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* add new doc (#5175) Co-authored-by: dreamer6680 <146868355@qq.com> * Test docs (#5235) * fix: change the page of doc * chore: add new dependencies, update global styles/layout, optimize docs, add Feishu & GitHub icons, update API examples * fix: docs/index 404 not found * Update environment variable names, optimize styles, add new API routes, fix component styles, adjust documentation, and update GitHub and Feishu icons * update readme * feat: add a linkfastgpt compontent * feat: update new doc * fix:remove unuse page and redirect homepage to docs (#5288) * fix：remove some unuse doc * fix: redirect homepage to doc * git ignore * fix:navbar to index (#5295) * sidbar * fix: navtab unlight (#5298) * doc --------- Co-authored-by: dreamer6680 <1468683855@qq.com> Co-authored-by: dreamer6680 <146868355@qq.com>
2025-10-19 18:14:38 +00:00 · 2025-07-23 21:35:03 +08:00
parent ce9ec1bf57
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--- a/document/content/docs/introduction/development/custom-models/bge-rerank.mdx
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+---
+title: 接入 bge-rerank 重排模型
+description: 接入 bge-rerank 重排模型
+---
+
+## 不同模型推荐配置
+
+推荐配置如下：
+
+
+| 模型名 | 内存 | 显存 | 硬盘空间 | 启动命令 |
+|------|---------|---------|----------|--------------------------|
+| bge-reranker-base | >=4GB | >=4GB | >=8GB | python app.py |
+| bge-reranker-large | >=8GB | >=8GB | >=8GB | python app.py |
+| bge-reranker-v2-m3 | >=8GB | >=8GB | >=8GB | python app.py |
+
+
+## 源码部署
+
+### 1. 安装环境
+
+- Python 3.9, 3.10
+- CUDA 11.7
+- 科学上网环境
+
+### 2. 下载代码
+
+3 个模型代码分别为：
+
+1. [https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-base](https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-base)
+2. [https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-large](https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-large)
+3. [https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-v2-m3](https://github.com/labring/FastGPT/tree/main/plugins/model/rerank-bge/bge-reranker-v2-m3)
+
+### 3. 安装依赖
+
+```sh
+pip install -r requirements.txt
+```
+
+### 4. 下载模型
+
+3个模型的 huggingface 仓库地址如下：
+
+1. [https://huggingface.co/BAAI/bge-reranker-base](https://huggingface.co/BAAI/bge-reranker-base)
+2. [https://huggingface.co/BAAI/bge-reranker-large](https://huggingface.co/BAAI/bge-reranker-large)
+3. [https://huggingface.co/BAAI/bge-reranker-v2-m3](https://huggingface.co/BAAI/bge-reranker-v2-m3)
+
+在对应代码目录下 clone 模型。目录结构：
+
+```
+bge-reranker-base/
+app.py
+Dockerfile
+requirements.txt
+```
+
+### 5. 运行代码
+
+```bash
+python app.py
+```
+
+启动成功后应该会显示如下地址：
+
+![](/imgs/rerank1.png)
+
+> 这里的 `http://0.0.0.0:6006` 就是连接地址。
+
+## docker 部署
+
+**镜像名分别为:**
+
+1. registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-base:v0.1 (4 GB+)
+2. registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-large:v0.1 (5 GB+)
+3. registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-v2-m3:v0.1 (5 GB+)
+
+**端口**
+
+6006
+
+**环境变量**
+
+```
+ACCESS_TOKEN=访问安全凭证，请求时，Authorization: Bearer ${ACCESS_TOKEN}
+```
+
+**运行命令示例**
+
+```sh
+# auth token 为mytoken
+docker run -d --name reranker -p 6006:6006 -e ACCESS_TOKEN=mytoken --gpus all registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-base:v0.1
+```
+
+**docker-compose.yml示例**
+```
+version: "3"
+services:
+  reranker:
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/bge-rerank-base:v0.1
+    container_name: reranker
+    # GPU运行环境，如果宿主机未安装，将deploy配置隐藏即可
+    deploy:
+      resources:
+        reservations:
+          devices:
+          - driver: nvidia
+            count: all
+            capabilities: [gpu]
+    ports:
+      - 6006:6006
+    environment:
+      - ACCESS_TOKEN=mytoken
+
+```
+## 接入 FastGPT
+
+1. 打开 FastGPT 模型配置，新增一个重排模型。
+2. 填写模型配置表单：模型 ID 为`bge-reranker-base`，地址填写`{{host}}/v1/rerank`，host 为你部署的域名/IP:Port。
+
+![alt text](/imgs/image-102.png)
+
+## QA
+
+### 403报错
+
+FastGPT中，自定义请求 Token 和环境变量的 ACCESS_TOKEN 不一致。 
+
+### Docker 运行提示 `Bus error (core dumped)`
+
+尝试增加 `docker-compose.yml` 配置项 `shm_size` ，以增加容器中的共享内存目录大小。
+
+```
+...
+services:
+  reranker:
+    ...
+    container_name: reranker
+    shm_size: '2gb'
+    ...
+```