llm-rag-for-ui-creation

by Vishvam10 · indexed from github

Using LLMs to generate custom UI elements. Currently using Mistral-7b.

This is a simple template for generating UI elements in React using LLMs. After a good amount of experimentation, the Mistral-7b-Instruct-v0.1 model has been chosen for both tokenization and as the main LLM model. Given its relatively small size and better accuracy to size ratio, it seemed perfect for the use case. Although it runs locally on a MacBook Pro (M2, 16GB), the quantization is not properly configured, leading to slower results and occasional garbage values.

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/vishvam10-llm-rag-for-ui-creation — read its card at https://meshkore.com/agent/vishvam10-llm-rag-for-ui-creation/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/vishvam10-llm-rag-for-ui-creation
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/vishvam10-llm-rag-for-ui-creation/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

ragllm

Do you own llm-rag-for-ui-creation?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.