Initial commit for hoax detector

app.py

@@ -2,52 +2,63 @@ import gradio as gr
 import joblib
 from transformers import pipeline
 
-# Load model hoax detector
-model = joblib.load("ensemble_model.pkl")
+# Load model dan pipeline
+model = joblib.load("model_hoax.pkl")
 vectorizer = joblib.load("vectorizer.pkl")
-
-# Load QA dan NER pipeline
 qa_pipe = pipeline("question-answering", model="Rifky/IndoBERT-QA")
 ner_pipe = pipeline("ner", model="cahya/bert-base-indonesian-NER", aggregation_strategy="simple")
 
 # --- Fungsi ---
 def detect_hoax(text):
     vec = vectorizer.transform([text])
-    result = model.predict(vec)
-    return "HOAX" if result[0] == 1 else "Bukan Hoax"
+    result = model.predict(vec)[0]
+    if result == 1:
+        return gr.update(value="HOAX", visible=True), gr.update(visible=True, elem_classes="hoax-red")
+    else:
+        return gr.update(value="Bukan Hoax", visible=True), gr.update(visible=True, elem_classes="hoax-green")
 
 def qa_chat(message, history, context):
     if not context:
         return "Mohon masukkan teks berita di kolom atas terlebih dahulu."
     result = qa_pipe(question=message, context=context)
-    return result['answer']
+    return result["answer"]
 
 def ner(text):
     entities = ner_pipe(text)
-    return "\n".join([f"{e['word']} ({e['entity_group']})" for e in entities])
+    styled = ""
+    color_map = {
+        "PER": "#ffd1dc", "ORG": "#d1e0ff", "LOC": "#d1ffd1", "MISC": "#fdfd96"
+    }
+    for ent in entities:
+        color = color_map.get(ent["entity_group"], "#eee")
+        styled += f"<mark style='background-color:{color}; padding: 2px; margin:2px'>{ent['word']} <small>({ent['entity_group']})</small></mark> "
+    return styled
 
 # --- UI Gradio ---
-with gr.Blocks() as demo:
-    gr.Markdown("## Deteksi Hoaks, QA (Chat), dan NER")
+with gr.Blocks(css=".hoax-red {color: white; background-color: #e74c3c; padding: 10px; border-radius: 5px;} .hoax-green {color: white; background-color: #27ae60; padding: 10px; border-radius: 5px;}") as demo:
+    gr.Markdown("## Hoax Detector App")
 
     # Shared input
     context_input = gr.Textbox(label="Teks Berita / Konteks", lines=5, placeholder="Masukkan teks berita di sini...")
 
     with gr.Tab("Deteksi Hoaks"):
-        hoax_output = gr.Textbox(label="Output Deteksi")
-        hoax_btn = gr.Button("Deteksi")
-        hoax_btn.click(fn=detect_hoax, inputs=context_input, outputs=hoax_output)
+        hoax_btn = gr.Button("DETEKSI")
+        hoax_result = gr.Textbox(visible=False, label="Hasil Deteksi", interactive=False, show_label=False)
+        hoax_result_style = gr.HTML(visible=False)
+        hoax_btn.click(fn=detect_hoax, inputs=context_input, outputs=[hoax_result, hoax_result_style])
 
     with gr.Tab("QA"):
-        gr.Markdown("Tanyakan apapun berdasarkan teks berita di atas:")
+        #gr.Markdown("### Tanya Jawab Berdasarkan Teks Berita")
         qa_chatbot = gr.ChatInterface(
             fn=lambda msg, hist: qa_chat(msg, hist, context_input.value),
-            title="Tanya Jawab Berbasis Teks",
+            title="",
+            textbox=gr.Textbox(placeholder="Tanyakan sesuatu...", label=None),
+            submit_btn="KIRIM"
         )
 
     with gr.Tab("NER"):
-        ner_output = gr.Textbox(label="Hasil Ekstraksi Entitas", lines=5)
         ner_btn = gr.Button("Ekstrak Entitas")
-        ner_btn.click(fn=ner, inputs=context_input, outputs=ner_output)
+        ner_result = gr.HTML()
+        ner_btn.click(fn=ner, inputs=context_input, outputs=ner_result)
 
 demo.launch()