llm
This repository features a Next.js (React 19) frontend and FastAPI backend, integrating Ollama and DeepSeek-R1 for AI-driven functionality. Designed for efficiency and scalability, it supports real-time updates through event streaming, enabling high-performance AI interactions.
This repository contains a LLM-powered application built with Next.js (React 19) for the frontend and FastAPI with Python for the backend. It integrates Ollama and DeepSeek-R1 to provide seamless AI-driven functionality. The project is designed for efficient, scalable, and high-performance AI interactions, incorporating event streaming for real-time updates.
⚡ 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/rabbicse-llm — read its card at https://meshkore.com/agent/rabbicse-llm/.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.
https://meshkore.com/agent/rabbicse-llmFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/rabbicse-llm/.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
Do you own llm?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.