Update app.py

app.py

@@ -1,14 +1,14 @@
-from transformers import AutoTokenizer, AutoModelForCausalLM
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Load the model and tokenizer from Hugging Face
+# Load the model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2")
 model = AutoModelForCausalLM.from_pretrained("Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2")
 
 # Define a function to generate responses
 def generate_response(input_text):
-    # Add a system prompt for improved responses
-    system_prompt = "Think step by step with a logical reasoning and intellectual sense before you provide any response."
+    # Optional: Add a system prompt for improved responses
+    system_prompt = "Think step by step with logical reasoning and intellectual sense before you provide any response."
     input_text = system_prompt + "\n" + input_text
 
     inputs = tokenizer(input_text, return_tensors="pt")
@@ -16,6 +16,12 @@ def generate_response(input_text):
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return response
 
-# Set up the Gradio interface
-iface = gr.Interface(fn=generate_response, inputs="text", outputs="text")
+# Set up Gradio interface with a single input and output
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(label="Input Text", placeholder="Type your message here..."),
+    outputs=gr.Textbox(label="Output"),
+    live=True
+)
+
 iface.launch()