Update app.py

app.py

@@ -1,64 +1,62 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load 5 reasonably sized models (avoid big ones like Falcon-7B)
+# Lightweight models that work within 16GB RAM
 models = {
-    "🧠 FLAN-T5 (large)": pipeline("text2text-generation", model="google/flan-t5-large"),
-    "✍️ GPT-Neo (1.3B)": pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B"),
-    "📖 BART": pipeline("text2text-generation", model="facebook/bart-large-cnn"),
-    "📚 Palmyra": pipeline("text-generation", model="Writer/palmyra-base"),
-    "📝 T5-Small": pipeline("text2text-generation", model="t5-small")
+    "📘 T5-Small": pipeline("text2text-generation", model="t5-small"),
+    "📗 DistilGPT2": pipeline("text-generation", model="distilgpt2"),
+    "📕 DistilBART": pipeline("text2text-generation", model="sshleifer/distilbart-cnn-12-6"),
+    "📙 Pegasus-Tiny": pipeline("text2text-generation", model="google/pegasus-small"),
+    "📒 FLAN-T5-Base": pipeline("text2text-generation", model="google/flan-t5-base")
 }
 
-def generate_text(prompt, model_name):
-    if not prompt.strip():
-        return "⚠️ Please enter a topic or idea."
-    
-    generator = models[model_name]
-    if "text2text" in generator.task:
-        result = generator(prompt, max_length=200)[0]["generated_text"]
-    else:
-        result = generator(prompt, max_length=200, do_sample=True, temperature=0.7)[0]["generated_text"]
-    
-    return result
-
+# Content generation function
+def generate_content(topic):
+    outputs = {}
+    for name, model in models.items():
+        try:
+            if "text-generation" in str(model):
+                result = model(topic, max_length=100, do_sample=False)[0]['generated_text']
+            else:
+                result = model(topic, max_length=100, do_sample=False)[0]['generated_text']
+            outputs[name] = result
+        except Exception as e:
+            outputs[name] = f"Error: {str(e)}"
+    return [outputs[name] for name in models.keys()]
+
+# Gradio UI
+gr.Theme.set("default")
 with gr.Blocks(css="""
 body {
-    background-color: #fffde7; /* Light lemon */
+    background-color: #fffde7;
 }
 #title {
-    color: #6b4f26; /* Brown */
     text-align: center;
-    font-size: 40px;
+    font-size: 34px;
     font-weight: bold;
-    margin-top: 20px;
-}
-#subtitle {
-    text-align: center;
-    color: #8d6e63;
-    font-size: 16px;
-    margin-bottom: 30px;
+    color: #8b4513;
+    margin-bottom: 20px;
 }
 .output-box {
-    background-color: #f9fbe7;
-    border: 2px dashed #c8b900;
-    padding: 15px;
+    border: 2px solid #d4af37;
+    padding: 10px;
     border-radius: 10px;
+    background-color: #fff8dc;
 }
 """) as demo:
 
-    gr.Markdown("<div id='title'>🪄 LLM for Content Generation</div>")
-    gr.Markdown("<div id='subtitle'>Enter a topic and see how different LLMs generate creative content.</div>")
+    gr.Markdown("<div id='title'>📝 LLM for Content Generation</div>")
 
     with gr.Row():
         with gr.Column():
-            user_input = gr.Textbox(label="Enter your topic or idea", lines=3, placeholder="e.g., The future of AI in education")
-            model_choice = gr.Radio(choices=list(models.keys()), label="Select a model", value="🧠 FLAN-T5 (large)")
-            gen_btn = gr.Button("✨ Generate Content")
+            topic = gr.Textbox(label="Enter your topic", placeholder="e.g. Climate Change Impact on Economy")
+            generate_button = gr.Button("Generate Content ✨")
 
         with gr.Column():
-            output = gr.Textbox(label="Generated Content", lines=12, elem_classes=["output-box"])
+            outputs = [gr.Textbox(label=model, lines=6, elem_classes=["output-box"]) for model in models.keys()]
+
+    generate_button.click(fn=generate_content, inputs=[topic], outputs=outputs)
 
-    gen_btn.click(fn=generate_text, inputs=[user_input, model_choice], outputs=output)
+    gr.Markdown("<center>💡 Compare outputs from 5 different lightweight LLMs. Fast, efficient, and creative!</center>")
 
 demo.launch()