Spaces:
Runtime error
Runtime error
File size: 7,724 Bytes
444f09e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 |
from transformers import AutoModel, AutoTokenizer
import time
import threading
import importlib
from toolbox import update_ui, get_conf
from multiprocessing import Process, Pipe
load_message = "jittorllms尚未加载,加载需要一段时间。注意,请避免混用多种jittor模型,否则可能导致显存溢出而造成卡顿,取决于`config.py`的配置,jittorllms消耗大量的内存(CPU)或显存(GPU),也许会导致低配计算机卡死 ……"
#################################################################################
class GetGLMHandle(Process):
def __init__(self):
super().__init__(daemon=True)
self.parent, self.child = Pipe()
self.jittorllms_model = None
self.info = ""
self.local_history = []
self.success = True
self.check_dependency()
self.start()
self.threadLock = threading.Lock()
def check_dependency(self):
try:
import pandas
self.info = "依赖检测通过"
self.success = True
except:
from toolbox import trimmed_format_exc
self.info = r"缺少jittorllms的依赖,如果要使用jittorllms,除了基础的pip依赖以外,您还需要运行`pip install -r request_llms/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I`"+\
r"和`git clone https://gitlink.org.cn/jittor/JittorLLMs.git --depth 1 request_llms/jittorllms`两个指令来安装jittorllms的依赖(在项目根目录运行这两个指令)。" +\
r"警告:安装jittorllms依赖后将完全破坏现有的pytorch环境,建议使用docker环境!" + trimmed_format_exc()
self.success = False
def ready(self):
return self.jittorllms_model is not None
def run(self):
# 子进程执行
# 第一次运行,加载参数
def validate_path():
import os, sys
dir_name = os.path.dirname(__file__)
env = os.environ.get("PATH", "")
os.environ["PATH"] = env.replace('/cuda/bin', '/x/bin')
root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
os.chdir(root_dir_assume + '/request_llms/jittorllms')
sys.path.append(root_dir_assume + '/request_llms/jittorllms')
validate_path() # validate path so you can run from base directory
def load_model():
import types
try:
if self.jittorllms_model is None:
device = get_conf('LOCAL_MODEL_DEVICE')
from .jittorllms.models import get_model
# availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
args_dict = {'model': 'chatrwkv'}
print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
print('done get model')
except:
self.child.send('[Local Message] Call jittorllms fail 不能正常加载jittorllms的参数。')
raise RuntimeError("不能正常加载jittorllms的参数!")
print('load_model')
load_model()
# 进入任务等待状态
print('进入任务等待状态')
while True:
# 进入任务等待状态
kwargs = self.child.recv()
query = kwargs['query']
history = kwargs['history']
# 是否重置
if len(self.local_history) > 0 and len(history)==0:
print('触发重置')
self.jittorllms_model.reset()
self.local_history.append(query)
print('收到消息,开始请求')
try:
for response in self.jittorllms_model.stream_chat(query, history):
print(response)
self.child.send(response)
except:
from toolbox import trimmed_format_exc
print(trimmed_format_exc())
self.child.send('[Local Message] Call jittorllms fail.')
# 请求处理结束,开始下一个循环
self.child.send('[Finish]')
def stream_chat(self, **kwargs):
# 主进程执行
self.threadLock.acquire()
self.parent.send(kwargs)
while True:
res = self.parent.recv()
if res != '[Finish]':
yield res
else:
break
self.threadLock.release()
global rwkv_glm_handle
rwkv_glm_handle = None
#################################################################################
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
"""
多线程方法
函数的说明请见 request_llms/bridge_all.py
"""
global rwkv_glm_handle
if rwkv_glm_handle is None:
rwkv_glm_handle = GetGLMHandle()
if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + rwkv_glm_handle.info
if not rwkv_glm_handle.success:
error = rwkv_glm_handle.info
rwkv_glm_handle = None
raise RuntimeError(error)
# jittorllms 没有 sys_prompt 接口,因此把prompt加入 history
history_feedin = []
for i in range(len(history)//2):
history_feedin.append([history[2*i], history[2*i+1]] )
watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
response = ""
for response in rwkv_glm_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
print(response)
if len(observe_window) >= 1: observe_window[0] = response
if len(observe_window) >= 2:
if (time.time()-observe_window[1]) > watch_dog_patience:
raise RuntimeError("程序终止。")
return response
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
"""
单线程方法
函数的说明请见 request_llms/bridge_all.py
"""
chatbot.append((inputs, ""))
global rwkv_glm_handle
if rwkv_glm_handle is None:
rwkv_glm_handle = GetGLMHandle()
chatbot[-1] = (inputs, load_message + "\n\n" + rwkv_glm_handle.info)
yield from update_ui(chatbot=chatbot, history=[])
if not rwkv_glm_handle.success:
rwkv_glm_handle = None
return
if additional_fn is not None:
from core_functional import handle_core_functionality
inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
# 处理历史信息
history_feedin = []
for i in range(len(history)//2):
history_feedin.append([history[2*i], history[2*i+1]] )
# 开始接收jittorllms的回复
response = "[Local Message] 等待jittorllms响应中 ..."
for response in rwkv_glm_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
chatbot[-1] = (inputs, response)
yield from update_ui(chatbot=chatbot, history=history)
# 总结输出
if response == "[Local Message] 等待jittorllms响应中 ...":
response = "[Local Message] jittorllms响应异常 ..."
history.extend([inputs, response])
yield from update_ui(chatbot=chatbot, history=history)
|