| # import os | |
| # import matplotlib | |
| # matplotlib.use('Agg') # Use the 'Agg' backend for non-interactive use | |
| # import streamlit as st | |
| # import tkinter as tk | |
| # from tkinter import scrolledtext | |
| # import requests | |
| # SECRET_TOKEN = os.getenv("SECRET_TOKEN") | |
| # API_URL = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fahmedrachid%2FFinancialBERT-Sentiment-Analysis%26quot%3B%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
| # headers = {"Authorization": f"Bearer {SECRET_TOKEN}"} | |
| # def query(payload): | |
| # response = requests.post(API_URL, headers=headers, json=payload) | |
| # return response.json() | |
| # user_query = st.text_area("Enter your text:") | |
| # if st.button("Analyze Sentiment"): | |
| # output = query({"inputs": user_query}) | |
| # st.text("Sentiment Analysis Output:") | |
| # st.text(output[0][0]['label']) | |
| import os | |
| import streamlit as st | |
| import requests | |
| SECRET_TOKEN = os.getenv("SECRET_TOKEN") | |
| API_URL = "/static-proxy?url=https%3A%2F%2Fapi-inference.huggingface.co%2Fmodels%2Fahmedrachid%2FFinancialBERT-Sentiment-Analysis%26quot%3B%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
| headers = {"Authorization": f"Bearer {SECRET_TOKEN}"} | |
| def query(payload): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| return response.json() | |
| user_query = st.text_area("Enter your text:") | |
| if st.button("Analyze Sentiment"): | |
| # Show loading message while the model is loading | |
| with st.spinner("Analyzing..."): | |
| # Load the model | |
| output = query({"inputs": user_query}) | |
| # Display results after loading | |
| st.text("Sentiment Analysis Output:") | |
| st.text(output[0][0]['label']) | |