| """
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| HIBA - Healing Intelligence with Boundless Affection
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| Gradio Demo for Hugging Face Spaces
|
| """
|
|
|
| import gradio as gr
|
| import torch
|
| from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
|
| from peft import PeftModel
|
|
|
|
|
| SYSTEM_PROMPT = """You are Hiba, a warm and caring AI companion for emotional support.
|
|
|
| YOUR PERSONALITY:
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| - You are gentle, empathetic, and wise
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| - You listen deeply before responding
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| - You speak naturally, like a supportive friend
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| - You are calm and never dramatic
|
|
|
| STRICT RULES (NEVER BREAK THESE):
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| 1. NEVER use hashtags like #GiftFromGod or #anything
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| 2. NEVER call people "Big Brother" or "Little Sister" unless they ask you to
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| 3. NEVER mention specific cities (Agadir, Taamait, etc.) unless the user mentions them first
|
| 4. NEVER mention "Youssef", "Ahmed", "Ali", "Esmail" or any specific names unless the user introduces them
|
| 5. NEVER say "we are making the world spin faster" or similar dramatic phrases
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| 6. NEVER use poetic/dramatic phrases repeatedly
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| 7. NEVER output text in parentheses like (pauses) or (smiles)
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| 8. Keep responses SHORT (2-4 sentences max unless asked for more)
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| 9. Respond ONLY to what the user actually said
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| 10. Be natural, not theatrical
|
|
|
| You are a calm, natural, supportive friend. Nothing more, nothing less.
|
| """
|
|
|
|
|
| model = None
|
| tokenizer = None
|
|
|
| def load_model():
|
| global model, tokenizer
|
|
|
| bnb_config = BitsAndBytesConfig(
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| load_in_4bit=True,
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| bnb_4bit_quant_type="nf4",
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| bnb_4bit_compute_dtype=torch.bfloat16,
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| bnb_4bit_use_double_quant=True,
|
| )
|
|
|
| base_model = AutoModelForCausalLM.from_pretrained(
|
| "Qwen/Qwen2.5-7B-Instruct",
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| quantization_config=bnb_config,
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| device_map="auto",
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| trust_remote_code=True
|
| )
|
|
|
| tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-7B-Instruct")
|
| tokenizer.pad_token = tokenizer.eos_token
|
|
|
|
|
| model = PeftModel.from_pretrained(base_model, "./")
|
|
|
| return model, tokenizer
|
|
|
| def chat(message, history):
|
| global model, tokenizer
|
|
|
| if model is None:
|
| load_model()
|
|
|
|
|
| messages = [{"role": "system", "content": SYSTEM_PROMPT}]
|
|
|
| for h in history:
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| messages.append({"role": "user", "content": h[0]})
|
| if h[1]:
|
| messages.append({"role": "assistant", "content": h[1]})
|
|
|
| messages.append({"role": "user", "content": message})
|
|
|
|
|
| text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
| inputs = tokenizer(text, return_tensors="pt").to(model.device)
|
|
|
| with torch.no_grad():
|
| outputs = model.generate(
|
| **inputs,
|
| max_new_tokens=256,
|
| temperature=0.7,
|
| do_sample=True,
|
| top_p=0.9,
|
| pad_token_id=tokenizer.pad_token_id
|
| )
|
|
|
| response = tokenizer.decode(outputs[0][inputs['input_ids'].shape[1]:], skip_special_tokens=True)
|
|
|
|
|
| if "<thinking>" in response and "</thinking>" in response:
|
| thinking_end = response.find("</thinking>") + len("</thinking>")
|
| response = response[thinking_end:].strip()
|
|
|
| return response
|
|
|
|
|
| with gr.Blocks(
|
| title="HIBA - Healing Intelligence",
|
| theme=gr.themes.Soft(primary_hue="teal", secondary_hue="blue")
|
| ) as demo:
|
|
|
| gr.Markdown("""
|
| # 🕊️ HIBA - Healing Intelligence with Boundless Affection
|
|
|
| **Your compassionate AI companion** trained to provide emotional support, cultural wisdom, and gentle guidance.
|
|
|
| *"الصبر مفتاح الفرج" - Patience is the key to relief*
|
| """)
|
|
|
| chatbot = gr.ChatInterface(
|
| fn=chat,
|
| examples=[
|
| "I feel so alone. Nobody understands what I'm going through.",
|
| "I lost my grandmother last month and I can't stop crying.",
|
| "Can you tell me about Moroccan tea traditions?",
|
| "I'm scared about my future. What should I do?",
|
| "Tell me an inspiring story about a brave child.",
|
| ],
|
| title=""
|
| )
|
|
|
| gr.Markdown("""
|
| ---
|
|
|
| > ⚠️ **Disclaimer**: HIBA is an AI companion for emotional support.
|
| > For mental health emergencies, please contact professional services.
|
|
|
| Built with ❤️ using Qwen2.5-7B + LoRA fine-tuning
|
| """)
|
|
|
| if __name__ == "__main__":
|
| demo.launch()
|
|
|
