ok

.gitea/workflows/build.yaml

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+name: Build
+run-name: ${{ github.actor }} is upgrade release 🚀
+on: [push]
+env:
+  REPOSITORY: ${{ github.repository }}
+  COMMIT_ID: ${{ github.sha }}
+jobs:
+  Build-Deploy-Actions:
+    runs-on: ubuntu-latest
+    steps:
+      - run: echo "🎉 The job was automatically triggered by a ${{ github.event_name }} event."
+      - run: echo "🐧 This job is now running on a ${{ runner.os }} server hosted by Gitea!"
+      - run: echo "🔎 The name of your branch is ${{ github.ref }} and your repository is ${{ github.repository }}."
+      - name: Check out repository code
+        uses: actions/checkout@v3
+      -
+        name: Setup Git LFS
+        run: |
+          git lfs install
+          git lfs fetch
+          git lfs checkout                    
+      - name: List files in the repository
+        run: |
+                                        ls ${{ github.workspace }}
+      -
+        name: Docker Image Info
+        id: image-info
+        run: |
+          echo "::set-output name=image_name::$(echo $REPOSITORY | tr '[:upper:]' '[:lower:]')"
+          echo "::set-output name=image_tag::${COMMIT_ID:0:10}"                    
+      -
+        name: Login to Docker Hub
+        uses: docker/login-action@v2
+        with:
+          registry: artifacts.iflytek.com
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v2
+      -
+        name: Build and push
+        run: |
+          docker version
+          docker buildx build -t artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }} . --file ${{ github.workspace }}/Dockerfile --load
+          docker push artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }}
+          docker rmi artifacts.iflytek.com/docker-private/atp/${{ steps.image-info.outputs.image_name }}:${{ steps.image-info.outputs.image_tag }}                    
+      - run: echo "🍏 This job's status is ${{ job.status }}."

Dockerfile

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+#FROM python:3.8.13
+FROM artifacts.iflytek.com/docker-private/atp/base_image_for_ailab:0.0.1
+
+WORKDIR /app
+
+COPY . /app
+
+RUN pip config set global.index-url https://pypi.mirrors.ustc.edu.cn/simple 
+#RUN pip install -r requirements.txt
+
+CMD ["python", "app.py"]

app.py

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+import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoConfig, AutoModelForSequenceClassification
+
+from gradio.themes.utils import sizes
+theme = gr.themes.Default(radius_size=sizes.radius_none).set(
+    block_label_text_color = '#4D63FF',
+    block_title_text_color = '#4D63FF',
+    button_primary_text_color = '#4D63FF',
+    button_primary_background_fill='#FFFFFF',
+    button_primary_border_color='#4D63FF',
+    button_primary_background_fill_hover='#EDEFFF',
+)
+
+modelName="Seethal/sentiment_analysis_generic_dataset"
+
+tokenizer = AutoTokenizer.from_pretrained(modelName)
+model = AutoModelForSequenceClassification.from_pretrained(modelName)
+sentimentPipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+Label2Des = {
+    "LABEL_0": "NEGATIVE",
+    "LABEL_1": "NEUTRAL",
+    "LABEL_2": "POSITIVE"
+}
+
+def sentiment_analysis(text):
+    results = sentimentPipeline(text)
+
+    return f"Sentiment: {Label2Des.get(results[0]['label'])}, Score: {results[0]['score']:.2f}" 
+    
+demo = gr.Interface(fn=sentiment_analysis, 
+                    inputs='text', 
+                    outputs='text',
+                    theme = theme,
+                    title = "文本情感分析"
+                    )
+
+
+if __name__ == "__main__":
+    demo.queue(concurrency_count=10)
+    demo.launch(server_name = "0.0.0.0")