InstaGraph takes text or URLs as input and uses GPT-3.5 to extract entities and their relationships, building a knowledge graph representation. The Flask application renders these graphs visually with color-coded nodes and edges. It optionally supports Neo4j or FalkorDB as graph databases for persistence. The core logic resides in main.py where LLM function calling handles the extraction of structured knowledge from unstructured text.