update app

app.py

@@ -1,205 +1,131 @@
 import gradio as gr
 import os
-import time
-from collections import defaultdict
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 import torch
 
-# Load secrets from environment
+print("🚀 Starting GPT-2 Text Generator...")
+
+# Load environment variables
 HF_TOKEN = os.getenv("HF_TOKEN")
-API_KEY = os.getenv("API_KEY")
+API_KEY = os.getenv("API_KEY") 
 ADMIN_PASSWORD = os.getenv("ADMIN_PASSWORD")
 
-print("🔐 Security Status:")
-print(f"   HF_TOKEN: {'✅ Set' if HF_TOKEN else '❌ Not set'}")
-print(f"   API_KEY: {'✅ Set' if API_KEY else '❌ Not set'}")
-print(f"   ADMIN_PASSWORD: {'✅ Set' if ADMIN_PASSWORD else '❌ Not set'}")
-
-# Simple rate limiting
-request_counts = defaultdict(list)
-
-# Load model
-model_name = "gpt2"
-print("📦 Loading model...")
+print(f"HF_TOKEN: {'Set' if HF_TOKEN else 'Not set'}")
+print(f"API_KEY: {'Set' if API_KEY else 'Not set'}")
+print(f"ADMIN_PASSWORD: {'Set' if ADMIN_PASSWORD else 'Not set'}")
 
+# Load model and tokenizer
+print("Loading GPT-2 model...")
 try:
-    if HF_TOKEN:
-        tokenizer = GPT2Tokenizer.from_pretrained(model_name, token=HF_TOKEN)
-        model = GPT2LMHeadModel.from_pretrained(model_name, token=HF_TOKEN)
-        print("✅ Model loaded with HF token")
-    else:
-        tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-        model = GPT2LMHeadModel.from_pretrained(model_name)
-        print("✅ Model loaded without token")
-        
+    tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+    model = GPT2LMHeadModel.from_pretrained("gpt2")
     tokenizer.pad_token = tokenizer.eos_token
-    print("✅ Model ready!")
-    
+    print("✅ Model loaded successfully!")
 except Exception as e:
-    print(f"❌ Model loading failed: {e}")
-    raise
+    print(f"❌ Error loading model: {e}")
+    raise e
 
-def check_api_key(provided_key):
-    """Simple API key validation with rate limiting"""
-    if not API_KEY:
-        return True, "Public access"
-    
-    if not provided_key or provided_key != API_KEY:
-        return False, "Invalid or missing API key"
-    
-    # Simple rate limiting (100 requests per hour)
-    now = time.time()
-    hour_ago = now - 3600
-    
-    # Clean old requests
-    request_counts[provided_key] = [
-        t for t in request_counts[provided_key] if t > hour_ago
-    ]
-    
-    if len(request_counts[provided_key]) >= 100:
-        return False, "Rate limit exceeded (100/hour)"
-    
-    request_counts[provided_key].append(now)
-    return True, f"Authenticated ({len(request_counts[provided_key])}/100)"
-
-def generate_text(prompt, max_length, temperature, top_p, top_k, api_key):
-    """Generate text with GPT-2"""
-    
-    # API key check
-    valid, msg = check_api_key(api_key)
-    if not valid:
-        return f"🔒 Error: {msg}"
-    
-    # Input validation  
-    if not prompt.strip():
-        return "❌ Please enter a prompt"
+def generate_text(prompt, max_length=100, temperature=0.7):
+    """Simple text generation function"""
+    if not prompt:
+        return "Please enter a prompt"
     
-    if len(prompt) > 1000:
-        return "❌ Prompt too long (max 1000 chars)"
+    if len(prompt) > 500:
+        return "Prompt too long (max 500 characters)"
     
     try:
-        print(f"🔑 {msg}")
-        print(f"📝 Generating: {prompt[:50]}...")
+        print(f"Generating text for: {prompt[:30]}...")
         
-        # Encode input
-        inputs = tokenizer.encode(
-            prompt, 
-            return_tensors="pt", 
-            max_length=400, 
-            truncation=True
-        )
+        # Encode the prompt
+        inputs = tokenizer.encode(prompt, return_tensors="pt", max_length=300, truncation=True)
         
-        # Generate
+        # Generate text
         with torch.no_grad():
             outputs = model.generate(
                 inputs,
-                max_length=min(inputs.shape[1] + max_length, 500),
-                temperature=max(0.1, min(2.0, temperature)),
-                top_p=max(0.1, min(1.0, top_p)),
-                top_k=max(1, min(100, top_k)),
+                max_length=inputs.shape[1] + max_length,
+                temperature=temperature,
                 do_sample=True,
                 pad_token_id=tokenizer.eos_token_id,
-                num_return_sequences=1,
+                eos_token_id=tokenizer.eos_token_id,
                 no_repeat_ngram_size=2
             )
         
-        # Decode result
-        generated = tokenizer.decode(outputs[0], skip_special_tokens=True)
-        result = generated[len(prompt):].strip()
+        # Decode the output
+        generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
         
-        print(f"✅ Generated {len(result)} characters")
-        return result if result else "❌ No text generated"
+        # Extract only the new text (remove the original prompt)
+        new_text = generated_text[len(prompt):].strip()
+        
+        print(f"✅ Generated {len(new_text)} characters")
+        return new_text if new_text else "No text generated. Try a different prompt."
         
     except Exception as e:
-        error = f"❌ Generation failed: {str(e)}"
-        print(error)
-        return error
+        error_msg = f"Error generating text: {str(e)}"
+        print(f"❌ {error_msg}")
+        return error_msg
 
-# Create simple interface - NO COMPLEX THEMES OR CSS
-demo = gr.Blocks(title="GPT-2 Text Generator")
+# Create the Gradio interface
+print("Creating Gradio interface...")
 
-with demo:
-    # Simple header
-    gr.Markdown("# 🤖 GPT-2 Text Generator")
-    
-    # Security info
-    if API_KEY:
-        gr.Markdown("🔒 **API Authentication Required**")
-    else:
-        gr.Markdown("🔓 **Public Access Mode**")
+with gr.Blocks() as demo:
+    gr.Markdown("# GPT-2 Text Generator")
+    gr.Markdown("Enter a prompt and click generate to create text using GPT-2")
     
     with gr.Row():
         with gr.Column():
-            # Input section
-            prompt = gr.Textbox(
-                label="Prompt", 
-                placeholder="Enter your text prompt...",
+            prompt_input = gr.Textbox(
+                label="Enter your prompt",
+                placeholder="Type your text here...",
                 lines=3
             )
             
-            # API key input (only if needed)
-            if API_KEY:
-                api_key = gr.Textbox(
-                    label="API Key",
-                    type="password",
-                    placeholder="Enter API key..."
-                )
-            else:
-                api_key = gr.Textbox(value="", visible=False)
-            
-            # Parameters
-            max_length = gr.Slider(
-                10, 200, 100, 
-                label="Max Length"
-            )
-            temperature = gr.Slider(
-                0.1, 2.0, 0.7, 
-                label="Temperature"
+            max_length_slider = gr.Slider(
+                minimum=20,
+                maximum=200,
+                value=100,
+                step=10,
+                label="Max length of generated text"
             )
-            top_p = gr.Slider(
-                0.1, 1.0, 0.9, 
-                label="Top-p"
-            )
-            top_k = gr.Slider(
-                1, 100, 50, 
-                label="Top-k"
+            
+            temperature_slider = gr.Slider(
+                minimum=0.1,
+                maximum=1.5,
+                value=0.7,
+                step=0.1,
+                label="Temperature (creativity)"
             )
             
-            # Generate button
-            generate_btn = gr.Button("Generate", variant="primary")
+            generate_button = gr.Button("Generate Text", variant="primary")
         
         with gr.Column():
-            # Output
-            output = gr.Textbox(
+            output_text = gr.Textbox(
                 label="Generated Text",
-                lines=10,
+                lines=8,
                 placeholder="Generated text will appear here..."
             )
     
-    # Examples
-    gr.Examples([
-        ["Once upon a time"],
-        ["The future of AI is"],
-        ["In a world where technology"],
-    ], inputs=prompt)
+    # Add some example prompts
+    gr.Examples(
+        examples=[
+            "Once upon a time",
+            "The future of technology is",
+            "In a world where",
+        ],
+        inputs=prompt_input
+    )
     
-    # Connect function
-    generate_btn.click(
-        generate_text,
-        inputs=[prompt, max_length, temperature, top_p, top_k, api_key],
-        outputs=output
+    # Connect the generate function
+    generate_button.click(
+        fn=generate_text,
+        inputs=[prompt_input, max_length_slider, temperature_slider],
+        outputs=output_text
     )
 
-# Simple launch - MINIMAL CONFIGURATION
+# Launch the app
+print("Launching Gradio app...")
+
 if __name__ == "__main__":
-    auth = ("admin", ADMIN_PASSWORD) if ADMIN_PASSWORD else None
-    
-    if auth:
-        print("🔐 Admin auth enabled")
-    
-    print("🚀 Starting server...")
-    
-    # MINIMAL launch config that works on HF Spaces
-    demo.launch(auth=auth)
-    
-    print("✅ Server running!")
+    demo.launch()
+
+print("✅ App is running!")

requirements.txt

@@ -1,4 +1,4 @@
-gradio
-transformers
-torch
-tokenizers
+gradio==4.44.0
+transformers==4.44.2
+torch==2.4.1
+tokenizers==0.19.1