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import gradio as gr |
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import sys |
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import subprocess |
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import pkg_resources |
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def install_package(package): |
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try: |
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subprocess.check_call([sys.executable, "-m", "pip", "install", package]) |
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return True |
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except: |
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return False |
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required_packages = ["torch", "comet"] |
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missing_packages = [] |
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for package in required_packages: |
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try: |
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pkg_resources.get_distribution(package) |
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except pkg_resources.DistributionNotFound: |
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missing_packages.append(package) |
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if missing_packages: |
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print(f"Missing packages: {', '.join(missing_packages)}") |
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for package in missing_packages: |
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if install_package(package): |
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print(f"Successfully installed {package}") |
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else: |
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print(f"Failed to install {package}") |
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print(f"Please install manually: pip install {' '.join(required_packages)}") |
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sys.exit(1) |
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import torch |
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from comet import download_model, load_from_checkpoint |
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def evaluate_translation(src_text, mt_text): |
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if not hasattr(evaluate_translation, "model"): |
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model_path = download_model("wasanx/ComeTH") |
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evaluate_translation.model = load_from_checkpoint(model_path) |
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translations = [{"src": src_text, "mt": mt_text}] |
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results = evaluate_translation.model.predict( |
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translations, |
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batch_size=1, |
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gpus=0 |
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) |
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return float(results['scores'][0]) |
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demo = gr.Interface( |
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fn=evaluate_translation, |
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inputs=[ |
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gr.Textbox(label="English Source Text"), |
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gr.Textbox(label="Thai Translation") |
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], |
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outputs=gr.Number(label="Quality Score"), |
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examples=[ |
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["This is a test sentence.", "นี่คือประโยคทดสอบ"], |
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["The weather is nice today.", "อากาศดีมากวันนี้"] |
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], |
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title="ComeTH Translator Evaluator" |
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) |
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if __name__ == "__main__": |
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demo.launch() |
