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Agent Evaluation Dashboard — Full-Stack LLM Observability Tool
Teams running AI agents in production need visibility into how those agents actually perform not just whether they respond, but how accurate, fast, and cost-efficient they are. I built a full-stack observability dashboard to solve exactly that: a single place to track accuracy, latency, API cost, and schema compliance across multiple LLM models and agent types.
What I built
A responsive Next.js (App Router) frontend styled with Tailwind CSS — deep purple sidebar, live accuracy/latency charts (Recharts), filterable eval-run tables, and per-model performance comparisons
A Python FastAPI backend serving the dashboard's data layer, with token-based authentication protecting every route
Full session handling: login, protected pages, automatic redirect for unauthenticated users
A fully responsive layout collapsible drawer sidebar on mobile, reflowing grid on tablet/desktop
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
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