diff --git "a/load_model.ipynb" "b/load_model.ipynb" new file mode 100644--- /dev/null +++ "b/load_model.ipynb" @@ -0,0 +1,4496 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "collapsed": true, + "id": "vYuUCZA9Ow-1", + "outputId": "731e5845-c7c0-420f-bcd5-c8dc174f654b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Defaulting to user installation because normal site-packages is not writeable\n", + "Collecting transformers==4.46.2\n", + " Using cached transformers-4.46.2-py3-none-any.whl.metadata (44 kB)\n", + "Collecting peft==0.13.2\n", + " Using cached peft-0.13.2-py3-none-any.whl.metadata (13 kB)\n", + "Collecting accelerate==1.1.1\n", + " Using cached accelerate-1.1.1-py3-none-any.whl.metadata (19 kB)\n", + "Collecting trl==0.12.1\n", + " Using cached trl-0.12.1-py3-none-any.whl.metadata (10 kB)\n", + "\u001b[31mERROR: Could not find a version that satisfies the requirement bitsandbytes==0.45.2 (from versions: 0.31.8, 0.32.0, 0.32.1, 0.32.2, 0.32.3, 0.33.0, 0.33.1, 0.34.0, 0.35.0, 0.35.1, 0.35.2, 0.35.3, 0.35.4, 0.36.0, 0.36.0.post1, 0.36.0.post2, 0.37.0, 0.37.1, 0.37.2, 0.38.0, 0.38.0.post1, 0.38.0.post2, 0.38.1, 0.39.0, 0.39.1, 0.40.0, 0.40.0.post1, 0.40.0.post2, 0.40.0.post3, 0.40.0.post4, 0.40.1, 0.40.1.post1, 0.40.2, 0.41.0, 0.41.1, 0.41.2, 0.41.2.post1, 0.41.2.post2, 0.41.3, 0.41.3.post1, 0.41.3.post2, 0.42.0)\u001b[0m\u001b[31m\n", + "\u001b[0m\u001b[31mERROR: No matching distribution found for bitsandbytes==0.45.2\u001b[0m\u001b[31m\n", + "\u001b[0m" + ] + } + ], + "source": [ + "# imports and libs\n", + "!pip3 -q install transformers\n", + "!pip3 install trl\n", + "!pip3 install -U bitsandbytes\n", + "!pip3 install datasets\n", + "!pip3 install peft\n", + "!pip3 install accelerate\n", + "# !pip install -q datasets trl peft bitsandbytes accelerate datasets\n", + "# !pip3 install transformers==4.46.2 peft==0.13.2 accelerate==1.1.1 trl==0.12.1 bitsandbytes==0.45.2 datasets==3.1.0 huggingface-hub==0.26.2 safetensors==0.4.5 pandas==2.2.2 matplotlib==3.8.0 numpy==1.26.4\n", + "\n", + "import torch\n", + "from transformers import AutoModelForCausalLM, DataCollatorWithPadding\n", + "from transformers import AutoTokenizer, AutoModelForSequenceClassification, BitsAndBytesConfig\n", + "from torch.optim import AdamW\n", + "from datasets import load_dataset\n", + "from torch.utils.data import DataLoader\n", + "from peft import LoraConfig, prepare_model_for_kbit_training, get_peft_model, TaskType\n", + "from transformers import Trainer, TrainingArguments\n", + "from trl import SFTConfig, SFTTrainer\n", + "from peft import PeftModel, PeftConfig" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 528, + "referenced_widgets": [ + "3997e0d75204427ba319a38ed09af7f6", + "be11cecd0b9844708b84e40582241275", + 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"id": "1ytailHyOPnt", + "outputId": "769d2fc5-3439-4cb5-b311-5e03c57f49ee" + }, + "outputs": [ + { + "ename": "ImportError", + "evalue": "Using `bitsandbytes` 4-bit quantization requires the latest version of bitsandbytes: `pip install -U bitsandbytes`", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[3], line 12\u001b[0m\n\u001b[1;32m 3\u001b[0m config \u001b[38;5;241m=\u001b[39m PeftConfig\u001b[38;5;241m.\u001b[39mfrom_pretrained(peft_model_id)\n\u001b[1;32m 5\u001b[0m bnb_config \u001b[38;5;241m=\u001b[39m BitsAndBytesConfig(\n\u001b[1;32m 6\u001b[0m load_in_4bit\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 7\u001b[0m bnb_4bit_quant_type\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnf4\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 8\u001b[0m bnb_4bit_use_double_quant\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m 9\u001b[0m bnb_4bit_compute_dtype\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mfloat32\n\u001b[1;32m 10\u001b[0m )\n\u001b[0;32m---> 12\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModelForCausalLM\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbase_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 14\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mauto\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43mquantization_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbnb_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m \u001b[49m\u001b[43moffload_folder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43moffload\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moffload_state_dict\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\n\u001b[1;32m 17\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m 18\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m AutoTokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(config\u001b[38;5;241m.\u001b[39mbase_model_name_or_path)\n\u001b[1;32m 20\u001b[0m \u001b[38;5;66;03m# Load the Lora model\u001b[39;00m\n", + "File \u001b[0;32m~/Library/Python/3.10/lib/python/site-packages/transformers/models/auto/auto_factory.py:571\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 569\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m model_class\u001b[38;5;241m.\u001b[39mconfig_class \u001b[38;5;241m==\u001b[39m config\u001b[38;5;241m.\u001b[39msub_configs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext_config\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 570\u001b[0m config \u001b[38;5;241m=\u001b[39m config\u001b[38;5;241m.\u001b[39mget_text_config()\n\u001b[0;32m--> 571\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mmodel_class\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 572\u001b[0m \u001b[43m \u001b[49m\u001b[43mpretrained_model_name_or_path\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mhub_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\n\u001b[1;32m 573\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 574\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 575\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 576\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 577\u001b[0m )\n", + "File \u001b[0;32m~/Library/Python/3.10/lib/python/site-packages/transformers/modeling_utils.py:282\u001b[0m, in \u001b[0;36mrestore_default_torch_dtype.._wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 280\u001b[0m old_dtype \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mget_default_dtype()\n\u001b[1;32m 281\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 282\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 283\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 284\u001b[0m torch\u001b[38;5;241m.\u001b[39mset_default_dtype(old_dtype)\n", + "File \u001b[0;32m~/Library/Python/3.10/lib/python/site-packages/transformers/modeling_utils.py:4296\u001b[0m, in \u001b[0;36mPreTrainedModel.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, weights_only, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m 4293\u001b[0m hf_quantizer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 4295\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m hf_quantizer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 4296\u001b[0m \u001b[43mhf_quantizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalidate_environment\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 4297\u001b[0m \u001b[43m \u001b[49m\u001b[43mtorch_dtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtorch_dtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4298\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrom_tf\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfrom_tf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4299\u001b[0m \u001b[43m \u001b[49m\u001b[43mfrom_flax\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfrom_flax\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4300\u001b[0m \u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdevice_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4301\u001b[0m \u001b[43m \u001b[49m\u001b[43mweights_only\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights_only\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4302\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4303\u001b[0m torch_dtype \u001b[38;5;241m=\u001b[39m hf_quantizer\u001b[38;5;241m.\u001b[39mupdate_torch_dtype(torch_dtype)\n\u001b[1;32m 4304\u001b[0m device_map \u001b[38;5;241m=\u001b[39m hf_quantizer\u001b[38;5;241m.\u001b[39mupdate_device_map(device_map)\n", + "File \u001b[0;32m~/Library/Python/3.10/lib/python/site-packages/transformers/quantizers/quantizer_bnb_4bit.py:76\u001b[0m, in \u001b[0;36mBnb4BitHfQuantizer.validate_environment\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 72\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[1;32m 73\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUsing `bitsandbytes` 4-bit quantization requires Accelerate: `pip install \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124maccelerate>=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mACCELERATE_MIN_VERSION\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 74\u001b[0m )\n\u001b[1;32m 75\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_bitsandbytes_available():\n\u001b[0;32m---> 76\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[1;32m 77\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUsing `bitsandbytes` 4-bit quantization requires the latest version of bitsandbytes: `pip install -U bitsandbytes`\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 78\u001b[0m )\n\u001b[1;32m 80\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mintegrations\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m validate_bnb_backend_availability\n\u001b[1;32m 81\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m is_bitsandbytes_multi_backend_available\n", + "\u001b[0;31mImportError\u001b[0m: Using `bitsandbytes` 4-bit quantization requires the latest version of bitsandbytes: `pip install -U bitsandbytes`" + ] + } + ], + "source": [ + "peft_model_id = \"./ai_model/\"\n", + "\n", + "config = PeftConfig.from_pretrained(peft_model_id)\n", + "\n", + "bnb_config = BitsAndBytesConfig(\n", + " load_in_4bit=True,\n", + " bnb_4bit_quant_type=\"nf4\",\n", + " bnb_4bit_use_double_quant=True,\n", + " bnb_4bit_compute_dtype=torch.float32\n", + ")\n", + "\n", + "model = AutoModelForCausalLM.from_pretrained(\n", + " config.base_model_name_or_path,\n", + " device_map='auto',\n", + " quantization_config=bnb_config,\n", + " offload_folder=\"offload\", offload_state_dict = True\n", + ")\n", + "tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)\n", + "\n", + "# Load the Lora model\n", + "model = PeftModel.from_pretrained(model, peft_model_id)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "id": "sRWsj9HVQUjB" + }, + "outputs": [], + "source": [ + "def generate(model, tokenizer, prompt, max_new_tokens=64, skip_special_tokens=False):\n", + " tokenized_input = tokenizer(prompt, add_special_tokens=False, return_tensors=\"pt\").to(model.device)\n", + "\n", + " model.eval()\n", + " generation_output = model.generate(**tokenized_input,\n", + " eos_token_id=tokenizer.eos_token_id,\n", + " max_new_tokens=max_new_tokens)\n", + "\n", + " output = tokenizer.batch_decode(generation_output,\n", + " skip_special_tokens=skip_special_tokens)\n", + " # output\n", + " output = output[0].split(\"<|assistant|>\")[1]\n", + " return output" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "id": "mtdiesgsRAQe" + }, + "outputs": [], + "source": [ + "def gen_prompt(tokenizer, sentence):\n", + " converted_sample = [\n", + " {\"role\": \"user\", \"content\": sentence},\n", + " ]\n", + " prompt = tokenizer.apply_chat_template(converted_sample,\n", + " tokenize=False,\n", + " add_generation_prompt=True)\n", + " return prompt" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 742 + }, + "id": "v8ebwqMpQl4l", + "outputId": "7ce67c5b-6785-4789-eec8-f40ac7d24fff" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + "<>:2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + ":2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + " while user_input is not \"q\" or user_input is not \"quit\":\n", + ":2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + " while user_input is not \"q\" or user_input is not \"quit\":\n", + ":2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + " while user_input is not \"q\" or user_input is not \"quit\":\n", + ":2: SyntaxWarning: \"is not\" with a literal. Did you mean \"!=\"?\n", + " while user_input is not \"q\" or user_input is not \"quit\":\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Enter q/quit to stop:\n", + "Enter something to ask doctor:hey\n", + " Hello, Welcome to Chat Doctor, I don't know if for sure this is a boil or a swollen lymph node in response to a wound or infection that you have on the lower limbs. If you have no wound, then this is most likely a swollen\n", + "Enter q/quit to stop:\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "Interrupted by user", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0muser_input\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m\"q\"\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0muser_input\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;34m\"quit\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Enter q/quit to stop:\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0muser_input\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Enter something to ask doctor:\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0muser_input\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"q\"\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0muser_input\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"quit\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Thank you, goodbye.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36mraw_input\u001b[0;34m(self, prompt)\u001b[0m\n\u001b[1;32m 1175\u001b[0m \u001b[0;34m\"raw_input was called, but this frontend does not support input requests.\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1176\u001b[0m )\n\u001b[0;32m-> 1177\u001b[0;31m return self._input_request(\n\u001b[0m\u001b[1;32m 1178\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1179\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parent_ident\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"shell\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/local/lib/python3.11/dist-packages/ipykernel/kernelbase.py\u001b[0m in \u001b[0;36m_input_request\u001b[0;34m(self, prompt, ident, parent, password)\u001b[0m\n\u001b[1;32m 1217\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1218\u001b[0m \u001b[0;31m# re-raise KeyboardInterrupt, to truncate traceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1219\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Interrupted by user\"\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1220\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1221\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Invalid Message:\"\u001b[0m\u001b[0;34m,\u001b[0m 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