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
This commit is contained in:
writinwaters
2025-01-06 20:25:47 +08:00
committed by GitHub
parent 1d93eb81ae
commit bb24e5f739
7 changed files with 49 additions and 20 deletions

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---
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.

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---
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

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slug: /run_health_check
---
# Run health check on RAGFlow's dependencies
# Run dependency health check
Double-check the health status of RAGFlow's dependencies.

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@ -57,7 +57,7 @@ You start an AI conversation by creating an assistant.
:::tip NOTE
Click the light bubble logo above the answer to view the expanded system prompt:
Click the light bubble icon above the answer to view the expanded system prompt:
![](https://github.com/user-attachments/assets/515ab187-94e8-412a-82f2-aba52cd79e09)
@ -74,10 +74,19 @@ Hover over an intended chat assistant **>** **Edit** to show the chat configurat
![chat_config](https://github.com/user-attachments/assets/1a4eaed2-5430-4585-8ab6-930549838c5b)
## Integrate chat capabilities into your application
## Integrate chat capabilities into your application or webpage
RAGFlow also offers HTTP and Python APIs for you to integrate RAGFlow's capabilities into your applications. Read the following documents for more information:
RAGFlow offers HTTP and Python APIs for you to integrate RAGFlow's capabilities into your applications. Read the following documents for more information:
- [Acquire a RAGFlow API key](./develop/acquire_ragflow_api_key.md)
- [HTTP API reference](../references/http_api_reference.md)
- [Python API reference](../references/python_api_reference.md)
- [Acquire a RAGFlow API key](https://ragflow.io/docs/dev/acquire_ragflow_api_key)
- [HTTP API reference](https://ragflow.io/docs/dev/http_api_reference)
- [Python API reference](https://ragflow.io/docs/dev/python_api_reference)
You can use iframe to embed the created chat assistant 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. Hover over an intended chat assistant **>** **Edit** to show the **iframe** window:
![chat-embed](https://github.com/user-attachments/assets/13ea3021-31c4-4a14-9b32-328cd3318fb5)
3. Copy the iframe and embed it into a specific location on your webpage.