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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
14 lines
396 B
YAML
14 lines
396 B
YAML
services:
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embedding-service:
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build:
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context: ../..
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dockerfile: examples/embedding_service/Dockerfile
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ports:
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- "8000:8000"
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healthcheck:
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test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health', timeout=5)"]
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interval: 10s
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timeout: 5s
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retries: 5
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start_period: 30s # Model loading time
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