wangyu
6ae24cb14d
- Train 3 MLP networks (acid speed 14→1, tension 4→10, quality 6→2) on 12,000 synthetic samples generated from physics models + noise - Export pre-trained ONNX models to pt_models/ directory - Rewrite prediction.py: ONNX inference first, physics fallback if unavailable - Add onnxruntime + numpy to requirements.txt (Aliyun mirror for Docker) - Use Tsinghua mirror in Dockerfile for pip installs Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
23 lines
420 B
Plaintext
23 lines
420 B
Plaintext
fastapi==0.111.0
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uvicorn[standard]==0.29.0
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sqlalchemy==2.0.30
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alembic==1.13.1
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asyncpg==0.29.0
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psycopg2-binary==2.9.9
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pydantic==2.7.1
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pydantic-settings==2.2.1
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python-dotenv==1.0.1
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python-jose[cryptography]==3.3.0
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passlib[bcrypt]==1.7.4
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python-multipart==0.0.9
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aiofiles==23.2.1
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websockets==12.0
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schedule==1.2.1
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APScheduler==3.10.4
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redis==5.0.4
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aioredis==2.0.1
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httpx==0.27.0
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loguru==0.7.2
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onnxruntime==1.18.0
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numpy==1.26.4
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