chore(security): enhance environment configuration, CI workflows, and wallet daemon with security improvements
- 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
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gpu_acceleration/api_service.py
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58
gpu_acceleration/api_service.py
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"""
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Refactored FastAPI GPU Acceleration Service
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Uses the new abstraction layer for backend-agnostic GPU acceleration.
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"""
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from typing import Dict, List, Optional
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import logging
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from .gpu_manager import GPUAccelerationManager, create_gpu_manager
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app = FastAPI(title="AITBC GPU Acceleration API")
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logger = logging.getLogger(__name__)
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# Initialize GPU manager
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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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class MultiScalarOperation(BaseModel):
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scalars: List[List[int]]
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points: List[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."""
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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.post("/field/mul")
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async def field_mul(op: FieldOperation):
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"""Perform field multiplication."""
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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_mul(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 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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