Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import os | |
| import cv2 | |
| import torch | |
| import torchaudio | |
| import torchvision | |
| import tensorflow as tf | |
| from transformers import pipeline | |
| from groq import Groq | |
| from openai import OpenAI | |
| # Set up the Groq client | |
| client = Groq(api_key=os.environ.get("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")) | |
| # Load a fake news detection model from Hugging Face | |
| fake_news_pipeline = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news-detection") | |
| # Streamlit UI | |
| st.set_page_config(page_title="Fake News Detector", layout="wide") | |
| st.title("📰 Fake News Detector") | |
| # Sidebar for navigation | |
| st.sidebar.title("Navigation") | |
| option = st.sidebar.radio("Select Input Type", ["Text", "Image", "Video Link"]) | |
| # Function to fetch real news links (mocked for now) | |
| def fetch_real_news_links(): | |
| return ["https://www.bbc.com/news", "https://www.cnn.com", "https://www.reuters.com"] | |
| if option == "Text": | |
| news_text = st.text_area("Enter the news content to check:", height=200) | |
| if st.button("Analyze News"): | |
| if not news_text.strip(): | |
| st.warning("Please enter some text.") | |
| else: | |
| with st.spinner("Analyzing..."): | |
| # Check using Groq API | |
| chat_completion = client.chat.completions.create( | |
| messages=[{"role": "user", "content": f"Classify this news as Real or Fake: {news_text}"}], | |
| model="llama-3.3-70b-versatile", | |
| stream=False, | |
| ) | |
| groq_result = chat_completion.choices[0].message.content.strip().lower() | |
| # Check using Hugging Face model | |
| hf_result = fake_news_pipeline(news_text)[0]['label'].lower() | |
| # Display result | |
| if "fake" in groq_result or hf_result == "fake": | |
| st.error("❌ This news is likely **Fake**!", icon="⚠️") | |
| st.markdown('<style>div.stAlert {background-color: #ffdddd;}</style>', unsafe_allow_html=True) | |
| elif "real" in groq_result or hf_result == "real": | |
| st.success("✅ This news is likely **Real**!", icon="✅") | |
| st.markdown('<style>div.stAlert {background-color: #ddffdd;}</style>', unsafe_allow_html=True) | |
| else: | |
| st.info("🤔 The result is uncertain. Please verify from trusted sources.") | |
| # Display real news sources | |
| st.subheader("🔗 Reliable News Sources") | |
| for link in fetch_real_news_links(): | |
| st.markdown(f"[🔗 {link}]({link})") | |
| elif option == "Image": | |
| uploaded_file = st.file_uploader("Upload an image of news article", type=["jpg", "png", "jpeg"]) | |
| if uploaded_file is not None: | |
| st.image(uploaded_file, caption="Uploaded Image", use_column_width=True) | |
| st.info("🔍 Image analysis coming soon!") | |
| elif option == "Video Link": | |
| video_url = st.text_input("Enter a video news link to check") | |
| if st.button("Analyze Video"): | |
| if not video_url.strip(): | |
| st.warning("Please enter a valid URL.") | |
| else: | |
| st.info("🔍 Video analysis coming soon!") | |