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update docs for release 0.8.0 (#1419)

### What problem does this PR solve?

update docs for release 0.8.0

### Type of change

- [x] Documentation Update

---------

Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com>
tags/v0.8.0
KevinHuSh 1 год назад
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+ 4
- 4
README.md Просмотреть файл

@@ -17,7 +17,7 @@
<a href="https://demo.ragflow.io" target="_blank">
<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:v0.7.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.7.0"></a>
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.8.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.8.0"></a>
<a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
</a>
@@ -64,16 +64,16 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
## 📌 Latest Updates
- 2024-07-08 Supports [Graph](./graph/README.md).
- 2024-06-27 Supports Markdown and Docx in the Q&A parsing method. Supports extracting images from Docx files. Supports extracting tables from Markdown files.
- 2024-06-14 Supports PDF in the Q&A parsing method.
- 2024-06-06 Supports [Self-RAG](https://huggingface.co/papers/2310.11511), which is enabled by default in dialog settings.
- 2024-05-30 Integrates [BCE](https://github.com/netease-youdao/BCEmbedding) and [BGE](https://github.com/FlagOpen/FlagEmbedding) reranker models.
- 2024-05-28 Supports LLM Baichuan and VolcanoArk.
- 2024-05-23 Supports [RAPTOR](https://arxiv.org/html/2401.18059v1) for better text retrieval.
- 2024-05-21 Supports streaming output and text chunk retrieval API.
- 2024-05-15 Integrates OpenAI GPT-4o.
- 2024-05-08 Integrates LLM DeepSeek-V2.
## 🌟 Key Features
@@ -150,7 +150,7 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
3. Build the pre-built Docker images and start up the server:
> Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_VERSION` in **docker/.env** to the intended version, for example `RAGFLOW_VERSION=v0.7.0`, before running the following commands.
> Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_VERSION` in **docker/.env** to the intended version, for example `RAGFLOW_VERSION=v0.8.0`, before running the following commands.
```bash
$ cd ragflow/docker

+ 7
- 7
README_ja.md Просмотреть файл

@@ -17,8 +17,8 @@
<a href="https://demo.ragflow.io" target="_blank">
<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:v0.7.0-brightgreen"
alt="docker pull infiniflow/ragflow:v0.7.0"></a>
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.8.0-brightgreen"
alt="docker pull infiniflow/ragflow:v0.8.0"></a>
<a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
</a>
@@ -45,15 +45,15 @@
## 📌 最新情報
- 2024-07-08 [Graph](./graph/README.md) に対応しました。.
- 2024-06-27 Q&A解析方式はMarkdownファイルとDocxファイルをサポートしています。Docxファイルからの画像の抽出をサポートします。Markdownファイルからテーブルを抽出することをサポートします。
- 2024-06-14 Q&A 解析メソッドは PDF ファイルをサポートしています。
- 2024-06-06 会話設定でデフォルトでチェックされている [Self-RAG](https://huggingface.co/papers/2310.11511) をサポートします。
- 2024-05-30 [BCE](https://github.com/netease-youdao/BCEmbedding)、[BGE](https://github.com/FlagOpen/FlagEmbedding) reranker を統合。
- 2024-05-30 [BCE](https://github.com/netease-youdao/BCEmbedding) 、[BGE](https://github.com/FlagOpen/FlagEmbedding) reranker を統合。
- 2024-05-28 LLM BaichuanとVolcanoArkを統合しました。
- 2024-05-23 より良いテキスト検索のために[RAPTOR](https://arxiv.org/html/2401.18059v1)をサポート。
- 2024-05-23 より良いテキスト検索のために [RAPTOR](https://arxiv.org/html/2401.18059v1) をサポート。
- 2024-05-21 ストリーミング出力とテキストチャンク取得APIをサポート。
- 2024-05-15 OpenAI GPT-4oを統合しました。
- 2024-05-08 LLM DeepSeek-V2を統合しました。
## 🌟 主な特徴
@@ -136,7 +136,7 @@
$ docker compose up -d
```
> 上記のコマンドを実行すると、RAGFlowの開発版dockerイメージが自動的にダウンロードされます。 特定のバージョンのDockerイメージをダウンロードして実行したい場合は、docker/.envファイルのRAGFLOW_VERSION変数を見つけて、対応するバージョンに変更してください。 例えば、RAGFLOW_VERSION=v0.7.0として、上記のコマンドを実行してください。
> 上記のコマンドを実行すると、RAGFlowの開発版dockerイメージが自動的にダウンロードされます。 特定のバージョンのDockerイメージをダウンロードして実行したい場合は、docker/.envファイルのRAGFLOW_VERSION変数を見つけて、対応するバージョンに変更してください。 例えば、RAGFLOW_VERSION=v0.8.0として、上記のコマンドを実行してください。
> コアイメージのサイズは約 9 GB で、ロードに時間がかかる場合があります。
@@ -198,7 +198,7 @@
```bash
$ git clone https://github.com/infiniflow/ragflow.git
$ cd ragflow/
$ docker build -t infiniflow/ragflow:v0.7.0 .
$ docker build -t infiniflow/ragflow:v0.8.0 .
$ cd ragflow/docker
$ chmod +x ./entrypoint.sh
$ docker compose up -d

+ 4
- 4
README_zh.md Просмотреть файл

@@ -17,7 +17,7 @@
<a href="https://demo.ragflow.io" target="_blank">
<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:v0.7.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.7.0"></a>
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.8.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.8.0"></a>
<a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
</a>
@@ -45,6 +45,7 @@

## 📌 近期更新

- 2024-07-08 支持 [Graph](./graph/README.md)。
- 2024-06-27 Q&A 解析方式支持 Markdown 文件和 Docx 文件。支持提取出 Docx 文件中的图片。支持提取出 Markdown 文件中的表格。
- 2024-06-14 Q&A 解析方式支持 PDF 文件。
- 2024-06-06 支持 [Self-RAG](https://huggingface.co/papers/2310.11511) ,在对话设置里面默认勾选。
@@ -53,7 +54,6 @@
- 2024-05-23 实现 [RAPTOR](https://arxiv.org/html/2401.18059v1) 提供更好的文本检索。
- 2024-05-21 支持流式结果输出和文本块获取API。
- 2024-05-15 集成大模型 OpenAI GPT-4o。
- 2024-05-08 集成大模型 DeepSeek。

## 🌟 主要功能

@@ -136,7 +136,7 @@
$ docker compose -f docker-compose-CN.yml up -d
```

> 请注意,运行上述命令会自动下载 RAGFlow 的开发版本 docker 镜像。如果你想下载并运行特定版本的 docker 镜像,请在 docker/.env 文件中找到 RAGFLOW_VERSION 变量,将其改为对应版本。例如 RAGFLOW_VERSION=v0.7.0,然后运行上述命令。
> 请注意,运行上述命令会自动下载 RAGFlow 的开发版本 docker 镜像。如果你想下载并运行特定版本的 docker 镜像,请在 docker/.env 文件中找到 RAGFLOW_VERSION 变量,将其改为对应版本。例如 RAGFLOW_VERSION=v0.8.0,然后运行上述命令。

> 核心镜像文件大约 9 GB,可能需要一定时间拉取。请耐心等待。

@@ -198,7 +198,7 @@
```bash
$ git clone https://github.com/infiniflow/ragflow.git
$ cd ragflow/
$ docker build -t infiniflow/ragflow:v0.7.0 .
$ docker build -t infiniflow/ragflow:v0.8.0 .
$ cd ragflow/docker
$ chmod +x ./entrypoint.sh
$ docker compose up -d

+ 1
- 1
docs/guides/configure_knowledge_base.md Просмотреть файл

@@ -124,7 +124,7 @@ RAGFlow uses multiple recall of both full-text search and vector search in its c

## Search for knowledge base

As of RAGFlow v0.7.0, the search feature is still in a rudimentary form, supporting only knowledge base search by name.
As of RAGFlow v0.8.0, 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)


+ 3
- 3
docs/guides/manage_files.md Просмотреть файл

@@ -45,11 +45,11 @@ You can link your file to one knowledge base or multiple knowledge bases at one

## Move file to specified folder

As of RAGFlow v0.7.0, this feature is *not* available.
As of RAGFlow v0.8.0, this feature is *not* available.

## Search files or folders

As of RAGFlow v0.7.0, the search feature is still in a rudimentary form, supporting only file and folder search in the current directory by name (files or folders in the child directory will not be retrieved).
As of RAGFlow v0.8.0, the search feature is still in a rudimentary form, supporting only file and folder search in the current directory by name (files or folders in the child directory will not be retrieved).

![search file](https://github.com/infiniflow/ragflow/assets/93570324/77ffc2e5-bd80-4ed1-841f-068e664efffe)

@@ -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 v0.7.0, bulk download is not supported, nor can you download an entire folder.
> As of RAGFlow v0.8.0, bulk download is not supported, nor can you download an entire folder.

+ 2
- 2
docs/quickstart.mdx Просмотреть файл

@@ -34,7 +34,7 @@ This section provides instructions on setting up the RAGFlow server on Linux. If

`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.

RAGFlow v0.7.0 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 v0.8.0 uses Elasticsearch for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning of the Elasticsearch component.

<Tabs
defaultValue="linux"
@@ -132,7 +132,7 @@ This section provides instructions on setting up the RAGFlow server on Linux. If

3. Build the pre-built Docker images and start up the server:

> Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_VERSION` in **docker/.env** to the intended version, for example `RAGFLOW_VERSION=v0.7.0`, before running the following commands.
> Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_VERSION` in **docker/.env** to the intended version, for example `RAGFLOW_VERSION=v0.8.0`, before running the following commands.

```bash
$ cd ragflow/docker

+ 10
- 6
graph/canvas.py Просмотреть файл

@@ -204,7 +204,8 @@ class Canvas(ABC):
cpn = self.get_component(cpn_id)
if not cpn["downstream"]: break

if self._find_loop(): raise OverflowError("Too much loops!")
loop = self._find_loop()
if loop: raise OverflowError(f"Too much loops: {loop}")

if cpn["obj"].component_name.lower() in ["switch", "categorize", "relevant"]:
switch_out = cpn["obj"].output()[1].iloc[0, 0]
@@ -277,15 +278,18 @@ class Canvas(ABC):

if len(path) < 2: return False

for l in range(1, len(path) // 2):
for l in range(2, len(path) // 2):
pat = ",".join(path[0:l])
path_str = ",".join(path)
if len(pat) >= len(path_str): return False
path_str = path_str[len(pat):]
loop = max_loops
while path_str.find(pat) >= 0 and loop >= 0:
while path_str.find(pat) == 0 and loop >= 0:
loop -= 1
path_str = path_str[len(pat):]
if loop < 0: return True
if len(pat)+1 >= len(path_str):
return False
path_str = path_str[len(pat)+1:]
if loop < 0:
pat = " => ".join([p.split(":")[0] for p in path[0:l]])
return pat + " => " + pat

return False

+ 1
- 1
graph/component/categorize.py Просмотреть файл

@@ -38,7 +38,7 @@ class CategorizeParam(GenerateParam):
self.check_empty(self.category_description, "[Categorize] Category examples")
for k, v in self.category_description.items():
if not k: raise ValueError(f"[Categorize] Category name can not be empty!")
if not v["to"]: raise ValueError(f"[Categorize] 'To' of category {k} can not be empty!")
if not v.get("to"): raise ValueError(f"[Categorize] 'To' of category {k} can not be empty!")

def get_prompt(self):
cate_lines = []

+ 4
- 1
graph/component/generate.py Просмотреть файл

@@ -72,7 +72,10 @@ class Generate(ComponentBase):
for para in self._param.parameters:
cpn = self._canvas.get_component(para["component_id"])["obj"]
_, out = cpn.output(allow_partial=False)
kwargs[para["key"]] = "\n - ".join(out["content"])
if "content" not in out.columns:
kwargs[para["key"]] = "Nothing"
else:
kwargs[para["key"]] = "\n - ".join(out["content"])

kwargs["input"] = input
for n, v in kwargs.items():

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