102 lines
3.7 KiB
Python
102 lines
3.7 KiB
Python
from server.model_workers.base import ApiModelWorker
|
||
from fastchat import conversation as conv
|
||
import sys
|
||
import json
|
||
from server.utils import get_httpx_client
|
||
from pprint import pprint
|
||
from typing import List, Dict
|
||
|
||
|
||
class MiniMaxWorker(ApiModelWorker):
|
||
BASE_URL = 'https://api.minimax.chat/v1/text/chatcompletion{pro}?GroupId={group_id}'
|
||
|
||
def __init__(
|
||
self,
|
||
*,
|
||
model_names: List[str] = ["minimax-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)
|
||
super().__init__(**kwargs)
|
||
|
||
# TODO: 确认模板是否需要修改
|
||
self.conv = conv.Conversation(
|
||
name=self.model_names[0],
|
||
system_message="",
|
||
messages=[],
|
||
roles=["USER", "BOT"],
|
||
sep="\n### ",
|
||
stop_str="###",
|
||
)
|
||
|
||
def prompt_to_messages(self, prompt: str) -> List[Dict]:
|
||
result = super().prompt_to_messages(prompt)
|
||
messages = [{"sender_type": x["role"], "text": x["content"]} for x in result]
|
||
return messages
|
||
|
||
def generate_stream_gate(self, params):
|
||
# 按照官网推荐，直接调用abab 5.5模型
|
||
# TODO: 支持指定回复要求，支持指定用户名称、AI名称
|
||
|
||
super().generate_stream_gate(params)
|
||
config = self.get_config()
|
||
group_id = config.get("group_id")
|
||
api_key = config.get("api_key")
|
||
|
||
pro = "_pro" if config.get("is_pro") else ""
|
||
headers = {
|
||
"Authorization": f"Bearer {api_key}",
|
||
"Content-Type": "application/json",
|
||
}
|
||
data = {
|
||
"model": "abab5.5-chat",
|
||
"stream": True,
|
||
"tokens_to_generate": 1024, # TODO: 1024为官网默认值
|
||
"mask_sensitive_info": True,
|
||
"messages": self.prompt_to_messages(params["prompt"]),
|
||
"temperature": params.get("temperature"),
|
||
"top_p": params.get("top_p"),
|
||
"bot_setting": [],
|
||
}
|
||
print("request data sent to minimax:")
|
||
pprint(data)
|
||
with get_httpx_client() as client:
|
||
response = client.stream("POST",
|
||
self.BASE_URL.format(pro=pro, group_id=group_id),
|
||
headers=headers,
|
||
json=data)
|
||
with response as r:
|
||
text = ""
|
||
for e in r.iter_text():
|
||
if e.startswith("data: "): # 真是优秀的返回
|
||
data = json.loads(e[6:])
|
||
if not data.get("usage"):
|
||
if choices := data.get("choices"):
|
||
chunk = choices[0].get("delta", "").strip()
|
||
if chunk:
|
||
print(chunk)
|
||
text += chunk
|
||
yield json.dumps({"error_code": 0, "text": text}, 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 = MiniMaxWorker(
|
||
controller_addr="http://127.0.0.1:20001",
|
||
worker_addr="http://127.0.0.1:21002",
|
||
)
|
||
sys.modules["fastchat.serve.model_worker"].worker = worker
|
||
MakeFastAPIOffline(app)
|
||
uvicorn.run(app, port=21002)
|