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Runtime error
Runtime error
File size: 2,934 Bytes
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{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"from langchain.document_loaders.csv_loader import CSVLoader\n",
"from langchain.docstore.document import Document"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"loader = CSVLoader(file_path='data/llm_test.csv')\n",
"\n",
"csv = loader.load()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "__init__() takes exactly 1 positional argument (3 given)",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m new_document \u001b[39m=\u001b[39m Document(\u001b[39m\"\u001b[39;49m\u001b[39mllm test by lizhen\u001b[39;49m\u001b[39m\"\u001b[39;49m, {\u001b[39m\"\u001b[39;49m\u001b[39ma\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39m\"\u001b[39;49m\u001b[39m1\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mb\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39m\"\u001b[39;49m\u001b[39m2\u001b[39;49m\u001b[39m\"\u001b[39;49m, \u001b[39m\"\u001b[39;49m\u001b[39mc\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39m\"\u001b[39;49m\u001b[39m3\u001b[39;49m\u001b[39m\"\u001b[39;49m})\n\u001b[1;32m 2\u001b[0m csv\u001b[39m.\u001b[39minsert(new_document)\n",
"File \u001b[0;32m~/anaconda3/lib/python3.10/site-packages/pydantic/main.py:332\u001b[0m, in \u001b[0;36mpydantic.main.BaseModel.__init__\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: __init__() takes exactly 1 positional argument (3 given)"
]
}
],
"source": [
"new_document = Document(page_content='\\ufeff日期: 20230312\\nsn: 703052302050002380\\n是否内测用户: 0\\nquery_sentence: 帮我批改这些练习题\\ndomain: 1000726\\ndomain释义: null\\ndomain_support: 1\\nresult_support: 1\\nintent_support: 1\\nquery_intent: 1\\n: ' metadata={'source': 'data/xbxb.csv', 'row': 0})\n",
"csv.insert(new_document)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(data)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.10"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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