iTea vs Agent Lab

iTea is a fast, native client for self-hosted Gitea (and Forgejo) instances. Browse repositories, manage issues and pull requests, and stay on top of notifications — all from your iPhone, iPad, or Mac. FEATURES • Browse repositories, file trees, and commit history • Read, create, and comment on issues • Track and review pull requests • Real-time notifications across every project you watch • Beautiful Markdown rendering for issues, PRs, and comments • Powerful search across repositories, issues, and pull requests • Universal app — one purchase covers iPhone, iPad, and Mac • Native SwiftUI throughout, optimised for each form factor • Secure: your access token lives only in the system Keychain PRIVACY iTea collects no data. There is no iTea-operated backend, no analytics, no third-party SDKs. Every request goes directly from your device to the Gitea (or Forgejo) server you configure. REQUIREMENTS • A self-hosted Gitea or Forgejo instance you have access to • A personal access token with read scopes for repositories, issues, and notifications (plus write scopes if you want to create issues or leave comments) ABOUT GITEA Gitea is a community-driven, open-source Git forge that you can self-host. Forgejo is a Gitea-compatible community fork. Both work seamlessly with iTea. Learn more at gitea.com.

Agent Lab is a learning and experimentation playground for AI agents, built for AI learners, agent developers, and product managers. It doesn't just run agents — it makes every step of an agent's execution visible, so you can finally understand how agents actually work. Unlike an ordinary AI chat app, Agent Lab is about learning, experimenting, debugging, and visualization. On every run you can see the prompts, tool calls, retrieval, tokens, and latency — nothing is hidden. Get started fast · On-device local models: download a small Qwen model on first use (Wi-Fi recommended), then run it fully offline — no API key and no second machine required. Cost is always 0, and tokens and latency are shown for real. · Download on demand: grab other open-source models your device can actually run, with capability gating based on your chip and memory. · Cloud models: works with Chat Completions-compatible APIs (DeepSeek, Moonshot, OpenRouter, and more) and Anthropic Claude — just enter your key, base URL, and model. Three built-in demos · Customer Support Agent — demonstrates tool calling and workflow with a built-in mock order system, no real backend needed. · RAG Knowledge Base — comes with curated reference docs (LangGraph, MCP, LLM APIs, Python) and lets you upload your own PDF / Markdown / TXT, then inspect the retrieved chunks, similarity scores, and final answer. · Research Agent — shows how an agent plans on its own: Planner → Search → Read → Summarize → Answer. Unified visual debugging Every demo offers three views: · Timeline — the full step-by-step sequence of LLM and tool calls · Graph — the workflow graph, highlighting the active node as it runs · Console — expand any step to see System / User / Assistant prompts, the complete LLM request and response JSON, tool requests and responses, tokens, estimated cost, latency, and errors Security and privacy · API keys are stored encrypted on-device via the system Keychain — local only, never uploaded to any server. · Uploaded knowledge-base files and the vector indexes built from them stay on your device and can be deleted anytime. · On-device inference runs fully offline; your data never leaves the device. No sign-up, no login — open it and go. Make every step an agent takes visible.