Update app.py

app.py

@@ -1,8 +1,6 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load a text generation pipeline from a Hugging Face model
-# You can replace this model with "meta-llama/Llama-2-7b-chat-hf" or "mistralai/Mistral-7B-Instruct" if available and compatible
 generator = pipeline("text-generation", model="meta-llama/Llama-2-7b-chat-hf")
 
 def evaluate_response(prompt):
@@ -10,7 +8,7 @@ def evaluate_response(prompt):
     outputs = generator(prompt, max_new_tokens=150, do_sample=True, temperature=0.7)
     generated_text = outputs[0]['generated_text']
 
-    # Simple quality evaluation: check length of generated response
+    # Simple quality evaluation: check if response length > 10 words
     word_count = len(generated_text.split())
     quality = "Good" if word_count > 10 else "Poor"
 
@@ -21,7 +19,7 @@ iface = gr.Interface(
     inputs=gr.Textbox(lines=4, label="Enter your prompt"),
     outputs=[gr.Textbox(label="Model Response"), gr.Textbox(label="Quality Analysis")],
     title="Model Understanding Test",
-    description="Enter instructions or a question, the app sends it to a language model and evaluates the response quality."
+    description="Enter a prompt, get a model response, and see an automatic quality evaluation."
 )
 
 if __name__ == "__main__":