Update app.py

app.py

@@ -1,36 +1,15 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-from transformers import AutoTokenizer
 import random
 from mySystemPrompt import SYSTEM_PROMPT
 
 # Model which is used
 checkpoint = "mistralai/Mistral-7B-Instruct-v0.2"
-# Tokenizer to convert into the right format
-tokenizer = AutoTokenizer.from_pretrained(checkpoint)
 # Inference client with the model (And HF-token if needed)
 client = InferenceClient(checkpoint)
 
 
-def format_promptOld(message, history, systemPrompt):
-    # Adjusting the format to fit the currently selected model
-    # First everything is converted into role format
-    # First a system prompt
-    messages = []
-    #messages.append({"role": "user", "content": systemPrompt})
-    #messages.append({"role": "assistant", "content": ""})
-    # Followed by the message history
-    for user_message, bot_message in history:
-        messages.append({"role": "user", "content": user_message})
-        messages.append({"role": "assistant", "content": bot_message})
-    # Followed by the current message
-    messages.append({"role": "user", "content": message})
-    # The tokenizer converts into the model format
-    conversationalPart = tokenizer.apply_chat_template(messages, tokenize=False)
-    conversationalPart = conversationalPart.removeprefix('<s>')
-    systemPromptMessage = f"<s>[INST] <<SYS>>\n{systemPrompt}\n<</SYS>>\n\n "
-    forPrompt=systemPromptMessage+str(messages)
-    return forPrompt
+
 def format_prompt(message,chatbot,system_prompt):
     if system_prompt != "":
         input_prompt = f"<s>[INST] <<SYS>>\n{system_prompt}\n<</SYS>>\n\n "