from server.model_workers.base import ApiModelWorker from configs.model_config import TEMPERATURE from fastchat import conversation as conv import sys import json from pprint import pprint from server.utils import get_model_worker_config from typing import List, Literal, Dict def request_volc_api( messages: List[Dict], model_name: str = "fangzhou-api", version: str = "chatglm-6b-model", temperature: float = TEMPERATURE, api_key: str = None, secret_key: str = None, ): from volcengine.maas import MaasService, MaasException, ChatRole maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing') config = get_model_worker_config(model_name) version = version or config.get("version") version_url = config.get("version_url") api_key = api_key or config.get("api_key") secret_key = secret_key or config.get("secret_key") maas.set_ak(api_key) maas.set_sk(secret_key) # document: "https://www.volcengine.com/docs/82379/1099475" req = { "model": { "name": version, }, "parameters": { # 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 "max_new_tokens": 1000, "temperature": temperature, }, "messages": messages, } try: resps = maas.stream_chat(req) for resp in resps: yield resp except MaasException as e: print(e) class FangZhouWorker(ApiModelWorker): """ 火山方舟 """ SUPPORT_MODELS = ["chatglm-6b-model"] def __init__( self, *, version: Literal["chatglm-6b-model"] = "chatglm-6b-model", model_names: List[str] = ["fangzhou-api"], controller_addr: str, worker_addr: str, **kwargs, ): kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr) kwargs.setdefault("context_len", 16384) # TODO: 不同的模型有不同的大小 super().__init__(**kwargs) config = self.get_config() self.version = version self.api_key = config.get("api_key") self.secret_key = config.get("secret_key") self.conv = conv.Conversation( name=self.model_names[0], 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。", messages=[], roles=["user", "assistant", "system"], sep="\n### ", stop_str="###", ) def generate_stream_gate(self, params): super().generate_stream_gate(params) messages = self.prompt_to_messages(params["prompt"]) text = "" for resp in request_volc_api(messages=messages, model_name=self.model_names[0], version=self.version, temperature=params.get("temperature", TEMPERATURE), ): error = resp.error if error.code_n > 0: data = {"error_code": error.code_n, "text": error.message} elif chunk := resp.choice.message.content: text += chunk data = {"error_code": 0, "text": text} yield json.dumps(data, ensure_ascii=False).encode() + b"\0" def get_embeddings(self, params): # TODO: 支持embeddings print("embedding") print(params) if __name__ == "__main__": import uvicorn from server.utils import MakeFastAPIOffline from fastchat.serve.model_worker import app worker = FangZhouWorker( controller_addr="http://127.0.0.1:20001", worker_addr="http://127.0.0.1:21005", ) sys.modules["fastchat.serve.model_worker"].worker = worker MakeFastAPIOffline(app) uvicorn.run(app, port=21005)