f353e00172
- Restructure .env.example with security-focused documentation, service-specific environment file references, and AWS Secrets Manager integration - Update CLI tests workflow to single Python 3.13 version, add pytest-mock dependency, and consolidate test execution with coverage - Add comprehensive security validation to package publishing workflow with manual approval gates, secret scanning, and release
50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
#!/usr/bin/env python3
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"""
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API Migration Example
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Shows how to migrate FastAPI endpoints to use the new abstraction layer.
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"""
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# BEFORE (CUDA-specific API)
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# from fastapi_cuda_zk_api import ProductionCUDAZKAPI
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#
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# cuda_api = ProductionCUDAZKAPI()
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# if not cuda_api.initialized:
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# raise HTTPException(status_code=500, detail="CUDA not available")
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# AFTER (Backend-agnostic API)
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from gpu_acceleration import GPUAccelerationManager, create_gpu_manager
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import numpy as np
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app = FastAPI(title="Refactored GPU API")
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# Initialize GPU manager (auto-detects best backend)
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gpu_manager = create_gpu_manager()
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class FieldOperation(BaseModel):
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a: list[int]
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b: list[int]
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@app.post("/field/add")
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async def field_add(op: FieldOperation):
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"""Perform field addition with any available backend."""
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try:
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a = np.array(op.a, dtype=np.uint64)
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b = np.array(op.b, dtype=np.uint64)
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result = gpu_manager.field_add(a, b)
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return {"result": result.tolist()}
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/backend/info")
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async def backend_info():
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"""Get current backend information."""
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return gpu_manager.get_backend_info()
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@app.get("/performance/metrics")
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async def performance_metrics():
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"""Get performance metrics."""
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return gpu_manager.get_performance_metrics()
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