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# **GraphRAG**
GraphRAG is a Python-based framework designed to build, manage, and query **Graph Retrieval-Augmented Generation (GraphRAG)** systems. It combines advanced graph processing tools like **Neo4j** and **NetworkX** with natural language capabilities powered by **LLMs (Large Language Models)** to create, visualize, and query knowledge graphs.
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## **Features**
- **Knowledge Graph Construction**: Extract entities and relationships from text and construct a knowledge graph.
- **Graph Management**:
- Store and query graphs in **Neo4j**.
- Perform analysis and operations on **NetworkX** graphs.
- **Graph Summarization**: Analyze and summarize communities within the graph.
- **Natural Language Interaction**: Generate answers to queries using the knowledge graph and language models.
- **Interactive Visualization**: Explore and interact with knowledge graphs using **Gradio**.
- **Modular Design**: A highly organized and reusable codebase for scalable development.
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## **File Structure**
├── graphRAG # Main project directory
├── init.py #Marks the directory as a Python package
├── main.py # Entry point to run the GraphRAG pipeline
├── community_summaries.pkl # Serialized summaries of graph communities
├── entities_extraction.py # Extract entities and relationships from text
├── generating_answers.py # Generate answers to queries using the graph
├── get_communities.py # Identify and analyze graph communities
├── gradio_viz.py # Gradio-based interactive graph visualization
├── graph_builder.py # Build the knowledge graph
├── graph_nx.py # Manage and analyze NetworkX-based graphs
├── KG_classes.py # Defines classes for knowledge graph objects
├── subgraphs.py # Extract and manage subgraphs
├── utils.py # Shared utility functions
├── graph.gpickle # Serialized NetworkX graph file
├── README.md # Project documentation (this file) |