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增加打印用户信息

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w_xiaolizu
2023-04-19 21:38:47 +08:00
parent 7a17eb2c9d
commit 9f3194619b
3 changed files with 15 additions and 15 deletions
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4
__main__.py
View File

@ -126,8 +126,8 @@ with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=
label="Temperature", )
max_length_sl = gr.Slider(minimum=256, maximum=4096, value=512, step=1, interactive=True, label="MaxLength",)
models_box = gr.CheckboxGroup(["input加密", "prompt提示"],
value=["input加密", "prompt提示"], label="对话模式")
models_box = gr.CheckboxGroup(["input加密"],
value=["input加密"], label="对话模式")
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"],
value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(

16
request_llm/bridge_chatgpt.py
View File

@ -60,7 +60,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
while True:
try:
# make a POST request to the API endpoint, stream=False
from bridge_all import model_info
from request_llm.bridge_all import model_info
endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
response = requests.post(endpoint, headers=headers, proxies=proxies,
json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
@ -134,7 +134,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
raw_input = inputs
logging.info(f'[raw_input] {raw_input}')
logging.info(f'[raw_input]_{llm_kwargs["ipaddr"]} {raw_input}')
chatbot.append((inputs, ""))
yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
@ -151,12 +151,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
while True:
try:
# make a POST request to the API endpoint, stream=True
from .bridge_all import model_info
from request_llm.bridge_all import model_info
endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
response = requests.post(endpoint, headers=headers, proxies=proxies,
json=payload, stream=True, timeout=TIMEOUT_SECONDS);
print(response)
break
json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
except:
retry += 1
chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
@ -182,7 +180,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
# 前者API2D的
if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
# 判定为数据流的结束，gpt_replying_buffer也写完了
logging.info(f'[response] {gpt_replying_buffer}')
logging.info(f'[response]_{llm_kwargs["ipaddr"]} {gpt_replying_buffer}')
break
# 处理数据流的主体
chunkjson = json.loads(chunk_decoded[6:])
@ -266,14 +264,14 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
"frequency_penalty": 0,
}
try:
print("\033[1;35m", f"{llm_kwargs['llm_model']} :", "\033[0m", f"{conversation_cnt} : {inputs[:100]} ..........")
print("\033[1;35m", f"{llm_kwargs['llm_model']}_{llm_kwargs['ipaddr']} :", "\033[0m", f"{conversation_cnt} : {inputs[:100]} ..........")
except:
print('输入中可能存在乱码。')
return headers, payload
if __name__ == '__main__':
llm_kwargs = {
'api_key': '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',
'api_key': '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',
'llm_model': 'gpt-3.5-turbo',
'top_p': 1,
'max_length': 512,

4
toolbox.py
View File

@ -27,7 +27,9 @@ def ArgsGeneralWrapper(f):
"""
装饰器函数，用于重组输入参数，改变输入参数的顺序与结构。
"""
def decorated(cookies, max_length, llm_model, txt, top_p, temperature, chatbot, history, system_prompt, models, ipaddr:gr.Request, *args):
def decorated(cookies, max_length, llm_model, txt, top_p, temperature,
chatbot, history, system_prompt, models, ipaddr:gr.Request, *args):
""""""
txt_passon = txt
if 'input加密' in models: txt_passon = func_box.encryption_str(txt)
# 引入一个有cookie的chatbot