Update Space

app.py

@@ -1,70 +1,40 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import requests
 
 
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-    """
-    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
 
-    messages = [{"role": "system", "content": system_message}]
+def chatbot_qwen(prompt,history):  
+        url = "https://qwen-3.p.rapidapi.com/chat/completions"
 
-    messages.extend(history)
+        payload = {
+            "model": "qwen3-14b",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ]
+        }
+        headers = {
+            "x-rapidapi-key": "3d66bcf268mshb7e2600a51aa227p1c07cajsn59f71d743737",
+            "x-rapidapi-host": "qwen-3.p.rapidapi.com",
+            "Content-Type": "application/json"
+        }
 
-    messages.append({"role": "user", "content": message})
+        response = requests.post(url, json=payload, headers=headers)
+        output = response.json()
 
-    response = ""
+        return output['choices'][0]['message']['content']
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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 (nucleus sampling)",
-        ),
-    ],
-)
+def vote(data: gr.LikeData):
+    if data.liked:
+        print("You upvoted this response: " + data.value["value"])
+    else:
+        print("You downvoted this response: " + data.value["value"])
 
 with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
-
-
-if __name__ == "__main__":
-    demo.launch()
+    chatbot = gr.Chatbot(placeholder="<strong>Qwen Chatbot</strong><br>Ask Me Anything")
+    chatbot.like(vote, None, None)
+    gr.ChatInterface(fn=chatbot_qwen,chatbot=chatbot)
+    
+demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+gradio
+requests