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import requests
import gradio as gr
API_URL = "https://api-inference.huggingface.co/models/ProsusAI/finbert"
headers = {"Authorization": "Bearer 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"}
def query(payload):
response = requests.post(API_URL, headers=headers, json=payload)
return response.json()[0]
output = query({
"inputs": "I like you. I love you",
})
# def predict_sentiment(payload):
# # Sentiment Analysis
# sentiment_inputs = sentiment_tokenizer(headline, padding=True, truncation=True, return_tensors='pt')
# with torch.no_grad():
# sentiment_outputs = sentiment_model(**sentiment_inputs)
# sentiment_prediction = torch.nn.functional.softmax(sentiment_outputs.logits, dim=-1)
# pos, neg, neutr = sentiment_prediction[:, 0].item(), sentiment_prediction[:, 1].item(), sentiment_prediction[:, 2].item()
# sentiment_label = "Positive" if pos > neg and pos > neutr else "Negative" if neg > pos and neg > neutr else "Neutral"
# return sentiment_label
# Gradio Interface
iface = gr.Interface(
fn=query,
inputs=[gr.Textbox(lines=2, label="Financial Statement")],
outputs=[
gr.Textbox(label="Sentiment"),
],
live=True,
title="Financial Content Sentiment Analysis",
description="Enter a financial statement to analyze its sentiment."
)
iface.launch() |