| import gradio as gr |
| from transformers import pipeline |
| from newspaper import Article |
|
|
| |
| model = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-fake-news-detection") |
|
|
| def analyze(input_text, input_type): |
| |
| if input_type == "Auto Detect": |
| if input_text.startswith("http://") or input_text.startswith("https://"): |
| input_type = "URL" |
| else: |
| input_type = "Text" |
|
|
| if input_type == "URL": |
| try: |
| article = Article(input_text) |
| article.download() |
| article.parse() |
| text = article.text |
| except Exception as e: |
| return f"❌ Failed to extract article: {e}", 0 |
| else: |
| text = input_text |
|
|
| if not text: |
| return "❌ No text provided", 0 |
|
|
| try: |
| result = model(text)[0] |
| label = result["label"] |
| score = result["score"] |
| verdict = "Authentic" if label == "REAL" else "Possibly Misinformation" |
| authenticity_score = round(score * 100, 2) |
| return verdict, authenticity_score |
| except Exception as e: |
| return f"❌ Model inference failed: {e}", 0 |
|
|
| interface = gr.Interface( |
| fn=analyze, |
| inputs=[ |
| gr.Textbox(lines=6, label="Paste article text or URL here"), |
| gr.Radio(["Auto Detect", "Text", "URL"], label="Input Type", value="Auto Detect") |
| ], |
| outputs=[ |
| gr.Textbox(label="Verdict"), |
| gr.Number(label="Authenticity Score (%)") |
| ], |
| title="Misinformation Detection Dashboard", |
| description="Enter article text or a URL to detect whether the content is authentic or possibly misinformation." |
| ) |
|
|
| interface.launch() |
|
|
