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@@ -11,9 +11,9 @@ This project provides a high-stability serving solution, consisting of two main
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**Note: This project relies on the following environment configurations:**
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-- **Operating System**: Linux
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-- **Docker Version**: `>= 20.10.0` (Used for image building and deployment)
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- **CPU Architecture**: x86-64
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+- **Operating System**: Linux
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+- **Docker Engine Version**: `>= 20.10.0` (Used for image building and deployment)
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This document mainly introduces how to set up a high stability serving environment and package related materials using the scripts provided by this project. The overall process consists of two main stages:
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@@ -32,13 +32,13 @@ Image Building Steps:
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1. Build a requirement collection image. (Optional)
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2. Freeze requirement versions to improve the reproducibility of deployment image building. (Optional)
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-3. Build the deployment image based on the frozen requirement information to generate the final deployment image and provide image support for subsequent pipeline execution.
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+3. Build the deployment image based on the frozen requirement information to generate the final deployment image and provide image support for subsequent pipeline execution.
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**If you do not need to modify requirement-related information, you can skip to [1.3 Building Image](./README_en.md#13-building-image) to build the deployment image using cached requirement information.**
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## 1.1 Build the Requirement Collection Image (Optional)
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-Navigate to the `server_env` directory and run follow script for building the requirement collection image in this directory.
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+Navigate to the `server_env` directory and run follow script for building the requirement collection image in this directory.
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```bash
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./scripts/prepare_rc_image.sh
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@@ -121,10 +121,10 @@ If the basic image cannot be pulled, please refer to the solutions in the [FAQ](
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After run successfully, the command line will display the following message:
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```text
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- => => exporting to image
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- => => exporting layers
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- => => writing image sha256:ba3d0b2b079d63ee0239a99043fec7e25f17bf2a7772ec2fc80503c1582b3459
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- => => naming to ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlex/hps:latest-gpu
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+ => => exporting to image
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+ => => exporting layers
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+ => => writing image sha256:ba3d0b2b079d63ee0239a99043fec7e25f17bf2a7772ec2fc80503c1582b3459
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+ => => naming to ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlex/hps:latest-gpu
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```
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To build both GPU and CPU images run the following command:
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@@ -140,7 +140,7 @@ This stage mainly introduces how to package pipeline materials. This function is
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- `client`: Responsible for invoking the model services.
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- `server`: Deployed using the images built in [1. Image Building](./README_en.md#1-image-building), serving as the runtime environment for model services.
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-Before packaging the pipeline materials, you need to switch to the `sdk` directory and run the `scripts/assemble.sh` script in this directory for packaging. For example, to package the general OCR pipeline, run:
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+Before packaging the pipeline materials, you need to switch to the `sdk` directory and run the `scripts/assemble.sh` script in this directory for packaging. For example, to package the general OCR pipeline, run:
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```bash
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./scripts/assemble.sh OCR
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@@ -175,7 +175,7 @@ The parameters for the packaging script are described as follows:
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</tbody>
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</table>
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-After run successfully, the packaged will be stored in the `/output` directory.
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+After run successfully, the packaged will be stored in the `output` directory.
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## 3. FAQ
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@@ -191,4 +191,4 @@ When running the image build scripts, you can use the `-p` parameter to specify
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```bash
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./scripts/prepare_rc_image.sh -p https://pypi.tuna.tsinghua.edu.cn/simple
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-```
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+```
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