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import json
import sys
from fastchat.conversation import Conversation
from configs import TEMPERATURE
from http import HTTPStatus
from typing import List, Literal, Dict
from fastchat import conversation as conv
from server.model_workers.base import *
from server.model_workers.base import ApiEmbeddingsParams
from configs import logger, log_verbose
class QwenWorker(ApiModelWorker):
DEFAULT_EMBED_MODEL = "text-embedding-v1"
def __init__(
self,
*,
version: Literal["qwen-turbo", "qwen-plus"] = "qwen-turbo",
model_names: List[str] = ["qwen-api"],
controller_addr: str = None,
worker_addr: str = None,
**kwargs,
):
kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
kwargs.setdefault("context_len", 16384)
super().__init__(**kwargs)
self.version = version
def do_chat(self, params: ApiChatParams) -> Dict:
import dashscope
params.load_config(self.model_names[0])
if log_verbose:
logger.info(f'{self.__class__.__name__}:params: {params}')
gen = dashscope.Generation()
responses = gen.call(
model=params.version,
temperature=params.temperature,
api_key=params.api_key,
messages=params.messages,
result_format='message', # set the result is message format.
stream=True,
)
for resp in responses:
if resp["status_code"] == 200:
if choices := resp["output"]["choices"]:
yield {
"error_code": 0,
"text": choices[0]["message"]["content"],
}
else:
data = {
"error_code": resp["status_code"],
"text": resp["message"],
"error": {
"message": resp["message"],
"type": "invalid_request_error",
"param": None,
"code": None,
}
}
self.logger.error(f"请求千问 API 时发生错误：{data}")
yield data
def do_embeddings(self, params: ApiEmbeddingsParams) -> Dict:
import dashscope
params.load_config(self.model_names[0])
if log_verbose:
logger.info(f'{self.__class__.__name__}:params: {params}')
result = []
i = 0
while i < len(params.texts):
texts = params.texts[i:i+25]
resp = dashscope.TextEmbedding.call(
model=params.embed_model or self.DEFAULT_EMBED_MODEL,
input=texts, # 最大25行
api_key=params.api_key,
)
if resp["status_code"] != 200:
data = {
"code": resp["status_code"],
"msg": resp.message,
"error": {
"message": resp["message"],
"type": "invalid_request_error",
"param": None,
"code": None,
}
}
self.logger.error(f"请求千问 API 时发生错误：{data}")
return data
else:
embeddings = [x["embedding"] for x in resp["output"]["embeddings"]]
result += embeddings
i += 25
return {"code": 200, "data": result}
def get_embeddings(self, params):
print("embedding")
print(params)
def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
return 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="###",
)
if __name__ == "__main__":
import uvicorn
from server.utils import MakeFastAPIOffline
from fastchat.serve.model_worker import app
worker = QwenWorker(
controller_addr="http://127.0.0.1:20001",
worker_addr="http://127.0.0.1:20007",
)
sys.modules["fastchat.serve.model_worker"].worker = worker
MakeFastAPIOffline(app)
uvicorn.run(app, port=20007)
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