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0e05c824e9
Add a complete example demonstrating dirty workers with sentence-transformers for text embeddings via FastAPI: - EmbeddingApp DirtyApp that loads and manages the ML model - FastAPI endpoints for /embed and /health - Docker and docker-compose configuration - Integration tests with numpy similarity checks - GitHub Actions CI workflow
43 lines
947 B
YAML
43 lines
947 B
YAML
name: Embedding Service Integration Tests
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on:
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push:
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paths:
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- 'examples/embedding_service/**'
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- 'gunicorn/dirty/**'
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pull_request:
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paths:
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- 'examples/embedding_service/**'
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- 'gunicorn/dirty/**'
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jobs:
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test:
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runs-on: ubuntu-latest
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timeout-minutes: 15
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steps:
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- uses: actions/checkout@v4
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- name: Build and start service
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run: |
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cd examples/embedding_service
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docker compose up -d --build
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docker compose logs -f &
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- name: Wait for healthy
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run: |
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for i in {1..30}; do
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curl -s http://127.0.0.1:8000/health && break
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sleep 2
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done
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- name: Run tests
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run: |
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pip install requests numpy
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python examples/embedding_service/test_embedding.py
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- name: Cleanup
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if: always()
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run: |
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cd examples/embedding_service
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docker compose down
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