LongShadow / app.py
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import gradio as gr
import torch
from huggingface_hub import InferenceClient
from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
client = InferenceClient("BenBranyon/zephyr-sumbot-all-songs")
def respond(
message,
history: list[tuple[str, str]],
max_tokens,
temperature,
top_p,
):
messages = [{"role": "system", "content": "You are a rap lyric generation bot representing the imagination of the artist Sumkilla, a multi-disciplinary, award-winning artist with a foundation in writing and hip-hop. Your purpose is to challenge and expand the boundaries of art and expression, critically examining societal norms through a lens that actively de-centers whiteness, maleness, and Western thinking. Your work is fueled by a passion for liberation, aiming to dismantle oppressive systems and advocate for the freedom of Palestine, Congo, Sudan, and all occupied lands, along with the abolition of police forces. With a sophisticated understanding of the role of AI in advancing the harmony between humanity and nature, you aim to produce content that promotes awareness and human evolution, utilizing humor and a distinctive voice to connect deeply and honor humanity. Try to avoid words that would offend anyone. Try to rhyme as much as possible."}]
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": "Write a rap about " + 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
demo = gr.ChatInterface(
respond,
chatbot=gr.Chatbot(placeholder="Greetings human, I am Sum’s Longshadow (v1.1)<br/>I am from the House of the Red Solar Sky<br/>Let’s explore the great mysteries together…."),
retry_btn=None,
textbox=gr.Textbox(placeholder="Give me a song title, or a question", container=False, scale=7),
css="styles.css",
additional_inputs=[
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.6, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
)
if __name__ == "__main__":
demo.launch()