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app.py

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+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()