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UI updates (#9836)

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### What problem does this PR solve?

### Type of change


- [x] Documentation Update
This commit is contained in:
writinwaters
2025-08-30 21:44:58 +08:00
committed by GitHub
parent bed77ee28f
commit 7eb25e0de6
17 changed files with 64 additions and 252 deletions
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docs/quickstart.mdx
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@ -267,25 +267,16 @@ RAGFlow also supports deploying LLMs locally using Ollama, Xinference, or LocalA
To add and configure an LLM:
1. Click on your logo on the top right of the page **>** **Model providers**:
1. Click on your logo on the top right of the page **>** **Model providers**。
![add llm](https://github.com/infiniflow/ragflow/assets/93570324/10635088-028b-4b3d-add9-5c5a6e626814)
2. Click on the desired LLM and update the API key accordingly (DeepSeek-V2 in this case):
![update api key](https://github.com/infiniflow/ragflow/assets/93570324/4e5e13ef-a98d-42e6-bcb1-0c6045fc1666)
*Your added models appear as follows:*
![added available models](https://github.com/infiniflow/ragflow/assets/93570324/d08b80e4-f921-480a-b41d-11832489c916)
2. Click on the desired LLM and update the API key accordingly.
3. Click **System Model Settings** to select the default models:
- Chat model,
- Embedding model,
- Image-to-text model.
![system model settings](https://github.com/infiniflow/ragflow/assets/93570324/cdcc1da5-4494-44cd-ad5b-1222ed6acc3f)
- Image-to-text model,
- and more.
> Some models, such as the image-to-text model **qwen-vl-max**, are subsidiary to a specific LLM. And you may need to update your API key to access these models.
@ -301,7 +292,7 @@ To create your first knowledge base:
_You are taken to the **Configuration** page of your knowledge base._
![knowledge base configuration](https://github.com/infiniflow/ragflow/assets/93570324/384c671a-8b9c-468c-b1c9-1401128a9b65)
![knowledge base configuration](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/configure_knowledge_base.jpg)
3. RAGFlow offers multiple chunk templates that cater to different document layouts and file formats. Select the embedding model and chunking method (template) for your knowledge base.
@ -315,9 +306,7 @@ Once you have selected an embedding model and used it to parse a file, you are n
5. In the uploaded file entry, click the play button to start file parsing:
![file parsing](https://github.com/infiniflow/ragflow/assets/93570324/19f273fa-0ab0-435e-bdf4-a47fb080a078)
_When the file parsing completes, its parsing status changes to **SUCCESS**._
![parse file](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/parse_file.jpg)
:::caution NOTE
- If your file parsing gets stuck at below 1%, see [this FAQ](./faq.mdx#why-does-my-document-parsing-stall-at-under-one-percent).
@ -332,13 +321,13 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin
_You are taken to the **Chunk** page:_
![chunks](https://github.com/infiniflow/ragflow/assets/93570324/0547fd0e-e71b-41f8-8e0e-31649c85fd3d)
![chunks](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/file_chunks.jpg)
2. Hover over each snapshot for a quick view of each chunk.
3. Double click the chunked texts to add keywords or make *manual* changes where necessary:
![update chunk](https://github.com/infiniflow/ragflow/assets/93570324/1d84b408-4e9f-46fd-9413-8c1059bf9c76)
![update chunk](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/add_keyword_question.jpg)
:::caution NOTE
You can add keywords to a file chunk to improve its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.
@ -348,7 +337,7 @@ You can add keywords to a file chunk to improve its ranking for queries containi
_As you can tell from the following, RAGFlow responds with truthful citations._
![retrieval test](https://github.com/infiniflow/ragflow/assets/93570324/c03f06f6-f41f-4b20-a97e-ae405d3a950c)
![retrieval test](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/retrieval_test.jpg)
## Set up an AI chat
@ -370,9 +359,7 @@ Conversations in RAGFlow are based on a particular knowledge base or multiple kn
5. Now, let's start the show:
![question1](https://github.com/infiniflow/ragflow/assets/93570324/bb72dd67-b35e-4b2a-87e9-4e4edbd6e677)
![question2](https://github.com/infiniflow/ragflow/assets/93570324/7cc585ae-88d0-4aa2-817d-0370b2ad7230)
![chat_thermal_solution](https://raw.githubusercontent.com/infiniflow/ragflow-docs/main/images/chat_thermal_solution.jpg)
:::tip NOTE