107 lines
3.7 KiB
Python
107 lines
3.7 KiB
Python
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from fastchat.conversation import Conversation
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from .base import *
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from fastchat import conversation as conv
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import sys
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from typing import List, Literal, Dict
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from configs import logger, log_verbose
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class FangZhouWorker(ApiModelWorker):
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"""
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火山方舟
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"""
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def __init__(
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self,
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*,
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model_names: List[str] = ["fangzhou-api"],
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controller_addr: str = None,
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worker_addr: str = None,
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version: Literal["chatglm-6b-model"] = "chatglm-6b-model",
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**kwargs,
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):
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kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
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kwargs.setdefault("context_len", 16384) # TODO: 不同的模型有不同的大小
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super().__init__(**kwargs)
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self.version = version
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def do_chat(self, params: ApiChatParams) -> Dict:
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from volcengine.maas import MaasService
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params.load_config(self.model_names[0])
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maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing')
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maas.set_ak(params.api_key)
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maas.set_sk(params.secret_key)
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# document: "https://www.volcengine.com/docs/82379/1099475"
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req = {
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"model": {
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"name": params.version,
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},
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"parameters": {
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# 这里的参数仅为示例，具体可用的参数请参考具体模型的 API 说明
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"max_new_tokens": params.max_tokens,
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"temperature": params.temperature,
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},
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"messages": params.messages,
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}
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text = ""
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if log_verbose:
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self.logger.info(f'{self.__class__.__name__}:maas: {maas}')
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for resp in maas.stream_chat(req):
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if error := resp.error:
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if error.code_n > 0:
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data = {
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"error_code": error.code_n,
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"text": error.message,
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"error": {
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"message": error.message,
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"type": "invalid_request_error",
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"param": None,
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"code": None,
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}
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}
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self.logger.error(f"请求方舟 API 时发生错误：{data}")
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yield data
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elif chunk := resp.choice.message.content:
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text += chunk
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yield {"error_code": 0, "text": text}
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else:
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data = {
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"error_code": 500,
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"text": f"请求方舟 API 时发生未知的错误: {resp}"
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}
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self.logger.error(data)
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yield data
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break
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def get_embeddings(self, params):
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# TODO: 支持embeddings
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print("embedding")
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print(params)
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def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
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return conv.Conversation(
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name=self.model_names[0],
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system_message="你是一个聪明、对人类有帮助的人工智能，你可以对人类提出的问题给出有用、详细、礼貌的回答。",
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messages=[],
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roles=["user", "assistant", "system"],
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sep="\n### ",
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stop_str="###",
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)
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if __name__ == "__main__":
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import uvicorn
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from server.utils import MakeFastAPIOffline
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from fastchat.serve.model_worker import app
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worker = FangZhouWorker(
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controller_addr="http://127.0.0.1:20001",
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worker_addr="http://127.0.0.1:21005",
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)
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sys.modules["fastchat.serve.model_worker"].worker = worker
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MakeFastAPIOffline(app)
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uvicorn.run(app, port=21005)
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