Update app.py

app.py

@@ -1,42 +1,51 @@
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Load lightweight model
-tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
-model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
+# Load model
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
 
 def generate_notes(topic):
     """
-    Takes a topic string and generates study-style notes.
+    Generate detailed paragraph-style study notes for a given topic.
     """
     if not topic.strip():
         return "⚠️ Please enter a topic first."
 
     prompt = (
-        f"Create clear, structured study notes about the topic '{topic}'. "
-        f"Include definitions, key points, and examples if possible. "
-        f"Keep it concise and easy to understand."
+        f"Write detailed, well-structured study notes about the topic '{topic}'. "
+        f"Include an introduction, key concepts, examples, and a conclusion. "
+        f"Make the notes clear, paragraph-based, and easy for a student to understand. "
+        f"Use complete sentences and proper formatting."
     )
 
+    # Encode input
     inputs = tokenizer(prompt, return_tensors="pt", truncation=True)
-    outputs = model.generate(**inputs, max_new_tokens=250, temperature=0.7, top_p=0.9)
+
+    # Generate long, detailed text
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=600,       # increase for longer output
+        temperature=0.8,          # adds variety
+        top_p=0.9,                # nucleus sampling
+        repetition_penalty=1.1,   # prevents repeating phrases
+        do_sample=True            # enables more creative generation
+    )
+
     notes = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return notes
+    return notes.strip()
 
 # Gradio UI
 iface = gr.Interface(
     fn=generate_notes,
-    inputs=gr.Textbox(lines=2, placeholder="Enter a topic (e.g. Photosynthesis, Quantum Physics)"),
-    outputs=gr.Textbox(label="Generated Notes", lines=10),
-    title="📘 AI Note Generator",
-    description=(
-        "Enter any topic and get concise, well-structured notes generated by "
-        "a free open-source model (FLAN-T5-small)."
-    ),
+    inputs=gr.Textbox(lines=2, placeholder="Enter a topic (e.g. Photosynthesis, Machine Learning)"),
+    outputs=gr.Textbox(label="Generated Detailed Notes", lines=15),
+    title="📘 AI Detailed Note Generator",
+    description="Generate detailed, structured notes with multiple paragraphs using FLAN-T5-large (runs free on CPU).",
     examples=[
-        ["The water cycle"],
-        ["Machine learning"],
-        ["World War II"]
+        ["Quantum computing"],
+        ["Climate change and its effects"],
+        ["Photosynthesis process"]
     ]
 )