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update README: add SQL support to file type table and feature description

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2026-05-01 10:16:20 +01:00
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README.md
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@@ -23,7 +23,7 @@
**An AI coding assistant skill.** Type `/graphify` in Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, VS Code Copilot Chat, Aider, OpenClaw, Factory Droid, Trae, Hermes, Kiro, or Google Antigravity - it reads your files, builds a knowledge graph, and gives you back structure you didn't know was there. Understand a codebase faster. Find the "why" behind architectural decisions.
Fully multimodal. Drop in code, PDFs, markdown, screenshots, diagrams, whiteboard photos, images in other languages, or video and audio files - graphify extracts concepts and relationships from all of it and connects them into one graph. Videos are transcribed with Whisper using a domain-aware prompt derived from your corpus. YAML/YML files (Kubernetes, Kustomize, Helm, config) are indexed for semantic extraction. 25 languages supported via tree-sitter AST (Python, JS, TS, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua, Zig, PowerShell, Elixir, Objective-C, Julia, Verilog, SystemVerilog, Vue, Svelte, Dart).
Fully multimodal. Drop in code, PDFs, markdown, screenshots, diagrams, whiteboard photos, images in other languages, or video and audio files - graphify extracts concepts and relationships from all of it and connects them into one graph. Videos are transcribed with Whisper using a domain-aware prompt derived from your corpus. YAML/YML files (Kubernetes, Kustomize, Helm, config) are indexed for semantic extraction. SQL files are AST-extracted deterministically — tables, views, functions, foreign keys, and FROM/JOIN relationships map directly into the graph with no LLM needed. 25 languages supported via tree-sitter AST (Python, JS, TS, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua, Zig, PowerShell, Elixir, Objective-C, Julia, Verilog, SystemVerilog, Vue, Svelte, Dart).
> Andrej Karpathy keeps a `/raw` folder where he drops papers, tweets, screenshots, and notes. graphify is the answer to that problem - 71.5x fewer tokens per query vs reading the raw files, persistent across sessions, honest about what it found vs guessed.
@@ -353,7 +353,7 @@ Works with any mix of file types:
| Type | Extensions | Extraction |
|------|-----------|------------|
| Code | `.py .ts .js .jsx .tsx .mjs .go .rs .java .c .cpp .rb .cs .kt .scala .php .swift .lua .zig .ps1 .ex .exs .m .mm .jl .vue .svelte` | AST via tree-sitter + call-graph (cross-file for all languages) + Java extends/implements + docstring/comment rationale |
| Code | `.py .ts .js .jsx .tsx .mjs .go .rs .java .c .cpp .rb .cs .kt .scala .php .swift .lua .zig .ps1 .ex .exs .m .mm .jl .vue .svelte .sql` | AST via tree-sitter + call-graph (cross-file for all languages) + Java extends/implements + docstring/comment rationale. SQL: tables, views, functions, foreign keys, FROM/JOIN edges (requires `pip install graphifyy[sql]`) |
| Docs | `.md .mdx .html .txt .rst .yaml .yml` | Concepts + relationships + design rationale via Claude |
| Office | `.docx .xlsx` | Converted to markdown then extracted via Claude (requires `pip install graphifyy[office]`) |
| Papers | `.pdf` | Citation mining + concept extraction |