Miscelleneous editorial updates (#5390)

### What problem does this PR solve?


### Type of change

- [x] Documentation Update
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writinwaters 2025-02-26 19:03:50 +08:00 committed by GitHub
parent 0284248c93
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19 changed files with 59 additions and 82 deletions

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@ -204,9 +204,6 @@ releases! 🌟
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network anormal`
@ -252,7 +249,9 @@ RAGFlow uses Elasticsearch by default for storing full text and vectors. To swit
```bash
$ docker compose -f docker/docker-compose.yml down -v
```
Note: `-v` will delete the docker container volumes, and the existing data will be cleared.
> [!WARNING]
> `-v` will delete the docker container volumes, and the existing data will be cleared.
2. Set `DOC_ENGINE` in **docker/.env** to `infinity`.

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@ -197,9 +197,6 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> Jika Anda melewatkan langkah ini dan langsung login ke RAGFlow, browser Anda mungkin menampilkan error `network anormal`

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@ -176,9 +176,6 @@
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> もし確認ステップをスキップして直接 RAGFlow にログインした場合、その時点で RAGFlow が完全に初期化されていない可能性があるため、ブラウザーがネットワーク異常エラーを表示するかもしれません。

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@ -177,9 +177,6 @@
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> 만약 확인 단계를 건너뛰고 바로 RAGFlow에 로그인하면, RAGFlow가 완전히 초기화되지 않았기 때문에 브라우저에서 `network anormal` 오류가 발생할 수 있습니다.

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@ -196,9 +196,6 @@ Experimente nossa demo em [https://demo.ragflow.io](https://demo.ragflow.io).
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Rodando em todos os endereços (0.0.0.0)
* Rodando em http://127.0.0.1:9380
* Rodando em http://x.x.x.x:9380
INFO:werkzeug:Pressione CTRL+C para sair
```
> Se você pular essa etapa de confirmação e acessar diretamente o RAGFlow, seu navegador pode exibir um erro `network anormal`, pois, nesse momento, seu RAGFlow pode não estar totalmente inicializado.

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@ -181,9 +181,6 @@
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> 如果您跳過這一步驟系統確認步驟就登入 RAGFlow你的瀏覽器有可能會提示 `network anormal``網路異常`,因為 RAGFlow 可能並未完全啟動成功。

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@ -182,9 +182,6 @@
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> 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``网络异常`,因为 RAGFlow 可能并未完全启动成功。

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@ -42,9 +42,9 @@ RAGFlow offers multiple chunking template to facilitate chunking files of differ
| **Template** | Description | File format |
|--------------|-----------------------------------------------------------------------|------------------------------------------------------|
| General | Files are consecutively chunked based on a preset chunk token number. | DOCX, EXCEL, PPT, PDF, TXT, JPEG, JPG, PNG, TIF, GIF |
| Q&A | | EXCEL, CSV/TXT |
| Q&A | | XLSX, CSV/TXT |
| Manual | | PDF |
| Table | | EXCEL, CSV/TXT |
| Table | | XLSX, CSV/TXT |
| Paper | | PDF |
| Book | | DOCX, PDF, TXT |
| Laws | | DOCX, PDF, TXT |

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@ -65,9 +65,9 @@ In a knowledge graph, a community is a cluster of entities linked by relationshi
2. The knowledge graph of your knowlege 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._
_A **Knowledge graph** entry appears under **Configuration** once a knowledge graph is created._
3. Click **Knowledge Graph** to view the details of the generated graph.
3. Click **Knowledge graph** to view the details of the generated graph.
## Frequently asked questions
@ -81,4 +81,4 @@ Nope. The knowledge graph does *not* automatically update *until* a newly upload
### How to remove a generated knowledge graph?
To remove the generated knowledge graph, delete all related files in your knowledge base. Although the **Knowledge Graph** entry will still be visible, the graph has actually been deleted.
To remove the generated knowledge graph, delete all related files in your knowledge base. Although the **Knowledge graph** entry will still be visible, the graph has actually been deleted.

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@ -223,9 +223,6 @@ This section provides instructions on setting up the RAGFlow server on Linux. If
/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network anomaly` error because, at that moment, your RAGFlow may not be fully initialized.

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@ -12,7 +12,7 @@ A complete list of models supported by RAGFlow, which will continue to expand.
<APITable>
```
| Provider | Chat | Embedding | Rerank | Img2txt | Sequence2txt | TTS |
| Provider | Chat | Embedding | Rerank | Img2txt | Speech2txt | TTS |
| --------------------- | ------------------ | ------------------ | ------------------ | ------------------ | ------------------ | ------------------ |
| Anthropic | :heavy_check_mark: | | | | | |
| Azure-OpenAI | :heavy_check_mark: | :heavy_check_mark: | | :heavy_check_mark: | :heavy_check_mark: | |

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@ -15,9 +15,9 @@ Released on February 6, 2025.
- Supports DeepSeek R1 and DeepSeek V3.
- GraphRAG refactor: Knowledge graph is dynamically built on an entire knowledge base (dataset) rather than on an individual file, and automatically updated when a newly uploaded file starts parsing. See [here](https://ragflow.io/docs/dev/construct_knowledge_graph).
- Adds an **Iteration** agent component and a **Research report generator** agent template. See [here](https://ragflow.io/docs/dev/iteration_component).
- Adds an **Iteration** agent component and a **Research report generator** agent template. See [here](./references/agent_component_reference/iteration.mdx).
- New UI language: Portuguese.
- Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See [here](https://ragflow.io/docs/dev/set_metada).
- Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See [here](./guides/configure_knowledge_base/set_metadata.md).
- Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.6.0.dev3.
- Supports GPU acceleration for DeepDoc (see [docker-compose-gpu.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose-gpu.yml)).
- Supports creating and referencing a **Tag** knowledge base as a key milestone towards bridging the semantic gap between query and response.
@ -30,22 +30,21 @@ The **Tag knowledge base** feature is *unavailable* on the [Infinity](https://gi
#### Added documents
- [Construct knowledge graph](https://ragflow.io/docs/dev/construct_knowledge_graph)
- [Set metadata](https://ragflow.io/docs/dev/set_metada)
- [Begin component](https://ragflow.io/docs/dev/begin_component)
- [Generate component](https://ragflow.io/docs/dev/generate_component)
- [Interact component](https://ragflow.io/docs/dev/interact_component)
- [Retrieval component](https://ragflow.io/docs/dev/retrieval_component)
- [Categorize component](https://ragflow.io/docs/dev/categorize_component)
- [Keyword component](https://ragflow.io/docs/dev/keyword_component)
- [Message component](https://ragflow.io/docs/dev/message_component)
- [Rewrite component](https://ragflow.io/docs/dev/rewrite_component)
- [Switch component](https://ragflow.io/docs/dev/switch_component)
- [Concentrator component](https://ragflow.io/docs/dev/concentrator_component)
- [Template component](https://ragflow.io/docs/dev/template_component)
- [Iteration component](https://ragflow.io/docs/dev/iteration_component)
- [Note component](https://ragflow.io/docs/dev/note_component)
- [Construct knowledge graph](./guides/configure_knowledge_base/construct_knowledge_graph.md)
- [Set metadata](./guides/configure_knowledge_base/set_metadata.md)
- [Begin component](./references/agent_component_reference/begin.mdx)
- [Generate component](./references/agent_component_reference/generate.mdx)
- [Interact component](./references/agent_component_reference/interact.mdx)
- [Retrieval component](./references/agent_component_reference/retrieval.mdx)
- [Categorize component](./references/agent_component_reference/categorize.mdx)
- [Keyword component](./references/agent_component_reference/keyword.mdx)
- [Message component](./references/agent_component_reference/message.mdx)
- [Rewrite component](./references/agent_component_reference/rewrite.mdx)
- [Switch component](./references/agent_component_reference/switch.mdx)
- [Concentrator component](./references/agent_component_reference/concentrator.mdx)
- [Template component](./references/agent_component_reference/template.mdx)
- [Iteration component](./references/agent_component_reference/iteration.mdx)
- [Note component](./references/agent_component_reference/note.mdx)
## v0.15.1

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@ -258,10 +258,10 @@ export default {
<i>This chunk method is automatically applied to all uploaded PPT files, so you do not need to specify it manually.</i></p>`,
qa: `
<p>
This chunk method supports <b>EXCEL</b> and <b>CSV/TXT</b> file formats.
This chunk method supports <b>XLSX</b> and <b>CSV/TXT</b> file formats.
</p>
<li>
If a file is in <b>Excel</b> format, it should contain two columns
If a file is in <b>XLSX</b> format, it should contain two columns
without headers: one for questions and the other for answers, with the
question column preceding the answer column. Multiple sheets are
acceptable, provided the columns are properly structured.
@ -281,7 +281,7 @@ export default {
Résumés of various forms are parsed and organized into structured data to facilitate candidate search for recruiters.
</p>
`,
table: `<p>Supported file formats are <b>EXCEL</b> and <b>CSV/TXT</b>.</p><p>
table: `<p>Supported file formats are <b>XLSX</b> and <b>CSV/TXT</b>.</p><p>
Here're some prerequisites and tips:
<ul>
<li>For CSV or TXT file, the delimiter between columns must be <em><b>TAB</b></em>.</li>
@ -317,8 +317,8 @@ export default {
<p>Knowlege base using 'Tag' as a chunking method is <b>NOT</b> supposed to be involved in RAG procedure.</p>
<p>The chunks in this knowledge base are examples of tags, which demonstrate the entire tag set and the relevance between chunk and tags.</p>
<p>This chunk method supports <b>EXCEL</b> and <b>CSV/TXT</b> file formats.</p>
<p>If a file is in <b>Excel</b> format, it should contain two columns without headers: one for content and the other for tags, with the content column preceding the tags column. Multiple sheets are acceptable, provided the columns are properly structured.</p>
<p>This chunk method supports <b>XLSX</b> and <b>CSV/TXT</b> file formats.</p>
<p>If a file is in <b>XLSX</b> format, it should contain two columns without headers: one for content and the other for tags, with the content column preceding the tags column. Multiple sheets are acceptable, provided the columns are properly structured.</p>
<p>If a file is in <b>CSV/TXT</b> format, it must be UTF-8 encoded with TAB as the delimiter to separate content and tags.</p>
<p>In tags column, there're English <b>comma</b> between tags.</p>
<i>Lines of texts that fail to follow the above rules will be ignored, and each pair will be considered a distinct chunk.</i>
@ -352,16 +352,16 @@ The above is the content you need to summarize.`,
searchTags: 'Search tags',
tagCloud: 'Cloud',
tagTable: 'Table',
tagSet: 'Tag set',
tagSet: 'Tag sets',
tagSetTip: `
<p> Selecting the 'Tag' knowledge bases helps to tag every chunks. </p>
<p>Query to those chunks will also be with tags too.</p>
This procedure will improve precision of retrieval by adding more information to the dataset, especially when there's a large set of chunks.
<p>Difference between tags and keywords:</p>
<p> Select one or multiple tag knowledge bases to auto-tag chunks in your knowledge base. </p>
<p>The user query will also be auto-tagged.</p>
This auto-tag feature enhances retrieval by adding another layer of domain-specific knowledge to the existing dataset.
<p>Difference between auto-tag and auto-keyword:</p>
<ul>
<li>Tag is a close set which is defined and manipulated by user while keyword is an open set.</li>
<li>You need to upload tag sets with samples prior to use.</li>
<li>Keywords are generated by LLM which is expensive and time consuming.</li>
<li>A tag knowledge base is a user-defined close set, whereas keywords extraced by the LLM can be regarded as an open set.</li>
<li>You must upload tag sets in specified formats before running the auto-tag feature.</li>
<li>The auto-keyword feature is dependent on the LLM and consumes a significant number of tokens.</li>
</ul>
`,
topnTags: 'Top-N Tags',
@ -420,7 +420,7 @@ This procedure will improve precision of retrieval by adding more information to
language: 'Language',
emptyResponse: 'Empty response',
emptyResponseTip: `Set this as a response if no results are retrieved from the knowledge bases for your query, or leave this field blank to allow the LLM to improvise when nothing is found.`,
emptyResponseMessage: `Empty response will be triggered when nothing relevant is retrieved from knowledge bases. Erase 'Empty response' since none of knowledge base is selected.`,
emptyResponseMessage: `Empty response will be triggered when nothing relevant is retrieved from knowledge bases. You must clear the 'Empty response' field if no knowledge base is selected.`,
setAnOpener: 'Opening greeting',
setAnOpenerInitial: `Hi! I'm your assistant, what can I do for you?`,
setAnOpenerTip: 'Set an opening greeting for users.',

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@ -225,10 +225,10 @@ export default {
<i>Semua file PPT yang Anda unggah akan dipotong menggunakan metode ini secara otomatis, pengaturan untuk setiap file PPT tidak diperlukan.</i></p>`,
qa: `
<p>
Metode potongan ini mendukung format file <b>EXCEL</b> dan <b>CSV/TXT</b>.
Metode potongan ini mendukung format file <b>XLSX</b> dan <b>CSV/TXT</b>.
</p>
<li>
Jika file dalam format <b>Excel</b>, harus terdiri dari dua kolom
Jika file dalam format <b>XLSX</b>, harus terdiri dari dua kolom
tanpa header: satu untuk pertanyaan dan yang lainnya untuk jawaban, dengan
kolom pertanyaan mendahului kolom jawaban. Lembar kerja ganda dapat diterima selama kolom terstruktur dengan benar.
</li>
@ -251,7 +251,7 @@ export default {
maka Anda dapat mencantumkan semua kandidat yang memenuhi kualifikasi hanya dengan berbicara dengan <i>'assistxsuite'</i>.
</p>
`,
table: `<p>Format file yang didukung adalah <b>EXCEL</b> dan <b>CSV/TXT</b>.</p><p>
table: `<p>Format file yang didukung adalah <b>XLSX</b> dan <b>CSV/TXT</b>.</p><p>
Berikut beberapa tips:
<ul>
<li>Untuk file csv atau txt, pembatas antara kolom adalah <em><b>TAB</b></em>.</li>

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@ -226,10 +226,10 @@ export default {
<i>PPTファイルに自動的に適用されるため</i></p>`,
qa: `
<p>
<b>EXCEL</b><b>CSV/TXT</b>
<b>XLSX</b><b>CSV/TXT</b>
</p>
<li>
<b>Excel</b>2
<b>XLSX</b>2
11
@ -249,7 +249,7 @@ export default {
</p>
`,
table: `<p>対応ファイル形式は<b>EXCEL</b>および<b>CSV/TXT</b>です。</p><p>
table: `<p>対応ファイル形式は<b>XLSX</b>および<b>CSV/TXT</b>です。</p><p>
<ul>
<li>CSVまたはTXTファイルの場合<b>TAB</b></li>

View File

@ -254,8 +254,8 @@ export default {
presentation: `<p>Os formatos de arquivo suportados são <b>PDF</b>, <b>PPTX</b>.</p><p>
Cada página do slide é tratada como um fragmento, com sua imagem em miniatura armazenada.</p><p>
<i>Esse método de fragmentação é aplicado automaticamente a todos os arquivos PPT enviados, então não é necessário especificá-lo manualmente.</i></p>`,
qa: `<p>Este método suporta arquivos nos formatos <b>EXCEL</b> e <b>CSV/TXT</b>.</p>
<li>Se o arquivo estiver no formato <b>Excel</b>, ele deve conter duas colunas sem cabeçalhos: uma para perguntas e outra para respostas, com a coluna de perguntas antes da de respostas. Múltiplas planilhas são aceitas, desde que as colunas estejam corretamente estruturadas.</li>
qa: `<p>Este método suporta arquivos nos formatos <b>XLSX</b> e <b>CSV/TXT</b>.</p>
<li>Se o arquivo estiver no formato <b>XLSX</b>, ele deve conter duas colunas sem cabeçalhos: uma para perguntas e outra para respostas, com a coluna de perguntas antes da de respostas. Múltiplas planilhas são aceitas, desde que as colunas estejam corretamente estruturadas.</li>
<li>Se o arquivo estiver no formato <b>CSV/TXT</b>, ele deve estar codificado em UTF-8 e usar TAB como delimitador para separar perguntas e respostas.</li>
<p><i>Linhas de texto que não seguirem essas regras serão ignoradas, e cada par de Pergunta & Resposta será tratado como um fragmento distinto.</i></p>`,
useRaptor: 'Usar RAPTOR para melhorar a recuperação',

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@ -239,10 +239,10 @@ export default {
<i>Phương thức phân khối này đưc tự đng áp dụng cho tất cả các tệp PPT đưc tải lên, do đó bạn không cần phải chỉ đnh thủ công.</i></p>`,
qa: `
<p>
Phương thức phân khối này hỗ trợ các đnh dạng tệp <b>EXCEL</b> <b>CSV/TXT</b>.
Phương thức phân khối này hỗ trợ các đnh dạng tệp <b>XLSX</b> <b>CSV/TXT</b>.
</p>
<li>
Nếu tệp đnh dạng <b>Excel</b>, phải chứa hai cột
Nếu tệp đnh dạng <b>XLSX</b>, phải chứa hai cột
không tiêu đề: một cột cho câu hỏi cột còn lại cho câu trả lời, với
cột câu hỏi đng trước cột câu trả lời. Nhiều trang tính đưc chấp nhận, miễn các cột đưc cấu trúc chính xác.
</li>
@ -260,7 +260,7 @@ export default {
</p><p>
Các bản lịch với nhiều hình thức khác nhau đưc phân tích pháp tổ chức thành dữ liệu cấu trúc đ hỗ trợ nhà tuyển dụng tìm kiếm ng viên.
</p>`,
table: `<p>Các định dạng tệp được hỗ trợ là <b>EXCEL</b> và <b>CSV/TXT</b>.</p><p>
table: `<p>Các định dạng tệp được hỗ trợ là <b>XLSX</b> và <b>CSV/TXT</b>.</p><p>
Dưới đây một số điều kiện tiên quyết mẹo:
<ul>
<li>Đi với tệp CSV hoặc TXT, dấu phân cách giữa các cột phải <em><b>TAB</b></em>.</li>
@ -319,8 +319,8 @@ export default {
tag: `<p>Cơ sở kiến thức sử dụng 'Tag' làm phương pháp phân đoạn được cho là sẽ được sử dụng bởi các cơ sở kiến thức khác để thêm thẻ vào các đoạn của chúng, các truy vấn tới đó cũng sẽ có thẻ.</p>
<p> sở kiến thức sử dụng 'Tag' làm phương pháp phân đoạn <b>KHÔNG</b> đưc dự đnh tham gia vào quy trình RAG.</p>
<p>Các đoạn trong sở kiến thức này dụ về thẻ, thể hiện toàn bộ tập hợp thẻ mối quan hệ giữa đoạn thẻ.</p>
<p>Phương pháp phân đoạn này hỗ trợ đnh dạng tệp <b>EXCEL</b> <b>CSV/TXT</b>.</p>
<p>Nếu tệp đnh dạng <b>Excel</b>, phải chứa hai cột không tiêu đề: một cho nội dung một cho thẻ, với cột nội dung đng trước cột thẻ. Nhiều trang tính đưc chấp nhận, miễn các cột đưc cấu trúc đúng.</p>
<p>Phương pháp phân đoạn này hỗ trợ đnh dạng tệp <b>XLSX</b> <b>CSV/TXT</b>.</p>
<p>Nếu tệp đnh dạng <b>XLSX</b>, phải chứa hai cột không tiêu đề: một cho nội dung một cho thẻ, với cột nội dung đng trước cột thẻ. Nhiều trang tính đưc chấp nhận, miễn các cột đưc cấu trúc đúng.</p>
<p>Nếu tệp đnh dạng <b>CSV/TXT</b>, phải đưc hóa UTF-8 với TAB làm dấu phân cách đ phân tách nội dung thẻ.</p>
<p>Trong cột thẻ, dấu <b>phẩy</b> tiếng Anh giữa các thẻ.</p>
<i>Các dòng văn bản không tuân theo các quy tắc trên sẽ bị bỏ qua mỗi cặp sẽ đưc coi một đoạn riêng biệt.</i>`,

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@ -277,7 +277,7 @@ export default {
<i>'ragflow'</i>
</p>
`,
table: `支持<p><b>excel</b>和<b>csv/txt</b>格式文件。</p><p>以下是一些提示: <ul> <li>对于Csv或Txt文件列之间的分隔符为 <em><b>tab</b></em>。</li> <li>第一行必须是列标题。</li> <li>列标题必须是有意义的术语,以便我们的大語言模型能够理解。列举一些同义词时最好使用斜杠<i>'/'</i>来分隔,甚至更好使用方括号枚举值,例如 <i>“性別/性別(男性,女性)”</i>.<p>以下是标题的一些示例:<ol> <li>供应商/供货商<b>'tab'</b>顏色(黃色、紅色、棕色)<b>'tab'</b>性別(男、女)<b>'tab'</B>尺码m、l、xl、xxl</li> <li>姓名/名字<b>'tab'</b>電話/手機/微信<b>'tab'</b>最高学历高中职高硕士本科博士初中中技中专专科专升本mpambaemba</li> </ol> </p> </li> <li>表中的每一行都将被视为一个块。</li> </ul>`,
table: `支持<p><b>XLSX</b>和<b>csv/txt</b>格式文件。</p><p>以下是一些提示: <ul> <li>对于Csv或Txt文件列之间的分隔符为 <em><b>tab</b></em>。</li> <li>第一行必须是列标题。</li> <li>列标题必须是有意义的术语,以便我们的大語言模型能够理解。列举一些同义词时最好使用斜杠<i>'/'</i>来分隔,甚至更好使用方括号枚举值,例如 <i>“性別/性別(男性,女性)”</i>.<p>以下是标题的一些示例:<ol> <li>供应商/供货商<b>'tab'</b>顏色(黃色、紅色、棕色)<b>'tab'</b>性別(男、女)<b>'tab'</B>尺码m、l、xl、xxl</li> <li>姓名/名字<b>'tab'</b>電話/手機/微信<b>'tab'</b>最高学历高中职高硕士本科博士初中中技中专专科专升本mpambaemba</li> </ol> </p> </li> <li>表中的每一行都将被视为一个块。</li> </ul>`,
picture: `
<p></p><p>
OCR
@ -302,8 +302,8 @@ export default {
<p>使<b></b> RAG
<p>
<p><b>EXCEL</b><b>CSV/TXT</b>
<p> <b>Excel</b>
<p><b>XLSX</b><b>CSV/TXT</b>
<p> <b>XLSX</b>
<p><b>CSV/TXT</b>UTF-8TAB作為分隔符號來分隔內容和標籤
<p><b></b>
<i>

View File

@ -278,7 +278,7 @@ export default {
<i>'RAGFlow'</i>
</p>
`,
table: `支持<p><b>EXCEL</b>和<b>CSV/TXT</b>格式文件。</p><p>
table: `支持<p><b>XLSX</b>和<b>CSV/TXT</b>格式文件。</p><p>
<ul>
<li> csv txt <em><b>TAB</b></em></li>
@ -318,8 +318,8 @@ export default {
<p>使<b></b> RAG </p>
<p></p>
<p><b>EXCEL</b><b>CSV/TXT</b></p>
<p><b>Excel</b></p>
<p><b>XLSX</b><b>CSV/TXT</b></p>
<p><b>XLSX</b></p>
<p> <b>CSV/TXT</b> 使 UTF-8 TAB </p>
<p>使 <b></b></p>
<i></i>