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import torch |
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import gradio as gr |
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from transformers import pipeline |
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pipe = pipeline("question-answering", model="deepset/roberta-base-squad2") |
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def read_file_content(file_obj): |
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try: |
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with open(file_obj.name, "r", encoding="utf-8") as f: |
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content = f.read() |
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return content |
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except Exception as e: |
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return f"An error occurred: {e}" |
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def get_answer(file, question): |
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context= read_file_content(file) |
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answer = pipe(question=question, context = context) |
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return (answer['answer']) |
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demo = gr.Interface(fn=get_answer, |
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inputs= [gr.File(label="Upload the file for context"), gr.Textbox(label='Ask the question')], |
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outputs=[gr.Textbox(label='Here is the answer to your question')], |
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title='Get the Answers to your question', |
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description='This application gives the answers to your questions' |
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) |
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demo.launch() |
