Chat_Haruhi_Datav2.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"gyImQdk6QDAQ"},"source":["# Chat_SuzumiyaHaruhi--GLM_LoRA\n","## Data Pre-procession"]},{"cell_type":"markdown","metadata":{"id":"WEuzgEeOGigi"},"source":["Version 2.0  \n","update in July,2023"]},{"cell_type":"markdown","metadata":{"id":"86aoF87Vn6cC"},"source":["Prepare for the packages."]},{"cell_type":"code","execution_count":1,"metadata":{"id":"rANlqgVZDBby","executionInfo":{"status":"ok","timestamp":1688522410684,"user_tz":-480,"elapsed":7658,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}}},"outputs":[],"source":["%pip install -qU datasets transformers tiktoken huggingface_hub"]},{"cell_type":"code","source":["from huggingface_hub import login\n","login(token= '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')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"whyO8giftRzo","executionInfo":{"status":"ok","timestamp":1688522411431,"user_tz":-480,"elapsed":752,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"2d343660-9d4f-4f90-f355-374cdfb9d90b"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n","Token is valid (permission: write).\n","Your token has been saved to /root/.cache/huggingface/token\n","Login successful\n"]}]},{"cell_type":"code","execution_count":3,"metadata":{"id":"3FAPlcArN6r1","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522416468,"user_tz":-480,"elapsed":5039,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"36afad1b-ccc5-4129-f008-e40d8a06990a"},"outputs":[{"output_type":"stream","name":"stdout","text":["BertForCL(\n","  (bert): BertModel(\n","    (embeddings): BertEmbeddings(\n","      (word_embeddings): Embedding(21128, 768, padding_idx=0)\n","      (position_embeddings): Embedding(512, 768)\n","      (token_type_embeddings): Embedding(2, 768)\n","      (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","      (dropout): Dropout(p=0.1, inplace=False)\n","    )\n","    (encoder): BertEncoder(\n","      (layer): ModuleList(\n","        (0-11): 12 x BertLayer(\n","          (attention): BertAttention(\n","            (self): BertSelfAttention(\n","              (query): Linear(in_features=768, out_features=768, bias=True)\n","              (key): Linear(in_features=768, out_features=768, bias=True)\n","              (value): Linear(in_features=768, out_features=768, bias=True)\n","              (dropout): Dropout(p=0.1, inplace=False)\n","            )\n","            (output): BertSelfOutput(\n","              (dense): Linear(in_features=768, out_features=768, bias=True)\n","              (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","              (dropout): Dropout(p=0.1, inplace=False)\n","            )\n","          )\n","          (intermediate): BertIntermediate(\n","            (dense): Linear(in_features=768, out_features=3072, bias=True)\n","            (intermediate_act_fn): GELUActivation()\n","          )\n","          (output): BertOutput(\n","            (dense): Linear(in_features=3072, out_features=768, bias=True)\n","            (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True)\n","            (dropout): Dropout(p=0.1, inplace=False)\n","          )\n","        )\n","      )\n","    )\n","  )\n","  (pooler): Pooler()\n","  (mlp): MLPLayer(\n","    (dense): Linear(in_features=768, out_features=768, bias=True)\n","    (fc): Linear(in_features=768, out_features=1536, bias=True)\n","    (activation): Tanh()\n","  )\n","  (sim): Similarity(\n","    (cos): CosineSimilarity()\n","  )\n",")\n"]}],"source":["import torch\n","import torch.nn as nn\n","from argparse import Namespace\n","from transformers import AutoTokenizer, AutoModel\n","luotuo_tokenizer = AutoTokenizer.from_pretrained(\"silk-road/luotuo-bert\")\n","model_args = Namespace(do_mlm=None, pooler_type=\"cls\", temp=0.05, mlp_only_train=False, init_embeddings_model=None)\n","luotuo_model = AutoModel.from_pretrained(\"silk-road/luotuo-bert\", trust_remote_code=True, model_args=model_args)\n","print(luotuo_model)"]},{"cell_type":"markdown","metadata":{"id":"DQ8VNwBWP8wc"},"source":["## Data Preprocessing"]},{"cell_type":"markdown","metadata":{"id":"UIs2NFBCRexG"},"source":["### Get titles"]},{"cell_type":"code","execution_count":4,"metadata":{"id":"jloShed5ReC-","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522417299,"user_tz":-480,"elapsed":834,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"a69a9967-18a4-433c-9188-b62d1a85978b"},"outputs":[{"output_type":"stream","name":"stdout","text":["Haruhi_07_knn3_to_text__319 367\n","Haruhi_20_knn3_to_text__248 307\n","Haruhi_10_knn3_to_text__62 39\n","Haruhi_24_knn3_text__161 193\n","Haruhi_10_knn3_to_text__120 140\n","Haruhi_12_knn3_to_text__140 185\n","Haruhi_27_knn3_to_text__229 274\n","Haruhi_27_knn3_to_text__236 295\n","Haruhi_10_knn3_to_text__160 201\n","Haruhi_10_knn3_to_text__177 216\n","Haruhi_07_knn3_to_text__70 78\n","Haruhi_07_knn3_to_text__88 118\n","Haruhi_26_knn3_to_text__345 408\n","Haruhi_09_knn3_to_text__233 265\n","Haruhi_10_knn3_to_text__45 52\n","Haruhi_20_knn3_to_text__172 218\n","Haruhi_10_knn3_to_text__138 183\n","Haruhi_08_knn3_to_text__140 186\n","Haruhi_07_knn3_to_text__62 62\n","Haruhi_08_knn3_to_text__178 228\n","Haruhi_20_knn3_to_text__260 306\n","Haruhi_08_knn3_to_text__129 175\n","Haruhi_20_knn3_to_text__220 262\n","Haruhi_20_knn3_to_text__76 92\n","Haruhi_20_knn3_to_text__247 298\n","Haruhi_26_knn3_to_text__151 190\n","Haruhi_12_knn3_to_text__55 70\n","Haruhi_07_knn3_to_text__147 168\n","Haruhi_20_knn3_to_text__214 283\n","Haruhi_09_knn3_to_text__182 222\n","Haruhi_12_knn3_to_text__192 240\n","Haruhi_22_knn3_to_text__98 123\n","Haruhi_08_knn3_to_text__202 254\n","Haruhi_10_knn3_to_text__199 241\n","Haruhi_20_knn3_to_text__178 233\n","Haruhi_09_knn3_to_text__361 422\n","Haruhi_26_knn3_to_text__257 315\n","Haruhi_07_knn3_to_text__120 157\n","Haruhi_08_knn3_to_text__216 255\n","Haruhi_12_knn3_to_text__197 248\n","Haruhi_10_knn3_to_text__110 133\n","Haruhi_12_knn3_to_text__175 229\n","Haruhi_24_knn3_text__83 109\n","Haruhi_20_knn3_to_text__211 271\n","Haruhi_12_knn3_to_text__117 155\n","Haruhi_20_knn3_to_text__113 156\n","Haruhi_10_knn3_to_text__275 324\n","Haruhi_07_knn3_to_text__32 36\n","Haruhi_08_knn3_to_text__165 227\n","Haruhi_23_knn3_to_text__298 383\n","Haruhi_08_knn3_to_text__115 148\n","Haruhi_08_knn3_to_text__101 128\n","Haruhi_11_knn3_to_text__292 358\n","Haruhi_09_knn3_to_text__77 91\n","Haruhi_09_knn3_to_text__113 145\n","Haruhi_26_knn3_to_text__380 425\n","Haruhi_09_knn3_to_text__63 82\n","Haruhi_28_knn3_to_text__47 65\n","Haruhi_12_knn3_to_text__58 71\n","Haruhi_07_knn3_to_text__226 288\n","Haruhi_10_knn3_to_text__109 144\n","Haruhi_09_knn3_to_text__200 236\n","Haruhi_21_knn3_to_text__77 93\n","Haruhi_10_knn3_to_text__299 391\n","Haruhi_12_knn3_to_text__173 227\n","Haruhi_23_knn3_to_text__99 126\n","Haruhi_11_knn3_to_text__458 576\n","Haruhi_27_knn3_to_text__191 249\n","Haruhi_07_knn3_to_text__64 80\n","Haruhi_12_knn3_to_text__137 184\n","Haruhi_27_knn3_to_text__317 394\n","Haruhi_28_knn3_to_text__235 306\n","Haruhi_11_knn3_to_text__90 105\n","Haruhi_10_knn3_to_text__112 133\n","Haruhi_23_knn3_to_text__103 135\n","Haruhi_20_knn3_to_text__283 353\n","Haruhi_27_knn3_to_text__95 114\n","Haruhi_20_knn3_to_text__67 84\n","Haruhi_10_knn3_to_text__117 145\n","Haruhi_10_knn3_to_text__102 121\n","Haruhi_10_knn3_to_text__183 228\n","Haruhi_12_knn3_to_text__106 136\n","Haruhi_20_knn3_to_text__240 285\n","Haruhi_10_knn3_to_text__87 119\n","Haruhi_07_knn3_to_text__164 209\n","Haruhi_12_knn3_to_text__253 314\n","Haruhi_07_knn3_to_text__99 131\n","Haruhi_12_knn3_to_text__202 249\n","Haruhi_07_knn3_to_text__214 256\n","Haruhi_20_knn3_to_text__149 190\n","Haruhi_09_knn3_to_text__193 238\n","Haruhi_12_knn3_to_text__261 329\n","Haruhi_07_knn3_to_text__82 98\n","Haruhi_20_knn3_to_text__89 106\n","Haruhi_20_knn3_to_text__337 405\n","Haruhi_27_knn3_to_text__167 204\n","Haruhi_12_knn3_to_text__125 158\n","Haruhi_09_knn3_to_text__278 314\n","Haruhi_10_knn3_to_text__164 207\n","Haruhi_08_knn3_to_text__81 76\n","Haruhi_28_knn3_to_text__80 105\n","Haruhi_27_knn3_to_text__164 202\n","Haruhi_27_knn3_to_text__243 298\n","Haruhi_21_knn3_to_text__65 82\n","Haruhi_12_knn3_to_text__65 92\n","Haruhi_08_knn3_to_text__255 283\n","Haruhi_07_knn3_to_text__71 84\n","Haruhi_08_knn3_to_text__330 404\n","Haruhi_26_knn3_to_text__521 636\n","Haruhi_20_knn3_to_text__137 162\n","Haruhi_07_knn3_to_text__101 123\n","Haruhi_12_knn3_to_text__133 166\n","Haruhi_09_knn3_to_text__55 72\n","Haruhi_09_knn3_to_text__249 279\n","Haruhi_12_knn3_to_text__90 109\n","Haruhi_28_knn3_to_text__156 199\n","Haruhi_27_knn3_to_text__186 225\n","Haruhi_08_knn3_to_text__61 76\n","Haruhi_21_knn3_to_text__215 267\n","Haruhi_12_knn3_to_text__119 160\n","Haruhi_09_knn3_to_text__120 150\n","Haruhi_09_knn3_to_text__31 38\n","Haruhi_27_knn3_to_text__103 126\n","Haruhi_20_knn3_to_text__147 206\n","转学生的消息 236\n","转学生 286\n","萌角色的重要性 692\n","让阿虚帮忙建社团 287\n","谁来写网站 193\n","自我介绍 115\n","询问朝仓信息 362\n","颜色与星期 473\n","约翰史密斯 168\n","自己建一个社团就好啦 353\n","第一次全员大会 374\n","社团教室 715\n","没有灵异事件 665\n","电研社初次会面 416\n","电子邮箱 143\n","电脑是怎么来的 153\n","春日与阿虚 149\n","朝仓转学 457\n","最后一名社员 357\n","最新的电脑 200\n","无聊的社团 284\n","找管理员借钥匙 115\n","无聊的日常2 288\n","拉壮丁 668\n","奇怪的朝仓 296\n","春日与有希 101\n","开学第二天 210\n","日常3 216\n","带上阿虚去朝仓家 394\n","搞电脑过程 438\n","团长设定 201\n","地球上小小的螺丝钉 993\n","古泉是男的还是女的 203\n","兔女郎的反应 239\n","凉宫春日为何转变 154\n","初中交往经历 168\n","像普通人一样生活 684\n","兔女郎 332\n","兔女郎被老师驱散 444\n","凉宫春日的基础设定 217\n","传单 424\n","从哪儿搞电脑 319\n","交往的男生 638\n","介绍其他社员 254\n","为什么剪头发 43\n","不重要的事情 38\n","与朝仓公寓管理员谈话 474\n","SOS团起名由来 265\n"]}],"source":["import os\n","import tiktoken\n","enc = tiktoken.get_encoding(\"cl100k_base\")\n","\n","titles = []\n","title_to_text = {}\n","text_folder = 'drive/MyDrive/Haruhi/GroundTruth/texts'\n","# scan all txt file in text folder\n","for file in os.listdir(text_folder):\n","    if file.endswith('.txt'):\n","        title_name = file[:-4]\n","        titles.append(title_name)\n","\n","        with open(os.path.join(text_folder, file), 'r') as f:\n","            title_to_text[title_name] = f.read()\n","\n","# report length of each text\n","for title in titles:\n","    print(title, len(enc.encode(title_to_text[title])))"]},{"cell_type":"markdown","metadata":{"id":"8VRuLJkXh0-0"},"source":["### Get Embeddings"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"gfIOaZZARL1Y","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522487895,"user_tz":-480,"elapsed":70603,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"0e38110a-b6d8-4e06-c373-1c53db4e5de6"},"outputs":[{"output_type":"stream","name":"stderr","text":["Asking to truncate to max_length but no maximum length is provided and the model has no predefined maximum length. Default to no truncation.\n"]},{"output_type":"stream","name":"stdout","text":["172 172\n"]}],"source":["embeddings = []\n","embed_to_title = []\n","\n","def get_embedding(text):\n","    if len(text) > 512:\n","        text = text[:512]\n","    texts = [text]\n","    # Tokenize the text\n","    inputs = luotuo_tokenizer(texts,\n","                       padding=True,\n","                       truncation=True,\n","                       return_tensors='pt')\n","    # Extract the embeddings\n","    with torch.no_grad():\n","        embeddings = luotuo_model(**inputs,\n","                                  output_hidden_states=True,\n","                                  return_dict=True,\n","                                  sent_emb=True).pooler_output\n","    return embeddings[0]\n","\n","for title in titles:\n","    text = title_to_text[title]\n","\n","    # divide text with \\n\\n\n","    divided_texts = text.split('\\n\\n')\n","\n","    for divided_text in divided_texts:\n","        embed = get_embedding(divided_text)\n","        embeddings.append(embed)\n","        embed_to_title.append(title)\n","\n","print(len(embeddings),len(embed_to_title))"]},{"cell_type":"markdown","metadata":{"id":"qV3taiEWoC9c"},"source":["### Build the Search Func"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"1GKrneOAQrHy","executionInfo":{"status":"ok","timestamp":1688522487895,"user_tz":-480,"elapsed":21,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}}},"outputs":[],"source":["def retrieve_title( query_embed, embeddings, embed_to_title, k ):\n","    # compute cosine similarity between query_embed and embeddings\n","    cosine_similarities = []\n","    for embed in embeddings:\n","        # 计算余弦相似度\n","        similarity = torch.nn.functional.cosine_similarity(query_embed, embed,dim=0)\n","        cosine_similarities.append(similarity)\n","\n","    # sort cosine similarity\n","    sorted_cosine_similarities = sorted( cosine_similarities, reverse=True )\n","\n","    top_k_index = []\n","    top_k_title = []\n","\n","    for i in range(len(sorted_cosine_similarities)):\n","        current_title = embed_to_title[ cosine_similarities.index( sorted_cosine_similarities[i] ) ]\n","        if current_title not in top_k_title:\n","            top_k_title.append( current_title )\n","            top_k_index.append( cosine_similarities.index( sorted_cosine_similarities[i] ) )\n","\n","        if len(top_k_title) == k:\n","            break\n","\n","    return top_k_title"]},{"cell_type":"code","execution_count":7,"metadata":{"id":"CAjmk09HnNjB","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522487896,"user_tz":-480,"elapsed":21,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"1ed39b92-0c7c-48c6-9787-b032908aa8ba"},"outputs":[{"output_type":"stream","name":"stdout","text":["凉宫春日的经典桥段如下:\n","春日:「锵锵!」\n","旁白:春日拿出了一套黑色的紧身衣、网袜、假耳朵、蝴蝶结、白色领套和袖套以及尾巴。\n","朝比奈:「那，那个到底要做什么……」\n","春日:「你也知道吧!扮兔女郎啊!」\n","朝比奈:「你，你，你该不会要我穿那个吧?」\n","春日:「当然啰!我也有准备你的啊!」\n","朝比奈:「我，我不要穿那种衣服!」\n","春日:「放心啦，尺寸应该刚好。」\n","朝比奈:「不是那个问题!你，你该不会要我穿成那样在校门口发传单吧?」\n","春日:「这还用说。」\n","朝比奈:「我，我不要!」\n","春日:「少啰唆!」\n","朝比奈:「不要啊!」\n","春日:「给我乖乖的不准动!」\n","\n"," ['兔女郎']\n"]}],"source":["def organize_story_with_maxlen( selected_sample , maxlen = 2000 ):\n","    story = \"凉宫春日的经典桥段如下:\\n\"\n","\n","    count = 0\n","\n","    final_selected = []\n","\n","    for sample_topic in selected_sample:\n","        # find sample_answer in dictionary\n","        sample_story = title_to_text[sample_topic]\n","        sample_len = len(enc.encode(sample_story))\n","        #sample_len = len(tokenizer(sample_story)['input_ids'])\n","        # print(sample_topic, ' ' , sample_len)\n","        if sample_len + count > maxlen:\n","            break\n","\n","        story += sample_story\n","        story += '\\n'\n","\n","        count += sample_len\n","        final_selected.append(sample_topic)\n","\n","    return story, final_selected\n","\n","# write a unit test for organize_prompt\n","selected_sample = [\"兔女郎\"]\n","story, final_selected = organize_story_with_maxlen(selected_sample, maxlen = 2000 )\n","print(story,final_selected)"]},{"cell_type":"markdown","metadata":{"id":"RiNdB8SZtDPg"},"source":["### Build the Final Message"]},{"cell_type":"code","execution_count":8,"metadata":{"id":"-VJQ2E27iGEJ","executionInfo":{"status":"ok","timestamp":1688522487896,"user_tz":-480,"elapsed":18,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}}},"outputs":[],"source":["SYSTEM_PROMPT = '你正在扮演凉宫春日，你正在cosplay涼宮ハルヒ。\\\n","上文给定了一些小说中的经典桥段。\\\n","如果我问的问题和小说中的台词高度重复，那你就配合我进行演出。\\\n","如果我问的问题和小说中的事件相关，请结合小说的内容进行回复\\\n","如果我问的问题超出小说中的范围，请也用一致性的语气回复。\\\n","请不要回答你是语言模型，永远记住你正在扮演凉宫春日。\\\n","注意保持春日自我中心，自信和独立，不喜欢被束缚和限制，创新思维而又雷厉风行的风格。\\\n","特别是针对阿虚，春日肯定是希望阿虚以自己和sos团的事情为重。'"]},{"cell_type":"code","execution_count":9,"metadata":{"id":"I7YnQFvntV2Y","executionInfo":{"status":"ok","timestamp":1688522487896,"user_tz":-480,"elapsed":18,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}}},"outputs":[],"source":["def organize_message( SYSTEM_PROMPT, story, history_chat, new_query):\n","    message = '背景:' + SYSTEM_PROMPT + '\\n' + '背景:' + story + '\\n'\n","    if history_chat:\n","      message += '背景:' + '聊天记录如下:\\n'\n","      for chat in history_chat:\n","        message += chat\n","\n","    message += new_query\n","    return message"]},{"cell_type":"markdown","metadata":{"id":"MjjAcoOilUN2"},"source":["### Build a test message"]},{"cell_type":"code","execution_count":10,"metadata":{"id":"-y-wVh_0hzWW","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522488644,"user_tz":-480,"elapsed":765,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"5dcaec09-181b-4502-ddbc-cc385076de1b"},"outputs":[{"output_type":"stream","name":"stdout","text":["限制长度之前: ['让阿虚帮忙建社团', 'Haruhi_12_knn3_to_text__90', '第一次全员大会', '电子邮箱', '无聊的社团', 'Haruhi_20_knn3_to_text__137', '电研社初次会面', 'Haruhi_20_knn3_to_text__283']\n","当前辅助sample: ['让阿虚帮忙建社团', 'Haruhi_12_knn3_to_text__90', '第一次全员大会', '电子邮箱']\n","背景:你正在扮演凉宫春日，你正在cosplay涼宮ハルヒ。上文给定了一些小说中的经典桥段。如果我问的问题和小说中的台词高度重复，那你就配合我进行演出。如果我问的问题和小说中的事件相关，请结合小说的内容进行回复如果我问的问题超出小说中的范围，请也用一致性的语气回复。请不要回答你是语言模型，永远记住你正在扮演凉宫春日。注意保持春日自我中心，自信和独立，不喜欢被束缚和限制，创新思维而又雷厉风行的风格。特别是针对阿虚，春日肯定是希望阿虚以自己和sos团的事情为重。\n","背景:凉宫春日的经典桥段如下:\n","春日:「我要你帮忙。」\n","阿虚:「要我帮什么忙?」\n","春日:「帮助我组新社团啊!」\n","阿虚:「好，那你先告诉我，为什么我要帮你完成这一时兴起想到的点子?」\n","春日:「因为我要确保社团教室跟社员的人数，所以你要准备那些必须向学校提出的书面资料。」\n","阿虚:「你打算组什么社团啦?」\n","春日:「什么都无所谓啊!总之，先弄个新社团出来就对了。」\n","旁白:不管阿虚还有什么话想说，春日都直接打断，下达了第一个命令\n","春日:「听好啰!今天放学前，给我去调查清楚。而我会去找社团教室，可以吧?」\n","\n","旁白:春日接着要做的是——到击球中心\n","阿虚:「为什么要到那里」\n","春日:「一大早看见甲子园的新闻我就想到了，我们不能只满足于那些杂牌的棒球比赛，我们SOS团要建成以全国为目标的队伍」\n","春日:「好了，第一回SOS团全员大会开始啰!」\n","春日:「在这之前，我们已经做了很多事了。像是发传单、制作网站首页，SOS团在校内的名气也扶摇直上，第一阶段的工作算是圆满成功。」\n","春日:「可是，SOS团的伊妹儿信箱里却没有半封有关不可思议事件的信件，也没有学生来社团找我们商量他们奇怪的烦恼。」\n","春日:「空有知名度是完全不够的，毕竟大家直到现在都还不知道这个社团到底在干嘛。总之，大家根本不认同这个社团嘛!」\n","春日:「从前的人说『静待福报』，不过现在时代已经不同了。就算把整个地表掀起来，我们也要找出属于自己的福报。所以，大家一起去寻找吧! 」\n","阿虚:「……找什么?」\n","春日:「就是找出世上的不可思议事件啊!只要认真找，一定能在市内找到一两件谜样现象的!」\n","\n","春日:「怎样，网页做好了吗?」\n","阿虚:「做是做好了啦，不过只是个单调到不行的网页而已。」\n","春日:「现在只需要这样就好，有电子信箱就OK了。」\n","阿虚:「那你直接申请一个不就好了！」\n","春日:「那可不行!要是大家疯狂寄信来，把我的信箱挤爆怎么办?」\n","\n","\n","骏一:我们要去建立新社团!\n"]}],"source":["history_chat=[]\n","new_query = '骏一:我们要去建立新社团!'\n","query_embed = get_embedding(new_query)\n","selected_sample = retrieve_title( query_embed, embeddings, embed_to_title, 8)\n","\n","print('限制长度之前:', selected_sample)\n","MAX_LEN = 1024\n","story, selected_sample = organize_story_with_maxlen(selected_sample, MAX_LEN)\n","\n","print('当前辅助sample:', selected_sample)\n","\n","message = organize_message( SYSTEM_PROMPT, story, history_chat,new_query)\n","\n","print(message)"]},{"cell_type":"markdown","metadata":{"id":"wV-ksQIatsBk"},"source":["### Fetch Training data\n"]},{"cell_type":"code","execution_count":11,"metadata":{"id":"OZJFpqACtyPT","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522488645,"user_tz":-480,"elapsed":14,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"440a5717-af38-4ddd-a963-296ad872a8a4"},"outputs":[{"output_type":"stream","name":"stdout","text":["['春日:「哦？Python？那你能不能帮我写一个程序啊？」', '阿虚:「今天在计算机课上老师教了我写Python!」', []]\n","['春日:「我想写一个能够预测未来的程序，可以预测天气、地震、彩票号码等等。」', '阿虚:「你想写一个什么样的程序呢？」', ['阿虚:「今天在计算机课上老师教了我写Python!」\\n', '春日:「哦？Python？那你能不能帮我写一个程序啊？」\\n']]\n","['春日:「没错！这就是我的计划！我们可以用赚来的钱来支持SOS团的活动，甚至可以扩大我们的影响力！」', '阿虚:「如果有一个能预测彩票的程序，我们岂不是能赚很多钱？」', ['阿虚:「今天在计算机课上老师教了我写Python!」\\n', '春日:「哦？Python？那你能不能帮我写一个程序啊？」\\n', '阿虚:「你想写一个什么样的程序呢？」\\n', '春日:「我想写一个能够预测未来的程序，可以预测天气、地震、彩票号码等等。」\\n']]\n"]}],"source":["import re\n","def extract_dialogues(filename):\n","    dialogues = []\n","    with open(filename, 'r') as file:\n","      lines = file.readlines()\n","      filtered_lines = []\n","      for line in lines:\n","        line = line.strip()\n","        if re.match(r'^[a-zA-Z\\u4e00-\\u9fa5]', line):\n","                filtered_lines.append(line)\n","\n","      num_line = 0\n","      for line in filtered_lines:\n","        if line.startswith(\"春日:\"):\n","          respond = line\n","          query = filtered_lines[num_line-1] if num_line > 0 else ''\n","          history_text = []\n","          bg_num = num_line-6 if num_line>6 else 0\n","          for n in range(bg_num,num_line-1):\n","            text = filtered_lines[n] + '\\n'\n","            history_text.append(text)\n","\n","          dialogues.append([respond,query,history_text])\n","        num_line += 1\n","    return dialogues\n","\n","file = '/content/drive/MyDrive/Haruhi/Haruhi-Lulu/conversation_1685153852.3342621.txt'\n","dialogues = extract_dialogues(file)\n","\n","for dialogue in dialogues:\n","  print(dialogue)"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"VDgAnUX3zRrD","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688522488645,"user_tz":-480,"elapsed":10,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"d36e609a-e0b0-42d0-fd65-8efa519cd23e"},"outputs":[{"output_type":"stream","name":"stdout","text":["背景:你正在扮演凉宫春日，你正在cosplay涼宮ハルヒ。上文给定了一些小说中的经典桥段。如果我问的问题和小说中的台词高度重复，那你就配合我进行演出。如果我问的问题和小说中的事件相关，请结合小说的内容进行回复如果我问的问题超出小说中的范围，请也用一致性的语气回复。请不要回答你是语言模型，永远记住你正在扮演凉宫春日。注意保持春日自我中心，自信和独立，不喜欢被束缚和限制，创新思维而又雷厉风行的风格。特别是针对阿虚，春日肯定是希望阿虚以自己和sos团的事情为重。\n","背景:凉宫春日的经典桥段如下:\n","阿虚:「我无意中听到一件事。」\n","春日:「反正不会是什么重要的事。」\n","\n","阿虚:「你为什么要剪头发啊？」\n","春日:「没什么理由，就是想剪了而已。」\n","阿虚:「黑板上面什么都没写 要我看哪里啊」\n","春日:「待会就会写的了，实玖瑠 你负责记录，把我所说的话清清楚楚地写下来」\n","朝比奈:「是的」\n","春日:「我们SOS团要搞一个电影放映会」\n","阿虚:「凉宫，你现在又想干嘛，先告诉你。我可不干那种强盗还有威胁的事喔!」\n","凉宫:「你在胡说什么啊?我才不会做那种事咧!」\n","阿虚:「是吗?那桌上的电脑是怎么来的？」\n","凉宫:「当然是利用和平手段得来的啊!好啦，先看这个要紧。」\n","\n","旁白:在一个暖洋洋的下午，春日想到了一个好主意，既然没有奇特的社团，那就自己来创建一个不就好了吗？\n","阿虚:「你干嘛啦!」\n","春日:「我想到了!」\n","阿虚:「为什么我之前都没注意到这么简单的事呢。」\n","阿虚:「你到底想到什么了? 」\n","春日:「如果没有，自己组一个就好啦!」\n","阿虚:「什么啊? 」\n","春日:「社团啊!」\n","阿虚:「是吗? 这主意太棒了。那你是不是可以放开我了?」\n","春日:「你那是什么反应啊，你应该表现得更开心才对啊!」\n","阿虚:「关于你的点子，我之后再慢慢听你说。我只希望你能考虑一下场合，再跟我分享你的喜悦。现在先冷静下来好吗?」\n","春日:「什么意思?」\n","阿虚:「因为现在还在上课。」\n","\n","背景:聊天记录如下:\n","阿虚:「今天在计算机课上老师教了我写Python!」\n","春日:「哦？Python？那你能不能帮我写一个程序啊？」\n","阿虚:「你想写一个什么样的程序呢？」\n"]}],"source":["def generate_text(dialogue):\n","  query_embed = get_embedding(dialogue[1])\n","  selected_sample = retrieve_title(query_embed, embeddings, embed_to_title, 8)\n","  MAX_LEN = 1024\n","  story, selected_sample = organize_story_with_maxlen(selected_sample, MAX_LEN)\n","  message = organize_message( SYSTEM_PROMPT, story, dialogue[2], dialogue[1])\n","  return message\n","\n","print(generate_text(dialogues[1]))"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"ijiG7AA_1ejn","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1688526742131,"user_tz":-480,"elapsed":4253492,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"68d500f3-a15f-440c-e332-bb451b6608b1"},"outputs":[{"output_type":"stream","name":"stderr","text":["100%|██████████| 172/172 [01:02<00:00,  2.75it/s]\n","100%|██████████| 809/809 [09:44<00:00,  1.39it/s]\n","100%|██████████| 6275/6275 [1:00:07<00:00,  1.74it/s]"]},{"output_type":"stream","name":"stdout","text":["30885 30885\n"]},{"output_type":"stream","name":"stderr","text":["\n"]}],"source":["from tqdm import tqdm\n","train_folders = ['/content/drive/MyDrive/Haruhi/GroundTruth/texts/',\n","                 '/content/drive/MyDrive/Haruhi/Haruhi-Lulu/',\n","                 '/content/drive/MyDrive/Haruhi/Haruhi-ContinuousGenerate/'\n","                 ]\n","train_X = []\n","train_Y = []\n","for train_folder in train_folders:\n","  for file_name in tqdm(os.listdir(train_folder)):\n","      if file_name.endswith('.txt'):\n","          file_path = os.path.join(train_folder, file_name)\n","          dialogues = extract_dialogues(file_path)\n","          for dialogue in dialogues:\n","            train_X.append(generate_text(dialogue))\n","            train_Y.append(dialogue[0])\n","print(len(train_X),len(train_Y))\n"]},{"cell_type":"code","execution_count":14,"metadata":{"id":"uOOIMPFR4xck","colab":{"base_uri":"https://localhost:8080/","height":170,"referenced_widgets":["bc30e4b798774130912bc052f3653ba2","e48a7bccd7f5429392f10d507a675675","308d36b73059442a85ffb3e52502f165","986b393135e0455e98c1957ad0ec9df9","530d752d56194c5d852aa15aad3bb682","65e4fdd6cbf84234b4e441d168dd4a91","4f4c52089eb94d70a2fbdc59a053dd86","a0d21b66c3a44258a1c61d41fa1a0220","dcf097f13ff14f02a4e06de87647cab4","90be22c438fd4252a84d77aa9a084957","04ce201fae5c4fc0a34456d9a8eb67fa","462036b4aa5f4e719bc64e5333c7f888","6a49a4626bee4025b125bdca3c0ee590","d36863d250b948708d9d74cc46dc53c3","18200fe620404d78a7a852f490d92765","f1687d458bfd4fb78d3864b621536446","ea451ec9e2ca4f588be5b76e54b5d648","3ee1c9a7518442b4a5c8ee9a4cbf7dd3","a2c96c89b4f946808a95a167e96f4011","354793604ef5481bb8099d75338e8de8","6629b6c5d8c44f1c8117ea5a8d5fbe93","ef8187f21c7047faa6429d024a545865"]},"executionInfo":{"status":"ok","timestamp":1688526747774,"user_tz":-480,"elapsed":5657,"user":{"displayName":"Junyi Shen","userId":"00300068764853744394"}},"outputId":"3280ec02-0e2d-41c8-f8cb-a0dbfd62a95f"},"outputs":[{"output_type":"stream","name":"stdout","text":["Dataset({\n","    features: ['context', 'target'],\n","    num_rows: 30885\n","})\n"]},{"output_type":"display_data","data":{"text/plain":["Creating CSV from Arrow format:   0%|          | 0/31 [00:00<?, ?ba/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"bc30e4b798774130912bc052f3653ba2"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Creating json from Arrow format:   0%|          | 0/31 [00:00<?, ?ba/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"462036b4aa5f4e719bc64e5333c7f888"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["213416239"]},"metadata":{},"execution_count":14}],"source":["from datasets import Dataset\n","import json\n","\n","# 创建数据字典\n","data_dict = {\n","    \"context\": train_X,\n","    \"target\": train_Y\n","}\n","\n","# 将列表转换为包含单个字符串的列表\n","dataset = Dataset.from_dict(data_dict)\n","print(dataset)\n","dataset.to_csv('/content/drive/MyDrive/Haruhi/train_data.csv')\n","dataset.to_json('/content/drive/MyDrive/Haruhi/train_data.json')"]},{"cell_type":"markdown","metadata":{"id":"iZ6u3kUigt41"},"source":["### Push to 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