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def request_gpt_model_in_new_thread_with_ui_alive(inputs, inputs_show_user, top_p, temperature, chatbot, history, sys_prompt, refresh_interval=0.2): | |
import time | |
from concurrent.futures import ThreadPoolExecutor | |
from request_llm.bridge_chatgpt import predict_no_ui_long_connection | |
# 用户反馈 | |
chatbot.append([inputs_show_user, ""]) | |
msg = '正常' | |
yield chatbot, [], msg | |
executor = ThreadPoolExecutor(max_workers=16) | |
mutable = ["", time.time()] | |
future = executor.submit(lambda: | |
predict_no_ui_long_connection( | |
inputs=inputs, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt, observe_window=mutable) | |
) | |
while True: | |
# yield一次以刷新前端页面 | |
time.sleep(refresh_interval) | |
# “喂狗”(看门狗) | |
mutable[1] = time.time() | |
if future.done(): | |
break | |
chatbot[-1] = [chatbot[-1][0], mutable[0]] | |
msg = "正常" | |
yield chatbot, [], msg | |
return future.result() | |
def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(inputs_array, inputs_show_user_array, top_p, temperature, chatbot, history_array, sys_prompt_array, refresh_interval=0.2, max_workers=10, scroller_max_len=30): | |
import time | |
from concurrent.futures import ThreadPoolExecutor | |
from request_llm.bridge_chatgpt import predict_no_ui_long_connection | |
assert len(inputs_array) == len(history_array) | |
assert len(inputs_array) == len(sys_prompt_array) | |
executor = ThreadPoolExecutor(max_workers=max_workers) | |
n_frag = len(inputs_array) | |
# 用户反馈 | |
chatbot.append(["请开始多线程操作。", ""]) | |
msg = '正常' | |
yield chatbot, [], msg | |
# 异步原子 | |
mutable = [["", time.time()] for _ in range(n_frag)] | |
def _req_gpt(index, inputs, history, sys_prompt): | |
gpt_say = predict_no_ui_long_connection( | |
inputs=inputs, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt, observe_window=mutable[ | |
index] | |
) | |
return gpt_say | |
# 异步任务开始 | |
futures = [executor.submit(_req_gpt, index, inputs, history, sys_prompt) for index, inputs, history, sys_prompt in zip( | |
range(len(inputs_array)), inputs_array, history_array, sys_prompt_array)] | |
cnt = 0 | |
while True: | |
# yield一次以刷新前端页面 | |
time.sleep(refresh_interval) | |
cnt += 1 | |
worker_done = [h.done() for h in futures] | |
if all(worker_done): | |
executor.shutdown() | |
break | |
# 更好的UI视觉效果 | |
observe_win = [] | |
# 每个线程都要“喂狗”(看门狗) | |
for thread_index, _ in enumerate(worker_done): | |
mutable[thread_index][1] = time.time() | |
# 在前端打印些好玩的东西 | |
for thread_index, _ in enumerate(worker_done): | |
print_something_really_funny = "[ ...`"+mutable[thread_index][0][-scroller_max_len:].\ | |
replace('\n', '').replace('```', '...').replace( | |
' ', '.').replace('<br/>', '.....').replace('$', '.')+"`... ]" | |
observe_win.append(print_something_really_funny) | |
stat_str = ''.join([f'执行中: {obs}\n\n' if not done else '已完成\n\n' for done, obs in zip( | |
worker_done, observe_win)]) | |
chatbot[-1] = [chatbot[-1][0], | |
f'多线程操作已经开始,完成情况: \n\n{stat_str}' + ''.join(['.']*(cnt % 10+1))] | |
msg = "正常" | |
yield chatbot, [], msg | |
# 异步任务结束 | |
gpt_response_collection = [] | |
for inputs_show_user, f in zip(inputs_show_user_array, futures): | |
gpt_res = f.result() | |
gpt_response_collection.extend([inputs_show_user, gpt_res]) | |
return gpt_response_collection | |
def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit): | |
def cut(txt_tocut, must_break_at_empty_line): # 递归 | |
if get_token_fn(txt_tocut) <= limit: | |
return [txt_tocut] | |
else: | |
lines = txt_tocut.split('\n') | |
estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines) | |
estimated_line_cut = int(estimated_line_cut) | |
for cnt in reversed(range(estimated_line_cut)): | |
if must_break_at_empty_line: | |
if lines[cnt] != "": | |
continue | |
print(cnt) | |
prev = "\n".join(lines[:cnt]) | |
post = "\n".join(lines[cnt:]) | |
if get_token_fn(prev) < limit: | |
break | |
if cnt == 0: | |
print('what the fuck ?') | |
raise RuntimeError("存在一行极长的文本!") | |
# print(len(post)) | |
# 列表递归接龙 | |
result = [prev] | |
result.extend(cut(post, must_break_at_empty_line)) | |
return result | |
try: | |
return cut(txt, must_break_at_empty_line=True) | |
except RuntimeError: | |
return cut(txt, must_break_at_empty_line=False) | |
def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit): | |
def cut(txt_tocut, must_break_at_empty_line): # 递归 | |
if get_token_fn(txt_tocut) <= limit: | |
return [txt_tocut] | |
else: | |
lines = txt_tocut.split('\n') | |
estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines) | |
estimated_line_cut = int(estimated_line_cut) | |
cnt = 0 | |
for cnt in reversed(range(estimated_line_cut)): | |
if must_break_at_empty_line: | |
if lines[cnt] != "": | |
continue | |
print(cnt) | |
prev = "\n".join(lines[:cnt]) | |
post = "\n".join(lines[cnt:]) | |
if get_token_fn(prev) < limit: | |
break | |
if cnt == 0: | |
# print('what the fuck ? 存在一行极长的文本!') | |
raise RuntimeError("存在一行极长的文本!") | |
# print(len(post)) | |
# 列表递归接龙 | |
result = [prev] | |
result.extend(cut(post, must_break_at_empty_line)) | |
return result | |
try: | |
return cut(txt, must_break_at_empty_line=True) | |
except RuntimeError: | |
try: | |
return cut(txt, must_break_at_empty_line=False) | |
except RuntimeError: | |
# 这个中文的句号是故意的,作为一个标识而存在 | |
res = cut(txt.replace('.', '。\n'), must_break_at_empty_line=False) | |
return [r.replace('。\n', '.') for r in res] | |