LightRAG/examples/test_split_by_character.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "4b5690db12e34685",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:40:58.307102Z",
"start_time": "2025-01-09T03:40:51.935233Z"
}
},
"outputs": [],
"source": [
"import os\n",
"import logging\n",
"import numpy as np\n",
"from lightrag import LightRAG, QueryParam\n",
"from lightrag.llm.openai import openai_complete_if_cache, openai_embed\n",
"from lightrag.utils import EmbeddingFunc\n",
"import nest_asyncio"
]
},
{
"cell_type": "markdown",
"id": "dd17956ec322b361",
"metadata": {},
"source": "#### split by character"
},
{
"cell_type": "code",
"execution_count": 3,
"id": "8c8ee7c061bf9159",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:41:13.961167Z",
"start_time": "2025-01-09T03:41:13.958357Z"
}
},
"outputs": [],
"source": [
"nest_asyncio.apply()\n",
"WORKING_DIR = \"../../llm_rag/paper_db/R000088_test1\"\n",
"logging.basicConfig(format=\"%(levelname)s:%(message)s\", level=logging.INFO)\n",
"if not os.path.exists(WORKING_DIR):\n",
" os.mkdir(WORKING_DIR)\n",
"API = os.environ.get(\"DOUBAO_API_KEY\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a5009d16e0851dca",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:41:16.862036Z",
"start_time": "2025-01-09T03:41:16.859306Z"
}
},
"outputs": [],
"source": [
"async def llm_model_func(\n",
" prompt, system_prompt=None, history_messages=[], keyword_extraction=False, **kwargs\n",
") -> str:\n",
" return await openai_complete_if_cache(\n",
" \"ep-20241218114828-2tlww\",\n",
" prompt,\n",
" system_prompt=system_prompt,\n",
" history_messages=history_messages,\n",
" api_key=API,\n",
" base_url=\"https://ark.cn-beijing.volces.com/api/v3\",\n",
" **kwargs,\n",
" )\n",
"\n",
"\n",
"async def embedding_func(texts: list[str]) -> np.ndarray:\n",
" return await openai_embed(\n",
" texts,\n",
" model=\"ep-20241231173413-pgjmk\",\n",
" api_key=API,\n",
" base_url=\"https://ark.cn-beijing.volces.com/api/v3\",\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "397fcad24ce4d0ed",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:41:24.950307Z",
"start_time": "2025-01-09T03:41:24.940353Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:lightrag:Logger initialized for working directory: ../../llm_rag/paper_db/R000088_test1\n",
"INFO:lightrag:Load KV llm_response_cache with 0 data\n",
"INFO:lightrag:Load KV full_docs with 0 data\n",
"INFO:lightrag:Load KV text_chunks with 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test1/vdb_entities.json'} 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test1/vdb_relationships.json'} 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test1/vdb_chunks.json'} 0 data\n",
"INFO:lightrag:Loaded document status storage with 0 records\n"
]
}
],
"source": [
"rag = LightRAG(\n",
" working_dir=WORKING_DIR,\n",
" llm_model_func=llm_model_func,\n",
" embedding_func=EmbeddingFunc(\n",
" embedding_dim=4096, max_token_size=8192, func=embedding_func\n",
" ),\n",
" chunk_token_size=512,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "1dc3603677f7484d",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:41:37.947456Z",
"start_time": "2025-01-09T03:41:37.941901Z"
}
},
"outputs": [],
"source": [
"with open(\n",
" \"../../llm_rag/example/R000088/auto/R000088_full_txt.md\", \"r\", encoding=\"utf-8\"\n",
") as f:\n",
" content = f.read()\n",
"\n",
"\n",
"async def embedding_func(texts: list[str]) -> np.ndarray:\n",
" return await openai_embed(\n",
" texts,\n",
" model=\"ep-20241231173413-pgjmk\",\n",
" api_key=API,\n",
" base_url=\"https://ark.cn-beijing.volces.com/api/v3\",\n",
" )\n",
"\n",
"\n",
"async def get_embedding_dim():\n",
" test_text = [\"This is a test sentence.\"]\n",
" embedding = await embedding_func(test_text)\n",
" embedding_dim = embedding.shape[1]\n",
" return embedding_dim"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "6844202606acfbe5",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:41:39.608541Z",
"start_time": "2025-01-09T03:41:39.165057Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n"
]
}
],
"source": [
"embedding_dimension = await get_embedding_dim()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d6273839d9681403",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:44:34.295345Z",
"start_time": "2025-01-09T03:41:48.324171Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:lightrag:Processing 1 new unique documents\n",
"Processing batch 1: 0%| | 0/1 [00:00<?, ?it/s]INFO:lightrag:Inserting 35 vectors to chunks\n",
"\n",
"Generating embeddings: 0%| | 0/2 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 50%|█████ | 1/2 [00:00<00:00, 1.36batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 100%|██████████| 2/2 [00:04<00:00, 2.25s/batch]\u001b[A\n",
"\n",
"Extracting entities from chunks: 0%| | 0/35 [00:00<?, ?chunk/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 1 chunks, 1 entities(duplicated), 0 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 3%|▎ | 1/35 [00:04<02:47, 4.93s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 2 chunks, 2 entities(duplicated), 0 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 6%|▌ | 2/35 [00:05<01:18, 2.37s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠸ Processed 3 chunks, 9 entities(duplicated), 5 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 9%|▊ | 3/35 [00:26<05:43, 10.73s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠼ Processed 4 chunks, 16 entities(duplicated), 11 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 11%|█▏ | 4/35 [00:26<03:24, 6.60s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠴ Processed 5 chunks, 24 entities(duplicated), 18 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 14%|█▍ | 5/35 [00:33<03:24, 6.82s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠦ Processed 6 chunks, 35 entities(duplicated), 28 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 17%|█▋ | 6/35 [00:42<03:38, 7.53s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠧ Processed 7 chunks, 47 entities(duplicated), 36 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 20%|██ | 7/35 [00:43<02:28, 5.31s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠇ Processed 8 chunks, 61 entities(duplicated), 49 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 23%|██▎ | 8/35 [00:45<01:52, 4.16s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠏ Processed 9 chunks, 81 entities(duplicated), 49 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠋ Processed 10 chunks, 90 entities(duplicated), 62 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 29%|██▊ | 10/35 [00:46<01:06, 2.64s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 11 chunks, 101 entities(duplicated), 80 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 31%|███▏ | 11/35 [00:52<01:19, 3.31s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 12 chunks, 108 entities(duplicated), 85 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 34%|███▍ | 12/35 [00:54<01:11, 3.12s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠸ Processed 13 chunks, 120 entities(duplicated), 100 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 37%|███▋ | 13/35 [00:59<01:18, 3.55s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠼ Processed 14 chunks, 131 entities(duplicated), 110 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 40%|████ | 14/35 [01:00<00:59, 2.82s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠴ Processed 15 chunks, 143 entities(duplicated), 110 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 43%|████▎ | 15/35 [01:02<00:52, 2.64s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠦ Processed 16 chunks, 162 entities(duplicated), 124 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 46%|████▌ | 16/35 [01:05<00:53, 2.80s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠧ Processed 17 chunks, 174 entities(duplicated), 132 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 49%|████▊ | 17/35 [01:06<00:39, 2.19s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠇ Processed 18 chunks, 185 entities(duplicated), 137 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 51%|█████▏ | 18/35 [01:12<00:53, 3.15s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠏ Processed 19 chunks, 193 entities(duplicated), 149 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 54%|█████▍ | 19/35 [01:18<01:06, 4.14s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠋ Processed 20 chunks, 205 entities(duplicated), 158 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 57%|█████▋ | 20/35 [01:19<00:50, 3.35s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 21 chunks, 220 entities(duplicated), 187 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 60%|██████ | 21/35 [01:27<01:02, 4.47s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 22 chunks, 247 entities(duplicated), 216 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 63%|██████▎ | 22/35 [01:30<00:54, 4.16s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠸ Processed 23 chunks, 260 entities(duplicated), 230 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 66%|██████▌ | 23/35 [01:34<00:48, 4.05s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠼ Processed 24 chunks, 291 entities(duplicated), 253 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 69%|██████▊ | 24/35 [01:38<00:44, 4.03s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠴ Processed 25 chunks, 304 entities(duplicated), 262 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 71%|███████▏ | 25/35 [01:41<00:36, 3.67s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠦ Processed 26 chunks, 313 entities(duplicated), 271 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 74%|███████▍ | 26/35 [01:41<00:24, 2.76s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠧ Processed 27 chunks, 321 entities(duplicated), 283 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 77%|███████▋ | 27/35 [01:47<00:28, 3.52s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠇ Processed 28 chunks, 333 entities(duplicated), 290 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 80%|████████ | 28/35 [01:52<00:28, 4.08s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠏ Processed 29 chunks, 348 entities(duplicated), 307 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 83%|████████▎ | 29/35 [01:59<00:29, 4.88s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠋ Processed 30 chunks, 362 entities(duplicated), 329 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 86%|████████▌ | 30/35 [02:02<00:21, 4.29s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 31 chunks, 373 entities(duplicated), 337 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 89%|████████▊ | 31/35 [02:03<00:13, 3.28s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 32 chunks, 390 entities(duplicated), 369 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 91%|█████████▏| 32/35 [02:03<00:07, 2.55s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠸ Processed 33 chunks, 405 entities(duplicated), 378 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 94%|█████████▍| 33/35 [02:07<00:05, 2.84s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠼ Processed 34 chunks, 435 entities(duplicated), 395 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 97%|█████████▋| 34/35 [02:10<00:02, 2.94s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠴ Processed 35 chunks, 456 entities(duplicated), 440 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 100%|██████████| 35/35 [02:23<00:00, 4.10s/chunk]\u001b[A\n",
"INFO:lightrag:Inserting entities into storage...\n",
"\n",
"Inserting entities: 100%|██████████| 324/324 [00:00<00:00, 17456.96entity/s]\n",
"INFO:lightrag:Inserting relationships into storage...\n",
"\n",
"Inserting relationships: 100%|██████████| 427/427 [00:00<00:00, 29956.31relationship/s]\n",
"INFO:lightrag:Inserting 324 vectors to entities\n",
"\n",
"Generating embeddings: 0%| | 0/11 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 9%|▉ | 1/11 [00:00<00:06, 1.48batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 18%|█▊ | 2/11 [00:02<00:11, 1.25s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 27%|██▋ | 3/11 [00:02<00:06, 1.17batch/s]\u001b[A\n",
"Generating embeddings: 36%|███▋ | 4/11 [00:03<00:04, 1.50batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 45%|████▌ | 5/11 [00:03<00:03, 1.78batch/s]\u001b[A\n",
"Generating embeddings: 55%|█████▍ | 6/11 [00:03<00:02, 2.01batch/s]\u001b[A\n",
"Generating embeddings: 64%|██████▎ | 7/11 [00:04<00:01, 2.19batch/s]\u001b[A\n",
"Generating embeddings: 73%|███████▎ | 8/11 [00:04<00:01, 2.31batch/s]\u001b[A\n",
"Generating embeddings: 82%|████████▏ | 9/11 [00:04<00:00, 2.41batch/s]\u001b[A\n",
"Generating embeddings: 91%|█████████ | 10/11 [00:05<00:00, 2.48batch/s]\u001b[A\n",
"Generating embeddings: 100%|██████████| 11/11 [00:05<00:00, 1.91batch/s]\u001b[A\n",
"INFO:lightrag:Inserting 427 vectors to relationships\n",
"\n",
"Generating embeddings: 0%| | 0/14 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 7%|▋ | 1/14 [00:01<00:14, 1.11s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 14%|█▍ | 2/14 [00:02<00:14, 1.18s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 21%|██▏ | 3/14 [00:02<00:08, 1.23batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 29%|██▊ | 4/14 [00:03<00:06, 1.56batch/s]\u001b[A\n",
"Generating embeddings: 36%|███▌ | 5/14 [00:03<00:04, 1.85batch/s]\u001b[A\n",
"Generating embeddings: 43%|████▎ | 6/14 [00:03<00:03, 2.05batch/s]\u001b[A\n",
"Generating embeddings: 50%|█████ | 7/14 [00:04<00:03, 2.23batch/s]\u001b[A\n",
"Generating embeddings: 57%|█████▋ | 8/14 [00:04<00:02, 2.37batch/s]\u001b[A\n",
"Generating embeddings: 64%|██████▍ | 9/14 [00:04<00:02, 2.46batch/s]\u001b[A\n",
"Generating embeddings: 71%|███████▏ | 10/14 [00:05<00:01, 2.54batch/s]\u001b[A\n",
"Generating embeddings: 79%|███████▊ | 11/14 [00:05<00:01, 2.59batch/s]\u001b[A\n",
"Generating embeddings: 86%|████████▌ | 12/14 [00:06<00:00, 2.64batch/s]\u001b[A\n",
"Generating embeddings: 93%|█████████▎| 13/14 [00:06<00:00, 2.65batch/s]\u001b[A\n",
"Generating embeddings: 100%|██████████| 14/14 [00:06<00:00, 2.05batch/s]\u001b[A\n",
"INFO:lightrag:Writing graph with 333 nodes, 427 edges\n",
"Processing batch 1: 100%|██████████| 1/1 [02:45<00:00, 165.90s/it]\n"
]
}
],
"source": [
"# rag.insert(content)\n",
"rag.insert(content, split_by_character=\"\\n#\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "c4f9ae517151a01d",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:45:11.668987Z",
"start_time": "2025-01-09T03:45:11.664744Z"
}
},
"outputs": [],
"source": [
"prompt1 = \"\"\"你是一名经验丰富的论文分析科学家,你的任务是对一篇英文学术研究论文进行关键信息提取并深入分析。\n",
"请按照以下步骤进行分析:\n",
"1. 该文献主要研究的问题是什么?\n",
"2. 该文献采用什么方法进行分析?\n",
"3. 该文献的主要结论是什么?\n",
"首先在<分析>标签中,针对每个问题详细分析你的思考过程。然后在<回答>标签中给出所有问题的最终答案。\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7a6491385b050095",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:45:40.829111Z",
"start_time": "2025-01-09T03:45:13.530298Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:lightrag:Local query uses 5 entites, 12 relations, 3 text units\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:lightrag:Global query uses 8 entites, 5 relations, 4 text units\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"<分析>\n",
"1. **该文献主要研究的问题是什么?**\n",
" - 思考过程通过浏览论文内容查找作者明确阐述研究目的的部分。文中多处提及“Our study was performed to explore whether folic acid treatment was associated with cancer outcomes and all-cause mortality after extended follow-up”表明作者旨在探究叶酸治疗与癌症结局及全因死亡率之间的关系尤其是在经过长期随访后。\n",
"2. **该文献采用什么方法进行分析?**\n",
" - 思考过程寻找描述研究方法和数据分析过程的段落。文中提到“Survival curves were constructed using the Kaplan-Meier method and differences in survival between groups were analyzed using the log-rank test. Estimates of hazard ratios (HRs) with 95% CIs were obtained by using Cox proportional hazards regression models stratified by trial”可以看出作者使用了Kaplan-Meier法构建生存曲线、log-rank检验分析组间生存差异以及Cox比例风险回归模型估计风险比等方法。\n",
"3. **该文献的主要结论是什么?**\n",
" - 思考过程定位到论文中总结结论的部分如“Conclusion Treatment with folic acid plus vitamin $\\mathsf{B}_{12}$ was associated with increased cancer outcomes and all-cause mortality in patients with ischemic heart disease in Norway, where there is no folic acid fortification of foods”可知作者得出叶酸加维生素$\\mathsf{B}_{12}$治疗与癌症结局和全因死亡率增加有关的结论。\n",
"<回答>\n",
"1. 该文献主要研究的问题是:叶酸治疗与癌症结局及全因死亡率之间的关系,尤其是在经过长期随访后,叶酸治疗是否与癌症结局和全因死亡率相关。\n",
"2. 该文献采用的分析方法包括使用Kaplan-Meier法构建生存曲线、log-rank检验分析组间生存差异、Cox比例风险回归模型估计风险比等。\n",
"3. 该文献的主要结论是:在挪威没有叶酸强化食品的情况下,叶酸加维生素$\\mathsf{B}_{12}$治疗与缺血性心脏病患者的癌症结局和全因死亡率增加有关。\n",
"\n",
"**参考文献**\n",
"- [VD] In2Norwegianhomocysteine-lowering trialsamongpatientswithischemicheart disease, there was a statistically nonsignificantincreaseincancerincidenceinthe groupsassignedtofolicacidtreatment.15,16 Our study was performed to explore whetherfolicacidtreatmentwasassociatedwithcanceroutcomesandall-cause mortality after extended follow-up.\n",
"- [VD] Survivalcurveswereconstructedusing theKaplan-Meiermethodanddifferences insurvivalbetweengroupswereanalyzed usingthelog-ranktest.Estimatesofhazard ratios (HRs) with $95\\%$ CIs were obtainedbyusingCoxproportionalhazards regressionmodelsstratifiedbytrial.\n",
"- [VD] Conclusion Treatment with folic acid plus vitamin $\\mathsf{B}_{12}$ was associated with increased cancer outcomes and all-cause mortality in patients with ischemic heart disease in Norway, where there is no folic acid fortification of foods.\n"
]
}
],
"source": [
"resp = rag.query(prompt1, param=QueryParam(mode=\"mix\", top_k=5))\n",
"print(resp)"
]
},
{
"cell_type": "markdown",
"id": "4e5bfad24cb721a8",
"metadata": {},
"source": "#### split by character only"
},
{
"cell_type": "code",
"execution_count": 11,
"id": "44e2992dc95f8ce0",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:47:40.988796Z",
"start_time": "2025-01-09T03:47:40.982648Z"
}
},
"outputs": [],
"source": [
"WORKING_DIR = \"../../llm_rag/paper_db/R000088_test2\"\n",
"if not os.path.exists(WORKING_DIR):\n",
" os.mkdir(WORKING_DIR)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "62c63385d2d973d5",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:51:39.951329Z",
"start_time": "2025-01-09T03:49:15.218976Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:lightrag:Logger initialized for working directory: ../../llm_rag/paper_db/R000088_test2\n",
"INFO:lightrag:Load KV llm_response_cache with 0 data\n",
"INFO:lightrag:Load KV full_docs with 0 data\n",
"INFO:lightrag:Load KV text_chunks with 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test2/vdb_entities.json'} 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test2/vdb_relationships.json'} 0 data\n",
"INFO:nano-vectordb:Init {'embedding_dim': 4096, 'metric': 'cosine', 'storage_file': '../../llm_rag/paper_db/R000088_test2/vdb_chunks.json'} 0 data\n",
"INFO:lightrag:Loaded document status storage with 0 records\n",
"INFO:lightrag:Processing 1 new unique documents\n",
"Processing batch 1: 0%| | 0/1 [00:00<?, ?it/s]INFO:lightrag:Inserting 12 vectors to chunks\n",
"\n",
"Generating embeddings: 0%| | 0/1 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 100%|██████████| 1/1 [00:02<00:00, 2.95s/batch]\u001b[A\n",
"\n",
"Extracting entities from chunks: 0%| | 0/12 [00:00<?, ?chunk/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 1 chunks, 0 entities(duplicated), 0 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 8%|▊ | 1/12 [00:03<00:43, 3.93s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 2 chunks, 8 entities(duplicated), 8 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 17%|█▋ | 2/12 [00:29<02:44, 16.46s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠸ Processed 3 chunks, 17 entities(duplicated), 15 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 25%|██▌ | 3/12 [00:30<01:25, 9.45s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠼ Processed 4 chunks, 27 entities(duplicated), 22 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 33%|███▎ | 4/12 [00:39<01:16, 9.52s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠴ Processed 5 chunks, 36 entities(duplicated), 33 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 42%|████▏ | 5/12 [00:40<00:43, 6.24s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠦ Processed 6 chunks, 49 entities(duplicated), 42 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 50%|█████ | 6/12 [00:49<00:43, 7.33s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠧ Processed 7 chunks, 62 entities(duplicated), 65 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 58%|█████▊ | 7/12 [01:05<00:50, 10.05s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠇ Processed 8 chunks, 81 entities(duplicated), 90 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 67%|██████▋ | 8/12 [01:23<00:50, 12.69s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠏ Processed 9 chunks, 99 entities(duplicated), 117 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 75%|███████▌ | 9/12 [01:32<00:34, 11.54s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠋ Processed 10 chunks, 123 entities(duplicated), 140 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 83%|████████▎ | 10/12 [01:48<00:25, 12.79s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠙ Processed 11 chunks, 158 entities(duplicated), 174 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 92%|█████████▏| 11/12 [02:03<00:13, 13.50s/chunk]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"⠹ Processed 12 chunks, 194 entities(duplicated), 221 relations(duplicated)\r"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n",
"Extracting entities from chunks: 100%|██████████| 12/12 [02:13<00:00, 11.15s/chunk]\u001b[A\n",
"INFO:lightrag:Inserting entities into storage...\n",
"\n",
"Inserting entities: 100%|██████████| 170/170 [00:00<00:00, 11610.25entity/s]\n",
"INFO:lightrag:Inserting relationships into storage...\n",
"\n",
"Inserting relationships: 100%|██████████| 218/218 [00:00<00:00, 15913.51relationship/s]\n",
"INFO:lightrag:Inserting 170 vectors to entities\n",
"\n",
"Generating embeddings: 0%| | 0/6 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 17%|█▋ | 1/6 [00:01<00:05, 1.10s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 33%|███▎ | 2/6 [00:02<00:04, 1.07s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 50%|█████ | 3/6 [00:02<00:02, 1.33batch/s]\u001b[A\n",
"Generating embeddings: 67%|██████▋ | 4/6 [00:02<00:01, 1.67batch/s]\u001b[A\n",
"Generating embeddings: 83%|████████▎ | 5/6 [00:03<00:00, 1.95batch/s]\u001b[A\n",
"Generating embeddings: 100%|██████████| 6/6 [00:03<00:00, 1.66batch/s]\u001b[A\n",
"INFO:lightrag:Inserting 218 vectors to relationships\n",
"\n",
"Generating embeddings: 0%| | 0/7 [00:00<?, ?batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 14%|█▍ | 1/7 [00:01<00:10, 1.74s/batch]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 29%|██▊ | 2/7 [00:02<00:05, 1.04s/batch]\u001b[A\n",
"Generating embeddings: 43%|████▎ | 3/7 [00:02<00:02, 1.35batch/s]\u001b[A\n",
"Generating embeddings: 57%|█████▋ | 4/7 [00:03<00:01, 1.69batch/s]\u001b[AINFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"\n",
"Generating embeddings: 71%|███████▏ | 5/7 [00:03<00:01, 1.96batch/s]\u001b[A\n",
"Generating embeddings: 86%|████████▌ | 6/7 [00:03<00:00, 2.17batch/s]\u001b[A\n",
"Generating embeddings: 100%|██████████| 7/7 [00:04<00:00, 1.68batch/s]\u001b[A\n",
"INFO:lightrag:Writing graph with 174 nodes, 218 edges\n",
"Processing batch 1: 100%|██████████| 1/1 [02:24<00:00, 144.69s/it]\n"
]
}
],
"source": [
"rag = LightRAG(\n",
" working_dir=WORKING_DIR,\n",
" llm_model_func=llm_model_func,\n",
" embedding_func=EmbeddingFunc(\n",
" embedding_dim=4096, max_token_size=8192, func=embedding_func\n",
" ),\n",
" chunk_token_size=512,\n",
")\n",
"\n",
"# rag.insert(content)\n",
"rag.insert(content, split_by_character=\"\\n#\", split_by_character_only=True)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "3c7aa9836d8d43c7",
"metadata": {
"ExecuteTime": {
"end_time": "2025-01-09T03:52:37.000418Z",
"start_time": "2025-01-09T03:52:09.933584Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:lightrag:Local query uses 5 entites, 3 relations, 2 text units\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/embeddings \"HTTP/1.1 200 OK\"\n",
"INFO:lightrag:Global query uses 9 entites, 5 relations, 4 text units\n",
"INFO:httpx:HTTP Request: POST https://ark.cn-beijing.volces.com/api/v3/chat/completions \"HTTP/1.1 200 OK\"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"<分析>\n",
"- **该文献主要研究的问题是什么?**\n",
" - **思考过程**通过浏览论文的标题、摘要、引言等部分寻找关于研究目的和问题的描述。论文标题为“Cancer Incidence and Mortality After Treatment With Folic Acid and Vitamin B12”摘要中的“Objective”部分明确指出研究目的是“To evaluate effects of treatment with B vitamins on cancer outcomes and all-cause mortality in 2 randomized controlled trials”。因此可以确定该文献主要研究的问题是评估B族维生素治疗对两项随机对照试验中癌症结局和全因死亡率的影响。\n",
"- **该文献采用什么方法进行分析?**\n",
" - **思考过程**在论文的“METHODS”部分详细描述了研究方法。文中提到这是一个对两项随机、双盲、安慰剂对照临床试验Norwegian Vitamin [NORVIT] trial和Western Norway B Vitamin Intervention Trial [WENBIT]数据的联合分析并进行了观察性的试验后随访。具体包括对参与者进行分组干预不同剂量的叶酸、维生素B12、维生素B6或安慰剂收集临床信息和血样分析循环B族维生素、同型半胱氨酸和可替宁等指标并进行基因分型等还涉及到多种统计分析方法如计算预期癌症发生率、构建生存曲线、进行Cox比例风险回归模型分析等。\n",
"- **该文献的主要结论是什么?**\n",
" - **思考过程**在论文的“Results”和“Conclusion”部分寻找主要结论。研究结果表明在治疗期间接受叶酸加维生素B12治疗的参与者血清叶酸浓度显著增加且在后续随访中该组癌症发病率、癌症死亡率和全因死亡率均有所上升主要是肺癌发病率增加而维生素B6治疗未显示出显著影响。结论部分明确指出“Treatment with folic acid plus vitamin $\\mathsf{B}_{12}$ was associated with increased cancer outcomes and all-cause mortality in patients with ischemic heart disease in Norway, where there is no folic acid fortification of foods”。\n",
"</分析>\n",
"\n",
"<回答>\n",
"- **主要研究问题**评估B族维生素治疗对两项随机对照试验中癌症结局和全因死亡率的影响。\n",
"- **研究方法**采用对两项随机、双盲、安慰剂对照临床试验Norwegian Vitamin [NORVIT] trial和Western Norway B Vitamin Intervention Trial [WENBIT])数据的联合分析,并进行观察性的试验后随访,涉及分组干预、多种指标检测以及多种统计分析方法。\n",
"- **主要结论**在挪威食品中未添加叶酸对于缺血性心脏病患者叶酸加维生素B12治疗与癌症结局和全因死亡率的增加有关而维生素B6治疗未显示出显著影响。\n",
"\n",
"**参考文献**\n",
"- [VD] Cancer Incidence and Mortality After Treatment With Folic Acid and Vitamin B12\n",
"- [VD] METHODS Study Design, Participants, and Study Intervention\n",
"- [VD] RESULTS\n",
"- [VD] Conclusion\n",
"- [VD] Objective To evaluate effects of treatment with B vitamins on cancer outcomes and all-cause mortality in 2 randomized controlled trials.\n"
]
}
],
"source": [
"resp = rag.query(prompt1, param=QueryParam(mode=\"mix\", top_k=5))\n",
"print(resp)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7ba6fa79a2550d10",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}