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strwythura


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Author: Paco Nathan
Summary: 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.
Latest version: 2.1.1
Required dependencies: accelerate | arrowspace | bs4 | datamodel-code-generator | datasets | datasketch | dspy | gensim | gliner | icecream | jinja2 | lance-namespace | lancedb | litellm | lxml | networkx | nltk | numpy | opik | placekey | polars | psutil | pydantic | pyinstrument | pyshacl | pyvis | rdflib | requests | requests-cache | senzing-grpc | spacy | streamlit | sz-semantics | transformers | validators | w3lib | yfiles-graphs-for-streamlit

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