Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import pipeline
+import pycountry
+
+# Load a language‐detection model with bfloat16 precision
+language_detector = pipeline(
+    "text-classification",
+    model="papluca/xlm-roberta-base-language-detection",
+    torch_dtype=torch.bfloat16
+)
+
+def detect_language(text: str) -> str:
+    """
+    Detects the language of the given text and returns
+    both the full language name and its ISO code with confidence.
+    """
+    result = language_detector(text)[0]
+    code = result["label"]      # e.g. "en", "ta", "fr"
+    score = result["score"]
+
+    # Map ISO code to full language name using pycountry
+    try:
+        lang = pycountry.languages.get(alpha_2=code).name
+    except:
+        lang = code.upper()
+
+    return f"{lang} ({code}) — {score:.2f}"
+
+# Build Gradio interface
+with gr.Blocks(theme=gr.themes.Default()) as demo:
+    gr.Markdown(
+        """
+        # 🌐 Text Language Detector  
+        Type or paste text below to detect its language (name + code + confidence).
+        """
+    )
+
+    with gr.Row():
+        text_input = gr.Textbox(
+            label="📝 Input Text",
+            placeholder="Type or paste text here...",
+            lines=4,
+            show_copy_button=True
+        )
+        lang_output = gr.Textbox(
+            label="✅ Detected Language",
+            placeholder="Full language name, ISO code, and confidence will appear here",
+            lines=1,
+            interactive=False
+        )
+
+    detect_btn = gr.Button("🔍 Detect Language")
+    detect_btn.click(fn=detect_language, inputs=text_input, outputs=lang_output)
+
+    gr.Markdown(
+        """
+        ---  
+        Built with 🤗 Transformers (`papluca/xlm-roberta-base-language-detection`),  
+        `pycountry` for language names, and 🚀 Gradio  
+        """
+    )
+
+demo.launch()