Fix typo and error (#5479)

### What problem does this PR solve?

_Briefly describe what this PR aims to solve. Include background context
that will help reviewers understand the purpose of the PR._

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Documentation Update

---------

Signed-off-by: Jin Hai <haijin.chn@gmail.com>

README.md

 
 - 2025-02-05 Updates the model list of 'SILICONFLOW' and adds support for Deepseek-R1/DeepSeek-V3.
 - 2025-01-26 Optimizes knowledge graph extraction and application, offering various configuration options.
-- 2024-12-18 Upgrades Document Layout Analysis model in Deepdoc.
+- 2024-12-18 Upgrades Document Layout Analysis model in DeepDoc.
 - 2024-12-04 Adds support for pagerank score in knowledge base.
 - 2024-11-22 Adds more variables to Agent.
 - 2024-11-01 Adds keyword extraction and related question generation to the parsed chunks to improve the accuracy of retrieval.

README_id.md

 </h4>
 
 <details open>
-<summary></b>📕 Daftar Isi</b></summary>
+<summary><b>📕 Daftar Isi </b> </summary>
 
 - 💡 [Apa Itu RAGFlow?](#-apa-itu-ragflow)
 - 🎮 [Demo](#-demo)
 
 - 2025-02-05 Memperbarui daftar model 'SILICONFLOW' dan menambahkan dukungan untuk Deepseek-R1/DeepSeek-V3.
 - 2025-01-26 Optimalkan ekstraksi dan penerapan grafik pengetahuan dan sediakan berbagai opsi konfigurasi.
-- 2024-12-18 Meningkatkan model Analisis Tata Letak Dokumen di Deepdoc.
+- 2024-12-18 Meningkatkan model Analisis Tata Letak Dokumen di DeepDoc.
 - 2024-12-04 Mendukung skor pagerank ke basis pengetahuan.
 - 2024-11-22 Peningkatan definisi dan penggunaan variabel di Agen.
 - 2024-11-01 Penambahan ekstraksi kata kunci dan pembuatan pertanyaan terkait untuk meningkatkan akurasi pengambilan.
    ```
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?                  |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|--------------------------|
    | v0.16.0           | &approx;9       | :heavy_check_mark:    | Stable release           |
-   | v0.16.0-slim      | &approx;2       | ❌                    | Stable release           |
+   | v0.16.0-slim      | &approx;2       | ❌                     | Stable release           |
    | nightly           | &approx;9       | :heavy_check_mark:    | _Unstable_ nightly build |
-   | nightly-slim      | &approx;2       | ❌                    | _Unstable_ nightly build |
+   | nightly-slim      | &approx;2       | ❌                     | _Unstable_ nightly build |
 
 4. Periksa status server setelah server aktif dan berjalan:
 

README_ja.md

 
 - 2025-02-05 シリコン フローの St およびモデル リストを更新し、Deep Seek-R1/Deep Seek-V3 のサポートを追加しました。
 - 2025-01-26 ナレッジ グラフの抽出と適用を最適化し、さまざまな構成オプションを提供します。
-- 2024-12-18 Deepdoc のドキュメント レイアウト分析モデルをアップグレードします。
+- 2024-12-18 DeepDoc のドキュメント レイアウト分析モデルをアップグレードします。
 - 2024-12-04 ナレッジ ベースへのページランク スコアをサポートしました。
 - 2024-11-22 エージェントでの変数の定義と使用法を改善しました。
 - 2024-11-01 再現の精度を向上させるために、解析されたチャンクにキーワード抽出と関連質問の生成を追加しました。
    ```
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?                  |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|--------------------------|
    | v0.16.0           | ≈9       | :heavy_check_mark:    | Stable release           |
-   | v0.16.0-slim      | ≈2       | ❌                    | Stable release           |
+   | v0.16.0-slim      | ≈2       | ❌                     | Stable release           |
    | nightly           | ≈9       | :heavy_check_mark:    | _Unstable_ nightly build |
-   | nightly-slim      | ≈2       | ❌                    | _Unstable_ nightly build |
+   | nightly-slim      | ≈2       | ❌                     | _Unstable_ nightly build |
 
 4. サーバーを立ち上げた後、サーバーの状態を確認する:
 

README_ko.md

 
 - 2025-02-05 'SILICONFLOW' 모델 목록을 업데이트하고 Deepseek-R1/DeepSeek-V3에 대한 지원을 추가합니다.
 - 2025-01-26 지식 그래프 추출 및 적용을 최적화하고 다양한 구성 옵션을 제공합니다.
-- 2024-12-18 Deepdoc의 문서 레이아웃 분석 모델 업그레이드.
+- 2024-12-18 DeepDoc의 문서 레이아웃 분석 모델 업그레이드.
 - 2024-12-04 지식베이스에 대한 페이지랭크 점수를 지원합니다.
 
 - 2024-11-22 에이전트의 변수 정의 및 사용을 개선했습니다.
    ```
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?                  |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|--------------------------|
    | v0.16.0           | ≈9       | :heavy_check_mark:    | Stable release           |
-   | v0.16.0-slim      | ≈2       | ❌                    | Stable release           |
+   | v0.16.0-slim      | ≈2       | ❌                     | Stable release           |
    | nightly           | ≈9       | :heavy_check_mark:    | _Unstable_ nightly build |
-   | nightly-slim      | ≈2       | ❌                    | _Unstable_ nightly build |
+   | nightly-slim      | ≈2       | ❌                     | _Unstable_ nightly build |
 
 4. 서버가 시작된 후 서버 상태를 확인하세요:
 

README_pt_br.md

 </h4>
 
 <details open>
-<summary></b>📕 Índice</b></summary>
+<summary><b>📕 Índice</b></summary>
 
 - 💡 [O que é o RAGFlow?](#-o-que-é-o-ragflow)
 - 🎮 [Demo](#-demo)
 
 - 05-02-2025 Atualiza a lista de modelos de 'SILICONFLOW' e adiciona suporte para Deepseek-R1/DeepSeek-V3.
 - 26-01-2025 Otimize a extração e aplicação de gráficos de conhecimento e forneça uma variedade de opções de configuração.
-- 18-12-2024 Atualiza o modelo de Análise de Layout de Documentos no Deepdoc.
+- 18-12-2024 Atualiza o modelo de Análise de Layout de Documentos no DeepDoc.
 - 04-12-2024 Adiciona suporte para pontuação de pagerank na base de conhecimento.
 - 22-11-2024 Adiciona mais variáveis para o Agente.
 - 01-11-2024 Adiciona extração de palavras-chave e geração de perguntas relacionadas aos blocos analisados para melhorar a precisão da recuperação.
     ```
 
     | Tag da imagem RAGFlow | Tamanho da imagem (GB) | Possui modelos de incorporação? | Estável?                 |
-    | --------------------- | ---------------------- | ------------------------------- | ------------------------ |
+    |-----------------------|------------------------|---------------------------------|--------------------------|
     | v0.16.0               | ~9                     | :heavy_check_mark:              | Lançamento estável       |
-    | v0.16.0-slim          | ~2                     | ❌                              | Lançamento estável       |
+    | v0.16.0-slim          | ~2                     | ❌                               | Lançamento estável       |
     | nightly               | ~9                     | :heavy_check_mark:              | _Instável_ build noturno |
-    | nightly-slim          | ~2                     | ❌                              | _Instável_ build noturno |
+    | nightly-slim          | ~2                     | ❌                               | _Instável_ build noturno |
 
 4.  Verifique o status do servidor após tê-lo iniciado:
 

README_tzh.md

 
 - 2025-02-05 更新「SILICONFLOW」的型號清單並新增 Deepseek-R1/DeepSeek-V3 的支援。
 - 2025-01-26 最佳化知識圖譜的擷取與應用，提供了多種配置選擇。
-- 2024-12-18 升級了 Deepdoc 的文檔佈局分析模型。
+- 2024-12-18 升級了 DeepDoc 的文檔佈局分析模型。
 - 2024-12-04 支援知識庫的 Pagerank 分數。
 - 2024-11-22 完善了 Agent 中的變數定義和使用。
 - 2024-11-01 對解析後的 chunk 加入關鍵字抽取和相關問題產生以提高回想的準確度。
    ```
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?                  |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|--------------------------|
    | v0.16.0           | ≈9       | :heavy_check_mark:    | Stable release           |
-   | v0.16.0-slim      | ≈2       | ❌                    | Stable release           |
+   | v0.16.0-slim      | ≈2       | ❌                     | Stable release           |
    | nightly           | ≈9       | :heavy_check_mark:    | _Unstable_ nightly build |
-   | nightly-slim      | ≈2       | ❌                    | _Unstable_ nightly build |
+   | nightly-slim      | ≈2       | ❌                     | _Unstable_ nightly build |
 
    > [!TIP]
    > 如果你遇到 Docker 映像檔拉不下來的問題，可以在 **docker/.env** 檔案內根據變數 `RAGFLOW_IMAGE` 的註解提示選擇華為雲或阿里雲的對應映像。
 
 系統配置涉及以下三份文件：
 
-- [.env](./docker/.env)：存放一些基本的系統環境變量，例如 `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` 等。
+- [.env](./docker/.env)：存放一些系統環境變量，例如 `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` 等。
 - [service_conf.yaml.template](./docker/service_conf.yaml.template)：設定各類別後台服務。
 - [docker-compose.yml](./docker/docker-compose.yml): 系統依賴該檔案完成啟動。
 

README_zh.md

 
 - 2025-02-05 更新硅基流动的模型列表，增加了对 Deepseek-R1/DeepSeek-V3 的支持。
 - 2025-01-26 优化知识图谱的提取和应用，提供了多种配置选择。
-- 2024-12-18 升级了 Deepdoc 的文档布局分析模型。
+- 2024-12-18 升级了 DeepDoc 的文档布局分析模型。
 - 2024-12-04 支持知识库的 Pagerank 分数。
 - 2024-11-22 完善了 Agent 中的变量定义和使用。
 - 2024-11-01 对解析后的 chunk 加入关键词抽取和相关问题生成以提高召回的准确度。
    ```
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?                  |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|--------------------------|
    | v0.16.0           | ≈9       | :heavy_check_mark:    | Stable release           |
-   | v0.16.0-slim      | ≈2       | ❌                    | Stable release           |
+   | v0.16.0-slim      | ≈2       | ❌                     | Stable release           |
    | nightly           | ≈9       | :heavy_check_mark:    | _Unstable_ nightly build |
-   | nightly-slim      | ≈2       | ❌                    | _Unstable_ nightly build |
+   | nightly-slim      | ≈2       | ❌                     | _Unstable_ nightly build |
 
    > [!TIP]
    > 如果你遇到 Docker 镜像拉不下来的问题，可以在 **docker/.env** 文件内根据变量 `RAGFLOW_IMAGE` 的注释提示选择华为云或者阿里云的相应镜像。
     * Running on all addresses (0.0.0.0)
    ```
 
-   > 如果您跳过这一步系统确认步骤就登录 RAGFlow，你的浏览器有可能会提示 `network anormal` 或 `网络异常`，因为 RAGFlow 可能并未完全启动成功。
+   > 如果您在没有看到上面的提示信息出来之前，就尝试登录 RAGFlow，你的浏览器有可能会提示 `network anormal` 或 `网络异常`。
 
 5. 在你的浏览器中输入你的服务器对应的 IP 地址并登录 RAGFlow。
    > 上面这个例子中，您只需输入 http://IP_OF_YOUR_MACHINE 即可：未改动过配置则无需输入端口（默认的 HTTP 服务端口 80）。

docs/guides/agent/text2sql_agent.md

 
 # Create a Text2SQL agent
 
-Build a Text2SQL agent leverging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
+Build a Text2SQL agent leveraging RAGFlow's RAG capabilities. Contributed by @TeslaZY.
 
 ## Scenario
 
 3. Create a Retrieval node and name it Thesaurus; create an ExeSQL node.
 4. Configure the Q->SQL, DDL, DB_Description, and TextSQL_Thesaurus knowledge bases. Please refer to the following:
    ![Configure Retrieval node](https://github.com/user-attachments/assets/25d67b01-954e-4eb4-87f5-c54262cf9a3e)
-5. Configure the Generate node, named LLM‘s prompt:
+5. Configure the Generate node, named LLM's prompt:
    - Add this content to the prompt provided by the template to provide the thesaurus content to the LLM:
      ```plaintext
      ## You may use the following Thesaurus statements. For example, what I ask is from Synonyms, you must use Standard noun to generate SQL. Use responses to past questions also to guide you: {sql_thesaurus}.

docs/guides/configure_knowledge_base/construct_knowledge_graph.md

 
 ## Prerequisites
 
-The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have an chat model properly configured:
+The system's default chat model is used to generate knowledge graph. Before proceeding, ensure that you have a chat model properly configured:
 
 ![Image](https://github.com/user-attachments/assets/6bc34279-68c3-4d99-8d20-b7bd1dafc1c1)
 
 
 1. On the **Configuration** page of your knowledge base, switch on **Extract knowledge graph** or adjust its settings as needed, and click **Save** to confirm your changes.
 
-   - *The default knowledge graph configurations for your knowlege base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
+   - *The default knowledge graph configurations for your knowledge base are now set and files uploaded from this point onward will automatically use these settings during parsing.*
    - *Files parsed before this update will retain their original knowledge graph settings.*
 
-2. The knowledge graph of your knowlege base does *not* automatically update *until* a newly uploaded file is parsed.
+2. The knowledge graph of your knowledge base does *not* automatically update *until* a newly uploaded file is parsed.
 
    _A **Knowledge graph** entry appears under **Configuration** once a knowledge graph is created._
 

docs/guides/deploy_local_llm.mdx

 
 ### 2. Ensure Ollama is accessible
 
-If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessiable from inside the RAGFlow container:
+If RAGFlow runs in Docker and Ollama runs on the same host machine, check if ollama is accessible from inside the RAGFlow container:
 ```bash
 sudo docker exec -it ragflow-server bash
 root@8136b8c3e914:/ragflow# curl  http://host.docker.internal:11434/
 Ollama is running
 ```
 
-If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessiable from RAGFlow host machine:
+If RAGFlow runs from source code and Ollama runs on the same host machine, check if ollama is accessible from RAGFlow host machine:
 ```bash
 curl  http://localhost:11434/
 Ollama is running
 ```
 
-If RAGFlow and Ollama run on different machines, check if ollama is accessiable from RAGFlow host machine:
+If RAGFlow and Ollama run on different machines, check if ollama is accessible from RAGFlow host machine:
 ```bash
 curl  http://${IP_OF_OLLAMA_MACHINE}:11434/
 Ollama is running

docs/references/faq.md

 
 ---
 
-### Where to find the version of RAGFlow? How to interprete it?
+### Where to find the version of RAGFlow? How to interpret it?
 
 You can find the RAGFlow version number on the **System** page of the UI:
 
 A correct Ollama IP address and port is crucial to adding models to Ollama:
 
 - If you are on demo.ragflow.io, ensure that the server hosting Ollama has a publicly accessible IP address. Note that 127.0.0.1 is not a publicly accessible IP address.
-- If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can comunicate with each other.
+- If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can communicate with each other.
 
 See [Deploy a local LLM](../guides/deploy_local_llm.mdx) for more information.
 
 ---
 
-#### Do you offer examples of using deepdoc to parse PDF or other files?
+#### Do you offer examples of using DeepDoc to parse PDF or other files?
 
 Yes, we do. See the Python files under the **rag/app** folder.
 

docs/references/python_api_reference.md

 
 #### Returns
 
-- Success: Respose [message](https://platform.openai.com/docs/api-reference/chat/create) like OpenAI
+- Success: Response [message](https://platform.openai.com/docs/api-reference/chat/create) like OpenAI
 - Failure: `Exception`
 
 #### Examples