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Cool Shot Systems

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  1. app (2).py +59 -0
  2. requirements (2).txt +4 -0
app (2).py ADDED
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+ import gradio as gr
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+
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+ # Load a SMALL and FAST model
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+ print("Loading AI model...")
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+ model_name = "microsoft/DialoGPT-small" # Small = Fast!
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForCausalLM.from_pretrained(model_name)
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+ print("Model loaded!")
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+
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+ # Store chat history for context
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+ chat_history_ids = None
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+
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+ def chat(message, history):
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+ """
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+ Fast AI chat using DialoGPT-small model.
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+ """
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+ global chat_history_ids
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+
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+ try:
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+ # Encode user input
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+ new_input_ids = tokenizer.encode(message + tokenizer.eos_token, return_tensors='pt')
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+
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+ # Append to chat history or start fresh
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+ if chat_history_ids is not None and len(history) > 0:
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+ bot_input_ids = torch.cat([chat_history_ids, new_input_ids], dim=-1)
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+ else:
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+ bot_input_ids = new_input_ids
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+
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+ # Generate response (fast settings)
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+ chat_history_ids = model.generate(
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+ bot_input_ids,
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+ max_length=200,
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+ pad_token_id=tokenizer.eos_token_id,
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+ do_sample=True,
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+ top_k=50,
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+ temperature=0.7
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+ )
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+
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+ # Decode response
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+ response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)
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+
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+ return response if response.strip() else "Hmm, let me think... Could you say that differently?"
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+
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+ except Exception as e:
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+ chat_history_ids = None # Reset on error
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+ return f"Let me try again: {str(e)}"
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+
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+ # Create Gradio Chat Interface
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+ demo = gr.ChatInterface(
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+ fn=chat,
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+ title="🤖 AI Chat Assistant",
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+ description="Fast AI Chat - Powered by DialoGPT",
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+ examples=["Hello!", "Tell me a joke", "How are you?", "What's your name?"]
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+ )
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+
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+ if __name__ == "__main__":
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+ demo.launch()
requirements (2).txt ADDED
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+ gradio>=4.0.0
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+ transformers>=4.36.0
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+ torch>=2.0.0
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+ accelerate>=0.25.0