app.py

import requests
import torch
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, text=payload)
	return response.text()
	
output = query({
	"inputs": "I like you. I love you",
})


# def predict_sentiment(payload):
#     # Sentiment Analysis
    
#     with torch.no_grad():
#         sentiment_outputs = requests.post(API_URL, headers=headers, json=payload)
#         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=predict_sentiment,
    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()