Update app.py

app.py

@@ -10,11 +10,12 @@ import io
 fake_news_pipeline = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news-detection")
 
 def classify_text(news_text):
-    result = fake_news_pipeline(news_text)[0]['label'].lower()
-    return "Fake" if result == "fake" else "Real"
+    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):
-    # Convert image to tensor (Placeholder: Model should be updated with a real image classifier)
     transform = transforms.Compose([transforms.Resize((224, 224)), transforms.ToTensor()])
     image_tensor = transform(image).unsqueeze(0)
     return "Image analysis feature coming soon!"
@@ -27,76 +28,72 @@ def verify_news(news_text):
 st.set_page_config(page_title="Fake News Detector", layout="wide")
 st.title("📰 Fake News Detector")
 
-# Tabs for Input and Results
-tab1, tab2 = st.tabs(["Input", "Results"])
+# Sidebar for Input Selection
+st.sidebar.title("Select Input Type")
+option = st.sidebar.radio("Choose an option", ["Text", "Image", "Video Link"])
 
-with tab1:
-    st.sidebar.title("Select Input Type")
-    option = st.sidebar.radio("Choose an option", ["Text", "Image", "Video Link"])
+# Input Section
+if option == "Text":
+    news_text = st.text_area("Enter the news content to check:", height=200)
+    if st.button("Analyze News", key="analyze_text"):
+        if not news_text.strip():
+            st.warning("Please enter some text.")
+        else:
+            result, accuracy = classify_text(news_text)
+            st.session_state["news_text"] = news_text
+            st.session_state["analyze_text"] = True
+            st.session_state["result_text"] = result
+            st.session_state["accuracy_text"] = accuracy
 
-    if option == "Text":
-        st.subheader("📝 Enter News Text")
-        news_text = st.text_area("Enter the news content to check:", height=200)
-        if st.button("Analyze News", key="text_analyze", help="Click to analyze the text input"):
-            if not news_text.strip():
-                st.warning("⚠️ Please enter some text.")
-            else:
-                st.session_state["news_text"] = news_text
-                st.session_state["analyze_text"] = True
-                st.rerun()
+elif option == "Image":
+    uploaded_image = st.file_uploader("Upload a news image", type=["jpg", "png", "jpeg"])
+    if uploaded_image and st.button("Analyze Image", key="analyze_image"):
+        image = Image.open(uploaded_image)
+        st.session_state["news_image"] = image
+        st.session_state["analyze_image"] = True
 
-    elif option == "Image":
-        st.subheader("🖼 Upload News Image")
-        uploaded_image = st.file_uploader("Upload a news image", type=["jpg", "png", "jpeg"], key="image_upload")
-        if uploaded_image and st.button("Analyze Image", key="image_analyze", help="Click to analyze the uploaded image"):
-            image = Image.open(uploaded_image)
-            st.session_state["news_image"] = image
-            st.session_state["analyze_image"] = True
-            st.rerun()
+elif option == "Video Link":
+    video_url = st.text_input("Enter the video link:")
+    if st.button("Analyze Video", key="analyze_video"):
+        if not video_url.strip():
+            st.warning("Please enter a valid video link.")
+        else:
+            st.session_state["video_url"] = video_url
+            st.session_state["analyze_video"] = True
 
-    elif option == "Video Link":
-        st.subheader("🎥 Enter Video Link")
-        video_url = st.text_input("Enter the video link:", key="video_input")
-        if st.button("Analyze Video", key="video_analyze", help="Click to analyze the video link"):
-            if not video_url.strip():
-                st.warning("⚠️ Please enter a valid video link.")
-            else:
-                st.session_state["video_url"] = video_url
-                st.session_state["analyze_video"] = True
-                st.rerun()
+# Results Section
+st.subheader("📊 Analysis Results")
+if st.session_state.get("analyze_text", False):
+    result = st.session_state.get("result_text")
+    accuracy = st.session_state.get("accuracy_text")
+    verification_link = verify_news(st.session_state.get("news_text"))
+    
+    if result == "Fake":
+        st.error(f"❌ This news is likely **Fake**! (Accuracy: {accuracy}%)", icon="⚠️")
+    else:
+        st.success(f"✅ This news is likely **Real**! (Accuracy: {accuracy}%)", icon="✅")
+    
+    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",
+        "https://deepfake-o-meter.ai",
+        "https://huggingface.co/models?pipeline_tag=text-classification"
+    ]
+    for link in sources:
+        st.markdown(f"[���� {link}]({link})")
+    st.markdown(f"[🔎 Verify on Google]({verification_link})")
 
-with tab2:
-    if st.session_state.get("analyze_text", False):
-        news_text = st.session_state.get("news_text", "")
-        with st.spinner("Analyzing text..."):
-            result = classify_text(news_text)
-            verification_link = verify_news(news_text)
-            
-            if result == "Fake":
-                st.error("❌ This news is likely **Fake**!", icon="⚠️")
-                st.markdown("<style>div.stAlert {background-color: #FFCCCC;}</style>", unsafe_allow_html=True)
-            else:
-                st.success("✅ This news is likely **Real**!", icon="✅")
-                st.markdown("<style>div.stAlert {background-color: #CCFFCC;}</style>", unsafe_allow_html=True)
-            
-            st.subheader("🔍 Verification & Trusted Sources")
-            sources = [
-                "https://www.bbc.com/news",
-                "https://www.cnn.com",
-                "https://www.reuters.com",
-                "https://huggingface.co/datasets",
-                "https://wildfireai.com/deepfake-detection"
-            ]
-            for link in sources:
-                st.markdown(f"[🔗 {link}]({link})")
-            st.markdown(f"[🔎 Verify on Google]({verification_link})")
+if st.session_state.get("analyze_image", False):
+    image = st.session_state.get("news_image")
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    st.info(analyze_image(image))
 
-    if st.session_state.get("analyze_image", False):
-        image = st.session_state.get("news_image")
-        st.image(image, caption="Uploaded Image", use_column_width=True)
-        st.info(analyze_image(image))
-
-    if st.session_state.get("analyze_video", False):
-        video_url = st.session_state.get("video_url", "")
-        st.video(video_url)
-        st.info("Video analysis feature coming soon!")
+if st.session_state.get("analyze_video", False):
+    video_url = st.session_state.get("video_url", "")
+    st.video(video_url)
+    st.info("Video analysis feature coming soon!")