Delete app.py with huggingface_hub

app.py

@@ -1,84 +0,0 @@
-import gradio as gr
-import torch
-from transformers import AutoTokenizer
-import sys
-
-# Import the architecture we defined locally
-sys.path.append('.')
-try:
-    from ares_model import AresModel
-except ImportError:
-    from ares_project.ares_model import AresModel
-
-print("Loading Ares Architecture...")
-tokenizer = AutoTokenizer.from_pretrained("gpt2")
-special_tokens = {'additional_special_tokens': ['<|system|>', '<|user|>', '<|assistant|>', '<|end|>']}
-tokenizer.add_special_tokens(special_tokens)
-VOCAB_SIZE = len(tokenizer)
-
-model = AresModel(
-    vocab_size=VOCAB_SIZE, 
-    dim=128, 
-    n_layers=4, 
-    n_heads=8, 
-    hidden_dim=256, 
-    max_seq_len=512
-)
-
-try:
-    model.load_state_dict(torch.load("ares_weights.pt", map_location="cpu"))
-    print("Successfully loaded trained PyTorch weights!")
-except Exception as e:
-    print(f"Warning: Could not load weights: {e}")
-
-model.eval()
-
-def generate_response(message, history):
-    prompt = f"<|system|>You are Ares.<|end|><|user|>{message}<|end|><|assistant|>"
-    inputs = tokenizer(prompt, return_tensors="pt")['input_ids']
-    
-    with torch.no_grad():
-        outputs = model.generate(
-            inputs, 
-            max_new_tokens=60,
-            temperature=0.75,
-            repetition_penalty=1.2,
-            stop_token=tokenizer.convert_tokens_to_ids("<|end|>")
-        )
-        
-    response = tokenizer.decode(outputs[0], skip_special_tokens=False)
-    # Extract only the assistant's response
-    reply = response.split("<|assistant|>")[-1].split("<|end|>")[0].strip()
-    return reply
-
-custom_css = """
-body, .gradio-container { background-color: #0f172a !important; color: #f8fafc !important; font-family: 'Inter', sans-serif !important; }
-h1 { color: #f8fafc; display: flex; align-items: center; gap: 10px; }
-.chatbot { background-color: #1e293b !important; border: 1px solid #334155 !important; border-radius: 12px; }
-.message.user { background-color: #3b82f6 !important; color: white !important; border-radius: 12px 12px 0 12px !important; }
-.message.bot { background-color: #334155 !important; color: white !important; border-radius: 12px 12px 12px 0 !important; }
-#component-0 { border: none !important; box-shadow: none !important; background: transparent !important; }
-textarea { background-color: #0f172a !important; color: white !important; border: 1px solid #334155 !important; border-radius: 24px !important; }
-"""
-
-with gr.Blocks(css=custom_css, theme=gr.themes.Monochrome()) as demo:
-    gr.HTML("<h1><span style='color:#3b82f6'>●</span> Ares General Intelligence</h1>")
-    
-    chatbot = gr.Chatbot(elem_id="chatbot", label="")
-    msg = gr.Textbox(placeholder="Message Ares...", label="", container=False)
-    
-    def user(user_message, history):
-        return "", history + [[user_message, None]]
-
-    def bot(history):
-        user_message = history[-1][0]
-        bot_message = generate_response(user_message, history)
-        history[-1][1] = bot_message
-        return history
-
-    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
-        bot, chatbot, chatbot
-    )
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)