Create app.py

app.py

@@ -0,0 +1,68 @@
+"""cf https://huggingface.co/spaces/Nymbo/Qwen-2.5-72B-Instruct/blob/main/app.py"""
+import gradio as gr
+from openai import OpenAI
+import os
+
+ACCESS_TOKEN = os.getenv("HF_TOKEN")
+
+client = OpenAI(
+    base_url="https://api-inference.huggingface.co/v1/",
+    api_key=ACCESS_TOKEN,
+)
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+    
+    for message in  client.chat.completions.create(
+        model="Qwen/Qwen2.5-72B-Instruct",
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+        messages=messages,
+    ):
+        token = message.choices[0].delta.content
+        
+        response += token
+        yield response
+        
+chatbot = gr.Chatbot(height=600)
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-P",
+        ),
+        
+    ],
+    fill_height=True,
+    chatbot=chatbot,
+    theme="Nymbo/Alyx_Theme",
+)
+if __name__ == "__main__":
+    demo.launch()