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This project is a tool for transforming unstructured text into semantic knowledge graphs. It uses local language models to extract entities and their relationships, converting text corpora into a structured network of linked concepts. The system provides a web interface for interactive network visualization, allowing users to navigate the resulting nodes and edges. It includes a topology analysis tool that calculates node degrees and identifies community clusters to determine the visual size and color of graph elements. Beyond visualization, the project enables graph-based information retrie
Spark NLP is a toolkit for scalable text analysis and machine learning built on the Apache Spark distributed computing framework. It provides a multimodal machine learning framework and a distributed pipeline system for sequencing annotators to process large-scale linguistic data. The library includes a transformer text processor for generating contextual vector embeddings and a dedicated inference engine for managing large language models. The project distinguishes itself through its ability to process heterogeneous data types, including text, audio, and images, within a unified vision-langu
This repository serves as a comprehensive library of architectural blueprints and code examples for integrating large language models into software applications. It functions as a developer learning resource, providing structured tutorials and implementation patterns that demonstrate how to build intelligent features using advanced prompting and data processing techniques. The collection distinguishes itself by focusing on complex reasoning and data-grounding workflows. It provides practical guidance on implementing retrieval-augmented generation pipelines, which connect language models to pr
Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr
GraphGPT is an LLM knowledge graph generator that extracts entities and relationships from unstructured text to create visual knowledge graphs. It functions as a natural language graph interface and an unstructured data extraction pipeline, transforming raw text into structured triples for mapping complex information networks.
The main features of varunshenoy/graphgpt are: Knowledge Graph Extraction, Data Extraction Pipelines, Entity Extraction Pipelines, Dynamic, Natural Language Query Interfaces, Text-to-Graph Transformers, Information Extraction, State Continuity Injections.
Projects with overlapping indexed features include: rahulnyk/knowledge_graph — This project is a tool for transforming unstructured text into semantic knowledge graphs. It uses local language… johnsnowlabs/spark-nlp — Spark NLP is a toolkit for scalable text analysis and machine learning built on the Apache Spark distributed computing… anthropics/claude-cookbooks — This repository serves as a comprehensive library of architectural blueprints and code examples for integrating large… memgraph/memgraph — Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management.… neo4j-labs/llm-graph-builder — llm-graph-builder is a tool for transforming unstructured data into structured Neo4j graph databases using large… yifanfeng97/hyper-extract — Hyper-Extract is a framework designed for automated knowledge extraction, graph construction, and retrieval-augmented…