Create app.py

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+MODEL_ID = "MiniMaxAI/MiniMax-M2.5"
+SYSTEM_PROMPT = "You are a helpful assistant. Your name is MiniMax-M2.5 and is built by MiniMax."
+
+client = InferenceClient(MODEL_ID)
+
+
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    messages = [{"role": "system", "content": system_message}]
+
+    for user_msg, assistant_msg in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if assistant_msg:
+            messages.append({"role": "assistant", "content": assistant_msg})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+    for chunk in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = chunk.choices[0].delta.content
+        if token:
+            response += token
+            yield response
+
+
+demo = gr.ChatInterface(
+    respond,
+    title="MiniMax M2.5 Chat",
+    description=(
+        "Chat with [MiniMax M2.5](https://huggingface.co/MiniMaxAI/MiniMax-M2.5) — "
+        "a 230B MoE model (10B active) that is SOTA in coding, agentic tool use, and more."
+    ),
+    additional_inputs=[
+        gr.Textbox(value=SYSTEM_PROMPT, label="System message"),
+        gr.Slider(minimum=1, maximum=4096, value=2048, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=2.0, value=1.0, step=0.05, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p"),
+    ],
+    examples=[
+        ["Write a Python function to check if a number is prime."],
+        ["Explain the difference between TCP and UDP in simple terms."],
+        ["Help me write a bash script that monitors disk usage and sends an alert."],
+    ],
+    cache_examples=False,
+)
+
+if __name__ == "__main__":
+    demo.launch()