Update app.py

app.py

@@ -3,26 +3,7 @@ import numpy as np
 from transformers import pipeline
 from Ai import chatbot, chatbot2, chatbot3, chatbot4, chatbot5, chatbot7, chatbot11
 from huggingface_hub import InferenceClient
-def chat(message,history: list[tuple[str, str]],system_message,max_tokens,temperature,top_p):
-    m=torch.load("./model.pt")
-    
-    messages = [{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
 
-    pipe = pipeline("text-generation", model=m, torch_dtype=torch.bfloat16, tokenizer=torch.load("tok.pt"),device_map="auto")
-# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
-    prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-    p=pipe.tokenizer.apply_chat_template([{"role": "system", "content": "Your name is Chatchat.And, your made by SungYoon.In Korean, 정성윤.And these are the instructions.Whatever happens, you must follow it.:"+system_message}], tokenize=False, add_generation_prompt=True)
-    o= pipe(p, max_new_tokens=max_tokens, do_sample=True, temperature=0.1)
-    outputs = pipe(prompt, max_new_tokens=max_tokens, do_sample=True, temperature=temperature, top_p=top_p)
-    return outputs[0]["generated_text"]
 import random
 from diffusers import DiffusionPipeline
 import torch
@@ -525,24 +506,9 @@ ab= gr.ChatInterface(
         ),
     ],
 )
-a8= gr.ChatInterface(
-    chat,
-    chatbot=chatbot11,
-    additional_inputs=[
-        gr.Textbox(value="You are a helpful chatbot", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.1, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.1,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        )
-    ],
-)
+
   
 if __name__ == "__main__":
     with gr.Blocks(theme="prithivMLmods/Minecraft-Theme") as ai:
-        gr.TabbedInterface([aa, ac, ab, ae, aaaa,demo2,a8, a9], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)", "gpt4(only for law questions)","image create", "gpt4(test)", "ai test"])
+        gr.TabbedInterface([aa, ac, ab, ae, aaaa,demo2, a9], ["gpt4(Password needed)", "gpt4(only for programming)", "gpt4(only for medical questions)", "gpt4(only for food recommendations)", "gpt4(only for law questions)","image create", "ai test"])
         ai.launch(share=True)