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aigc-apps · Jul 31, 2024 · 05ad029 · 05ad029
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diff --git a/README.md b/README.md
@@ -162,7 +162,7 @@ To make it easier to use and save time on environment installation, we also prov
 - CPU
 
   ```bash
-  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2
+  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0
 
   # -p (port) -v (mount embedding and rerank model directories) -e (set environment variables, if using Dashscope LLM/Embedding, need to be introduced) -w (number of workers, can be specified as the approximate number of CPU cores)
   docker run --name pai_rag \
@@ -171,13 +171,13 @@ To make it easier to use and save time on environment installation, we also prov
               -v /your_local_documents_path:/data \
               -e DASHSCOPE_API_KEY=${DASHSCOPE_API_KEY} \
               -d \
-              mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2 gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
+              mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0 gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
   ```
 
 - GPU
 
   ```bash
-  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-gpu
+  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-gpu
 
   # -p (port) -v (mount embedding and rerank model directories) -e (set environment variables, if using Dashscope LLM/Embedding, you need to introduce it) -w (number of workers, which can be specified as the approximate number of CPU cores)
   docker run --name pai_rag \
@@ -187,7 +187,7 @@ To make it easier to use and save time on environment installation, we also prov
               --gpus all \
               -e DASHSCOPE_API_KEY=${DASHSCOPE_API_KEY} \
               -d \
-              mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-gpu gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
+              mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-gpu gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
   ```
 
 2. Load Data
@@ -211,17 +211,17 @@ To make it easier to use and save time on environment installation, we also prov
    Linux:
 
 ```bash
-docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 
-docker run --network host -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker run --network host -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 ```
 
 Mac/Windows:
 
 ```bash
-docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 
-docker run -p 8002:8002 -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui pai_rag ui -p 8002 -c http://host.docker.internal:8001/
+docker run -p 8002:8002 -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0_ui pai_rag ui -p 8002 -c http://host.docker.internal:8001/
 ```
 
 You can also open http://127.0.0.1:8002/ to configure the RAG service and upload local data.

diff --git a/README_zh.md b/README_zh.md
@@ -162,36 +162,36 @@ evaluation [-c src/pai_rag/config/settings.yaml] [-o False] [-t retrieval]
 - CPU
 
   ```bash
-  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2
+  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0
 
   # 启动: -p(端口) -v(挂载embedding和rerank模型目录) -e(设置环境变量，若使用Dashscope LLM/Embedding，需要引入) -w(worker数量，可以指定为近似cpu核数)
-  docker run -p 8001:8001 -v /huggingface:/huggingface -e DASHSCOPE_API_KEY=sk-xxxx -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2 gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
+  docker run -p 8001:8001 -v /huggingface:/huggingface -e DASHSCOPE_API_KEY=sk-xxxx -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0 gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
   ```
 
 - GPU
 
   ```bash
-  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-gpu
+  docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-gpu
 
   # 启动: -p(端口) -v(挂载embedding和rerank模型目录) -e(设置环境变量，若使用Dashscope LLM/Embedding，需要引入) -w(worker数量，可以指定为近似cpu核数)
-  docker run -p 8001:8001 -v /huggingface:/huggingface --gpus all -e DASHSCOPE_API_KEY=sk-xxxx -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-gpu gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
+  docker run -p 8001:8001 -v /huggingface:/huggingface --gpus all -e DASHSCOPE_API_KEY=sk-xxxx -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-gpu gunicorn -b 0.0.0.0:8001 -w 16 -k uvicorn.workers.UvicornH11Worker pai_rag.main:app
   ```
 
 2. 启动RAG WebUI
    Linux:
 
 ```bash
-docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 
-docker run --network host -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker run --network host -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 ```
 
 Mac/Windows:
 
 ```bash
-docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui
+docker pull mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui
 
-docker run -p 8002:8002 -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.0.2-ui pai_rag ui -p 8002 -c http://host.docker.internal:8001/
+docker run -p 8002:8002 -d mybigpai-public-registry.cn-beijing.cr.aliyuncs.com/mybigpai/pairag:0.1.0-ui pai_rag ui -p 8002 -c http://host.docker.internal:8001/
 ```
 
 ### 基于Dockerfile自行构建镜像