Create app.py

app.py

@@ -0,0 +1,56 @@
+import gradio as gr
+from transformers import pipeline
+
+# Translation pipeline (mBART)
+translation_pipeline = pipeline(
+    "translation", model="facebook/mbart-large-50-many-to-many-mmt"
+)
+
+# Text generation pipeline (GPT-2)
+generation_pipeline = pipeline(
+    "text-generation", model="gpt2"
+)
+
+LANG_CODES = {
+    "English":    "en_XX",
+    "Spanish":    "es_XX",
+    "Portuguese": "pt_XX",
+    "Italian":    "it_IT",
+    "Korean":     "ko_KR",
+}
+
+def translate(text, src, tgt):
+    if src == tgt:
+        return text
+    out = translation_pipeline(text, src_lang=LANG_CODES[src], tgt_lang=LANG_CODES[tgt])
+    return out[0]["translation_text"]
+
+def generate(text, max_length=100, temperature=1.0, top_p=0.95):
+    out = generation_pipeline(
+        text, max_length=int(max_length), temperature=float(temperature), top_p=float(top_p)
+    )
+    return out[0]["generated_text"]
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🌎 Translation & Text Generation Demo")
+    with gr.Tab("Translation"):
+        src_lang = gr.Dropdown(list(LANG_CODES.keys()), label="Source Language", value="English")
+        tgt_lang = gr.Dropdown(list(LANG_CODES.keys()), label="Target Language", value="Spanish")
+        inp = gr.Textbox(label="Text to Translate")
+        out = gr.Textbox(label="Translation")
+        btn = gr.Button("Translate")
+        btn.click(fn=translate, inputs=[inp, src_lang, tgt_lang], outputs=out)
+    with gr.Tab("Text Generation"):
+        prompt = gr.Textbox(label="Prompt")
+        gen_out = gr.Textbox(label="Generated Text")
+        max_len = gr.Slider(10, 256, value=100, label="Max Length")
+        temp = gr.Slider(0.5, 1.5, value=1.0, label="Temperature")
+        topp = gr.Slider(0.5, 1.0, value=0.95, label="Top-p")
+        gen_btn = gr.Button("Generate")
+        gen_btn.click(
+            fn=generate,
+            inputs=[prompt, max_len, temp, topp],
+            outputs=gen_out,
+        )
+
+demo.launch()