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How to Use Graphify with Claude or Other AI Models? Step-by-Step Setup Guide Needed #868
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
-
Can Graphify directly connect with AI models like:
- Claude
- ChatGPT/OpenAI
- Gemini
- Ollama/local models
- Any other APIs?
-
What is the recommended architecture/workflow?
- Frontend → Graphify → AI API?
- Backend middleware?
- Webhooks?
- MCP support?
- Agent-based workflow?
-
How do you securely handle:
- API keys
- Authentication
- Rate limits
- User sessions
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Is there any official example project or starter template available?
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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.
All reactions
Replies: 1 comment
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ドル.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.