Update app.py

app.py

@@ -1,19 +1,19 @@
 import streamlit as st
 import torch
-from transformers import AutoTokenizer, AutoModelForSequenceClassification,pipeline
-
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+from deep_translator import GoogleTranslator
 import requests
-import json
-
+import os
 
-st.set_page_config(page_title="News Prediction", page_icon=":earth_africa:")
-
-# Load tokenizer and model
+# Load tokenizer and fake news model
 tokenizer = AutoTokenizer.from_pretrained("hamzab/roberta-fake-news-classification")
 model = AutoModelForSequenceClassification.from_pretrained("hamzab/roberta-fake-news-classification")
 
+# Load summarizer pipeline
+summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")
 
-from deep_translator import GoogleTranslator
+# Google Fact Check API key (replace with your actual key or use st.secrets)
+GOOGLE_API_KEY = "AIzaSyAf5v5380xkpo0Rk3kBiSxpxYVBQwcDi2A"
 
 def translate_to_english(text):
     try:
@@ -21,7 +21,12 @@ def translate_to_english(text):
     except Exception as e:
         return f"Error in translation: {e}"
 
-
+def summarize_text(text):
+    try:
+        summary = summarizer(text, max_length=60, min_length=15, do_sample=False)
+        return summary[0]['summary_text']
+    except Exception as e:
+        return f"Error in summarization: {e}"
 
 def predict_fake(title, text):
     input_str = "<title>" + title + "<content>" + text + "<end>"
@@ -34,111 +39,46 @@ def predict_fake(title, text):
 
 def fact_check_with_google(api_key, query):
     url = f"https://factchecktools.googleapis.com/v1alpha1/claims:search"
-    params = {
-        "query": query,
-        "key": api_key
-    }
+    params = {"query": query, "key": api_key}
     response = requests.get(url, params=params)
     if response.status_code == 200:
         return response.json()
     else:
-        return {"error": f"Unable to fetch results from Google Fact Check API. HTTP {response.status_code}: {response.text}"}
-
-'''def main():
-    st.title("Fake News Prediction")
-
-    # Load Google API key from a secure location or environment variable
-    
-
-    # Create the form for user input
-    with st.form("news_form"):
-        st.subheader("Enter News Details")
-        title = st.text_input("Title")
-        text = st.text_area("Text")
-        language = st.selectbox("Select Language", options=["English", "Other"])
-        submit_button = st.form_submit_button("Submit")
-
-    # Process form submission and make prediction
-    if submit_button:
-        if language == "Other":
-            title = translate_to_english(title)
-            text = translate_to_english(text)
-
-        prediction = predict_fake(title, text)
-
-        st.subheader("Prediction:")
-        st.write("Prediction: ", prediction)
-
-        if prediction.get("Real") > 0.5:
-            st.write("This news is predicted to be **real** :muscle:")
-        else:
-            st.write("This news is predicted to be **fake** :shit:")
-     
-            '''
-# Load summarizer
-@st.cache_resource
-def load_summarizer():
-    return pipeline("summarization", model="facebook/bart-large-cnn")
-
-summarizer = load_summarizer()
-
-
-
-def summarize_text(text):
-    try:
-        summary = summarizer(text, max_length=30, min_length=5, do_sample=False)
-        return summary[0]['summary_text']
-    except Exception as e:
-        return f"Error in summarization: {e}"
-
+        return {"error": f"Unable to fetch fact-checks. HTTP {response.status_code}: {response.text}"}
 
 def main():
-    st.title("Fake News Prediction")
-
-    # Store your API key here or load from environment variable
-    GOOGLE_API_KEY = "AIzaSyAf5v5380xkpo0Rk3kBiSxpxYVBQwcDi2A"  # 🔐 Replace this!
+    st.set_page_config(page_title="News Credibility Checker", page_icon="🧠")
+    st.title("🧠 Fake News Detection & Fact Check")
 
     with st.form("news_form"):
-        st.subheader("Enter News Details")
-        title = st.text_input("Title")
-        text = st.text_area("Text")
-        language = st.selectbox("Select Language", options=["English", "Other"])
-        check_fact = st.checkbox("Also check with Google Fact Check API")
-        submit_button = st.form_submit_button("Submit")
+        title = st.text_input("News Title")
+        text = st.text_area("News Content")
+        language = st.selectbox("Select Language", ["English", "Other"])
+        check_fact = st.checkbox("Check with Google Fact Check API")
+        submit_button = st.form_submit_button("Analyze")
 
     if submit_button:
         if language == "Other":
             title = translate_to_english(title)
             text = translate_to_english(text)
-
+        
         prediction = predict_fake(title, text)
 
-        st.subheader("Prediction:")
-        st.write("Prediction: ", prediction)
-
-        if prediction.get("Real") > 0.5:
-            st.write("This news is predicted to be **real** :muscle:")
-        else:
-            st.write("This news is predicted to be **fake** :shit:")
-
+        st.subheader("Prediction Result:")
+        st.write("Prediction Score:", prediction)
+        verdict = "real" if prediction.get("Real") > 0.5 else "fake"
+        st.success(f"This news is predicted to be **{verdict}**.")
 
         if check_fact and GOOGLE_API_KEY:
-            st.subheader("Google Fact Check Results")
-        
-            # Optional: user-provided claim input
-           # custom_claim = st.text_input("Optional: Enter a specific claim to fact-check", "")
-           # query = custom_claim if custom_claim else title  # Use custom claim if provided
-            summarized_claim = summarize_text(title)
-            st.info(f"🔍 Fact check query (summarized): **{summarized_claim}**")
-        
-            fact_check_data = fact_check_with_google(GOOGLE_API_KEY, summarized_claim)
-        
-            # Optional: show raw data for debugging
-            # st.json(fact_check_data)
-        
+            # Generate summary for fact-checking
+            summary_text = summarize_text(title + ". " + text)
+            st.markdown("**Fact-check Query (Summary):** " + summary_text)
 
+            # Call Google Fact Check API
+            fact_check_data = fact_check_with_google(GOOGLE_API_KEY, summary_text)
+            st.subheader("Google Fact Check Results")
 
-            if "claims" in fact_check_data and len(fact_check_data["claims"]) > 0:
+            if "claims" in fact_check_data:
                 for claim in fact_check_data["claims"]:
                     st.markdown(f"**Claim:** {claim.get('text', 'N/A')}")
                     for review in claim.get("claimReview", []):
@@ -147,9 +87,7 @@ def main():
                         st.write(f"- **URL**: {review.get('url', 'N/A')}")
                         st.write("---")
             else:
-                st.warning("No fact-check results found. Try changing the title or query.")
+                st.info("No fact-check results found.")
 
-       
 if __name__ == "__main__":
     main()
-