceeding, you must [acquire an API key](https://ragflow.io/docs/dev/acquire_ragflow_api_key); otherwise, an error message would appear.
+2. On the **Agent** page, click an intended agent **>** **Edit** to access its editing page.
+3. Click **Embed into webpage** on the top right corner of the canvas to show the **iframe** window:
+
+   ![agent_embed](https://github.com/user-attachments/assets/f748bb91-1a48-45ca-89ea-5b1c257407cb)
+
+4. Copy the iframe and embed it into a specific location on your webpage.

docs/guides/agent/text2sql_agent.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 3
+sidebar_position: 10
 slug: /text2sql_agent
 ---
 
@@ -9,7 +9,7 @@ Build a Text2SQL agent leverging RAGFlow's RAG capabilities. Contributed by @Tes
 
 ## Scenario
 
-The Text2SQL agent is designed to bridge the gap between Natural Language Processing (NLP) and Structured Query Language (SQL). Its key advantages are as follows:
+The Text2SQL agent bridges the gap between Natural Language Processing (NLP) and Structured Query Language (SQL). Its key advantages are as follows:
 
 - **Assisting non-technical users with SQL**: Not all users have a background in SQL or understand the structure of the tables involved in queries. With a Text2SQL agent, users can pose questions or request data in natural language without needing an in-depth knowledge of the database structure or SQL syntax.
 
@@ -31,7 +31,7 @@ However, traditional Text2SQL solutions often require model fine-tuning, which c
 
 A list of components required:
 
-- Begin
+- [Begin](https://ragflow.io/docs/dev/begin_component)
 - Interface
 - Retrieval
 - Generate