Skip to main content

No project description provided

Project description

Knowledge Graph RAG

Create a graph of interconnected documents and boost performance on RAG

1. Install Knowledge Graph RAG:

pip install knowledge_graph_rag

2. Create a Document Graph:

documents = ["Cardiovascular disease ...",
             "Emerging therapeutic interventions ...",
             "The epidemiological burden ...
             "Cardiovascular disease also ...",
             "Advanced imaging techniques, ...",
             "Role of novel biomarkers ..."
]

documents_graph = DocumentsGraph(documents=documents)
documents_graph.plot()

alt text

3. Find interconnected documents

documents_containing_connected_terminology = documents_graph.find_connected_documents(vectordb_search_result)
documents_containing_connected_terminology
[{'document': 'emerging therapeutic intervention ...'},
 {'document': 'management cardiovascular ...'},
 {'document': 'role novel biomarkers ...'}]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

knowledge_graph_rag-0.0.2.tar.gz (4.8 kB view details)

Uploaded Source

Built Distribution

knowledge_graph_rag-0.0.2-py3-none-any.whl (6.5 kB view details)

Uploaded Python 3

File details

Details for the file knowledge_graph_rag-0.0.2.tar.gz.

File metadata

  • Download URL: knowledge_graph_rag-0.0.2.tar.gz
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.9

File hashes

Hashes for knowledge_graph_rag-0.0.2.tar.gz
Algorithm Hash digest
SHA256 55c816d035d8918931e49daee36054d7a034ddb6f18fea150699664d0251d52e
MD5 7e9f005053982a5aa0274d5836b2dc76
BLAKE2b-256 e898f8dd6becfe36eb4c8291ce319257cbcdbd8353c515ece66eabeca09190f4

See more details on using hashes here.

File details

Details for the file knowledge_graph_rag-0.0.2-py3-none-any.whl.

File metadata

File hashes

Hashes for knowledge_graph_rag-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 8eeb9848286849a56a723cf8623fd40a72dc6a62151d06d8e21be2800ef359de
MD5 6f5af5c542d7d06ce67afa912217ae8a
BLAKE2b-256 43dcbadec991b52992ca3c00896b6fd8e7bd81f6858a2a1a511e809ceb1ca141

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page