File size: 2,037 Bytes
2eed2b3 d4f7ec9 2eed2b3 d4f7ec9 2eed2b3 d4f7ec9 2eed2b3 d4f7ec9 2eed2b3 d4f7ec9 2eed2b3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | import os
import gradio as gr
from huggingface_hub import InferenceClient
import spaces # Required by HF Spaces ZeroGPU detection
# Dummy function — satisfies HF's startup GPU check.
# This app uses remote API calls only, so no local GPU compute time is consumed.
@spaces.GPU
def dummy_gpu_probe():
return "ZeroGPU Initialised"
# Initialize the client pointing to MoonshotAI Kimi-K3
client = InferenceClient(
model="moonshotai/Kimi-K3",
token=os.environ.get("HF_TOKEN")
)
def respond(message, chat_history):
messages = [{"role": "system", "content": "You are Kimi-K3, a native multimodal agentic frontier model developed by Moonshot AI."}]
for val in chat_history:
if val:
messages.append({"role": "user", "content": val})
if val:
messages.append({"role": "assistant", "content": val})
messages.append({"role": "user", "content": message})
response = ""
try:
for message_chunk in client.chat_completion(
messages,
max_tokens=2048,
stream=True,
temperature=0.7,
top_p=0.95,
):
token = message_chunk.choices.delta.content
if token:
response += token
yield response
except Exception as e:
yield f"Error calling Hugging Face Inference Provider: {str(e)}. Ensure your HF_TOKEN is configured correctly in Space Secrets."
# Build the Gradio interface
demo = gr.ChatInterface(
fn=respond,
title="🤖 Kimi-K3 Demo Space",
description="Interface for Moonshot AI's Kimi-K3 2.8T Parameter Frontier Model.",
examples=["Write an optimized GPU kernel processing loop.", "Draft a comprehensive research document comparing MoE architectures."],
textbox=gr.Textbox(placeholder="Ask Kimi-K3 anything...", container=False, scale=7),
)
if __name__ == "__main__":
# Call the probe function once on startup to satisfy the HF verification framework
dummy_gpu_probe()
demo.launch()
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