chunzhi/chatgpt_academic
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修复一些细节

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Your Name 2023-04-23 22:44:18 +08:00
parent 4a494354b1
commit 781ef4487c
2 changed files with 9 additions and 5 deletions
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2
request_llm/bridge_all.py
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@ -192,7 +192,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
def mutex_manager(window_mutex, observe_window):
while True:
time.sleep(0.5)
time.sleep(0.25)
if not window_mutex[-1]: break
# 看门狗（watchdog）
for i in range(n_model):

12
request_llm/bridge_newbing.py
View File

@ -406,7 +406,7 @@ class Chatbot:
load_message = ""
load_message = "等待NewBing响应。"
"""
========================================================================
@ -574,13 +574,16 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
response = ""
for response in newbing_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']):
observe_window[0] = response
observe_window[0] = preprocess_newbing_out_simple(response)
if len(observe_window) >= 2:
if (time.time()-observe_window[1]) > watch_dog_patience:
raise RuntimeError("程序终止。")
return response
return preprocess_newbing_out_simple(response)
def preprocess_newbing_out_simple(result):
if '[1]' in result:
result += '\n\n```\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
return result
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
"""
@ -609,6 +612,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
for i in range(len(history)//2):
history_feedin.append([history[2*i], history[2*i+1]] )
chatbot[-1] = (inputs, preprocess_newbing_out(response))
yield from update_ui(chatbot=chatbot, history=history, msg="NewBing响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
for response in newbing_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, preprocess_newbing_out(response))