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https://github.com/infiniflow/ragflow.git
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Add language portugese br (#4550)
### What problem does this PR solve? Add language Portugese from Brazil ### Type of change - [X] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Henrique
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README_zh.md
65
README_zh.md
@ -9,7 +9,8 @@
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<a href="./README_zh.md">简体中文</a> |
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<a href="./README_ja.md">日本語</a> |
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<a href="./README_ko.md">한국어</a> |
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<a href="./README_id.md">Bahasa Indonesia</a>
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<a href="./README_id.md">Bahasa Indonesia</a> |
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<a href="/README_pt_br.md">Português (Brasil)</a>
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</p>
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<p align="center">
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@ -30,7 +31,6 @@
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</a>
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</p>
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<h4 align="center">
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<a href="https://ragflow.io/docs/dev/">Document</a> |
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<a href="https://github.com/infiniflow/ragflow/issues/4214">Roadmap</a> |
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@ -46,12 +46,12 @@
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## 🎮 Demo 试用
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请登录网址 [https://demo.ragflow.io](https://demo.ragflow.io) 试用 demo。
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<div align="center" style="margin-top:20px;margin-bottom:20px;">
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<img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
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<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
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</div>
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## 🔥 近期更新
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- 2024-12-18 升级了 Deepdoc 的文档布局分析模型。
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@ -62,12 +62,13 @@
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- 2024-08-02 支持 GraphRAG 启发于 [graphrag](https://github.com/microsoft/graphrag) 和思维导图。
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## 🎉 关注项目
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⭐️点击右上角的 Star 关注RAGFlow，可以获取最新发布的实时通知 !🌟
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⭐️ 点击右上角的 Star 关注 RAGFlow，可以获取最新发布的实时通知 !🌟
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<div align="center" style="margin-top:20px;margin-bottom:20px;">
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<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
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</div>
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## 🌟 主要功能
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### 🍭 **"Quality in, quality out"**
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@ -154,11 +155,12 @@
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| ----------------- | --------------- | --------------------- | ------------------------ |
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| v0.15.1 | ≈9 | :heavy_check_mark: | Stable release |
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| v0.15.1-slim | ≈2 | ❌ | Stable release |
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| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
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| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
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| nightly | ≈9 | :heavy_check_mark: | _Unstable_ nightly build |
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| nightly-slim | ≈2 | ❌ | _Unstable_ nightly build |
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> [!TIP]
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> [!TIP]
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> 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。
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>
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> - 华为云镜像名：`swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow`
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> - 阿里云镜像名：`registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow`
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@ -171,17 +173,18 @@
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_出现以下界面提示说明服务器启动成功：_
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```bash
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____ ___ ______ ______ __
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____ ___ ______ ______ __
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/ __ \ / | / ____// ____// /____ _ __
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/ /_/ // /| | / / __ / /_ / // __ \| | /| / /
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/ _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
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/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
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/ _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /
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/_/ |_|/_/ |_|\____//_/ /_/ \____/ |__/|__/
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* Running on all addresses (0.0.0.0)
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* Running on http://127.0.0.1:9380
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* Running on http://x.x.x.x:9380
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INFO:werkzeug:Press CTRL+C to quit
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```
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> 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。
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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。
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@ -232,10 +235,9 @@ RAGFlow 默认使用 Elasticsearch 存储文本和向量数据. 如果要切换
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$ docker compose -f docker/docker-compose.yml up -d
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```
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> [!WARNING]
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> [!WARNING]
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> Infinity 目前官方并未正式支持在 Linux/arm64 架构下的机器上运行.
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## 🔧 源码编译 Docker 镜像（不含 embedding 模型）
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本 Docker 镜像大小约 2 GB 左右并且依赖外部的大模型和 embedding 服务。
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@ -258,53 +260,59 @@ docker build --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:night
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## 🔨 以源代码启动服务
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1. 安装 uv。如已经安装，可跳过本步骤：
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1. 安装 uv。如已经安装，可跳过本步骤：
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```bash
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pipx install uv
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export UV_INDEX=https://pypi.tuna.tsinghua.edu.cn/simple
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```
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2. 下载源代码并安装 Python 依赖：
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2. 下载源代码并安装 Python 依赖：
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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uv sync --python 3.10 --all-extras # install RAGFlow dependent python modules
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```
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3. 通过 Docker Compose 启动依赖的服务（MinIO, Elasticsearch, Redis, and MySQL）：
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3. 通过 Docker Compose 启动依赖的服务（MinIO, Elasticsearch, Redis, and MySQL）：
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```bash
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docker compose -f docker/docker-compose-base.yml up -d
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```
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在 `/etc/hosts` 中添加以下代码，将 **conf/service_conf.yaml** 文件中的所有 host 地址都解析为 `127.0.0.1`：
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在 `/etc/hosts` 中添加以下代码，将 **conf/service_conf.yaml** 文件中的所有 host 地址都解析为 `127.0.0.1`：
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```
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127.0.0.1 es01 infinity mysql minio redis
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```
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```
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4. 如果无法访问 HuggingFace，可以把环境变量 `HF_ENDPOINT` 设成相应的镜像站点：
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4. 如果无法访问 HuggingFace，可以把环境变量 `HF_ENDPOINT` 设成相应的镜像站点：
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```bash
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export HF_ENDPOINT=https://hf-mirror.com
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```
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5. 启动后端服务：
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5. 启动后端服务：
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```bash
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source .venv/bin/activate
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export PYTHONPATH=$(pwd)
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bash docker/launch_backend_service.sh
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```
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6. 安装前端依赖：
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6. 安装前端依赖：
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```bash
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cd web
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npm install
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```
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7. 启动前端服务：
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```bash
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npm run dev
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```
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```
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7. 启动前端服务：
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_以下界面说明系统已经成功启动：_
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```bash
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npm run dev
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```
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_以下界面说明系统已经成功启动：_
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@ -340,4 +348,3 @@ RAGFlow 只有通过开源协作才能蓬勃发展。秉持这一精神,我们
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<p align="center">
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<img src="https://github.com/infiniflow/ragflow/assets/7248/bccf284f-46f2-4445-9809-8f1030fb7585" width=50% height=50%>
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</p>
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