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'''
Contributed by SagsMug. Modified by binary-husky
https://github.com/oobabooga/text-generation-webui/pull/175
'''
import asyncio
import json
import random
import string
import websockets
import logging
import time
import threading
import importlib
from toolbox import get_conf, update_ui
def random_hash():
letters = string.ascii_lowercase + string.digits
return ''.join(random.choice(letters) for i in range(9))
async def run(context, max_token, temperature, top_p, addr, port):
params = {
'max_new_tokens': max_token,
'do_sample': True,
'temperature': temperature,
'top_p': top_p,
'typical_p': 1,
'repetition_penalty': 1.05,
'encoder_repetition_penalty': 1.0,
'top_k': 0,
'min_length': 0,
'no_repeat_ngram_size': 0,
'num_beams': 1,
'penalty_alpha': 0,
'length_penalty': 1,
'early_stopping': True,
'seed': -1,
}
session = random_hash()
async with websockets.connect(f"ws://{addr}:{port}/queue/join") as websocket:
while content := json.loads(await websocket.recv()):
#Python3.10 syntax, replace with if elif on older
if content["msg"] == "send_hash":
await websocket.send(json.dumps({
"session_hash": session,
"fn_index": 12
}))
elif content["msg"] == "estimation":
pass
elif content["msg"] == "send_data":
await websocket.send(json.dumps({
"session_hash": session,
"fn_index": 12,
"data": [
context,
params['max_new_tokens'],
params['do_sample'],
params['temperature'],
params['top_p'],
params['typical_p'],
params['repetition_penalty'],
params['encoder_repetition_penalty'],
params['top_k'],
params['min_length'],
params['no_repeat_ngram_size'],
params['num_beams'],
params['penalty_alpha'],
params['length_penalty'],
params['early_stopping'],
params['seed'],
]
}))
elif content["msg"] == "process_starts":
pass
elif content["msg"] in ["process_generating", "process_completed"]:
yield content["output"]["data"][0]
# You can search for your desired end indicator and
# stop generation by closing the websocket here
if (content["msg"] == "process_completed"):
break
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
"""
发送至chatGPT，流式获取输出。
用于基础的对话功能。
inputs 是本次问询的输入
top_p, temperature是chatGPT的内部调优参数
history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
additional_fn代表点击的哪个按钮，按钮见functional.py
"""
if additional_fn is not None:
from core_functional import handle_core_functionality
inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
raw_input = "What I would like to say is the following: " + inputs
history.extend([inputs, ""])
chatbot.append([inputs, ""])
yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
prompt = raw_input
tgui_say = ""
model_name, addr_port = llm_kwargs['llm_model'].split('@')
assert ':' in addr_port, "LLM_MODEL 格式不正确！" + llm_kwargs['llm_model']
addr, port = addr_port.split(':')
mutable = ["", time.time()]
def run_coorotine(mutable):
async def get_result(mutable):
# "tgui:galactica-1.3b@localhost:7860"
async for response in run(context=prompt, max_token=llm_kwargs['max_length'],
temperature=llm_kwargs['temperature'],
top_p=llm_kwargs['top_p'], addr=addr, port=port):
print(response[len(mutable[0]):])
mutable[0] = response
if (time.time() - mutable[1]) > 3:
print('exit when no listener')
break
asyncio.run(get_result(mutable))
thread_listen = threading.Thread(target=run_coorotine, args=(mutable,), daemon=True)
thread_listen.start()
while thread_listen.is_alive():
time.sleep(1)
mutable[1] = time.time()
# Print intermediate steps
if tgui_say != mutable[0]:
tgui_say = mutable[0]
history[-1] = tgui_say
chatbot[-1] = (history[-2], history[-1])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience=False):
raw_input = "What I would like to say is the following: " + inputs
prompt = raw_input
tgui_say = ""
model_name, addr_port = llm_kwargs['llm_model'].split('@')
assert ':' in addr_port, "LLM_MODEL 格式不正确！" + llm_kwargs['llm_model']
addr, port = addr_port.split(':')
def run_coorotine(observe_window):
async def get_result(observe_window):
async for response in run(context=prompt, max_token=llm_kwargs['max_length'],
temperature=llm_kwargs['temperature'],
top_p=llm_kwargs['top_p'], addr=addr, port=port):
print(response[len(observe_window[0]):])
observe_window[0] = response
if (time.time() - observe_window[1]) > 5:
print('exit when no listener')
break
asyncio.run(get_result(observe_window))
thread_listen = threading.Thread(target=run_coorotine, args=(observe_window,))
thread_listen.start()
return observe_window[0]
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