mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-26 00:33:35 +08:00
78 lines
2.6 KiB
Python
78 lines
2.6 KiB
Python
import json
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from typing import List
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from loom_core.openai_plugins.core.adapter import LLMWorkerInfo
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from loom_core.openai_plugins.core.profile_endpoint.core import ProfileEndpointAdapter
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import os
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import sys
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import logging
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logger = logging.getLogger(__name__)
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# 为了能使用插件中的函数，需要将当前目录加入到sys.path中
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root_dir = os.path.dirname(os.path.abspath(__file__))
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sys.path.append(root_dir)
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from imitater_config import ImitaterCfg
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import imitater_process_dict
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class ImitaterProfileEndpointAdapter(ProfileEndpointAdapter):
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"""Adapter for the profile endpoint."""
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def __init__(self, cfg=None, state_dict: dict = None):
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self._cfg = ImitaterCfg(cfg=cfg)
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super().__init__(state_dict=state_dict)
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def class_name(self) -> str:
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"""Get class name."""
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return self.__name__
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def list_running_models(self) -> List[LLMWorkerInfo]:
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"""模型列表及其配置项"""
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list_worker = []
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for worker_name, process in imitater_process_dict.processes.items():
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list_worker.append(self.get_model_config(worker_name))
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return list_worker
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def list_llm_models(self) -> List[LLMWorkerInfo]:
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"""获取已配置模型列表"""
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list_worker = []
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workers_names = self._cfg.get_imitate_model_workers_names()
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for worker_name in workers_names:
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list_worker.append(self.get_model_config(worker_name))
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return list_worker
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def get_model_config(self, model_name) -> LLMWorkerInfo:
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'''
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获取LLM模型配置项（合并后的）
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'''
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worker_cfg = self._cfg.get_imitate_model_workers_by_name(model_name)
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info_obj = LLMWorkerInfo(worker_id=model_name,
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model_name=model_name,
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model_description="",
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providers=["model", "embedding"],
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model_extra_info=json.dumps(dict(worker_cfg), ensure_ascii=False, indent=4))
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return info_obj
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@classmethod
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def from_config(cls, cfg=None):
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_state_dict = {
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"profile_name": "Imitate",
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"profile_version": "0.0.1",
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"profile_description": "Imitate profile endpoint",
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"profile_author": "Imitate"
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}
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state_dict = cfg.get("state_dict", {})
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if state_dict is not None and _state_dict is not None:
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_state_dict = {**state_dict, **_state_dict}
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else:
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# 处理其中一个或两者都为 None 的情况
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_state_dict = state_dict or _state_dict or {}
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return cls(cfg=cfg, state_dict=_state_dict)
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