Update app.py

app.py

@@ -1,8 +1,35 @@
+# import gradio as gr
+# from transformers import pipeline
+# model = pipeline("text-generation", model="DmitryYarov/aristotle_based_on_rugpt3large_based_on_gpt")
+# def predict(prompt):
+#     completion = model(prompt)[0]["generated_text"]
+#     return completion
+
+# gr.Interface(fn=predict, inputs="text", outputs="text").launch(share=True)
+
 import gradio as gr
 from transformers import pipeline
+
+# Load the text generation model
 model = pipeline("text-generation", model="DmitryYarov/aristotle_based_on_rugpt3large_based_on_gpt")
+
 def predict(prompt):
-    completion = model(prompt)[0]["generated_text"]
-    return completion
+    # Generate text with specified parameters for larger and philosophical answers
+    completions = model(
+        prompt,
+        repetition_penalty=2.0,  # Penalty for repetitions
+        no_repeat_ngram_size=2,   # Prevent repetition of bigrams
+        max_length=500,           # Increased maximum length for more extensive responses
+        num_return_sequences=3,   # Generate multiple sequences for variety
+        num_beams=5,              # Beam search for better quality
+        do_sample=True,           # Enable sampling for generation
+        temperature=0.7,          # Temperature for randomness in generation
+        top_k=50,                 # Limit sampling to top-K probabilities
+        top_p=0.95,               # Limit sampling to top-P probabilities (nucleus sampling)
+        truncation=True            # Truncate text if it exceeds max length
+    )
+    
+    return completions
 
+# Create a Gradio interface with improved layout options
 gr.Interface(fn=predict, inputs="text", outputs="text").launch(share=True)