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.huggingface.yaml

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+sdk: gradio
+python_version: "3.10"

app.py

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+
+import requests
+from collections import Counter
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+import re
+import gradio as gr
+
+# ✅ Load Roberta fake news model
+model_name = "hamzab/roberta-fake-news-classification"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
+
+# ✅ API Keys
+GOOGLE_API_KEY = "AIzaSyCKnDlhWih34GdCuheNusnrEw_YE_q6GWQ"
+NEWSAPI_KEY = "fcb304918fce4fb29b17b6c95dbc7518"
+
+# ✅ Keyword extractor
+def extract_keywords(text, max_words=5):
+    words = re.findall(r'\b\w+\b', text.lower())
+    stopwords = {"the", "and", "is", "in", "to", "of", "a", "on", "for", "with", "as", "by", "at", "an", "be", "are", "from", "this", "it", "that"}
+    filtered = [w for w in words if w not in stopwords and len(w) > 2]
+    return " ".join([w for w, _ in Counter(filtered).most_common(max_words)])
+
+# ✅ Google Fact Check
+def check_google_fact_check(query):
+    try:
+        response = requests.get("https://factchecktools.googleapis.com/v1alpha1/claims:search", params={"query": query, "key": GOOGLE_API_KEY}).json()
+        if "claims" in response and response["claims"]:
+            result = ""
+            for claim in response["claims"][:3]:
+                text = claim.get("text", "")
+                review = claim.get("claimReview", [{}])[0]
+                rating = review.get("textualRating", "Unrated")
+                source = review.get("publisher", {}).get("name", "Unknown")
+                url = review.get("url", "")
+                result += f"✅ Claim: {text}\n📊 Verdict: {rating}\n📰 Source: {source}\n🔗 {url}\n\n"
+            return result.strip()
+        return None
+    except Exception as e:
+        return f"❌ Google API error: {e}"
+
+# ✅ NewsAPI fallback
+def search_newsapi(query):
+    try:
+        response = requests.get("https://newsapi.org/v2/everything", params={
+            "q": query, "apiKey": NEWSAPI_KEY, "language": "en", "sortBy": "relevancy", "pageSize": 3
+        }).json()
+        if response.get("status") != "ok":
+            return f"❌ NewsAPI error: {response.get('message')}"
+        articles = response.get("articles", [])
+        if not articles:
+            return "ℹ️ No similar real news articles found."
+        output = "📰 No official fact-check found.\n\nBut here are similar real news articles:\n\n"
+        for article in articles:
+            title = article.get("title", "No title")
+            source = article.get("source", {}).get("name", "Unknown")
+            url = article.get("url", "#")
+            output += f"• 📰 Source: {source}\n  📌 Title: {title}\n  🔗 {url}\n\n"
+        return output.strip()
+    except Exception as e:
+        return f"❌ NewsAPI error: {e}"
+
+# ✅ Chatbot logic
+def fake_news_chatbot(message, history):
+    try:
+        prediction = classifier(message)[0]
+        label = prediction['label']
+        confidence = round(prediction['score'], 2)
+
+        if confidence < 0.7:
+            verdict = "🟡 UNSURE"
+        elif label == "FAKE":
+            verdict = "🟥 FAKE"
+        else:
+            verdict = "🟩 REAL"
+
+        ml_result = f"📊 ML Prediction: {verdict}\n🔢 Confidence: {confidence}"
+
+        keywords = extract_keywords(message)
+        fact_result = check_google_fact_check(keywords)
+        if fact_result:
+            return f"{ml_result}\n\n🔍 Keywords Used: {keywords}\n\n{fact_result}"
+
+        newsapi_result = search_newsapi(keywords)
+        if "📰 Source:" in newsapi_result and verdict == "🟥 FAKE":
+            ml_result += " ⚠️ ML says FAKE but similar real news found"
+        elif "No similar" in newsapi_result and verdict == "🟩 REAL":
+            ml_result += " ⚠️ ML says REAL but no matching news found"
+
+        return f"{ml_result}\n\n🔍 Keywords Used: {keywords}\n\n{newsapi_result}"
+
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# ✅ Launch Chatbot
+gr.ChatInterface(
+    fn=fake_news_chatbot,
+    title="🧠 Fake News Detection Chatbot",
+    description="Ask me if a news item is real or fake. I’ll use an ML model + Google Fact Check + NewsAPI!",
+    examples=[
+        "The Prime Minister announced a new moon mission",
+        "Aliens landed in New York yesterday",
+        "COVID vaccine turns you into a lizard"
+    ],
+).launch()

requirements.txt

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+transformers
+gradio
+torch
+requests