added space_app.py

space_app.py

@@ -0,0 +1,41 @@
+import os
+import gradio as gr
+from transformers import pipeline
+
+MODEL_NAME = os.getenv("HF_MODEL_GENERATION", "distilgpt2")
+
+_pipe = None
+def _get_pipe():
+    global _pipe
+    if _pipe is None:
+        _pipe = pipeline("text-generation", model=MODEL_NAME)
+    return _pipe
+
+def chat_fn(message, max_new_tokens=128, temperature=0.8, top_p=0.95):
+    message = (message or "").strip()
+    if not message:
+        return "Please type something!"
+    pipe = _get_pipe()
+    out = pipe(
+        message,
+        max_new_tokens=int(max_new_tokens),
+        do_sample=True,
+        temperature=float(temperature),
+        top_p=float(top_p),
+        pad_token_id=50256
+    )
+    return out[0]["generated_text"]
+
+with gr.Blocks(title="Agentic-Chat-bot") as demo:
+    gr.Markdown("# 🤖 Agentic Chat Bot\nGradio + Transformers demo")
+    prompt = gr.Textbox(label="Prompt", placeholder="Ask me anything…", lines=4)
+    out = gr.Textbox(label="Response", lines=6)
+    max_new = gr.Slider(32, 512, 128, 1, label="Max new tokens")
+    temp = gr.Slider(0.1, 1.5, 0.8, 0.05, label="Temperature")
+    topp = gr.Slider(0.1, 1.0, 0.95, 0.05, label="Top-p")
+    btn = gr.Button("Send")
+    btn.click(chat_fn, [prompt, max_new, temp, topp], out)
+    prompt.submit(chat_fn, [prompt, max_new, temp, topp], out)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=int(os.getenv("PORT", "7860")))