我已经在我的requirements.txt中添加了google-cloud-storage，我的azure函数Http存储库位于如下文件夹结构中：

• Init.py和function.json在HttpTrigger文件夹中，其余文件在HttpTrigger文件夹外的根目录中，包括requirements.txt：-*

现在，我使用Functions Premium计划创建了Azure Function应用程序，并选择了Python 3.10：

在我的函数应用部署之后，我去了部署中心，将我的函数连接到上面的github存储库，并启动了github工作流：

我的Github工作流程：-

你可以在这里找到我的Github工作流程

name: Build and deploy Python project to Azure Function App - siliconfunc1

on:
  push:
    branches:
      - main
  workflow_dispatch:

env:
  AZURE_FUNCTIONAPP_PACKAGE_PATH: '.' # set this to the path to your web app project, defaults to the repository root
  PYTHON_VERSION: '3.10' # set this to the python version to use (supports 3.6, 3.7, 3.8)

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout repository
        uses: actions/checkout@v2

      - name: Setup Python version
        uses: actions/setup-python@v1
        with:
          python-version: ${{ env.PYTHON_VERSION }}

      - name: Create and start virtual environment
        run: |
          python -m venv venv
          source venv/bin/activate
      - name: Install dependencies
        run: pip install -r requirements.txt
        
      # Optional: Add step to run tests here

      - name: Upload artifact for deployment job
        uses: actions/upload-artifact@v2
        with:
          name: python-app
          path: |
            . 
            !venv/
  deploy:
    runs-on: ubuntu-latest
    needs: build
    environment:
      name: 'Production'
      url: ${{ steps.deploy-to-function.outputs.webapp-url }}

    steps:
      - name: Download artifact from build job
        uses: actions/download-artifact@v2
        with:
          name: python-app
          path: .

      - name: 'Deploy to Azure Functions'
        uses: Azure/functions-action@v1
        id: deploy-to-function
        with:
          app-name: 'siliconfunc1'
          slot-name: 'Production'
          package: ${{ env.AZURE_FUNCTIONAPP_PACKAGE_PATH }}
          publish-profile: ${{ secrets.AZUREAPPSERVICE_PUBLISHPROFILE_D29DD8E1DA1B41A68C550903EEF23B74 }}
          scm-do-build-during-deployment: true
          enable-oryx-build: true

输出：-

• HttpTrigger成功部署，当我运行该函数时，我收到了与您相同的错误代码。但是，当我检查日志时，我看到了一个与protobuf包相关的错误，该错误限制了Azure Function HttpTrigger成功运行，请参阅以下内容：-***
  错误：-

2023-06-15T08:21:20.763 [Error] TypeError: Descriptors cannot not be created directly.
2023-06-15T08:21:20.826 [Information] If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
2023-06-15T08:21:20.827 [Information] If you cannot immediately regenerate your protos, some other possible workarounds are:
2023-06-15T08:21:20.827 [Information] 1. Downgrade the protobuf package to 3.20.x or lower.
2023-06-15T08:21:20.827 [Information] 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

我引用了Kushan Gunasekara的SO thread answer，并在requirements.txt中添加了protobuf==3.20. 沿着google-cloud-storage，并再次运行了部署，HttpTrigger部署后成功运行，参考如下：-*
我的更新需求.txt：-

azure-functions
protobuf==3.20.*
google-cloud-storage