chunzhi/chatgpt_academic
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修正一些细节

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Your Name 2023-04-19 12:29:33 +08:00
parent acaf8cdbf4
commit 23c5a77f82
4 changed files with 11 additions and 9 deletions
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2
config.py
View File

@ -45,7 +45,7 @@ MAX_RETRY = 2
# OpenAI模型选择是（gpt4现在只对申请成功的人开放）
LLM_MODEL = "gpt-3.5-turbo" # 可选 "chatglm"
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "chatglm", "gpt-4", "api2d-gpt-4", "api2d-gpt-3.5-turbo"]
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm"]
# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"

4
main.py
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@ -95,13 +95,13 @@ def main():
with gr.Row():
with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=(LAYOUT == "TOP-DOWN")):
with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN")):
system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
max_length_sl = gr.Slider(minimum=256, maximum=4096, value=512, step=1, interactive=True, label="MaxLength",)
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区", "输入清除键"], 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="").style(container=False)
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
gr.Markdown(description)
with gr.Accordion("备选输入区", open=True, visible=False) as area_input_secondary:

12
request_llm/bridge_chatgpt.py
View File

@ -175,15 +175,17 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
if chunk:
try:
if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
chunk_decoded = chunk.decode()
# 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}')
break
# 处理数据流的主体
chunkjson = json.loads(chunk.decode()[6:])
chunkjson = json.loads(chunk_decoded[6:])
status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
# 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk_decoded[6:])['choices'][0]["delta"]["content"]
history[-1] = gpt_replying_buffer
chatbot[-1] = (history[-2], history[-1])
yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
@ -192,7 +194,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
traceback.print_exc()
yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
chunk = get_full_error(chunk, stream_response)
error_msg = chunk.decode()
error_msg = chunk_decoded
if "reduce the length" in error_msg:
chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长，或历史数据过长. 历史缓存数据现已释放，您可以请再次尝试.")
history = [] # 清除历史
@ -205,7 +207,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
else:
from toolbox import regular_txt_to_markdown
tb_str = '```\n' + traceback.format_exc() + '```'
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk.decode()[4:])}")
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded[4:])}")
yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
return

2
version
View File

@ -1,5 +1,5 @@
{
"version": 3.1,
"show_feature": true,
"new_feature": "添加支持清华ChatGLM和GPT-4 <-> 添加支持API2D（国内不需要代理） <-> 改进架构，支持与多个LLM模型同时对话 <-> 支持多API-KEY负载均衡（并列填写，逗号分割） <-> 添加输入区文本清除按键"
"new_feature": "添加支持清华ChatGLM和GPT-4 <-> 改进架构，支持与多个LLM模型同时对话 <-> 添加支持API2D（国内，可支持gpt4）<-> 支持多API-KEY负载均衡（并列填写，逗号分割） <-> 添加输入区文本清除按键"
}