import streamlit as st
import requests
from transformers import pipeline
from deepface import DeepFace
from PIL import Image
import io

# Load Fake News Detection Model from Hugging Face
fake_news_pipeline = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news-detection")

def classify_text(news_text):
    """Classifies text as Fake or Real with accuracy."""
    result = fake_news_pipeline(news_text)[0]
    label = result['label'].lower()
    score = result['score'] * 100  # Convert to percentage
    return ("Fake" if label == "fake" else "Real"), round(score, 2)

def analyze_image(image):
    """Analyzes image using DeepFace and provides a result."""
    try:
        analysis = DeepFace.analyze(image, actions=['emotion'])
        dominant_emotion = analysis[0]['dominant_emotion']
        return f"Analysis Complete - Dominant Emotion: {dominant_emotion}", 90.0  # Dummy Accuracy
    except Exception as e:
        return f"Error: {str(e)}", 0.0

def verify_news(news_text):
    """Generates a Google search link for verification."""
    search_url = f"https://www.google.com/search?q={'+'.join(news_text.split())}"
    return search_url

def check_video_fake_news(video_url):
    """Uses Google Fact-Check API for video verification."""
    api_url = f"https://factchecktools.googleapis.com/v1alpha1/claims:search?query={video_url}&key=YOUR_API_KEY"
    response = requests.get(api_url)
    
    if response.status_code == 200:
        data = response.json()
        if 'claims' in data:
            return "Fake", 85.0  # Fake News Detected (Dummy Value)
        else:
            return "Real", 92.0  # Seems Real (Dummy Value)
    return "Unknown", 0.0  # Could Not Verify

# Streamlit UI
st.set_page_config(page_title="Fake News Detector", layout="wide")
st.title("📰 Fake News Detector")

# 🔹 Sidebar for Input Selection
st.sidebar.title("Select Input Type")
option = st.sidebar.radio("Choose an option", ["Text", "Image", "Video Link"])

# 🔹 Ensure session state variables are initialized
for key in ["analyze_text", "result_text", "accuracy_text", "analyze_image", "analyze_video", "news_image", "video_url"]:
    if key not in st.session_state:
        st.session_state[key] = None

# 🔹 Text Input Section
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:
            result, accuracy = classify_text(news_text)
            st.session_state["result_text"] = result
            st.session_state["accuracy_text"] = accuracy

# 🔹 Image Upload Section
elif option == "Image":
    uploaded_image = st.file_uploader("Upload a news image", type=["jpg", "png", "jpeg"])
    if uploaded_image and st.button("Analyze Image"):
        image = Image.open(uploaded_image)
        st.session_state["news_image"] = image
        result, accuracy = analyze_image(image)
        st.session_state["result_text"] = result
        st.session_state["accuracy_text"] = accuracy

# 🔹 Video Link Section
elif option == "Video Link":
    video_url = st.text_input("Enter the video link:")
    if st.button("Analyze Video"):
        if not video_url.strip():
            st.warning("Please enter a valid video link.")
        else:
            st.session_state["video_url"] = video_url
            result, accuracy = check_video_fake_news(video_url)
            st.session_state["result_text"] = result
            st.session_state["accuracy_text"] = accuracy

# 🔹 Results Section
st.subheader("📊 Analysis Results")
if st.session_state["result_text"]:
    result = st.session_state["result_text"]
    accuracy = st.session_state["accuracy_text"]
    
    if result == "Fake":
        st.error(f"❌ This is likely **Fake News**! (Accuracy: {accuracy}%)", icon="⚠️")
    else:
        st.success(f"✅ This is likely **Real News**! (Accuracy: {accuracy}%)", icon="✅")

    # 🔹 Verification Sources
    st.subheader("🔍 Verification & Trusted Sources")
    sources = [
        "https://www.bbc.com/news",
        "https://www.cnn.com",
        "https://www.reuters.com",
        "https://factcheck.org",
        "https://www.snopes.com",
        "https://www.politifact.com"
    ]
    for link in sources:
        st.markdown(f"[🔗 {link}]({link})")

    if option == "Text":
        verification_link = verify_news(st.session_state["result_text"])
        st.markdown(f"[🔎 Verify on Google]({verification_link})")

# 🔹 Display Image if Uploaded
if st.session_state["news_image"]:
    st.image(st.session_state["news_image"], caption="Uploaded Image", use_column_width=True)

# 🔹 Display Video if Entered
if st.session_state["video_url"]:
    st.video(st.session_state["video_url"])