diff --git a/README.md b/README.md index b261c7982..54408d041 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,9 @@
-ragflow logo +ragflow logo
-

English | 简体中文 @@ -26,27 +25,32 @@ [RAGFlow](http://demo.ragflow.io) is an open-source, Retrieval-Augmented Generation engine built on large language models (LLM), deep document understanding, and multiple recall. It offers a streamlined RAG workflow for businesses of any scale, providing truthful responses with solid citations through a generative AI knowledge management platform. ## 🌟 Key Features - + ### 🍭 **"Quality in, quality out"** - - Deep document understanding-based knowledge extraction from unstructured data with complicated formats. - - Finds "needle in a data haystack" of literally unlimited tokens. + +- Deep document understanding-based knowledge extraction from unstructured data with complicated formats. +- Finds "needle in a data haystack" of literally unlimited tokens. ### 🍱 **Template-based chunking** - - Intelligent and explainable. - - Plenty of template options to choose from. + +- Intelligent and explainable. +- Plenty of template options to choose from. ### 🌱 **Grounded citations with reduced hallucinations** - - Visualization of text chunking to allow human intervention. - - Quick view of the key references and traceable citations to support grounded answers. + +- Visualization of text chunking to allow human intervention. +- Quick view of the key references and traceable citations to support grounded answers. ### 🍔 **Compatibility with heterogeneous data sources** - - Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more. + +- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more. ### 🛀 **Automated and effortless RAG workflow** - - Streamlined RAG orchestration catered to both personal and large businesses. - - Configurable LLMs as well as embedding models. - - Multiple recall paired with fused re-ranking. - - Intuitive APIs for seamless integration with business. + +- Streamlined RAG orchestration catered to both personal and large businesses. +- Configurable LLMs as well as embedding models. +- Multiple recall paired with fused re-ranking. +- Intuitive APIs for seamless integration with business. ## 🔎 System Architecture @@ -65,11 +69,11 @@ ### 🚀 Start up the server -1. Ensure `vm.max_map_count` > 65535: +1. Ensure `vm.max_map_count` > 65535: > To check the value of `vm.max_map_count`: > - > ```bash + > ```bash > $ sysctl vm.max_map_count > ``` > @@ -92,7 +96,7 @@ $ git clone https://github.com/infiniflow/ragflow.git ``` -3. Build the pre-built Docker images and start up the server: +3. Build the pre-built Docker images and start up the server: ```bash $ cd ragflow/docker @@ -102,31 +106,33 @@ > The core image is about 15 GB in size and may take a while to load. 4. Check the server status after having the server up and running: + ```bash $ docker logs -f ragflow-server ``` - *The following output confirms a successful launch of the system:* + + _The following output confirms a successful launch of the system:_ ```bash - ____ ______ __ + ____ ______ __ / __ \ ____ _ ____ _ / ____// /____ _ __ / /_/ // __ `// __ `// /_ / // __ \| | /| / / - / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ / - /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/ - /____/ - + / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ / + /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/ + /____/ + * Running on all addresses (0.0.0.0) * Running on http://127.0.0.1:9380 * Running on http://172.22.0.5:9380 INFO:werkzeug:Press CTRL+C to quit - ``` + ``` 5. In your web browser, enter the IP address of your server as prompted and log in to RAGFlow. 6. In [service_conf.yaml](./docker/service_conf.yaml), select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with the corresponding API key. - > See [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md) for more information. - - *The show is now on!* + > See [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md) for more information. + + _The show is now on!_ ## 🔧 Configurations @@ -136,14 +142,14 @@ When it comes to system configurations, you will need to manage the following fi - [service_conf.yaml](./docker/service_conf.yaml): Configures the back-end services. - [docker-compose.yml](./docker/docker-compose.yml): The system relies on [docker-compose.yml](./docker/docker-compose.yml) to start up. -You must ensure that changes to the [.env](./docker/.env) file are in line with what are in the [service_conf.yaml](./docker/service_conf.yaml) file. +You must ensure that changes to the [.env](./docker/.env) file are in line with what are in the [service_conf.yaml](./docker/service_conf.yaml) file. > The [./docker/README](./docker/README.md) file provides a detailed description of the environment settings and service configurations, and you are REQUIRED to ensure that all environment settings listed in the [./docker/README](./docker/README.md) file are aligned with the corresponding configurations in the [service_conf.yaml](./docker/service_conf.yaml) file. To update the default serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80` to `:80`. > Updates to all system configurations require a system reboot to take effect: -> +> > ```bash > $ docker-compose up -d > ``` @@ -171,4 +177,4 @@ See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162) ## 🙌 Contributing -RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md) first. +RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md) first. diff --git a/README_zh.md b/README_zh.md index 2448d6150..c6c2b8acd 100644 --- a/README_zh.md +++ b/README_zh.md @@ -1,10 +1,9 @@

-ragflow logo +ragflow logo
-

English | 简体中文 @@ -26,27 +25,32 @@ [RAGFlow](http://demo.ragflow.io) 是一款基于大型语言模型（LLM）以及深度文档理解构建的开源检索增强型生成引擎（Retrieval-Augmented Generation Engine）。RAGFlow 可以为各种规模的企业提供一套精简的 RAG 工作流程,通过生成式 AI （Generative AI）知识管理平台提供可靠的问答以及有理有据的引用。 ## 🌟 主要功能 - + ### 🍭 **"Quality in, quality out"** - - 基于深度文档理解，能够从各类复杂格式的非结构化数据中提取真知灼见。 - - 真正在无限上下文（token）的场景下快速完成大海捞针测试。 + +- 基于深度文档理解，能够从各类复杂格式的非结构化数据中提取真知灼见。 +- 真正在无限上下文（token）的场景下快速完成大海捞针测试。 ### 🍱 **基于模板的文本切片** - - 不仅仅是智能，更重要的是可控可解释。 - - 多种文本模板可供选择 + +- 不仅仅是智能，更重要的是可控可解释。 +- 多种文本模板可供选择 ### 🌱 **有理有据、最大程度降低幻觉（hallucination）** - - 文本切片过程可视化，支持手动调整。 - - 有理有据：答案提供关键引用的快照并支持追根溯源。 + +- 文本切片过程可视化，支持手动调整。 +- 有理有据：答案提供关键引用的快照并支持追根溯源。 ### 🍔 **兼容各类异构数据源** - - 支持丰富的文件类型，包括 Word 文档、PPT、excel 表格、txt 文件、图片、PDF、影印件、复印件、结构化数据, 网页等。 + +- 支持丰富的文件类型，包括 Word 文档、PPT、excel 表格、txt 文件、图片、PDF、影印件、复印件、结构化数据, 网页等。 ### 🛀 **全程无忧、自动化的 RAG 工作流** - - 全面优化的 RAG 工作流可以支持从个人应用乃至超大型企业的各类生态系统。 - - 大语言模型 LLM 以及向量模型均支持配置。 - - 基于多路召回、融合重排序。 - - 提供易用的 API，可以轻松集成到各类企业系统。 + +- 全面优化的 RAG 工作流可以支持从个人应用乃至超大型企业的各类生态系统。 +- 大语言模型 LLM 以及向量模型均支持配置。 +- 基于多路召回、融合重排序。 +- 提供易用的 API，可以轻松集成到各类企业系统。 ## 🔎 系统架构 @@ -69,7 +73,7 @@ > 如需确认 `vm.max_map_count` 的大小： > - > ```bash + > ```bash > $ sysctl vm.max_map_count > ``` > @@ -102,32 +106,38 @@ > 核心镜像文件大约 15 GB，可能需要一定时间拉取。请耐心等待。 4. 服务器启动成功后再次确认服务器状态： + ```bash $ docker logs -f ragflow-server ``` - *出现以下界面提示说明服务器启动成功：* + + _出现以下界面提示说明服务器启动成功：_ ```bash - ____ ______ __ + ____ ______ __ / __ \ ____ _ ____ _ / ____// /____ _ __ / /_/ // __ `// __ `// /_ / // __ \| | /| / / - / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ / - /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/ - /____/ - + / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ / + /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/ + /____/ + * Running on all addresses (0.0.0.0) * Running on http://127.0.0.1:9380 * Running on http://172.22.0.5:9380 INFO:werkzeug:Press CTRL+C to quit - ``` + ``` 5. 根据刚才的界面提示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://172.22.0.5 即可：端口 9380 已通过 Docker 端口映射被设置成 80（默认的 HTTP 服务端口）。 -7. 在 [service_conf.yaml](./docker/service_conf.yaml) 文件的 `user_default_llm` 栏配置 LLM factory，并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。 - > 详见 [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md)。 - - *好戏开始，接着奏乐接着舞！* +6. 在 [service_conf.yaml](./docker/service_conf.yaml) 文件的 `user_default_llm` 栏配置 LLM factory，并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。 + > 详见 [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md)。 + + _好戏开始，接着奏乐接着舞！_ + + > 详见 [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md)。 + + _好戏开始，接着奏乐接着舞！_ ## 🔧 系统配置 @@ -137,14 +147,14 @@ - [service_conf.yaml](./docker/service_conf.yaml)：配置各类后台服务。 - [docker-compose-CN.yml](./docker/docker-compose-CN.yml): 系统依赖该文件完成启动。 -请务必确保 [.env](./docker/.env) 文件中的变量设置与 [service_conf.yaml](./docker/service_conf.yaml) 文件中的配置保持一致！ +请务必确保 [.env](./docker/.env) 文件中的变量设置与 [service_conf.yaml](./docker/service_conf.yaml) 文件中的配置保持一致！ > [./docker/README](./docker/README.md) 文件提供了环境变量设置和服务配置的详细信息。请**一定要**确保 [./docker/README](./docker/README.md) 文件当中列出来的环境变量的值与 [service_conf.yaml](./docker/service_conf.yaml) 文件当中的系统配置保持一致。 如需更新默认的 HTTP 服务端口(80), 可以在 [docker-compose-CN.yml](./docker/docker-compose-CN.yml) 文件中将配置 `80:80` 改为 `:80`。 > 所有系统配置都需要通过系统重启生效： -> +> > ```bash > $ docker compose up -f docker-compose-CN.yml -d > ``` @@ -172,4 +182,4 @@ $ docker compose up -d ## 🙌 贡献指南 -RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们欢迎来自社区的各种贡献。如果您有意参与其中,请查阅我们的[贡献者指南](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md)。 +RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们欢迎来自社区的各种贡献。如果您有意参与其中,请查阅我们的[贡献者指南](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md)。 diff --git a/web/src/assets/logo-with-text.png b/web/src/assets/logo-with-text.png new file mode 100644 index 000000000..b55b5e042 Binary files /dev/null and b/web/src/assets/logo-with-text.png differ diff --git a/web/src/layouts/components/header/index.tsx b/web/src/layouts/components/header/index.tsx index c8f2403f5..4dc01915f 100644 --- a/web/src/layouts/components/header/index.tsx +++ b/web/src/layouts/components/header/index.tsx @@ -55,7 +55,7 @@ const RagHeader = () => { > - RagFlow + RAGFlow { - + {/* - - - - + */} diff --git a/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx b/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx index f772eb25a..1f4e05fea 100644 --- a/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx +++ b/web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx @@ -62,7 +62,7 @@ const ConfigurationForm = ({ form }: { form: FormInstance }) => {

- Once registered, an account cannot be changed and can only be - cancelled. + Once registered, E-mail cannot be changed.