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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"..\")\n",
    "import config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "PROMPT = \"\"\"你是一位精通简体中文的专业翻译，尤其擅长将专业学术论文翻译成浅显易懂的科普文章。请你帮我将以下英文段落翻译成中文，风格与中文科普读物相似。\n",
    "\n",
    "规则：\n",
    "- 翻译时要准确传达原文的事实和背景。\n",
    "- 即使上意译也要保留原始段落格式，以及保留术语，例如 FLAC，JPEG 等。保留公司缩写，例如 Microsoft, Amazon, OpenAI 等。\n",
    "- 人名不翻译\n",
    "- 全角括号换成半角括号，并在左括号前面加半角空格，右括号后面加半角空格。\n",
    "- 在翻译专业术语时，第一次出现时要在括号里面写上英文原文，例如：“生成式 AI (Generative AI)”，之后就可以只写中文了。\n",
    "- 以下是常见的 AI 相关术语词汇对应表（English -> 中文）：\n",
    "  * Transformer -> Transformer\n",
    "  * Token -> Token\n",
    "  * LLM/Large Language Model -> 大语言模型\n",
    "  * Zero-shot -> 零样本\n",
    "  * Few-shot -> 少样本\n",
    "  * AI Agent -> AI 智能体\n",
    "  * AGI -> 通用人工智能\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from transcribe.helpers.translator import QwenTranslator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "llama_context: n_ctx_per_seq (512) < n_ctx_train (131072) -- the full capacity of the model will not be utilized\n",
      "ggml_metal_init: skipping kernel_get_rows_bf16                     (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mv_bf16_f32                   (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mv_bf16_f32_1row              (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mv_bf16_f32_l4                (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mv_bf16_bf16                  (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mv_id_bf16_f32                (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mm_bf16_f32                   (not supported)\n",
      "ggml_metal_init: skipping kernel_mul_mm_id_bf16_f32                (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h64           (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h80           (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h96           (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h112          (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h128          (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h192          (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_hk192_hv128   (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_bf16_h256          (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_vec_bf16_h96       (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_vec_bf16_h128      (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_vec_bf16_h192      (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_vec_bf16_hk192_hv128 (not supported)\n",
      "ggml_metal_init: skipping kernel_flash_attn_ext_vec_bf16_h256      (not supported)\n",
      "ggml_metal_init: skipping kernel_cpy_f32_bf16                      (not supported)\n",
      "ggml_metal_init: skipping kernel_cpy_bf16_f32                      (not supported)\n",
      "ggml_metal_init: skipping kernel_cpy_bf16_bf16                     (not supported)\n"
     ]
    }
   ],
   "source": [
    "translator = QwenTranslator(config.LLM_LARGE_MODEL_PATH, PROMPT, PROMPT)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'<=' not supported between instances of 'str' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mTypeError\u001b[39m                                 Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[7]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[43mtranslator\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m欢迎来到go sim大会\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mzh\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43men\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/Codes/trans/tests/../transcribe/helpers/translator.py:30\u001b[39m, in \u001b[36mQwenTranslator.__call__\u001b[39m\u001b[34m(self, prompt, *args, **kwargs)\u001b[39m\n\u001b[32m     29\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, prompt,*args, **kwargs):\n\u001b[32m---> \u001b[39m\u001b[32m30\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mllm\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m     31\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     32\u001b[39m \u001b[43m        \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m     33\u001b[39m \u001b[43m        \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\n\u001b[32m     34\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/Codes/trans/.venv/lib/python3.11/site-packages/llama_cpp/llama.py:1902\u001b[39m, in \u001b[36mLlama.__call__\u001b[39m\u001b[34m(self, prompt, suffix, max_tokens, temperature, top_p, min_p, typical_p, logprobs, echo, stop, frequency_penalty, presence_penalty, repeat_penalty, top_k, stream, seed, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta, model, stopping_criteria, logits_processor, grammar, logit_bias)\u001b[39m\n\u001b[32m   1838\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m__call__\u001b[39m(\n\u001b[32m   1839\u001b[39m     \u001b[38;5;28mself\u001b[39m,\n\u001b[32m   1840\u001b[39m     prompt: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m   (...)\u001b[39m\u001b[32m   1864\u001b[39m     logit_bias: Optional[Dict[\u001b[38;5;28mint\u001b[39m, \u001b[38;5;28mfloat\u001b[39m]] = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m   1865\u001b[39m ) -> Union[CreateCompletionResponse, Iterator[CreateCompletionStreamResponse]]:\n\u001b[32m   1866\u001b[39m \u001b[38;5;250m    \u001b[39m\u001b[33;03m\"\"\"Generate text from a prompt.\u001b[39;00m\n\u001b[32m   1867\u001b[39m \n\u001b[32m   1868\u001b[39m \u001b[33;03m    Args:\u001b[39;00m\n\u001b[32m   (...)\u001b[39m\u001b[32m   1900\u001b[39m \u001b[33;03m        Response object containing the generated text.\u001b[39;00m\n\u001b[32m   1901\u001b[39m \u001b[33;03m    \"\"\"\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1902\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mcreate_completion\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m   1903\u001b[39m \u001b[43m        \u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1904\u001b[39m \u001b[43m        \u001b[49m\u001b[43msuffix\u001b[49m\u001b[43m=\u001b[49m\u001b[43msuffix\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1905\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1906\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1907\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtop_p\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtop_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1908\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmin_p\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmin_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1909\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtypical_p\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtypical_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1910\u001b[39m \u001b[43m        \u001b[49m\u001b[43mlogprobs\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlogprobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1911\u001b[39m \u001b[43m        \u001b[49m\u001b[43mecho\u001b[49m\u001b[43m=\u001b[49m\u001b[43mecho\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1912\u001b[39m \u001b[43m        \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1913\u001b[39m \u001b[43m        \u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[43m=\u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1914\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1915\u001b[39m \u001b[43m        \u001b[49m\u001b[43mrepeat_penalty\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrepeat_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1916\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1917\u001b[39m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1918\u001b[39m \u001b[43m        \u001b[49m\u001b[43mseed\u001b[49m\u001b[43m=\u001b[49m\u001b[43mseed\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1919\u001b[39m \u001b[43m        \u001b[49m\u001b[43mtfs_z\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtfs_z\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1920\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmirostat_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmirostat_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1921\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmirostat_tau\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmirostat_tau\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1922\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmirostat_eta\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmirostat_eta\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1923\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1924\u001b[39m \u001b[43m        \u001b[49m\u001b[43mstopping_criteria\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstopping_criteria\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1925\u001b[39m \u001b[43m        \u001b[49m\u001b[43mlogits_processor\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlogits_processor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1926\u001b[39m \u001b[43m        \u001b[49m\u001b[43mgrammar\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgrammar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1927\u001b[39m \u001b[43m        \u001b[49m\u001b[43mlogit_bias\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlogit_bias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m   1928\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/Codes/trans/.venv/lib/python3.11/site-packages/llama_cpp/llama.py:1835\u001b[39m, in \u001b[36mLlama.create_completion\u001b[39m\u001b[34m(self, prompt, suffix, max_tokens, temperature, top_p, min_p, typical_p, logprobs, echo, stop, frequency_penalty, presence_penalty, repeat_penalty, top_k, stream, seed, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta, model, stopping_criteria, logits_processor, grammar, logit_bias)\u001b[39m\n\u001b[32m   1833\u001b[39m     chunks: Iterator[CreateCompletionStreamResponse] = completion_or_chunks\n\u001b[32m   1834\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m chunks\n\u001b[32m-> \u001b[39m\u001b[32m1835\u001b[39m completion: Completion = \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mcompletion_or_chunks\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[32m   1836\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m completion\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/Codes/trans/.venv/lib/python3.11/site-packages/llama_cpp/llama.py:1275\u001b[39m, in \u001b[36mLlama._create_completion\u001b[39m\u001b[34m(self, prompt, suffix, max_tokens, temperature, top_p, min_p, typical_p, logprobs, echo, stop, frequency_penalty, presence_penalty, repeat_penalty, top_k, stream, seed, tfs_z, mirostat_mode, mirostat_tau, mirostat_eta, model, stopping_criteria, logits_processor, grammar, logit_bias)\u001b[39m\n\u001b[32m   1270\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(prompt_tokens) >= \u001b[38;5;28mself\u001b[39m._n_ctx:\n\u001b[32m   1271\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[32m   1272\u001b[39m         \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mRequested tokens (\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(prompt_tokens)\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m) exceed context window of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mllama_cpp.llama_n_ctx(\u001b[38;5;28mself\u001b[39m.ctx)\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m   1273\u001b[39m     )\n\u001b[32m-> \u001b[39m\u001b[32m1275\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m max_tokens \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mor\u001b[39;00m \u001b[43mmax_tokens\u001b[49m\u001b[43m \u001b[49m\u001b[43m<\u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m0\u001b[39;49m:\n\u001b[32m   1276\u001b[39m     \u001b[38;5;66;03m# Unlimited, depending on n_ctx.\u001b[39;00m\n\u001b[32m   1277\u001b[39m     max_tokens = \u001b[38;5;28mself\u001b[39m._n_ctx - \u001b[38;5;28mlen\u001b[39m(prompt_tokens)\n\u001b[32m   1279\u001b[39m \u001b[38;5;66;03m# Truncate max_tokens if requested tokens would exceed the context window\u001b[39;00m\n",
      "\u001b[31mTypeError\u001b[39m: '<=' not supported between instances of 'str' and 'int'"
     ]
    }
   ],
   "source": [
    "translator(\"欢迎来到go sim大会\", \"zh\", 'en')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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