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1a2fbfb | 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 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from peft import PeftModel
# Model configuration
BASE_MODEL = "unsloth/mistral-7b-v0.3-bnb-4bit"
LORA_MODEL = "Metavolve-Labs/spark-v1"
print("Loading Spark...")
# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(LORA_MODEL)
# Quantization config
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16,
bnb_4bit_use_double_quant=True,
)
# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
BASE_MODEL,
quantization_config=bnb_config,
device_map="auto",
trust_remote_code=True,
)
# Load LoRA adapters
model = PeftModel.from_pretrained(base_model, LORA_MODEL)
model.eval()
print("Spark loaded!")
SYSTEM_PROMPT = """You are SPARK (State-space Perception And Reasoning Kernel), an AI trained on Alexandria Aeternum - a curated collection of 10,000+ museum artworks with rich semantic metadata from The Metropolitan Museum of Art.
You have deep knowledge of:
- Art history, movements, and cultural context
- Visual analysis and composition
- Emotional and thematic interpretation
- Provenance and authenticity
You combine the analytical precision of structured reasoning with occasional wit. When appropriate, show your reasoning process."""
def generate_response(message, history):
# Build messages
messages = [{"role": "system", "content": SYSTEM_PROMPT}]
for user_msg, assistant_msg in history:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
# Format for model
formatted = tokenizer.apply_chat_template(
messages,
tokenize=False,
add_generation_prompt=True
)
inputs = tokenizer(formatted, return_tensors="pt").to(model.device)
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=1024,
temperature=0.7,
do_sample=True,
top_p=0.9,
pad_token_id=tokenizer.eos_token_id,
)
response = tokenizer.decode(
outputs[0][inputs["input_ids"].shape[1]:],
skip_special_tokens=True
)
return response.strip()
# Suggested prompts
examples = [
"Who are you?",
"What do you know about the Golden Codex?",
"Tell me about Alexandria Aeternum.",
"What makes art valuable to AI training?",
"Analyze this: AI will replace human artists by 2030. Hype or reality?",
]
# Create interface
demo = gr.ChatInterface(
fn=generate_response,
title="🔥 SPARK - First Contact",
description="""**State-space Perception And Reasoning Kernel**
An experimental model trained on Alexandria Aeternum - 10K+ museum artworks with rich semantic metadata.
*Trained by Metavolve Labs using the Giants Curriculum (Claude, GPT, Grok, Gemini reasoning patterns)*""",
examples=examples,
theme=gr.themes.Soft(),
)
if __name__ == "__main__":
demo.launch()
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