pulkitsinghall commited on
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Create app.py

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  1. app.py +54 -0
app.py ADDED
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+ import torch # type: ignore
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+ from transformers import pipeline # type: ignore
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+ import gradio as gr # type: ignore
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+ from dotenv import load_dotenv # type: ignore
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+ import os
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+
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+ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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+
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+ load_dotenv()
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+
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+ task = 'text-classification'
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+ model = 'SamLowe/roberta-base-go_emotions'
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+ gitHubLink = 'https://github.com/pulkit-singhall'
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+ linkedInLink = 'https://www.linkedin.com/in/pulkit-singhal-a8113822a/'
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+
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+ pipe = pipeline(task, model, device=device, framework='pt')
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+
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+
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+ def classify_text(text, top_results):
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+ result = pipe(text, top_k = top_results) # array of dict
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+ output = result[0]['label']
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+ output = output[:1].upper() + output[1:]
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+
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+ for i in range(1,len(result)):
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+ label = result[i]['label']
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+ label = label[:1].upper() + label[1:]
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+ output = '\n'.join([output, label])
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+ return output
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+
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+
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+ with gr.Blocks() as app:
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+ gr.Markdown(value = 'Get emotions from any textual sentence...', height = 28)
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+ with gr.Row():
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+ with gr.Column():
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+ sentence = gr.Textbox(label="English Sentence Here")
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+ slider = gr.Slider(
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+ label = 'Top Results you want', value = 1,
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+ minimum = 1, maximum = 10, step = 1)
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+ with gr.Row():
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+ clear_btn = gr.ClearButton(components = [sentence], variant = 'secondary')
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+ classify_btn = gr.Button(value="Submit", variant = 'primary')
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+ with gr.Column():
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+ result = gr.Textbox(label="Required Emotions")
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+
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+ classify_btn.click(classify_text, inputs=[sentence, slider], outputs=[result])
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+ examples = gr.Examples(examples=["That movie was amazing but I did not like the actors.",
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+ "Helen is a good swimmer.",
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+ 'What do you think about Elon Musk and his accomplishments?',
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+ 'Today was a horrible day'],
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+ inputs=[sentence])
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+ gr.Markdown(value = f'Check out my [GitHub]({gitHubLink}) and [LinkedIn]({linkedInLink})',
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+ height = 28)
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+
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+ app.launch(share = True)