离散事件模拟服务器

# Clone and install
git clone https://github.com/bulentsoykan/Simulation-AI-Agent.git
cd Simulation-AI-Agent
pip install -r requirements.txt

# Terminal 1: Start FastAPI server (port 8000)
python server.py

# Terminal 2: Start MCP server (port 8001)
python mcp_server.py

curl -X POST http://localhost:8000/simulations/queueing/run \
  -H "Content-Type: application/json" \
  -d '{"params": {"n_servers": 3, "arrival_rate": 10, "service_time": 2, "sim_time": 480}}'

curl -X POST http://localhost:8000/simulations/manufacturing/run \
  -H "Content-Type: application/json" \
  -d '{"params": {"stations": ["Cutting", "Assembly", "QC"], "processing_times": [2.0, 5.0, 1.5], "arrival_rate": 0.3}}'

curl -X POST http://localhost:8000/simulations/inventory/run \
  -H "Content-Type: application/json" \
  -d '{"params": {"reorder_point": 20, "order_up_to": 100, "demand_rate": 5.0, "lead_time": 5.0}}'

curl -X POST http://localhost:8000/simulations/logistics/run \
  -H "Content-Type: application/json" \
  -d '{"params": {"num_vehicles": 3, "vehicle_capacity": 100, "num_customers": 20}}'

{
  "mcpServers": {
    "simulation": {
      "command": "npx",
      "args": ["mcp-remote", "http://localhost:8001/mcp"]
    }
  }
}

from simulations.base import BaseSimulation
from simulations.registry import SimulationRegistry

@SimulationRegistry.register
class MySimulation(BaseSimulation):
    name = "my_simulation"
    description = "My custom simulation"

    def get_parameter_schema(self) -> dict:
        return {
            "type": "object",
            "properties": {
                "my_param": {"type": "number", "default": 1.0}
            }
        }

    def get_metrics_schema(self) -> dict:
        return {
            "type": "object",
            "properties": {
                "my_metric": {"type": "number"}
            }
        }

    def run(self, params: dict, callback=None) -> dict:
        validated = self.validate_params(params)
        # Run your simulation logic
        return {"my_metric": 42.0}

simulation-ai-agent/
├── server.py              # FastAPI application
├── mcp_server.py          # MCP server
├── config.py              # Configuration settings
├── simulations/           # Simulation plugins
│   ├── base.py            # BaseSimulation class
│   ├── registry.py        # Plugin registry
│   ├── queueing.py        # M/M/c queue
│   ├── manufacturing.py   # Production line
│   ├── inventory.py       # Inventory management
│   └── logistics.py       # Vehicle routing
├── database/              # SQLAlchemy models
│   ├── connection.py      # DB session management
│   └── models.py          # ORM models
├── auth/                  # JWT authentication
│   ├── jwt_handler.py     # Token creation/validation
│   ├── dependencies.py    # FastAPI dependencies
│   └── schemas.py         # Pydantic schemas
├── analytics/             # Reporting
│   ├── aggregations.py    # Query aggregations
│   └── reports.py         # Report generation
├── ml/                    # Machine learning
│   ├── predictor.py       # PyTorch inference
│   └── trainer.py         # Model training
├── websocket/             # Real-time updates
│   └── manager.py         # Connection manager
└── monitoring/            # Prometheus metrics
    └── metrics.py         # Metric collectors

┌─────────────────┐    WS/HTTP   ┌─────────────────┐
│  MCP Clients    │ ◄──────────► │  mcp_server.py  │
└─────────────────┘    :8001     └────────┬────────┘
                                          │
┌─────────────────┐    WS/HTTP   ┌────────▼────────┐    ┌─────────────────┐
│  Web Clients    │ ◄──────────► │   server.py     │◄──►│  SQLite DB      │
└─────────────────┘    :8000     │   (FastAPI)     │    │  (SQLAlchemy)   │
                                 └────────┬────────┘    └─────────────────┘
                                          │
              ┌───────────────────────────┼───────────────────────────┐
              ▼                           ▼                           ▼
    ┌─────────────────┐         ┌─────────────────┐         ┌─────────────────┐
    │ simulations/    │         │  ml/            │         │  analytics/     │
    │  base.py        │         │  predictor.py   │         │  reports.py     │
    │  registry.py    │         │   (PyTorch)     │         │  aggregations.py│
    │  queueing.py    │         └─────────────────┘         └─────────────────┘
    │  manufacturing.py│
    │  inventory.py   │
    │  logistics.py   │
    └─────────────────┘

# Install dependencies
pip install -r requirements.txt

# Terminal 1: FastAPI server (port 8000)
python server.py

# Terminal 2: MCP server (port 8001)
python mcp_server.py

from simulations.base import BaseSimulation
from simulations.registry import SimulationRegistry

@SimulationRegistry.register
class MySimulation(BaseSimulation):
    name = "my_simulation"
    description = "Description here"

    def get_parameter_schema(self) -> dict:
        return {"type": "object", "properties": {...}}

    def get_metrics_schema(self) -> dict:
        return {"type": "object", "properties": {...}}

    def run(self, params: dict, callback=None) -> dict:
        validated = self.validate_params(params)
        # Simulation logic here
        return {"metric": value}