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Fix typo and error (#5479)

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### 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>
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Jin Hai 2025-02-28 16:09:40 +08:00 committed by GitHub
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2
README.md
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@ -80,7 +80,7 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
- 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.

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README_id.md
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@ -41,7 +41,7 @@
</h4>
<details open>
<summary></b>📕 Daftar Isi</b></summary>
<summary><b>📕 Daftar Isi </b> </summary>
- 💡 [Apa Itu RAGFlow?](#-apa-itu-ragflow)
- 🎮 [Demo](#-demo)
@ -77,7 +77,7 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
- 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.
@ -174,11 +174,11 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
```
| 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:

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README_ja.md
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@ -57,7 +57,7 @@
- 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。
@ -154,11 +154,11 @@
```
| 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. サーバーを立ち上げた後、サーバーの状態を確認する:

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README_ko.md
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@ -57,7 +57,7 @@
- 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.
@ -155,11 +155,11 @@
```
| 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. 서버가 시작된 후 서버 상태를 확인하세요:

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README_pt_br.md
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@ -41,7 +41,7 @@
</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)
@ -77,7 +77,7 @@ Experimente nossa demo em [https://demo.ragflow.io](https://demo.ragflow.io).
- 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.
@ -174,11 +174,11 @@ Experimente nossa demo em [https://demo.ragflow.io](https://demo.ragflow.io).
```
| 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:

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README_tzh.md
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@ -56,7 +56,7 @@
- 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。
@ -153,11 +153,11 @@
```
| 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 |
> [!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。
@ -197,7 +197,7 @@
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。

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@ -57,7 +57,7 @@
- 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。
@ -154,11 +154,11 @@
```
| 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 |
> [!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。
@ -184,7 +184,7 @@
* 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）。

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@ -5,7 +5,7 @@ slug: /text2sql_agent
# 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
@ -343,7 +343,7 @@ Synonyms: laptop computer,laptop pc
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}.

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@ -25,7 +25,7 @@ Knowledge graphs are especially useful for multi-hop question-answering involvin
## 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)
@ -60,10 +60,10 @@ In a knowledge graph, a community is a cluster of entities linked by relationshi
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._

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docs/guides/deploy_local_llm.mdx
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@ -59,20 +59,20 @@ success
### 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

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@ -22,7 +22,7 @@ The "garbage in garbage out" status quo remains unchanged despite the fact that
---
### 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:
@ -345,13 +345,13 @@ Your IP address or port number may be incorrect. If you are using the default co
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.

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@ -42,7 +42,7 @@ Whether to receive the response as a stream. Set this to `false` explicitly if y
#### 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