119 lines
4.7 KiB
Python
119 lines
4.7 KiB
Python
from fastapi import Body
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from configs import logger, log_verbose, LLM_MODEL, HTTPX_DEFAULT_TIMEOUT,LANGCHAIN_LLM_MODEL
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from server.utils import (BaseResponse, fschat_controller_address, list_config_llm_models,
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get_httpx_client, get_model_worker_config)
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def list_running_models(
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controller_address: str = Body(None, description="Fastchat controller服务器地址", examples=[fschat_controller_address()]),
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placeholder: str = Body(None, description="该参数未使用，占位用"),
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) -> BaseResponse:
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'''
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从fastchat controller获取已加载模型列表及其配置项
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'''
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try:
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controller_address = controller_address or fschat_controller_address()
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with get_httpx_client() as client:
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r = client.post(controller_address + "/list_models")
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models = r.json()["models"]
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data = {m: get_model_config(m).data for m in models}
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return BaseResponse(data=data)
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except Exception as e:
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logger.error(f'{e.__class__.__name__}: {e}',
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exc_info=e if log_verbose else None)
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return BaseResponse(
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code=500,
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data={},
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msg=f"failed to get available models from controller: {controller_address}。错误信息是： {e}")
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def list_config_models() -> BaseResponse:
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'''
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从本地获取configs中配置的模型列表
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'''
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configs = list_config_llm_models()
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# 删除ONLINE_MODEL配置中的敏感信息
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for config in configs["online"].values():
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del_keys = set(["worker_class"])
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for k in config:
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if "key" in k.lower() or "secret" in k.lower():
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del_keys.add(k)
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for k in del_keys:
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config.pop(k, None)
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return BaseResponse(data=configs)
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def get_model_config(
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model_name: str = Body(description="配置中LLM模型的名称"),
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placeholder: str = Body(description="占位用，无实际效果")
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) -> BaseResponse:
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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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config = get_model_worker_config(model_name=model_name)
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# 删除ONLINE_MODEL配置中的敏感信息
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del_keys = set(["worker_class"])
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for k in config:
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if "key" in k.lower() or "secret" in k.lower():
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del_keys.add(k)
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for k in del_keys:
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config.pop(k, None)
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return BaseResponse(data=config)
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def stop_llm_model(
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model_name: str = Body(..., description="要停止的LLM模型名称", examples=[LLM_MODEL]),
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controller_address: str = Body(None, description="Fastchat controller服务器地址", examples=[fschat_controller_address()])
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) -> BaseResponse:
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'''
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向fastchat controller请求停止某个LLM模型。
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注意：由于Fastchat的实现方式，实际上是把LLM模型所在的model_worker停掉。
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'''
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try:
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controller_address = controller_address or fschat_controller_address()
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with get_httpx_client() as client:
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r = client.post(
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controller_address + "/release_worker",
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json={"model_name": model_name},
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)
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return r.json()
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except Exception as e:
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logger.error(f'{e.__class__.__name__}: {e}',
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exc_info=e if log_verbose else None)
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return BaseResponse(
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code=500,
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msg=f"failed to stop LLM model {model_name} from controller: {controller_address}。错误信息是： {e}")
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def change_llm_model(
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model_name: str = Body(..., description="当前运行模型", examples=[LLM_MODEL]),
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new_model_name: str = Body(..., description="要切换的新模型", examples=[LLM_MODEL]),
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controller_address: str = Body(None, description="Fastchat controller服务器地址", examples=[fschat_controller_address()])
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):
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'''
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向fastchat controller请求切换LLM模型。
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'''
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try:
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controller_address = controller_address or fschat_controller_address()
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with get_httpx_client() as client:
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r = client.post(
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controller_address + "/release_worker",
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json={"model_name": model_name, "new_model_name": new_model_name},
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timeout=HTTPX_DEFAULT_TIMEOUT, # wait for new worker_model
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)
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return r.json()
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except Exception as e:
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logger.error(f'{e.__class__.__name__}: {e}',
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exc_info=e if log_verbose else None)
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return BaseResponse(
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code=500,
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msg=f"failed to switch LLM model from controller: {controller_address}。错误信息是： {e}")
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def list_search_engines() -> BaseResponse:
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from server.chat.search_engine_chat import SEARCH_ENGINES
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return BaseResponse(data=list(SEARCH_ENGINES))
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