Discover the Best AI Resources
Curated essentials, no noise — just what matters
AI Client2025
Web and mobile front-end for terminal coding agents — Claude Code, Cursor CLI, Codex, and Gemini-CLI. Drive live sessions from a browser with an integrated shell, file/Git explorers, and a plugin system. Self-host or use the managed Cloud option.
AI Client2025
Browser-based AI development platform that runs tasks inside isolated cloud development environments: natural-language agents read code, run commands, modify files, and integrate results back into Git. Key features include per-task sandboxes, multi-model selection, and an enterprise private-deploy option.
AI Agent2025
Provides a visual, low-code environment to build, debug, and deploy AI agents—integrates model services (OpenAI, Volcengine), RAG, plugins, workflows, and a Chat SDK for embedding agents into apps.
AI Agent2025
Chinese-enhanced fork of TradingAgents that runs multi-agent LLM stock analysis for A-share, HK and US markets, adding domestic models (Qwen, DeepSeek) and local data sources (Tushare, AkShare, BaoStock), with report export to Word and PDF.
AI Agent2025
Terminal coding agent forked from Google's Gemini CLI, retuned for Qwen3-Coder with a custom parser and tool protocol. Runs against OpenAI, Anthropic, Gemini, Qwen or local models, and adds subagents, agent teams, auto-memory and MCP.
AI Client2025
Source code for the GitHub Copilot Chat extension in VS Code: inline chat, an agent mode that plans and edits files autonomously, next-edit suggestions, and MCP integration. Open-sourced so developers can study how Copilot connects to an editor.
Embodied AI2025
Provides a unified Python interface to collect data, train visual/dynamics world models, and evaluate them with model-predictive control across many standardized environments. Includes reference baselines, planning solvers, dataset converters, and LanceDB-backed formats for reproducible experiments. Best suited for researchers benchmarking world-model algorithms.
Teaches agent harness engineering — the permissions, memory, persistence, and coordination layer that lets an LLM act — across 20 progressive lessons, each adding one mechanism with standalone runnable code. Chinese-first, plus English and Japanese.
AI Infra2025
Stores a pruned proximity graph instead of all embeddings, recomputing vectors on demand at query time. A 60M-doc index takes 6GB, not 201GB (97% less), at comparable recall. Powers private local RAG over files, mail, chat, and browser history.
AI Train2025
Forecasts financial candlesticks (OHLCV K-lines) with a decoder-only transformer pre-trained on 12B+ records from 45 exchanges. A tokenizer turns market data into discrete tokens, enabling price/volatility forecasting and synthetic K-line generation.
A template and workflow for feeding AI coding assistants structured context — project rules, code examples, and validation gates — instead of one-off prompts. Centers on Product Requirements Prompts (PRPs) that an agent generates, then executes.
Official, runnable examples for Amazon Bedrock AgentCore, AWS's framework- and model-agnostic platform for deploying AI agents. Spans Runtime, Memory, Gateway, Identity, and Observability through notebooks, code, and infrastructure templates.