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GraphRAG

بواسطة bCloud LLC

Version 3.1.2 + Free Support on Ubuntu 26.04

Microsoft GraphRAG 3.1.2 is a command-line artificial intelligence solution that converts unstructured text into structured knowledge graphs. It uses graph-based Retrieval-Augmented Generation (RAG) to identify entities, relationships, communities, and important information within documents.

The solution supports document indexing, knowledge-graph creation, community detection, semantic retrieval, and context-aware question answering. It is suitable for research, enterprise knowledge management, document analysis, and AI-powered information retrieval.

Features of Microsoft GraphRAG 3.1.2:

  • Creates structured knowledge graphs from text documents.
  • Identifies entities and relationships within uploaded information.
  • Supports local, global, DRIFT, and basic search methods.
  • Generates community summaries for large datasets.
  • Provides context-aware answers through supported AI models.
  • Supports OpenAI, Azure OpenAI, and compatible model providers.
  • Runs through a command-line interface on Ubuntu.

Usage instructions for Microsoft GraphRAG:
$ sudo su
$ cd /opt/graphrag
$ source .venv/bin/activate
$ cd /opt/graphrag/workspace
$ graphrag index
$ graphrag query --method local --query "Enter your question"

Configuration and API credentials are saved in: /opt/graphrag/workspace/.env

GraphRAG configuration is saved in: /opt/graphrag/workspace/settings.yaml

Access Microsoft GraphRAG:

Connect to the Azure virtual machine using SSH and run GraphRAG commands from the terminal.

Microsoft GraphRAG is a CLI application. It does not provide an official web dashboard and does not require a browser URL or application port.

Disclaimer: Microsoft GraphRAG 3.1.2 is provided “as is” under its applicable open-source license. Users are responsible for configuring supported AI providers, protecting API credentials, monitoring model usage costs, securing input data, and validating generated responses. AI-generated results may contain incomplete or inaccurate information and should be reviewed before production use.

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