mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-19 13:23:16 +08:00
03e55e11c4
* move get_default_llm_model from webui to ApiRequest 增加API接口及其测试用例： - /server/get_prompt_template: 获取服务器配置的 prompt 模板 - 增加知识库多线程访问测试用例 支持lite模式：无需安装torch等重依赖，通过在线API实现LLM对话和搜索引擎对话 * fix bug in server.api --------- Co-authored-by: imClumsyPanda <littlepanda0716@gmail.com>
104 lines
3.7 KiB
Python
104 lines
3.7 KiB
Python
from fastchat.conversation import Conversation
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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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from server.utils import get_httpx_client
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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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def prompt_to_messages(self, prompt: str) -> List[Dict]:
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result = super().prompt_to_messages(prompt)
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messages = [{"sender_type": x["role"], "text": x["content"]} for x in result]
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return messages
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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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with get_httpx_client() as client:
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response = client.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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def make_conv_template(self, conv_template: str = None, model_path: str = None) -> Conversation:
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# TODO: 确认模板是否需要修改
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return 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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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://127.0.0.1:21002",
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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=21002)
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