123 lines
4.0 KiB
Python
123 lines
4.0 KiB
Python
from server.model_workers.base import ApiModelWorker
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from configs.model_config import TEMPERATURE
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from fastchat import conversation as conv
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import sys
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import json
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from pprint import pprint
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from server.utils import get_model_worker_config
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from typing import List, Literal, Dict
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def request_volc_api(
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messages: List[Dict],
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model_name: str = "fangzhou-api",
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version: str = "chatglm-6b-model",
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temperature: float = TEMPERATURE,
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api_key: str = None,
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secret_key: str = None,
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):
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from volcengine.maas import MaasService, MaasException, ChatRole
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maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing')
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config = get_model_worker_config(model_name)
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version = version or config.get("version")
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version_url = config.get("version_url")
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api_key = api_key or config.get("api_key")
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secret_key = secret_key or config.get("secret_key")
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maas.set_ak(api_key)
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maas.set_sk(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": 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": 1000,
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"temperature": temperature,
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},
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"messages": messages,
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}
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try:
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resps = maas.stream_chat(req)
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for resp in resps:
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yield resp
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except MaasException as e:
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print(e)
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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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SUPPORT_MODELS = ["chatglm-6b-model"]
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def __init__(
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self,
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*,
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version: Literal["chatglm-6b-model"] = "chatglm-6b-model",
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model_names: List[str] = ["fangzhou-api"],
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controller_addr: str,
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worker_addr: str,
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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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config = self.get_config()
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self.version = version
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self.api_key = config.get("api_key")
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self.secret_key = config.get("secret_key")
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self.conv = 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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def generate_stream_gate(self, params):
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super().generate_stream_gate(params)
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messages = self.prompt_to_messages(params["prompt"])
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text = ""
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for resp in request_volc_api(messages=messages,
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model_name=self.model_names[0],
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version=self.version,
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temperature=params.get("temperature", TEMPERATURE),
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):
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error = resp.error
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if error.code_n > 0:
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data = {"error_code": error.code_n, "text": error.message}
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elif chunk := resp.choice.message.content:
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text += chunk
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data = {"error_code": 0, "text": text}
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yield json.dumps(data, ensure_ascii=False).encode() + b"\0"
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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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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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