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Update version info to v0.14.1 (#3720)

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### What problem does this PR solve?

Update version info to v0.14.1

### Type of change

- [x] Documentation Update

---------

Signed-off-by: jinhai <haijin.chn@gmail.com>
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6
README.md
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@ -20,7 +20,7 @@
<img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
</a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.1-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.1">
</a>
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
@ -176,14 +176,14 @@ releases! 🌟
```
> - To download a RAGFlow slim Docker image of a specific version, update the `RAGFLOW_IMAGE` variable in *
*docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`. After
*docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim`. After
making this change, rerun the command above to initiate the download.
> - To download the dev version of RAGFlow Docker image *including* embedding models and Python libraries, update the
`RAGFLOW_IMAGE` variable in **docker/.env** to `RAGFLOW_IMAGE=infiniflow/ragflow:dev`. After making this change,
rerun the command above to initiate the download.
> - To download a specific version of RAGFlow Docker image *including* embedding models and Python libraries, update
the `RAGFLOW_IMAGE` variable in **docker/.env** to your desired version. For example,
`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`. After making this change, rerun the command above to initiate the
`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`. After making this change, rerun the command above to initiate the
download.
> **NOTE:** A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size

6
README_id.md
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@ -20,7 +20,7 @@
<img alt="Lencana Daring" src="https://img.shields.io/badge/Online-Demo-4e6b99">
</a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.1-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.1">
</a>
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Rilis%20Terbaru" alt="Rilis Terbaru">
@ -169,14 +169,14 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
```
> - Untuk mengunduh versi tertentu dari image Docker RAGFlow slim, perbarui variabel `RAGFlow_IMAGE` di *
*docker/.env** sesuai dengan versi yang diinginkan. Misalnya, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`.
*docker/.env** sesuai dengan versi yang diinginkan. Misalnya, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim`.
Setelah mengubah ini, jalankan ulang perintah di atas untuk memulai unduhan.
> - Untuk mengunduh versi dev dari image Docker RAGFlow *termasuk* model embedding dan library Python, perbarui
variabel `RAGFlow_IMAGE` di **docker/.env** menjadi `RAGFLOW_IMAGE=infiniflow/ragflow:dev`. Setelah mengubah ini,
jalankan ulang perintah di atas untuk memulai unduhan.
> - Untuk mengunduh versi tertentu dari image Docker RAGFlow *termasuk* model embedding dan library Python, perbarui
variabel `RAGFlow_IMAGE` di **docker/.env** sesuai dengan versi yang diinginkan. Misalnya,
`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`. Setelah mengubah ini, jalankan ulang perintah di atas untuk memulai unduhan.
`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`. Setelah mengubah ini, jalankan ulang perintah di atas untuk memulai unduhan.
> **CATATAN:** Image Docker RAGFlow yang mencakup model embedding dan library Python berukuran sekitar 9GB
dan mungkin memerlukan waktu lebih lama untuk dimuat.

6
README_ja.md
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@ -20,7 +20,7 @@
<img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
</a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.1-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.1">
</a>
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
@ -148,9 +148,9 @@
$ docker compose -f docker-compose.yml up -d
```
> - 特定のバージョンのRAGFlow slim Dockerイメージをダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
> - 特定のバージョンのRAGFlow slim Dockerイメージをダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
> - RAGFlowの埋め込みモデルとPythonライブラリを含む開発版Dockerイメージをダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を`RAGFLOW_IMAGE=infiniflow/ragflow:dev`に更新します。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
> - 特定のバージョンのRAGFlow Dockerイメージ（埋め込みモデルとPythonライブラリを含む）をダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
> - 特定のバージョンのRAGFlow Dockerイメージ（埋め込みモデルとPythonライブラリを含む）をダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
> **NOTE:** 埋め込みモデルとPythonライブラリを含むRAGFlow Dockerイメージのサイズは約9GBであり、読み込みにかなりの時間がかかる場合があります。

6
README_ko.md
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@ -20,7 +20,7 @@
<img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
</a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.1-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.1">
</a>
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
@ -152,9 +152,9 @@
$ docker compose -f docker-compose.yml up -d
```
> - 특정 버전의 RAGFlow slim Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`으로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
> - 특정 버전의 RAGFlow slim Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim`으로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
> - RAGFlow의 임베딩 모델과 Python 라이브러리를 포함한 개발 버전 Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 `RAGFLOW_IMAGE=infiniflow/ragflow:dev`로 업데이트하세요. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
> - 특정 버전의 RAGFlow Docker 이미지를 임베딩 모델과 Python 라이브러리를 포함하여 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0` 로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
> - 특정 버전의 RAGFlow Docker 이미지를 임베딩 모델과 Python 라이브러리를 포함하여 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1` 로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
> **NOTE:** 임베딩 모델과 Python 라이브러리를 포함한 RAGFlow Docker 이미지의 크기는 약 9GB이며, 로드하는 데 상당히 오랜 시간이 걸릴 수 있습니다.

6
README_zh.md
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@ -20,7 +20,7 @@
<img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
</a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.1-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.1">
</a>
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
@ -149,9 +149,9 @@
$ docker compose -f docker-compose.yml up -d
```
> - 如果你想下载并运行特定版本的 RAGFlow slim Docker 镜像，请在 **docker/.env** 文件中找到 `RAGFLOW_IMAGE` 变量，将其改为对应版本。例如 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`，然后再运行上述命令。
> - 如果你想下载并运行特定版本的 RAGFlow slim Docker 镜像，请在 **docker/.env** 文件中找到 `RAGFLOW_IMAGE` 变量，将其改为对应版本。例如 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim`，然后再运行上述命令。
> - 如果您想安装内置 embedding 模型和 Python 库的 dev 版本的 Docker 镜像，需要将 **docker/.env** 文件中的 `RAGFLOW_IMAGE` 变量修改为： `RAGFLOW_IMAGE=infiniflow/ragflow:dev`。
> - 如果您想安装内置 embedding 模型和 Python 库的指定版本的 RAGFlow Docker 镜像，需要将 **docker/.env** 文件中的 `RAGFLOW_IMAGE` 变量修改为： `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`。修改后，再运行上面的命令。
> - 如果您想安装内置 embedding 模型和 Python 库的指定版本的 RAGFlow Docker 镜像，需要将 **docker/.env** 文件中的 `RAGFLOW_IMAGE` 变量修改为： `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`。修改后，再运行上面的命令。
> **注意：** 安装内置 embedding 模型和 Python 库的指定版本的 RAGFlow Docker 镜像大小约 9 GB，可能需要更长时间下载，请耐心等待。
4. 服务器启动成功后再次确认服务器状态：

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docs/guides/configure_knowledge_base.md
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@ -103,7 +103,7 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin
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:
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)
@ -111,7 +111,7 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin
You can add keywords to a file chunk to increase its ranking for queries containing those keywords. This action increases its keyword weight and can improve its position in search list.
:::
4. In Retrieval testing, ask a quick question in **Test text** to double check if your configurations work:
4. In Retrieval testing, ask a quick question in **Test text** to double-check if your configurations work:
_As you can tell from the following, RAGFlow responds with truthful citations._
@ -128,7 +128,7 @@ RAGFlow uses multiple recall of both full-text search and vector search in its c
## Search for knowledge base
As of RAGFlow v0.14.0, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
As of RAGFlow v0.14.1, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
![search knowledge base](https://github.com/infiniflow/ragflow/assets/93570324/836ae94c-2438-42be-879e-c7ad2a59693e)

4
docs/guides/deploy_local_llm.mdx
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@ -108,7 +108,7 @@ Click on your logo **>** **Model Providers** **>** **System Model Settings** to
Update your chat model accordingly in **Chat Configuration**:
> If your local model is an embedding model, update it on the configruation page of your knowledge base.
> If your local model is an embedding model, update it on the configuration page of your knowledge base.
## Deploy a local model using Xinference
@ -161,7 +161,7 @@ Click on your logo **>** **Model Providers** **>** **System Model Settings** to
Update your chat model accordingly in **Chat Configuration**:
> If your local model is an embedding model, update it on the configruation page of your knowledge base.
> If your local model is an embedding model, update it on the configuration page of your knowledge base.
## Deploy a local model using IPEX-LLM

2
docs/guides/develop/acquire_ragflow_api_key.md
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@ -7,7 +7,7 @@ slug: /acquire_ragflow_api_key
A key is required for the RAGFlow server to authenticate your requests via HTTP or a Python API. This documents provides instructions on obtaining a RAGFlow API key.
1. Click your avatar on the top right corner of the RAGFlow UI to access the configuration page.
1. Click your avatar in the top right corner of the RAGFlow UI to access the configuration page.
2. Click **API** to switch to the **API** page.
3. Obtain a RAGFlow API key:

2
docs/guides/manage_files.md
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@ -81,4 +81,4 @@ RAGFlow's file management allows you to download an uploaded file:
![download_file](https://github.com/infiniflow/ragflow/assets/93570324/cf3b297f-7d9b-4522-bf5f-4f45743e4ed5)
> As of RAGFlow v0.14.0, bulk download is not supported, nor can you download an entire folder.
> As of RAGFlow v0.14.1, bulk download is not supported, nor can you download an entire folder.

2
docs/guides/manage_team_members.md
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@ -17,7 +17,7 @@ By default, each RAGFlow user is assigned a single team named after their name.
Team members are currently *not* allowed to invite users to your team, and only you, the team owner, is permitted to do so.
:::
To enter the **Team** page, click on your avatar on the top right corner of the page **>** Team:
To enter the **Team** page, click on your avatar in the top right corner of the page **>** Team:
![team](https://github.com/user-attachments/assets/0eac2503-26bc-4568-b3f2-bcd84069a07a)

4
docs/guides/run_health_check.md
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@ -5,7 +5,7 @@ slug: /run_health_check
# Run health check on RAGFlow's dependencies
Double check the health status of RAGFlow's dependencies.
Double-check the health status of RAGFlow's dependencies.
The operation of RAGFlow depends on four services:
@ -16,7 +16,7 @@ The operation of RAGFlow depends on four services:
If an exception or error occurs related to any of the above services, such as `Exception: Can't connect to ES cluster`, refer to this document to check their health status.
You can also click you avatar on the top right corner of the page **>** System to view the visualized health status of RAGFlow's core services. The following screenshot shows that all services are 'green' (running healthily). The task executor displays the *cumulative* number of completed and failed document parsing tasks from the past 30 minutes:
You can also click you avatar in the top right corner of the page **>** System to view the visualized health status of RAGFlow's core services. The following screenshot shows that all services are 'green' (running healthily). The task executor displays the *cumulative* number of completed and failed document parsing tasks from the past 30 minutes:
![system_status_page](https://github.com/user-attachments/assets/b0c1a11e-93e3-4947-b17a-1bfb4cdab6e4)

2
docs/guides/start_chat.md
View File

@ -19,7 +19,7 @@ You start an AI conversation by creating an assistant.
- **Assistant name** is the name of your chat assistant. Each assistant corresponds to a dialogue with a unique combination of knowledge bases, prompts, hybrid search configurations, and large model settings.
- **Empty response**:
- If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then when it doesn't retrieve an answer, it *uniformly* responds with what you set here.
- If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then, when it doesn't retrieve an answer, it *uniformly* responds with what you set here.
- If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, which may give rise to hallucinations.
- **Show Quote**: This is a key feature of RAGFlow and enabled by default. RAGFlow does not work like a black box. instead, it clearly shows the sources of information that its responses are based on.
- Select the corresponding knowledge bases. You can select one or multiple knowledge bases, but ensure that they use the same embedding model, otherwise an error would occur.

6
docs/guides/upgrade_ragflow.mdx
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@ -62,16 +62,16 @@ To upgrade RAGFlow, you must upgrade **both** your code **and** your Docker imag
git clone https://github.com/infiniflow/ragflow.git
```
2. Switch to the latest, officially published release, e.g., `v0.14.0`:
2. Switch to the latest, officially published release, e.g., `v0.14.1`:
```bash
git checkout v0.14.0
git checkout v0.14.1
```
3. Update **ragflow/docker/.env** as follows:
```bash
RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0
RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1
```
4. Update the RAGFlow image and restart RAGFlow:

8
docs/quickstart.mdx
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@ -32,9 +32,9 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
<details>
<summary>1. Ensure <code>vm.max_map_count</code> &ge; 262144:</summary>
`vm.max_map_count`. This value sets the maximum number of memory map areas a process may have. Its default value is 65530. While most applications require fewer than a thousand maps, reducing this value can result in abmornal behaviors, and the system will throw out-of-memory errors when a process reaches the limitation.
`vm.max_map_count`. This value sets the maximum number of memory map areas a process may have. Its default value is 65530. While most applications require fewer than a thousand maps, reducing this value can result in abnormal behaviors, and the system will throw out-of-memory errors when a process reaches the limitation.
RAGFlow v0.14.0 uses Elasticsearch for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.
RAGFlow v0.14.1 uses Elasticsearch or [Infinity](https://github.com/infiniflow/infinity) for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.
<Tabs
defaultValue="linux"
@ -184,9 +184,9 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
$ docker compose -f docker-compose.yml up -d
```
> - To download a RAGFlow slim Docker image of a specific version, update the `RAGFlOW_IMAGE` variable in **docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`. After making this change, rerun the command above to initiate the download.
> - To download a RAGFlow slim Docker image of a specific version, update the `RAGFlOW_IMAGE` variable in **docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1-slim`. After making this change, rerun the command above to initiate the download.
> - To download the dev version of RAGFlow Docker image *including* embedding models and Python libraries, update the `RAGFlOW_IMAGE` variable in **docker/.env** to `RAGFLOW_IMAGE=infiniflow/ragflow:dev`. After making this change, rerun the command above to initiate the download.
> - To download a specific version of RAGFlow Docker image *including* embedding models and Python libraries, update the `RAGFlOW_IMAGE` variable in **docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`. After making this change, rerun the command above to initiate the download.
> - To download a specific version of RAGFlow Docker image *including* embedding models and Python libraries, update the `RAGFlOW_IMAGE` variable in **docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1`. After making this change, rerun the command above to initiate the download.
:::tip NOTE
A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size and may take significantly longer time to load.