module 19 demo remove verify jon

Author: amalF

module-19-ci-cd/demo/.github/workflows/ci.yml

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+name: Deploy and Verify
+
+on:
+  push:
+    branches: [content]
+
+env:
+  ECR_REPOSITORY: ner-api
+  TASK_DEFINITION: ner-api
+  CONTAINER_NAME: ner-api
+  ECS_SERVICE: ner-api-service
+  ECS_CLUSTER: ner-api-cluster
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-session-token: ${{ secrets.AWS_SESSION_TOKEN }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - name: Download current task definition
+        run: |
+          aws ecs describe-task-definition \
+            --task-definition ${{ env.TASK_DEFINITION }} \
+            --query taskDefinition > task-definition.json
+
+      - name: Render ECS task definition with latest image
+        id: task-def
+        uses: aws-actions/amazon-ecs-render-task-definition@v1
+        with:
+          task-definition: task-definition.json
+          container-name: ${{ env.CONTAINER_NAME }}
+          image: ${{ secrets.ECR_REGISTRY }}/${{ env.ECR_REPOSITORY }}:latest
+
+      - name: Deploy to ECS
+        uses: aws-actions/amazon-ecs-deploy-task-definition@v2
+        with:
+          task-definition: ${{ steps.task-def.outputs.task-definition }}
+          service: ${{ env.ECS_SERVICE }}
+          cluster: ${{ env.ECS_CLUSTER }}
+          wait-for-service-stability: true
+
+

module-19-ci-cd/demo/Dockerfile

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+FROM python:3.12-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY main.py .
+
+EXPOSE 8000
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

module-19-ci-cd/demo/main.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from transformers import pipeline
+
+app = FastAPI()
+
+# Load the model
+MODEL_NAME = "elastic/distilbert-base-cased-finetuned-conll03-english"
+classifier = pipeline("ner", model=MODEL_NAME, aggregation_strategy="simple")
+
+
+class TextRequest(BaseModel):
+    text: str
+
+
+@app.post("/predict")
+async def predict(request: TextRequest):
+    if not request.text.strip():
+        raise HTTPException(status_code=400, detail="Text cannot be empty")
+
+    # Run NER inference
+    entities = classifier(request.text)
+
+    # Transformers returns objects that aren't always JSON-serializable
+    # (like numpy floats), so we clean them up
+    results = []
+    for entity in entities:
+        results.append(
+            {
+                "entity_group": entity["entity_group"],
+                "score": float(entity["score"]),
+                "word": entity["word"],
+                "start": entity["start"],
+                "end": entity["end"],
+            }
+        )
+
+    return {"entities": results}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="0.0.0.0", port=8000)

module-19-ci-cd/demo/requirements.txt

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+fastapi==0.110.0
+uvicorn==0.27.1
+transformers>=4.44.0
+torch>=2.4.0
+pillow==10.2.0
+python-multipart==0.0.9