Update app.py

app.py

@@ -1,15 +1,17 @@
 import asyncio
-asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy())  # <<< FIXES THE ERROR
+asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy())  # avoid fd errors
 
 import os
 import gradio as gr
 from openai import OpenAI
+from fastapi import FastAPI
+import uvicorn
 
 HF_API_KEY = os.getenv("HF_TOKEN")
 
 client = OpenAI(
     base_url="https://router.huggingface.co/v1",
-    api_key=HF_API_KEY,
+    api_key=HF_API_KEY
 )
 
 def chat_with_model(user_message, history):
@@ -17,6 +19,7 @@ def chat_with_model(user_message, history):
         history = []
 
     messages = [{"role": "system", "content": "You are a helpful assistant."}]
+
     for human, bot in history:
         messages.append({"role": "user", "content": human})
         messages.append({"role": "assistant", "content": bot})
@@ -28,24 +31,30 @@ def chat_with_model(user_message, history):
             model="openai/gpt-oss-20b:nebius",
             messages=messages
         )
-
         reply = completion.choices[0].message["content"]
+    except Exception as e:
+        reply = f"Error: {e}"
 
-        history.append((user_message, reply))
-        return history
+    history.append((user_message, reply))
+    return history
 
-    except Exception as e:
-        history.append((user_message, f"Error: {str(e)}"))
-        return history
 
+with gr.Blocks() as interface:
+    gr.Markdown("## 🤖 Chat with HuggingFace Router API (OpenAI-Compatible)")
+    chatbot = gr.Chatbot()
+    msg = gr.Textbox(label="Message")
+
+    msg.submit(chat_with_model, [msg, chatbot], chatbot)
+    msg.submit(lambda: "", None, msg)
 
-with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 Chat with HuggingFace Router (OpenAI API Compatible)")
+# FastAPI wrapper to avoid file-descriptor errors
+app = FastAPI()
 
-    chatbot = gr.Chatbot(height=500)
-    text_input = gr.Textbox(label="Your message")
+@app.get("/")
+def read_main():
+    return {"message": "Gradio app is running"}
 
-    text_input.submit(chat_with_model, [text_input, chatbot], chatbot)
-    text_input.submit(lambda: "", None, text_input)
+app = gr.mount_gradio_app(app, interface, path="/chat")
 
-demo.launch()
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)