微软在今年4月份的时候提出了GraphRAG的概念，然后在上周开源了GraphRAG,Github链接见https://github.com/microsoft/graphrag,截止当前，已有6900+Star。

安装教程

官方推荐使用Python3.10-3.12版本，我使用Python3.10版本安装时，在初始化项目过程中会报错，切换到Python3.11版本后运行正常，推测是Python3.10与微软的一些最新的SDK不兼容。所以建议使用Python3.11的环境，安装GraphRAG比较简单，直接下面一行代码即可安装成功。

<code>pip install graphrag

使用教程

在这个教程中，我们使用马伯庸的《太白金星有点烦》这个短篇小说为例，测试下使用微软开源的GraphRAG的处理效果。

注意，GraphRAG是使用LLM来提取文本片段中的实体关系，因此耗费Token数较多，如果是个人调研使用，不建议使用GPT4级别的模型（费用太高，不差钱的大佬请忽略此条建议）。综合成本和效果，我这里使用的是DeepSeek-Chat模型。

初始化项目

我这边先创建了一个临时测试目录myTest，然后按照官方教程，在myTest目录下创建了input目录，并把《太白金星有点烦》这本书的txt版本重命名为book.txt后放到input目录下。然后调用python -m graphrag.index --init 进行初始化工作，生成一些配置文件。

mkdir ./myTest/input

curl https://www.xxx.com/太白金星有点烦.txt > ./myTest/input/book.txt // 这里是示例代码，大家在测试时根据实际情况放入自己要测试的txt文本即可。

cd ./myTest

python -m graphrag.index --init

执行完成后，会在当前目录（即MyTest）目录下生成几个新的文件夹：output-后续执行生成的中间结果会保存到这个目录中；prompts-处理过程中用到的一些Prompt内容；.env-大模型API配置文件，里面默认就一个GRAPHRAG_API_KEY 用于配置大模型的apiKey；settings.yaml-该文件是整体的配置信息，如果我们使用的非OPENAI的官方模型和官方API，我们需要修改此配置文件来让GraphRAG按照我们指定的配置文件执行。

配置相关文件

先在.env文件中配置大模型API的Key，这个配置是全局生效的。我们在.env文件中配置完成后，不需要在settings.yaml文件中重复配置。settings.yaml中使用的默认模型为gpt-4-turbo-preview ，如果不需要修改模型以及调用的API地址，那现在就已经配置完成了，后续的配置内容可以执行忽略并直接到执行阶段。

我这里使用的是agicto 提供的APIkey(主要是新用户注册可以免费获取到10块钱的调用额度，白嫖还是挺爽的)。我在这里主要就修改了API地址和调用模型的名称，修改完成后的settings文件完整内容如下：

encoding_model: cl100k_base

skip_workflows: []

llm:

api_key: ${ GRAPHRAG_API_KEY}

type: openai_chat # or azure_openai_chat

model: deepseek-chat

model_supports_json: false # recommended if this is available for your model.

api_base: https://api.agicto.cn/v1

# max_tokens: 4000

# request_timeout: 180.0

# api_version: 2024-02-15-preview

# organization: <organization_id>

# deployment_name: <azure_model_deployment_name>

# tokens_per_minute: 150_000 # set a leaky bucket throttle

# requests_per_minute: 10_000 # set a leaky bucket throttle

# max_retries: 10

# max_retry_wait: 10.0

# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times

# concurrent_requests: 25 # the number of parallel inflight requests that may be made

parallelization:

stagger: 0.3

# num_threads: 50 # the number of threads to use for parallel processing

async_mode: threaded # or asyncio

embeddings:

## parallelization: override the global parallelization settings for embeddings

async_mode: threaded # or asyncio

llm:

api_key: ${ GRAPHRAG_API_KEY}

type: openai_embedding # or azure_openai_embedding

model: text-embedding-3-small

api_base: https://api.agicto.cn/v1

# api_base: https://<instance>.openai.azure.com

# api_version: 2024-02-15-preview

# organization: <organization_id>

# deployment_name: <azure_model_deployment_name>

# tokens_per_minute: 150_000 # set a leaky bucket throttle

# requests_per_minute: 10_000 # set a leaky bucket throttle

# max_retries: 10

# max_retry_wait: 10.0

# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times

# concurrent_requests: 25 # the number of parallel inflight requests that may be made

# batch_size: 16 # the number of documents to send in a single request

# batch_max_tokens: 8191 # the maximum number of tokens to send in a single request

# target: required # or optional

chunks:

size: 300

overlap: 100

group_by_columns: [id] # by default, we don't allow chunks to cross documents

input:

type: file # or blob

file_type: text # or csv

base_dir: "input"

file_encoding: utf-8

file_pattern: ".*\\.txt$"

cache:

type: file # or blob

base_dir: "cache"

# connection_string: <azure_blob_storage_connection_string>

# container_name: <azure_blob_storage_container_name>

storage:

type: file # or blob

base_dir: "output/${timestamp}/artifacts"

# connection_string: <azure_blob_storage_connection_string>

# container_name: <azure_blob_storage_container_name>

reporting:

type: file # or console, blob

base_dir: "output/${timestamp}/reports"

# connection_string: <azure_blob_storage_connection_string>

# container_name: <azure_blob_storage_container_name>

entity_extraction:

## llm: override the global llm settings for this task

## parallelization: override the global parallelization settings for this task

## async_mode: override the global async_mode settings for this task

prompt: "prompts/entity_extraction.txt"

entity_types: [organization,person,geo,event]

max_gleanings: 0

summarize_descriptions:

## llm: override the global llm settings for this task

## parallelization: override the global parallelization settings for this task

## async_mode: override the global async_mode settings for this task

prompt: "prompts/summarize_descriptions.txt"

max_length: 500

claim_extraction:

## llm: override the global llm settings for this task

## parallelization: override the global parallelization settings for this task

## async_mode: override the global async_mode settings for this task

# enabled: true

prompt: "prompts/claim_extraction.txt"

description: "Any claims or facts that could be relevant to information discovery."

max_gleanings: 0

community_report:

## llm: override the global llm settings for this task

## parallelization: override the global parallelization settings for this task

## async_mode: override the global async_mode settings for this task

prompt: "prompts/community_report.txt"

max_length: 2000

max_input_length: 8000

cluster_graph:

max_cluster_size: 10

embed_graph:

enabled: false # if true, will generate node2vec embeddings for nodes

# num_walks: 10

# walk_length: 40

# window_size: 2

# iterations: 3

# random_seed: 597832

umap:

enabled: false # if true, will generate UMAP embeddings for nodes

snapshots:

graphml: false

raw_entities: false

top_level_nodes: false

local_search:

# text_unit_prop: 0.5

# community_prop: 0.1

# conversation_history_max_turns: 5

# top_k_mapped_entities: 10

# top_k_relationships: 10

# max_tokens: 12000

global_search:

# max_tokens: 12000

# data_max_tokens: 12000

# map_max_tokens: 1000

# reduce_max_tokens: 2000

# concurrency: 32

执行并构建图索引

此流程是GraphRAG的核心流程，即构建基于图的知识库用于后续的问答环节，通过以下代码即可触发执行。

python -m graphrag.index

基于微软在论文中提到的实现思路，执行过程GraphRAG主要实现了如下功能：

Source Documents → Text Chunks：将源文档分割成文本块。Text Chunks → Element Instances：从每个文本块中提取图节点和边的实例。Element Instances → Element Summaries：为每个图元素生成摘要。Element Summaries → Graph Communities：使用社区检测算法将图划分为社区。Graph Communities → Community Summaries：为每个社区生成摘要。Community Summaries → Community Answers → Global Answer：使用社区摘要生成局部答案，然后汇总这些局部答案以生成全局答案。

整体执行耗时与具体的文本大小有关。我这个例子整体耗时大概20分钟，耗费人民币大约4块钱。执行过程中的输出如下：

🚀 Reading settings from settings.yaml

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

🚀 create_base_text_units

id chunk ... document_ids n_tokens

0 5fe95645e8592dc5146ae4e6e2343ad4 \n附：每天更新最新最全的小说：飞马书屋(FEIＭASＷ.COM)\n\n《太白金星有点烦》... ... [764c0e80c3fc53191ccd9e87ad9e4803]

300

1 e91ee08e3684833d1dd3cb26679a8e6a 歪斜斜落在殿旁台阶上。\n李长庚从鹤背上跳下来，猫腰检查了一下。台阶倒没什么事，只是仙鹤的右... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

2 7eea0da373e721b9f87ad6c7c05565de 同期飞升的神仙早换成了更威风的神兽坐骑，只有李长庚念旧，一直骑着这头老鹤四处奔波。\n李长庚... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

3 d0fbd3139f977d98891f5aeae2ac9180 形了。\n“您回来啦？” 织女头也没抬，专心看着宝鉴。\n“嗯！回来了。”\n李长庚端起童子... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

4 ab349a2200a3878ba2a340c71ba1641f 来泡，平白被自己的牛饮糟蹋了。\n李长庚嘬了嘬牙花子，悻悻坐下，把一沓玉简文书从怀里取出来。... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

.. ... ... ... ... ...

214 7f8d6ded30cb1488837df6102c77cab4 旅游。编辑说，买ps5也不能报哦。我说鹓雏非梧桐不止，非练实不食，非醴泉不饮，会看得上你这点... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

215 73b2cf432f11036b715a7ced295a6091 《两京十五日》之后，我也是写了个短篇《长安的荔枝》休息，权当运动之后的拉伸。\n最初我并没打... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

216 1a10c703e1637de884a1fad7f109a50b 头一看，好嘛，居然有十万字。\n也好，尽兴了，疲惫一扫而空，这波不亏。\n有朋友问我，你是不... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 300

217 239fe13a155eb285cebc6938559cf0e9 味，也不合心意。\n当然，这种乘兴而写的东西，神在意前，一气呵成，固然写得舒畅，细节不免粗糙... ...

[764c0e80c3fc53191ccd9e87ad9e4803] 214

218 b9fb2d6193b2840cdce5a3cf25542ca7 凑个整，不然心里难受。\n\n ... [764c0e80c3fc53191ccd9e87ad9e4803] 14

[877 rows x 5 columns]

🚀 create_base_extracted_entities

entity_graph

0 <graphml xmlns="http://graphml.graphdrawing.or...

🚀 create_summarized_entities

entity_graph

0 <graphml xmlns="http://graphml.graphdrawing.or...code>

🚀 create_base_entity_graph

level clustered_graph

0 0 <graphml xmlns="http://graphml.graphdrawing.or...

1 1 <graphml xmlns="http://graphml.graphdrawing.or...code>

2 2 <graphml xmlns="http://graphml.graphdrawing.or...

3 3 <graphml xmlns="http://graphml.graphdrawing.or...code>

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

🚀 create_final_entities

id name ... text_unit_ids description_embedding

0 b45241d70f0e43fca764df95b2b81f77 "飞马书屋" ... [159e9102707eeaef1f9188407e428111, 45e28cf587e... [0.008881675079464912, 0.012866131030023098, -...

1 4119fd06010c494caa07f439b333f4c5 "马伯庸" ... [5fe95645e8592dc5146ae4e6e2343ad4] [0.03241756930947304, 0.03757039085030556, -0....

2 d3835bf3dda84ead99deadbeac5d0d7d "太白金星李长庚" ... [5fe95645e8592dc5146ae4e6e2343ad4] [0.002768812933936715, 0.020227784290909767,

-...

3 077d2820ae1845bcbb1803379a3d1eae "启明殿" ... [02c57ca370b4c0316a20148d00723bac, 046ed708031... [0.01269223727285862, 0.026068691164255142, 0....

4 3671ea0dd4e84c1a9b02c5ab2c8f4bac "《太白金星有点烦》" ... [5fe95645e8592dc5146ae4e6e2343ad4, 7f8d6ded30c... [0.003794945077970624, 0.016000036150217056,

-...

.. ... ... ... ... ...

207 7ea0bc1467e84184842de2d5e5bdd78e "《长安的荔枝》" ... [7f8d6ded30cb1488837df6102c77cab4] [0.012446477077901363, 0.005391148384660482,

0...

208 056f23eb710f471393ae5dc417d83fd9 "两京十五日" ... [73b2cf432f11036b715a7ced295a6091] [0.021373916417360306, -0.0032437569461762905,...

209 e1ae27016d63447a8dfa021370cba0fa "长安的荔枝" ... [73b2cf432f11036b715a7ced295a6091] [0.022816641256213188, -0.0042687226086854935,...

210 f8c10f61a8f344cea7bdafa2d8af14b8 "新书" ... [239fe13a155eb285cebc6938559cf0e9] [0.05925222113728523, 0.02118016593158245, -0....

211 aa7d003f25624e19bc88d3951d4dc943 "读者" ... [239fe13a155eb285cebc6938559cf0e9] [0.0453583225607872, 0.020338334143161774, -0....

[851 rows x 8 columns]

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/datashaper/engine/verbs/convert.py:72: FutureWarning: errors='ignore' is deprecated and code>

will raise in a future version. Use to_datetime without passing `errors` and catch exceptions explicitly instead

datetime_column = pd.to_datetime(column, errors="ignore")code>

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/datashaper/engine/verbs/convert.py:72: UserWarning: Could not infer format, so each

element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.

datetime_column = pd.to_datetime(column, errors="ignore")code>

🚀 create_final_nodes

level title type description ... graph_embedding top_level_node_id x y

0 0 "飞马书屋" "ORGANIZATION" 飞马书屋是一个多功能的在线阅读平台，其域名为FEIMASW.COM。作为一个组织，飞马书屋不... ... None

b45241d70f0e43fca764df95b2b81f77 0 0

1 0 "马伯庸" "PERSON" "马伯庸是一位小说作者，著有《太白金星有点烦》。" ... None

4119fd06010c494caa07f439b333f4c5 0 0

2 0 "太白金星李长庚" "PERSON" "太白金星李长庚是小说《太白金星有点烦》中的主要角色，最近感到烦恼。" ... None

d3835bf3dda84ead99deadbeac5d0d7d 0 0

3 0 "启明殿" "GEO" 启明府是位于仙界的一个重要组织，与三官府、二十八星宿相当，显示了其在仙界中的地位。李长庚在此... ... None

077d2820ae1845bcbb1803379a3d1eae 0 0

4 0 "《太白金星有点烦》" "EVENT" 《太白金星有点烦》是由马伯庸所著的一部小说，讲述了太白金星李长庚的故事。这部作品是作者创作的... ...

None 3671ea0dd4e84c1a9b02c5ab2c8f4bac 0 0

... ... ... ... ... ... ... ... .. ..

3399 3 "《长安的荔枝》" "EVENT" "作者在完成《两京十五日》后创作的短篇作品，作为休息和拉伸。" ... None

7ea0bc1467e84184842de2d5e5bdd78e 0 0

3400 3 "两京十五日" "EVENT" "《两京十五日》是一个文学作品，作者在此之后创作了另一个短篇《长安的荔枝》。" ... None

056f23eb710f471393ae5dc417d83fd9 0 0

3401 3 "长安的荔枝" "EVENT" "《长安的荔枝》是作者在创作《两京十五日》后写的一个短篇，作为休息和创作的延续。" ... None

e1ae27016d63447a8dfa021370cba0fa 0 0

3402 3 "新书" "EVENT" "新书发布是一个即将发生的事件，作者希望得到读者的支持和关注。" ... None

f8c10f61a8f344cea7bdafa2d8af14b8 0 0

3403 3 "读者" ... None aa7d003f25624e19bc88d3951d4dc943 0 0

[3404 rows x 14 columns]

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

🚀 create_final_communities

id title level raw_community relationship_ids text_unit_ids

0 0 Community 0 0 0 [1c97184ce5ea4049be417a3fd125357b, 13a044c4043... [159e9102707eeaef1f9188407e428111,45e28cf587e6...

1 2 Community 2 0 2 [8d9ded5fc9cf4c4faba8c6c8cd50e2f4, 595a841aa60... [02c57ca370b4c0316a20148d00723bac,046ed708031c...

2 4 Community 4 0 4 [5a224002ecbc4725abeb5a424aaca6a6, 8826a17bbda... [d0fbd3139f977d98891f5aeae2ac9180, 27248272776...

3 3 Community 3 0 3 [ea465e5cd92247829f52ff0c8591d1bb, 2dbac25b512... [003906d4aeb4b30451d6b15477f474cf,00aa40cc8961...

4 6 Community 6 0 6 [40c2425cb1c34c1591f7cb89f9f5e0bf, 7cf59650687... [0c08b05560ec3763c4eef3215d9de406,1bf7f3f6d2d8...

.. ... ... ... ... ... ...

167 171 Community 171 3 171 [cc08fc303cdc4177ad77e6e7d3d15cfd, 318a9d64ba7... [0110b1a44d2939f061fabdca3c0c822a,050f809899ba...

168 169 Community 169 3 169 [22dc64e73efe47c1be1be0552c3e935a, 0a983d6c050... [13318cc421ba835d8ee409100f7e3c43,4c0646412c3c...

169 166 Community 166 3 166 [2edf3e83c1c64da393d5206ce5b352a3, 58ff8f61ba2... [1a10c703e1637de884a1fad7f109a50b,d25d9589f7d4...

170 168 Community 168 3 168 [6104e6eabe444d6195ec6efc79a2d618, f7bdce302b5... [06047f1634e84ec122354736d0da0512,2cd2d62cc35c...

171 170 Community 170 3 170 [1268f164ec404b48a520fe672bca0f16, 2456d7a68d0... [4502bb159a6b1ae4429141760179b1f3,4a14da17885b...

[172 rows x 6 columns]

🚀 join_text_units_to_entity_ids

text_unit_ids entity_ids id

0 159e9102707eeaef1f9188407e428111 [b45241d70f0e43fca764df95b2b81f77, 19a7f254a5d... 159e9102707eeaef1f9188407e428111

1 45e28cf587e6d50704fd6ed866278782 [b45241d70f0e43fca764df95b2b81f77, 077d2820ae1... 45e28cf587e6d50704fd6ed866278782

2 4b8b97e111eb9dc6d262c5ec7eb60801 [b45241d70f0e43fca764df95b2b81f77, 19a7f254a5d... 4b8b97e111eb9dc6d262c5ec7eb60801

3 5fe95645e8592dc5146ae4e6e2343ad4 [b45241d70f0e43fca764df95b2b81f77, 4119fd06010... 5fe95645e8592dc5146ae4e6e2343ad4

4 6fe888799b2e26cd911859f9c31f85d6 [b45241d70f0e43fca764df95b2b81f77, 19a7f254a5d... 6fe888799b2e26cd911859f9c31f85d6

.. ... ... ...

871 73b2cf432f11036b715a7ced295a6091 [47f6d6573cf34e1096c95e36251dd60c, 056f23eb710... 73b2cf432f11036b715a7ced295a6091

872 da06f0769e85e52a06407bdf7dec4c2c [3f3a2d7aa1294116814f0b4d89baa23d, bbdd53a15e9... da06f0769e85e52a06407bdf7dec4c2c

873 239fe13a155eb285cebc6938559cf0e9 [5d398b88ee4242a59c32feb188683ec3, f8c10f61a8f... 239fe13a155eb285cebc6938559cf0e9

874 7837d3a4069066d3a313a050c5401a77 [bbdd53a15e99452a9deff05d1de2d965, d2ed972353a... 7837d3a4069066d3a313a050c5401a77

875 27b95fa0e9192d3c4088bbdd1d820b5c [9532cf83e9324ea0a46e5ac89bac407d, 8919fa72a9e... 27b95fa0e9192d3c4088bbdd1d820b5c

[876 rows x 3 columns]

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/numpy/core/fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will

be removed in a future version. Please use 'DataFrame.transpose' instead.

return bound(*args, **kwds)

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/datashaper/engine/verbs/convert.py:65: FutureWarning: errors='ignore' is deprecated and code>

will raise in a future version. Use to_numeric without passing `errors` and catch exceptions explicitly instead

column_numeric = cast(pd.Series, pd.to_numeric(column, errors="ignore"))code>

🚀 create_final_relationships

source target weight description ... human_readable_id source_degree target_degree rank

0 "飞马书屋" "《太白金星有点烦》" 1.0 "飞马书屋提供《太白金星有点烦》这部小说的最新最全版本。" ... 0

4 4 8

1 "飞马书屋" "李长庚" 4.0 李长庚是飞马书屋小说中的角色，显示他与这个组织有文学上的联系。李长庚的对话内容被记录在飞马书... ...

1 4 323 327

2 "飞马书屋" "小说更新" 1.0 "飞马书屋提供每天最新最全的小说更新服务。" ... 2 4

1 5

3 "飞马书屋" "最好看的小说" 1.0 "飞马书屋提供最好看的小说，满足读者的阅读需求。" ... 3 4

1 5

4 "马伯庸" "《太白金星有点烦》" 1.0 "马伯庸是《太白金星有点烦》这部小说的作者。" ... 4 1

4 5

... ... ... ... ... ... ... ... ... ...

1891 "编辑" "出版社" 1.0 "编辑在出版社工作，负责处理作者的稿件。" ... 1891 3 1

4

1892 "编辑" "我" 1.0 "作者与编辑之间存在关于创作内容和休息方式的交流和分歧。" ... 1892 3

3 6

1893 "我" "《长安的荔枝》" 1.0 "作者在完成《两京十五日》后创作了《长安的荔枝》作为休息。" ... 1893 3

2 5

1894 "《两京十五日》" "《长安的荔枝》" 1.0 "《长安的荔枝》是作者在《两京十五日》之后创作的短篇作品，作为休息。" ... 1894

1 2 3

1895 "新书" "读者" 1.0 "新书发布时，作者希望得到读者的支持和捧场，这是一种期待和互动的关系。" ... 1895 2

1 3

[1896 rows x 10 columns]

🚀 join_text_units_to_relationship_ids

id relationship_ids

0 5fe95645e8592dc5146ae4e6e2343ad4 [1c97184ce5ea4049be417a3fd125357b, ae0d3104647...

1 45e28cf587e6d50704fd6ed866278782 [13a044c404394c34af1e9b07c48aa985, 8d9ded5fc9c...

2 4b8b97e111eb9dc6d262c5ec7eb60801 [13a044c404394c34af1e9b07c48aa985, a9b900821b8...

3 a55a87d948656692651bffe4d3aa5f82 [13a044c404394c34af1e9b07c48aa985, 8d9ded5fc9c...

4 e080b0c08ed32f44c6adc344b9771781 [13a044c404394c34af1e9b07c48aa985, f8402b10349...

.. ... ...

871 613f893eee700fad17498654df3182c0 [58126221b0894f01bae564e2608b754d, 69b67d3b170...

872 239fe13a155eb285cebc6938559cf0e9 [fc757d03e1814784a3a213d87ea36e23, 21bd7045ca9...

873 b0c5905978e8e25106a43ca347427229 [9636a7d02e614d00ac8602bd65da987b, 1a315dfbb60...

874 7837d3a4069066d3a313a050c5401a77 [3fa936635320477cbb990905f5db11d6, 616436c3a00...

875 27b95fa0e9192d3c4088bbdd1d820b5c [c86a30f7f1fe4a01807dd66719394ec3, 392721fc26e...

[876 rows x 2 columns]

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/graphrag/index/graph/extractors/community_reports/prep_community_report_context.py:57:

SettingWithCopyWarning:

A value is trying to be set on a copy of a slice from a DataFrame.

Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

invalid_context_df[schemas.CONTEXT_STRING] = _sort_and_trim_context(

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/graphrag/index/graph/extractors/community_reports/utils.py:16: SettingWithCopyWarning:

A value is trying to be set on a copy of a slice from a DataFrame.

Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

df[schemas.CONTEXT_SIZE] = df[schemas.CONTEXT_STRING].apply(lambda x: num_tokens(x))

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/graphrag/index/graph/extractors/community_reports/prep_community_report_context.py:61:

SettingWithCopyWarning:

A value is trying to be set on a copy of a slice from a DataFrame.

Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

invalid_context_df[schemas.CONTEXT_EXCEED_FLAG] = 0

🚀 create_final_community_reports

community full_content ... full_content_json id

0 164 # 天廷与神话组织\n\n天廷是一个神话中的组织，负责管理仙界事务和财务，与多个神话人物和地... ... {\n "title": "\u5929\u5ef7\u4e0e\u795e\u8bd...

7d7397c8-e65a-40ca-8f5e-c8ee95ec9bb0

1 166 # 宝象国与八十一难\n\n宝象国是一个地理位置，涉及多个重要事件和人物，包括玄奘、李长庚、... ... {\n "title": "\u5b9d\u8c61\u56fd\u4e0e\u516...

d9067bdd-b669-4ce7-b2e8-de33e6487bcf

2 168 # 阿傩与黄风怪的复杂关系\n\n该社区围绕阿傩和黄风怪展开，涉及多个角色和组织，如正途弟子... ... {\n "title": "\u963f\u50a9\u4e0e\u9ec4\u98c...

7288eb84-717e-46aa-8ccf-90432682a374

3 169 # 三星洞与石猴社区\n\n该社区以三星洞为核心组织，涉及多个关键实体如石猴、六耳、冒名顶替... ... {\n "title": "\u4e09\u661f\u6d1e\u4e0e\u77f...

4db3be55-ad2a-4e7e-a311-29d4743a71be

4 170 # 通臂与三星洞社区\n\n该社区围绕通臂展开，涉及多个关键实体如三星洞都管、孙悟空、六耳等... ... {\n "title": "\u901a\u81c2\u4e0e\u4e09\u661...

d993b5ec-6ec2-4d66-859d-512ca93bf01c

.. ... ... ... ... ...

148 3 # 两界山与取经之旅\n\n该社区以两界山和取经之旅为核心，涉及多个关键实体如玄奘、阿傩长老... ... {\n "title": "\u4e24\u754c\u5c71\u4e0e\u53d...

d78001e2-5247-4bf9-b2af-fd2cbb109bf4

149 4 # 天庭与神话组织社区\n\n该社区以天庭为核心，涉及多个神话组织和人物，如释门、广目天王、... ... {\n "title": "\u5929\u5ead\u4e0e\u795e\u8bd...

085b720d-4f87-43a4-8a29-4a9da687789e

150 6 # 西王母与天庭关系网络\n\n该社区以西王母为核心，涉及天庭、卷帘大将、李长庚等多个关键实... ... {\n "title": "\u897f\u738b\u6bcd\u4e0e\u592...

72ae5d47-5b05-43d1-a60a-de2f92557b56

151 8 # 文殊与普贤的佛教神祇社区\n\n该社区以文殊和普贤两位佛教菩萨为核心，围绕他们的活动和互... ... {\n "title": "\u6587\u6b8a\u4e0e\u666e\u8d2...

cb782e19-0886-4bf9-93b7-bf864adfa2f3

152 9 # 护法渡劫与师徒四人\n\n该社区围绕‘护法渡劫’事件展开，涉及‘师徒四人’、‘菩萨’等关... ... {\n "title": "\u62a4\u6cd5\u6e21\u52ab\u4e0...

52ddd79d-cfa7-43d1-a070-5598db14461d

[153 rows x 10 columns]

🚀 create_final_text_units

id ... relationship_ids

0 5fe95645e8592dc5146ae4e6e2343ad4 ... [1c97184ce5ea4049be417a3fd125357b, ae0d3104647...

1 e91ee08e3684833d1dd3cb26679a8e6a ... [26c926c6016d4639b05427f01ba629f5, 8f6872eeb81...

2 7eea0da373e721b9f87ad6c7c05565de ... [8d9ded5fc9cf4c4faba8c6c8cd50e2f4, 595a841aa60...

3 d0fbd3139f977d98891f5aeae2ac9180 ... [ac80a99fda2b488285d29596dd4d1471, 67d6a3481e4...

4 ab349a2200a3878ba2a340c71ba1641f ... [904cd052ec194654bb72f4027e43daa3, 7e88fd2e835...

.. ... ... ...

872 7f8d6ded30cb1488837df6102c77cab4 ... [6bb9bed2e39c4e31a81f12479af3d16c, 7dbca0fef7d...

873 73b2cf432f11036b715a7ced295a6091 ... [2f13e93b77b84d5994605e27c17c3244, 20574c1c47c...

874 1a10c703e1637de884a1fad7f109a50b ... [e65667ec99e145fea2055d6b583cb05b, 2edf3e83c1c...

875 239fe13a155eb285cebc6938559cf0e9 ... [fc757d03e1814784a3a213d87ea36e23, 21bd7045ca9...

876 b9fb2d6193b2840cdce5a3cf25542ca7 ... None

[877 rows x 6 columns]

/home/xinfeng/miniconda3/envs/graphrag-new/lib/python3.11/site-packages/datashaper/engine/verbs/convert.py:72: FutureWarning: errors='ignore' is deprecated and code>

will raise in a future version. Use to_datetime without passing `errors` and catch exceptions explicitly instead

datetime_column = pd.to_datetime(column, errors="ignore")code>

🚀 create_base_documents

id text_units raw_content title

0 764c0e80c3fc53191ccd9e87ad9e4803 [5fe95645e8592dc5146ae4e6e2343ad4, e91ee08e368...

\n附：每天更新最新最全的小说：飞马书屋(FEIＭASＷ.COM)\n\n《太白金星有点烦》... book.txt

🚀 create_final_documents

id text_unit_ids raw_content title

0 764c0e80c3fc53191ccd9e87ad9e4803 [5fe95645e8592dc5146ae4e6e2343ad4, e91ee08e368...

\n附：每天更新最新最全的小说：飞马书屋(FEIＭASＷ.COM)\n\n《太白金星有点烦》... book.txt

⠋ GraphRAG Indexer

├── Loading Input (InputFileType.text) - 1 files loaded (0 filtered) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 0:00:00

├── create_base_text_units

├── create_base_extracted_entities

├── create_summarized_entities

├── create_base_entity_graph

├── create_final_entities

├── create_final_nodes

├── create_final_communities

├── join_text_units_to_entity_ids

├── create_final_relationships

├── join_text_units_to_relationship_ids

├── create_final_community_reports

├── create_final_text_units

├── create_base_documents

└── create_final_documents

🚀 All workflows completed successfully.

基于构建的知识库进行提问