这个提交包含在:
binary-husky
2024-02-25 22:16:46 +08:00
父节点 47289f863d
当前提交 d0703ef32d
共有 96 个文件被更改,包括 7507 次插入2453 次删除

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@@ -1,15 +1,21 @@
import time
import os
from toolbox import update_ui, get_conf, update_ui_lastest_msg
from toolbox import check_packages, report_exception
from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
model_name = '智谱AI大模型'
zhipuai_default_model = 'glm-4'
def validate_key():
ZHIPUAI_API_KEY = get_conf("ZHIPUAI_API_KEY")
if ZHIPUAI_API_KEY == '': return False
return True
def make_media_input(inputs, image_paths):
for image_path in image_paths:
inputs = inputs + f'<br/><br/><div align="center"><img src="file={os.path.abspath(image_path)}"></div>'
return inputs
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
"""
⭐多线程方法
@@ -18,34 +24,40 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
watch_dog_patience = 5
response = ""
if llm_kwargs["llm_model"] == "zhipuai":
llm_kwargs["llm_model"] = zhipuai_default_model
if validate_key() is False:
raise RuntimeError('请配置ZHIPUAI_API_KEY')
from .com_zhipuapi import ZhipuRequestInstance
sri = ZhipuRequestInstance()
for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
# 开始接收回复
from .com_zhipuglm import ZhipuChatInit
zhipu_bro_init = ZhipuChatInit()
for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, sys_prompt):
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。")
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):
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, ""))
chatbot.append([inputs, ""])
yield from update_ui(chatbot=chatbot, history=history)
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
check_packages(["zhipuai"])
except:
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install zhipuai==1.0.7```。",
chatbot=chatbot, history=history, delay=0)
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。",
chatbot=chatbot, history=history, delay=0)
return
if validate_key() is False:
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
return
@@ -53,16 +65,29 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
if additional_fn is not None:
from core_functional import handle_core_functionality
inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
# 开始接收回复
from .com_zhipuapi import ZhipuRequestInstance
sri = ZhipuRequestInstance()
for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
chatbot[-1] = (inputs, response)
chatbot[-1] = [inputs, ""]
yield from update_ui(chatbot=chatbot, history=history)
# 总结输出
if response == f"[Local Message] 等待{model_name}响应中 ...":
response = f"[Local Message] {model_name}响应异常 ..."
if llm_kwargs["llm_model"] == "zhipuai":
llm_kwargs["llm_model"] = zhipuai_default_model
if llm_kwargs["llm_model"] in ["glm-4v"]:
have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot)
if not have_recent_file:
chatbot.append((inputs, "没有检测到任何近期上传的图像文件,请上传jpg格式的图片,此外,请注意拓展名需要小写"))
yield from update_ui(chatbot=chatbot, history=history, msg="等待图片") # 刷新界面
return
if have_recent_file:
inputs = make_media_input(inputs, image_paths)
chatbot[-1] = [inputs, ""]
yield from update_ui(chatbot=chatbot, history=history)
# 开始接收回复
from .com_zhipuglm import ZhipuChatInit
zhipu_bro_init = ZhipuChatInit()
for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, system_prompt):
chatbot[-1] = [inputs, response]
yield from update_ui(chatbot=chatbot, history=history)
history.extend([inputs, response])
yield from update_ui(chatbot=chatbot, history=history)