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Create app.py
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app.py
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import spaces
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import gradio as gr
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# 1. Load your model at the root level (required for ZeroGPU)
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model_id = "erdemozkan/YOLO-7B-Qwen-Coder"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16,
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device_map="auto"
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)
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# 2. The GPU-decorated function
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@spaces.GPU(duration=60) # Declares a 60s window on the H200
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def yoco_heal(broken_code):
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prompt = f"### System: You are YOLO CODER. Analyze the following broken code and provide a self-healed, working version.\n\n### Broken Code:\n{broken_code}\n\n### Fixed Code:"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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with torch.no_grad():
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outputs = model.generate(
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**inputs,
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max_new_tokens=1024,
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temperature=0.7,
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do_sample=True
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)
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response = tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Extract only the code part from the response
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if "### Fixed Code:" in response:
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return response.split("### Fixed Code:")[1].strip()
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return response
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# 3. The "YOLO" Themed UI
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yoco_theme = gr.themes.Soft(
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primary_hue="yellow",
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secondary_hue="zinc",
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neutral_hue="slate",
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).set(
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body_background_fill="#09090b", # Dark OLED black
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block_background_fill="#18181b",
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button_primary_background_fill="*primary_500",
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button_primary_text_color="black",
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)
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with gr.Blocks(theme=yoco_theme) as demo:
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gr.Markdown("# 🚀 YOLO CODER: Self-Healing AI")
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gr.Markdown("Drop your broken code. Let **yoco** fix it while you grab a coffee.")
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with gr.Row():
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with gr.Column():
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input_code = gr.Code(label="Paste Broken Code", language="python", lines=15)
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heal_btn = gr.Button("YOLO IT!", variant="primary")
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with gr.Column():
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output_code = gr.Code(label="Self-Healed Output", language="python", lines=15)
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heal_btn.click(fn=yoco_heal, inputs=input_code, outputs=output_code)
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gr.Markdown("---")
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gr.Markdown("Built by [Erdem Ozkan](https://huggingface.co/erdemozkan) | Powered by Qwen 7B & ZeroGPU")
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demo.launch()
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