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122 lines
3.0 KiB
Python
122 lines
3.0 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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from enum import Enum
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from typing import TypedDict, Optional, Dict, List, Any
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from dataclasses import dataclass, asdict
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import time
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from datetime import datetime
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from dbgpt.util.parameter_utils import ParameterDescription
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from dbgpt.util.model_utils import GPUInfo
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class ModelType:
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""" "Type of model"""
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HF = "huggingface"
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LLAMA_CPP = "llama.cpp"
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PROXY = "proxy"
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VLLM = "vllm"
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# TODO, support more model type
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@dataclass
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class ModelInstance:
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"""Model instance info"""
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model_name: str
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host: str
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port: int
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weight: Optional[float] = 1.0
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check_healthy: Optional[bool] = True
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healthy: Optional[bool] = False
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enabled: Optional[bool] = True
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prompt_template: Optional[str] = None
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last_heartbeat: Optional[datetime] = None
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class WorkerApplyType(str, Enum):
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START = "start"
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STOP = "stop"
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RESTART = "restart"
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UPDATE_PARAMS = "update_params"
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@dataclass
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class WorkerApplyOutput:
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message: str
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success: Optional[bool] = True
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# The seconds cost to apply some action to worker instances
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timecost: Optional[int] = -1
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@staticmethod
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def reduce(outs: List["WorkerApplyOutput"]) -> "WorkerApplyOutput":
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"""Merge all outputs
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Args:
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outs (List["WorkerApplyOutput"]): The list of WorkerApplyOutput
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"""
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if not outs:
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return WorkerApplyOutput("Not outputs")
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combined_success = all(out.success for out in outs)
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max_timecost = max(out.timecost for out in outs)
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combined_message = ", ".join(out.message for out in outs)
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return WorkerApplyOutput(combined_message, combined_success, max_timecost)
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@dataclass
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class SupportedModel:
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model: str
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path: str
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worker_type: str
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path_exist: bool
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proxy: bool
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enabled: bool
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params: List[ParameterDescription]
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@classmethod
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def from_dict(cls, model_data: Dict) -> "SupportedModel":
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params = model_data.get("params", [])
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if params:
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params = [ParameterDescription(**param) for param in params]
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model_data["params"] = params
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return cls(**model_data)
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@dataclass
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class WorkerSupportedModel:
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host: str
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port: int
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models: List[SupportedModel]
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@classmethod
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def from_dict(cls, worker_data: Dict) -> "WorkerSupportedModel":
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models = [
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SupportedModel.from_dict(model_data) for model_data in worker_data["models"]
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]
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worker_data["models"] = models
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return cls(**worker_data)
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@dataclass
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class FlatSupportedModel(SupportedModel):
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"""For web"""
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host: str
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port: int
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@staticmethod
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def from_supports(
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supports: List[WorkerSupportedModel],
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) -> List["FlatSupportedModel"]:
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results = []
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for s in supports:
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host, port, models = s.host, s.port, s.models
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for m in models:
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kwargs = asdict(m)
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kwargs["host"] = host
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kwargs["port"] = port
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results.append(FlatSupportedModel(**kwargs))
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return results
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