https://github.com/rathod-shubham/graphifymind

GraphifyMind transforms PDFs or raw text into interactive Knowledge Graphs using LLMs like GPT-4. It extracts key entities and maps relationships visually with LangChain and Streamlit. Fully Dockerized and customizable with node filtering for focused insights.
https://github.com/rathod-shubham/graphifymind

docker graphs knowledge-graphs langchain llm natural-language-processing neo4j python3 relationships streamlit visualization

Last synced: 3 months ago
JSON representation

Host: GitHub
URL: https://github.com/rathod-shubham/graphifymind
Owner: RATHOD-SHUBHAM
Created: 2025-06-27T13:08:46.000Z (3 months ago)
Default Branch: master
Last Pushed: 2025-06-28T13:00:53.000Z (3 months ago)
Last Synced: 2025-06-28T13:21:10.323Z (3 months ago)
Topics: docker, graphs, knowledge-graphs, langchain, llm, natural-language-processing, neo4j, python3, relationships, streamlit, visualization
Language: Jupyter Notebook
Homepage: https://hub.docker.com/r/gibbo96/knowledgegraph
Size: 196 KB
Stars: 0
Watchers: 0
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# GraphifyMind

**GraphifyMind** is a Streamlit application that transforms plain text or PDF documents into interactive knowledge graphs, powered by Large Language Models (LLMs), graph databases, and AI-driven visualization.

Docker Image: [Link](https://hub.docker.com/r/gibbo96/knowledgegraph)

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## 🚀 Features

- **Text & PDF Input**: Paste text or upload PDF documents for processing.
- **Entity Filtering**: Optionally specify *allowed nodes* (e.g., Person, Place) to focus the graph.
- **Interactive Visualization**: Generates a web-based graph (HTML) showing entities and relationships.
- **Docker Support**: Run the app in a container for easy deployment.

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## 📂 Folder Structure

```
GraphifyMind/
├── graph/ # Generated HTML graphs
├── input/ # Uploaded PDF files
├── src/ # Python source code
│ └── knowledgeGraph.py # Core graph-generation logic
├── icon.jpg # App icon
├── main.py # Streamlit application script
├── requirements.txt # Python dependencies
├── Dockerfile # Container build instructions
└── README.md # This file
```

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## ⚙️ Prerequisites

- **Python 3.10+**
- **OpenAI API Key** (set at runtime via the sidebar)
- **Docker** (optional, for containerized deployment)

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