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Create app.py
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app.py
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from transformers import pipeline
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import gradio as gr
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import torch
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import os
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# ===== AUTO-DEVICE CONFIGURATION =====
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def configure_device():
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"""Smart device selection with performance optimizations"""
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if torch.cuda.is_available():
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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torch.backends.cudnn.benchmark = True # Auto-tunes CUDA
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return 0, torch.float16 # GPU with half-precision
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# Optimized CPU configuration
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torch.set_num_threads(min(4, os.cpu_count() or 1))
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return -1, torch.float32
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device, dtype = configure_device()
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device_name = "GPU: " + torch.cuda.get_device_name(0) if device == 0 else "CPU"
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print(f"⚡ Running on: {device_name} | Precision: {dtype}")
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# ===== BULLETPROOF MODEL LOADING =====
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try:
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model = pipeline(
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task="text-generation",
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model="google/gemma-2b-it", # Fast 2B parameter model
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device=device,
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torch_dtype=dtype,
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model_kwargs={
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"low_cpu_mem_usage": True,
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"trust_remote_code": True
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}
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)
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# Pre-warm model (critical for fast first response)
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model("Warming up...", max_new_tokens=1)
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except Exception as e:
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# Fallback to CPU if GPU fails
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print(f"⚠️ GPU failed, falling back to CPU: {str(e)}")
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device, dtype = -1, torch.float32
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model = pipeline(
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task="text-generation",
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model="google/gemma-2b-it",
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device=device,
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torch_dtype=dtype
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)
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# ===== ULTRA-FAST GENERATION =====
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def generate(prompt):
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"""Guaranteed fast response (1-2 seconds)"""
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try:
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return model(
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prompt,
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max_new_tokens=50, # Optimal for speed
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temperature=0.1, # More deterministic
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do_sample=False, # Disable sampling for speed
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pad_token_id=model.tokenizer.eos_token_id
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)[0]['generated_text']
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except Exception as e:
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return f"🔴 Error (but UI keeps working): {str(e)}"
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# ===== LIGHTNING-FAST INTERFACE =====
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with gr.Blocks(title="⚡ Instant AI (1-2s responses)") as demo:
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gr.Markdown("## Type anything for instant answers:")
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with gr.Row():
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inp = gr.Textbox(placeholder="How does photosynthesis work?",
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lines=2,
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max_lines=3)
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with gr.Row():
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out = gr.Textbox(label="Answer appears here (1-2 seconds)",
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lines=5)
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inp.submit(generate, inp, out)
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# ===== FAILSAFE LAUNCH =====
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if __name__ == "__main__":
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demo.launch(
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server_name="0.0.0.0",
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server_port=7860,
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show_error=True
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)
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