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import gradio as gr
import os
import requests
API_TOKEN = os.environ.get("HF_HUB_API_TOKEN") # 或直接写 token
API_URL = "https://api-inference.huggingface.co/models/Qwen/Qwen3-8B-Base"
headers = {
"Authorization": f"Bearer {API_TOKEN}",
"Content-Type": "application/json",
}
def respond(message, history, system_message, max_tokens, temperature, top_p):
payload = {
"inputs": {
"past_user_inputs": [m[0] for m in history],
"generated_responses": [m[1] for m in history],
"text": message
},
"parameters": {
"temperature": temperature,
"max_new_tokens": max_tokens,
"top_p": top_p
}
}
try:
response = requests.post(API_URL, headers=headers, json=payload)
if response.status_code != 200:
return f"[HTTP {response.status_code}] {response.text}"
result = response.json()
if isinstance(result, dict) and result.get("error"):
return f"[ERROR] {result['error']}"
return result[0]["generated_text"]
except Exception as e:
return f"[Exception] {str(e)}"
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a helpful assistant.", 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"),
],
)
if __name__ == "__main__":
demo.launch()
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