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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1dabd320-903a-4f6c-9634-e8bd5993f90f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* Running on local URL:  http://127.0.0.1:7860\n",
      "* To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
    "import torch\n",
    "import gradio as gr\n",
    "\n",
    "# مدل و توکنایزر\n",
    "model_name = \"HuggingFaceTB/SmolLM2-360M-Instruct\"\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_name)\n",
    "model = AutoModelForCausalLM.from_pretrained(model_name)\n",
    "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
    "model.to(device)\n",
    "model.eval()\n",
    "\n",
    "# پیام‌های اولیه مکالمه\n",
    "def format_messages(user_prompt):\n",
    "    system_message = \"<|im_start|>system\\n<|im_end|>\\n\"\n",
    "    user_message = f\"<|im_start|>user\\n{user_prompt}<|im_end|>\\n\"\n",
    "    assistant_prefix = \"<|im_start|>assistant\\n\"\n",
    "    full_prompt = system_message + user_message + assistant_prefix\n",
    "    return full_prompt\n",
    "\n",
    "# تابع چت\n",
    "def chat(user_input):\n",
    "    prompt = format_messages(user_input)\n",
    "    inputs = tokenizer(prompt, return_tensors=\"pt\").to(device)\n",
    "\n",
    "    with torch.no_grad():\n",
    "        outputs = model.generate(\n",
    "            **inputs,\n",
    "            max_new_tokens=256,\n",
    "            do_sample=True,\n",
    "            temperature=0.7,\n",
    "            top_p=0.9,\n",
    "            pad_token_id=tokenizer.eos_token_id\n",
    "        )\n",
    "\n",
    "    response = tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
    "    \n",
    "    # پاسخ مدل بعد از آخرین <|im_start|>assistant\n",
    "    if \"<|im_start|>assistant\" in response:\n",
    "        response = response.split(\"<|im_start|>assistant\")[-1].strip()\n",
    "    if \"<|im_end|>\" in response:\n",
    "        response = response.split(\"<|im_end|>\")[0].strip()\n",
    "    \n",
    "    return response\n",
    "\n",
    "# رابط گرافیکی Gradio\n",
    "interface = gr.Interface(\n",
    "    fn=chat,\n",
    "    inputs=gr.Textbox(lines=3, placeholder=\"پیام خود را وارد کنید...\"),\n",
    "    outputs=\"text\",\n",
    "    title=\"💬 SmolLM2 Chatbot\",\n",
    "    description=\"مدل سبک و مکالمه‌محور SmolLM2 از Hugging Face با فرمت قالب رسمی\"\n",
    ")\n",
    "\n",
    "interface.launch()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f00bd7a-f925-4970-aeb6-96f1dcbad3c8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:base] *",
   "language": "python",
   "name": "conda-base-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
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