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import gradio as gr |
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import torch |
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from score_fincat import score_fincat |
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from sus_fls import get_sustainability,fls |
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from Cuad_others import quad,summarize_text,fin_ner |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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def load_questions(): |
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questions = [] |
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with open('questionshort.txt') as f: |
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questions = f.readlines() |
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return questions |
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questions = load_questions() |
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answer_main='' |
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def mainFun(query,file): |
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text='' |
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with open(file.name) as f: |
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text = f.read() |
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answer_main,answer_p=quad(query,file) |
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return text,answer_p,summarize_text(answer_main) |
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def mainFun2(temp): |
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return fin_ner(answer_main) |
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demo = gr.Blocks() |
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with demo: |
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txt_file = gr.File(label='CONTRACT') |
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text = gr.Textbox(lines=10) |
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selected_ques=gr.Dropdown(choices=questions,label='SEARCH QUERY') |
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b1 = gr.Button("Analyze File") |
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answer = gr.Textbox(lines=2) |
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summarize = gr.Textbox(lines=2) |
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b1.click(mainFun, inputs=[selected_ques,txt_file], outputs=[text,answer,summarize]) |
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b2=gr.Button("Get NER") |
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label_ner = gr.HighlightedText() |
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b2.click(mainFun2,inputs=answer,outputs=label_ner) |
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b3=gr.Button("Get CLAIM") |
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label_claim = gr.Label() |
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b4=gr.Button("Get SUSTAINABILITY") |
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label_sus = gr.Label() |
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b5=gr.Button("Get FLS") |
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label_fls = gr.Label() |
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demo.launch() |
