kbt-devops
fe76bc7629
Implements FastAPI backend with ML model support for energy trading, including price prediction models and RL-based battery trading policy. Features dashboard, trading, backtest, and settings API routes with WebSocket support for real-time updates.
55 lines
1.1 KiB
Markdown
55 lines
1.1 KiB
Markdown
# Energy Trading Backend
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FastAPI backend for the energy trading system with ML model support.
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## Setup
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```bash
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cd backend
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pip install -r requirements.txt
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cp .env.example .env
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```
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## Running
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```bash
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uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
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```
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## API Documentation
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- Swagger UI: http://localhost:8000/docs
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- ReDoc: http://localhost:8000/redoc
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## Project Structure
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```
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backend/
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├── app/
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│ ├── api/ # API routes and WebSocket
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│ ├── services/ # Business logic services
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│ ├── tasks/ # Background tasks
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│ ├── ml/ # ML models and training
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│ ├── models/ # Pydantic models
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│ └── utils/ # Utilities
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├── models/ # Trained models
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├── results/ # Backtest results
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└── tests/ # Tests
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```
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## Training ML Models
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```bash
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# Train price prediction models
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python -m app.ml.training.cli price --horizons 1 5 15 60
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# Train RL battery policy
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python -m app.ml.training.cli rl --episodes 1000
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```
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## Running Tests
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```bash
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pytest
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```
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