LLM Graph Builder - Construct Knowledge Graphs from Unstructured Text (PDF, YouTube, Webpages)

The LLM Graph Builder is a demo application for turning unstructured text into a knowledge graph, it provides a magical text to graph experience.

It uses ML models (LLM, Diffbot) to transform PDFs, web pages, and YouTube videos into a graph of entities and their relationships.

The frontend is a React Application and the backend a Python FastAPI application. It uses the llm-graph-transformer module that we contributed to LangChain.

Functionality Includes

Connect to a Neo4j (Aura) instance
Provide your PDF files, Youtube URLs, Wikipedia Keywords or S3/GCS buckets
Construct Graph with LLM / Diffbot
Visualize Knowledge Graph in App
Chat with your data with GraphRAG
Open Neo4j Bloom for further visual exploration
Use the constructed knowledge graph in your applications

How it works

Uploaded Sources are stored as Document nodes in the graph
Each document (type) is loaded with the LangChain Loaders
The content is split into Chunks
Chunks are stored in the graph and connected to the Document and to each other for advanced RAG patterns
Highly similar Chunks are connected with a SIMILAR relationship to form a kNN Graph
Embeddings are computed and stored in the Chunks and Vector index
Using the llm-graph-transformer or diffbot-graph-transformer entities and relationships are extracted from the text
Entities are stored in the graph and connected to the originating Chunks