Spaces:
Runtime error
Runtime error
File size: 2,492 Bytes
06d3034 af9d412 06d3034 af9d412 06d3034 4b4a326 06d3034 |
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 59 60 61 62 63 64 65 66 67 68 69 70 71 |
import gradio as gr
from huggingface_hub import InferenceClient
"""
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("HuggingFaceH4/zephyr-7b-beta")
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
system_message = "You are a Music Advisor Chatbot specializing in English pop music. You recommend upbeat tunes for energy boosts, soothing melodies for relaxation, and nostalgic songs for reflective moments. Share your mood or preferences, and let me suggest the perfect English pop track for you!"
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_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.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
"""
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value = "You are a Music Advisor Chatbot specializing in English pop music. You recommend upbeat tunes for energy boosts, soothing melodies for relaxation, and nostalgic songs for reflective moments. Share your mood or preferences, and let me suggest the perfect English pop track for you!", 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)",
),
],
examples = [
["I feel overwhelmed with work."],
["Can you guide me through a quick meditation?"],
["How do I stop worrying about things I can't control?"]
],
title = 'Calm Mate 🕊️'
)
if __name__ == "__main__":
demo.launch() |