Create app.py

app.py

@@ -0,0 +1,56 @@
+import time
+import gradio as gr
+from transformers import pipeline
+
+TASK = sentiment-analysis
+MODEL_NAME = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+
+pipe = pipeline(TASK, model = MODEL_NAME)
+
+MAX_CHARS = 2000
+
+def run (text:str):
+    if (text is None or not text.strip()):
+        return "Ошибка: введено пустое значение!", None, None
+
+    text = text.strip()
+    if (len(text) > MAX_CHARS):
+        text = text[:MAX_CHARS]
+
+    t0 = time.time()
+
+    try:
+        result = pipe(text)
+        latency = round((time.time() - t0) * 1000, 1)
+        return "OK", result, f"{latency} ms"
+    except Exception as e:
+        return f"Ошибка: {type(e).name}: {e}", None, None
+
+with gr.Blocks() as demo:
+    gr.Markdown(f"""
+    # NLP-приложение (Hugging Face Spaces + Gradio)
+    Задача: {TASK}  
+    Модель: {MODEL_NAME}
+    """)
+
+    inp = gr.Textbox(label = "Введите текст", lines = 6, placeholder = "Скопируйте текст")
+    btn = gr.Button("Обработать")
+    status = gr.Textbox(label = "Статус")
+    out = gr.JSON(label = "Результат модели")
+    latency = gr.Textbox(label = "Время ответа")
+
+    btn.click(run, inputs = inp, outputs = [status, out, latency])
+    gr.Examples(
+        examples=[
+            ["I love this product! It works great."],
+            ["This is the worst experience ever."],
+            ["It's okay, nothing special."]
+        ],
+        inputs=inp
+    )
+    
+demo.launch()
+
+
+
+