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>

README.md

     <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>
 
 ## 📌 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
 
 
 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

README_ja.md

     <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>
 
 
 ## 📌 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
 
    $ 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。
 
 ```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

README_zh.md

     <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>
 
 ## 📌 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。
 - 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
 
    $ 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。
 
 ```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

docs/guides/configure_knowledge_base.md

 
 ## 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)
 

docs/guides/manage_files.md

 
 ## 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)
 
 
 ![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. 

docs/quickstart.mdx

 
    `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"
 
 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

graph/canvas.py

             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]
 
         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

graph/component/categorize.py

         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 = []

graph/component/generate.py

         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():