添加MiniMax在线API支持 (#1445)
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liunux4odoo
GitHub
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@ -88,6 +88,14 @@ llm_model_dict = {
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"provider": "ChatGLMWorker",
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"version": "chatglm_pro", # 可选包括 "chatglm_lite", "chatglm_std", "chatglm_pro"
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},
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"minimax-api": {
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"api_base_url": "http://127.0.0.1:8888/v1",
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"group_id": "",
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"api_key": "",
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"is_pro": False,
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"provider": "MiniMaxWorker",
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},
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}
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# LLM 名称
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@ -66,6 +66,9 @@ FSCHAT_MODEL_WORKERS = {
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"chatglm-api": { # 请为每个在线API设置不同的端口
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"port": 20003,
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},
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"minimax-api": { # 请为每个在线API设置不同的端口
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"port": 20004,
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},
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}
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# fastchat multi model worker server
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@ -1 +1,2 @@
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from .zhipu import ChatGLMWorker
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from .minimax import MiniMaxWorker
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@ -69,3 +69,8 @@ class ApiModelWorker(BaseModelWorker):
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target=fastchat.serve.model_worker.heart_beat_worker, args=(self,), daemon=True,
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)
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self.heart_beat_thread.start()
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# help methods
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def get_config(self):
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from server.utils import get_model_worker_config
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return get_model_worker_config(self.model_names[0])
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@ -0,0 +1,108 @@
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from server.model_workers.base import ApiModelWorker
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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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import httpx
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from pprint import pprint
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from typing import List, Dict
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class MiniMaxWorker(ApiModelWorker):
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BASE_URL = 'https://api.minimax.chat/v1/text/chatcompletion{pro}?GroupId={group_id}'
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def __init__(
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self,
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*,
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model_names: List[str] = ["minimax-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)
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super().__init__(**kwargs)
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# TODO: 确认模板是否需要修改
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self.conv = conv.Conversation(
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name=self.model_names[0],
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system_message="",
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messages=[],
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roles=["USER", "BOT"],
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sep="\n### ",
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stop_str="###",
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)
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def prompt_to_messages(self, prompt: str) -> List[Dict]:
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result = []
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user_start = self.conv.roles[0] + ":"
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bot_start = self.conv.roles[1] + ":"
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for msg in prompt.split(self.conv.sep)[1:-1]:
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if msg.startswith(user_start):
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result.append({"sender_type": "USER", "text": msg[len(user_start):].strip()})
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elif msg.startswith(bot_start):
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result.append({"sender_type": "BOT", "text": msg[len(bot_start)].strip()})
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else:
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raise RuntimeError(f"unknow role in msg: {msg}")
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return result
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def generate_stream_gate(self, params):
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# 按照官网推荐，直接调用abab 5.5模型
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# TODO: 支持历史消息，支持指定回复要求，支持指定用户名称、AI名称
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super().generate_stream_gate(params)
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config = self.get_config()
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group_id = config.get("group_id")
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api_key = config.get("api_key")
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pro = "_pro" if config.get("is_pro") else ""
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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data = {
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"model": "abab5.5-chat",
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"stream": True,
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"tokens_to_generate": 1024, # TODO: 1024为官网默认值
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"mask_sensitive_info": True,
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"messages": self.prompt_to_messages(params["prompt"]),
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"temperature": params.get("temperature"),
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"top_p": params.get("top_p"),
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"bot_setting": [],
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}
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print("request data sent to minimax:")
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pprint(data)
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response = httpx.stream("POST",
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self.BASE_URL.format(pro=pro, group_id=group_id),
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headers=headers,
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json=data)
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with response as r:
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text = ""
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for e in r.iter_text():
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if e.startswith("data: "): # 真是优秀的返回
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data = json.loads(e[6:])
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if not data.get("usage"):
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if choices := data.get("choices"):
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chunk = choices[0].get("delta", "").strip()
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if chunk:
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print(chunk)
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text += chunk
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yield json.dumps({"error_code": 0, "text": text}, 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 = MiniMaxWorker(
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controller_addr="http://127.0.0.1:20001",
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worker_addr="http://127.0.0.1:20004",
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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=20003)
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@ -25,7 +25,7 @@ class ChatGLMWorker(ApiModelWorker):
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# 这里的是chatglm api的模板，其它API的conv_template需要定制
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self.conv = conv.Conversation(
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name="chatglm-api",
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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=["Human", "Assistant"],
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@ -34,12 +34,11 @@ class ChatGLMWorker(ApiModelWorker):
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)
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def generate_stream_gate(self, params):
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# TODO: 支持stream参数，维护request_id，传过来的prompt也有问题
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from server.utils import get_model_worker_config
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# TODO: 维护request_id
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import zhipuai
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super().generate_stream_gate(params)
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zhipuai.api_key = get_model_worker_config("chatglm-api").get("api_key")
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zhipuai.api_key = self.get_config().get("api_key")
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response = zhipuai.model_api.sse_invoke(
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model=self.version,
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