Update app.py
Browse files
app.py
CHANGED
@@ -37,22 +37,22 @@ def get_sustainability(text):
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return highlight
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#SUSTAINABILITY ENDS
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##Summarization
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def summarize_text(text):
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summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
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resp = summarizer(text)
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stext = resp[0]['summary_text']
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return stext
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##Forward Looking Statement
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def fls(text):
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fls_model = pipeline("text-classification", model="yiyanghkust/finbert-fls", tokenizer="yiyanghkust/finbert-fls")
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results = fls_model(split_in_sentences(text))
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return make_spans(text,results)
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##Company Extraction
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def fin_ner(text):
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ner=pipeline('ner',model='Jean-Baptiste/camembert-ner-with-dates',tokenizer='Jean-Baptiste/camembert-ner-with-dates', aggregation_strategy="simple")
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replaced_spans = ner(text)
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return replaced_spans
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@@ -89,10 +89,12 @@ def quad(query,file):
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raw_answer=data['0'][i]['text']
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answer += f"Answer {i+1}: {data['0'][i]['text']} -- \n"
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answer += f"Probability: {round(data['0'][i]['probability']*100,1)}%\n\n"
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summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
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resp = summarizer(answer)
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stext = resp[0]['summary_text']
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# b6 = gr.Button("Get Sustainability")
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@@ -102,5 +104,7 @@ def quad(query,file):
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#iface = gr.Interface(fn=get_sustainability, inputs="textbox", title="CONBERT",description="SUSTAINABILITY TOOL", outputs=gr.HighlightedText(), allow_flagging="never")
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#iface.launch()
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iface = gr.Interface(fn=quad, inputs=[gr.inputs.Textbox(label='SEARCH QUERY'),gr.inputs.File(label='TXT FILE')], title="CONBERT",description="SUSTAINABILITY TOOL",article='Article', outputs=[gr.outputs.Textbox(label='Answer'),gr.outputs.Textbox(label='Summary')], allow_flagging="never")
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iface.launch()
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return highlight
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#SUSTAINABILITY ENDS
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##Summarization
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summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
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def summarize_text(text):
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resp = summarizer(text)
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stext = resp[0]['summary_text']
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return stext
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##Forward Looking Statement
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fls_model = pipeline("text-classification", model="yiyanghkust/finbert-fls", tokenizer="yiyanghkust/finbert-fls")
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def fls(text):
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results = fls_model(split_in_sentences(text))
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return make_spans(text,results)
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##Company Extraction
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ner=pipeline('ner',model='Jean-Baptiste/camembert-ner-with-dates',tokenizer='Jean-Baptiste/camembert-ner-with-dates', aggregation_strategy="simple")
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def fin_ner(text):
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replaced_spans = ner(text)
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return replaced_spans
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raw_answer=data['0'][i]['text']
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answer += f"Answer {i+1}: {data['0'][i]['text']} -- \n"
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answer += f"Probability: {round(data['0'][i]['probability']*100,1)}%\n\n"
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#summarizer = pipeline("summarization", model="knkarthick/MEETING_SUMMARY")
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#resp = summarizer(answer)
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#stext = resp[0]['summary_text']
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return answer,summarize_text(answer),fin_ner(answer),get_sustainability(answer),fls(answer)
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# b6 = gr.Button("Get Sustainability")
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#iface = gr.Interface(fn=get_sustainability, inputs="textbox", title="CONBERT",description="SUSTAINABILITY TOOL", outputs=gr.HighlightedText(), allow_flagging="never")
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#iface.launch()
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iface = gr.Interface(fn=quad, inputs=[gr.inputs.Textbox(label='SEARCH QUERY'),gr.inputs.File(label='TXT FILE')], title="CONBERT",description="SUSTAINABILITY TOOL",article='Article', outputs=[gr.outputs.Textbox(label='Answer'),gr.outputs.Textbox(label='Summary'),gr.HighlightedText(label='NER'),gr.HighlightedText(label='SUSTAINABILITY'),gr.HighlightedText(label='FLS')], allow_flagging="never")
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iface.launch()
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