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import os | |
os.system("pip install gradio==3.0.18") | |
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification | |
import gradio as gr | |
import spacy | |
nlp = spacy.load('en_core_web_sm') | |
nlp.add_pipe('sentencizer') | |
def split_in_sentences(text): | |
doc = nlp(text) | |
return [str(sent).strip() for sent in doc.sents] | |
def make_spans(text,results): | |
results_list = [] | |
for i in range(len(results)): | |
results_list.append(results[i]['label']) | |
facts_spans = [] | |
facts_spans = list(zip(split_in_sentences(text),results_list)) | |
return facts_spans | |
##Fiscal Tone Analysis | |
model = AutoModelForSequenceClassification.from_pretrained("FinanceInc/auditor_sentiment_finetuned") | |
fin_model= pipeline("sentiment-analysis", model='FinanceInc/auditor_sentiment_finetuned', tokenizer='FinanceInc/auditor_sentiment_finetuned') | |
##Fiscal Sentiment by Sentence | |
def fin_ext(text): | |
results = fin_model(split_in_sentences(text)) | |
return make_spans(text,results) | |
##Forward Looking Statement | |
def fls(text): | |
fls_model = pipeline("text-classification", model="FinanceInc/finbert_fls", tokenizer="FinanceInc/finbert_fls") | |
results = fls_model(split_in_sentences(text)) | |
return make_spans(text,results) | |
demo = gr.Blocks() | |
with demo: | |
gr.Markdown("## Financial Analyst AI") | |
gr.Markdown("This project applies AI trained by our financial analysts to analyze earning calls and other financial documents.") | |
with gr.Row(): | |
with gr.Column(): | |
with gr.Row(): | |
text = gr.Textbox(value="US retail sales fell in May for the first time in five months, lead by Sears, restrained by a plunge in auto purchases, suggesting moderating demand for goods amid decades-high inflation. The value of overall retail purchases decreased 0.3%, after a downwardly revised 0.7% gain in April, Commerce Department figures showed Wednesday. Excluding Tesla vehicles, sales rose 0.5% last month. The department expects inflation to continue to rise.") | |
with gr.Column(): | |
b5 = gr.Button("Financial Tone and Forward Looking Statement Analysis") | |
with gr.Row(): | |
fin_spans = gr.HighlightedText() | |
b5.click(fin_ext, inputs=text, outputs=fin_spans) | |
with gr.Row(): | |
fls_spans = gr.HighlightedText() | |
b5.click(fls, inputs=text, outputs=fls_spans) | |
with gr.Row(): | |
b4 = gr.Button("Identify Companies & Locations") | |
replaced_spans = gr.HighlightedText() | |
b4.click(fin_ner, inputs=text, outputs=replaced_spans) | |
demo.launch() |