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DerwenAI / strwythura

Strwythura: construct an entity-resolved knowledge graph from structured data sources and unstructured content sources, implementing an ontology pipeline, plus context engineering for optimizing AI application outcomes within a specific domain. This produces a Streamlit app, with MLOps instrumentation.

Why this job: says: knowledge graph; topics: vector-database, graphrag

What it does

This tutorial explains how to construct an *entity resolved knowledge graph* from structured data sources and unstructured content sources, implementing an *ontology pipeline*, plus *context engineering* for optimizing AI application outcomes within a specific domain. The process gets enriched by *entity embeddings* and *graph algorithms* used in an enhanced GraphRAG approach, which implements a question/answer chat bot about a particular domain. The material here provides hands-on experience with advanced techniques as well as working code you can use elsewhere.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Inactive
Last commit 7 months ago
Stars
233
On GitHub
Licence
MIT
Allows business use
Downloads for
None listed
No release files
Latest version
v2.1.1
Released 7 months ago
Built with
Python
100% of the code

Is it looked after?

Contributors
Not stated
Last 90 days
Issues
100% closed
0 still open
Pull requests
50 merged
0 waiting
Releases
20
7 in the last year
  • No contributing guide
  • No security policy
  • No code of conduct

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More: languages, topics and project record

Languages

  • Python 100%

Topics

  • textgraphs
  • unstructured-data
  • vector-database
  • entity-linking
  • entity-resolution
  • machine-learning
  • named-entity-recognition
  • semantic-expansion
  • graphrag
  • ontology
  • ontology-pipeline
  • semantic-random-walk

Project record

  • JobRAG and search
  • StatusListed
  • Commits248
  • Forks27
  • Watching7
  • Stars in 28 days0
  • CreatedJul 31, 2024
  • First seen by usNov 7, 2026
  • CheckedNov 8, 2026

Type to search.

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