Upload 132 files

app.py

@@ -17,7 +17,7 @@ def main():
 
     from check_proxy import get_current_version
     initial_prompt = "Serve me as a writing and programming assistant."
-    title_html = f"<h1 align=\"center\">ChatGPT 学术优化 {get_current_version()}</h1>"
+    title_html = f'<h1 align=\"center\">ChatGPT 学术优化 {get_current_version()}<a href="https://huggingface.co/fb700/chatglm-fitness-RLHF">（模型by帛凡Ai）</a></h1>'
     description =  """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
 
     # 问询记录, python 版本建议3.9+（越新越好）
@@ -56,7 +56,7 @@ def main():
     cancel_handles = []
     with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
         gr.HTML(title_html)
-        gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”（Duplicate Space）按钮！<font color="#FF00FF">使用时，先在输入框填入API-KEY然后回车。</font><br/>切忌在“复制空间”（Duplicate Space）之前填入API_KEY或进行提问，否则您的API_KEY将极可能被空间所有者攫取！<br/>支持任意数量的OpenAI的密钥和API2D的密钥共存，例如输入"OpenAI密钥1,API2D密钥2"，然后提交，即可同时使用两种模型接口。</center>''')
+        gr.HTML('''<center>本应用基于chatglm6b【帛凡 AI】的微调模型进行部署，模型中文总结能力优于GPT3.5，欢迎体验<a href="https://huggingface.co/fb700/chatglm-fitness-RLHF">下载地址</a></center>''')
         cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
         with gr_L1():
             with gr_L2(scale=2):
@@ -107,7 +107,7 @@ def main():
                     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="Local LLM MaxLength",)
+                    max_length_sl = gr.Slider(minimum=256, maximum=40960, value=5120, step=1, interactive=True, label="Local LLM MaxLength",)
                     checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区", "输入清除键", "插件参数区"], 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(container=False)
 

check_proxy.py

@@ -150,6 +150,12 @@ def warm_up_modules():
     enc.encode("模块预热", disallowed_special=())
     enc = model_info["gpt-4"]['tokenizer']
     enc.encode("模块预热", disallowed_special=())
+    from request_llm.bridge_chatglm import predict_no_ui_long_connection
+    llm_kwargs = {'max_length': 51200,'top_p': 1,'temperature': 1,}
+    result = predict_no_ui_long_connection( inputs="请问什么是质子？", 
+                                            llm_kwargs=llm_kwargs,
+                                            history=["你好", "我好！"],
+                                            sys_prompt="")
 
 if __name__ == '__main__':
     import os

request_llm/bridge_all.py

@@ -157,7 +157,7 @@ model_info = {
         "fn_with_ui": chatglm_ui,
         "fn_without_ui": chatglm_noui,
         "endpoint": None,
-        "max_token": 1024,
+        "max_token": 40960,
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
@@ -165,7 +165,7 @@ model_info = {
         "fn_with_ui": chatglm_ui,
         "fn_without_ui": chatglm_noui,
         "endpoint": None,
-        "max_token": 1024,
+        "max_token": 40960,
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },

requirements.txt

@@ -15,6 +15,7 @@ openai
 numpy
 arxiv
 rich
+pdfminer
 protobuf
 transformers==4.27.1
 cpm_kernels