How to Use Graphify with Claude or Other AI Models? Step-by-Step Setup Guide Needed

[vedangdhuri]

How to Use Graphify with Claude or Other AI Models? Step-by-Step Setup Guide Needed

Hi everyone,

I’m new to Graphify and currently exploring how to integrate or use it with AI tools like Claude, ChatGPT, Gemini, or any other LLM-based assistants.

I checked the documentation, but I’m still confused about the proper workflow and setup process. I want to understand how people are actually using Graphify together with AI in real projects.

Questions

1. Can Graphify directly connect with AI models like:

   • Claude
   • ChatGPT/OpenAI
   • Gemini
   • Ollama/local models
   • Any other APIs?

2. What is the recommended architecture/workflow?

   • Frontend → Graphify → AI API?
   • Backend middleware?
   • Webhooks?
   • MCP support?
   • Agent-based workflow?

3. How do you securely handle:

   • API keys
   • Authentication
   • Rate limits
   • User sessions

4. Is there any official example project or starter template available?

5. Can someone provide a beginner-friendly setup guide step by step?
   For example:

   • Installation
   • Configuration
   • Connecting AI provider
   • Sending prompts
   • Receiving responses
   • Deployment

---

What I’m Trying to Build

I’m planning to experiment with AI-powered applications and want to understand whether Graphify is suitable for:

• AI dashboards
• Chat systems
• AI workflow automation
• Visualization tools
• Agent systems
• Multi-model AI integrations

---

What Would Help Most

A practical explanation would help more than theory.

Even a simple example like:

“Connect Graphify with Claude API and build a basic AI chat workflow”

would be extremely useful.

If possible, please also share:

• GitHub repos
• Tutorials
• Videos
• Documentation links
• Best practices
• Common mistakes beginners make

Thanks in advance.

[RCNSISAug2026]

I can answer part of this from direct experience — I've just spent three days running Graphify with Claude via a consumer subscription, no API key, on a prose-only corpus (my own exported claude.ai conversation history plus ~100 PDFs). The working setup on Windows:

Install uv: winget install astral-sh.uv (then open a fresh terminal)
Install Graphify: uv tool install graphifyy (note the double-y — that's the official package), then uv tool update-shell and a fresh terminal
Install Claude Code: powershell -c "irm https://claude.ai/install.ps1 | iex" — then run claude once and log in with your Claude subscription account (not the API/Console option)
Extract: graphify extract ./yourfolder --backend claude-cli — this runs headless, no IDE needed, and bills nothing beyond your subscription (est. cost: $0.0000)
Outputs land in yourfolder/graphify-out/: graph.html (interactive visualisation), GRAPH_REPORT.md, and graph.json
Query from the command line: graphify explain "X", graphify query "question", graphify god-nodes --top 20 (add --graph yourfolder/graphify-out/graph.json if running from elsewhere)

Things I learned the hard way: Claude Code and claude.ai chat share the same session usage pool, so big extractions can hit the 5-hour session limit mid-run — the cache resumes cleanly on re-run, so nothing is lost. And very concept-dense documents can hit an output-token ceiling ("truncated at max_completion_tokens" / hollow responses); pre-splitting dense docs into ~8K-character chunks fixed that completely for me. For API-key routes instead, graphify extract --help lists gemini/openai/deepseek/ollama backends including local models via OPENAI_BASE_URL.

I'm writing up a fuller field report of the whole experiment (prose corpus, no code at all — it works well) which I'll post in Show and tell.