Update app.py

app.py

@@ -16,14 +16,6 @@ def wrap_text(text, width=90):
     return wrapped_text
 
 def multimodal_prompt(user_input, system_prompt="You are an expert medical analyst:"):
-    """
-    Generates text using a large language model, given a user input and a system prompt.
-    Args:
-        user_input: The user's input text to generate a response for.
-        system_prompt: Optional system prompt.
-    Returns:
-        A string containing the generated text.
-    """
     # Combine user input and system prompt
     formatted_input = f"<s>[INST]{system_prompt} {user_input}[/INST]"
 
@@ -44,18 +36,14 @@ def multimodal_prompt(user_input, system_prompt="You are an expert medical analy
         do_sample=True
     )
 
-    # Decode the response
     response_text = tokenizer.decode(output[0], skip_special_tokens=True)
 
     return response_text
 
-# Define the device
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-# Use the base model's ID
 base_model_id = "OpenLLM-France/Claire-Mistral-7B-0.1"
 
-# Instantiate the Tokenizer
 tokenizer = AutoTokenizer.from_pretrained("OpenLLM-France/Claire-Mistral-7B-0.1", trust_remote_code=True, padding_side="left")
 tokenizer.pad_token = tokenizer.eos_token
 tokenizer.padding_side = 'left'
@@ -91,7 +79,7 @@ class ChatBot:
 bot = ChatBot()
 
 title = "👋🏻Welcome to Tonic's Claire Chat🚀"
-description = "You can use this Space to test out the current model (ClaireLLM) or duplicate this Space and use it for any other model on 🤗HuggingFace. Join me on Discord to build together."
+description = "You can use this Space to test out the current model ([ClaireLLM](https://huggingface.co/OpenLLM-France/Claire-Mistral-7B-0.1)) or duplicate this Space and use it for any other model on 🤗HuggingFace. Join me on [Discord to build together](https://discord.gg/nXx5wbX9)."
 examples = [["Oueche Normal, Claire, ça va ou quoi?", "bonjour je m'appele Claire et je suis une assistante francophone-first conçu par openLLM"]]
 
 iface = gr.Interface(