AI API2023
Gives developers direct REST access to Claude models for chat, coding, agents, batch jobs, token counting, and structured outputs. It is best for teams that want Anthropic's newest features without routing through a cloud marketplace.
Zirui Guo, Lianghao Xia +3University of Hong Kong, Beijing University of Posts and Telecommunications
A graph-based RAG framework pairing a knowledge graph with vector retrieval and a dual-level (low/high) query mode. New documents merge into the graph via set operations instead of triggering a rebuild, cutting the cost of keeping the index current.
Official tutorial hub teaching how to code effectively with AI agents inside Cursor, from AI foundations to working with agents and reviewing their output. Lessons cover rules, tools, context as working memory, and which tasks agents handle well.
AI API2020
Lets developers build AI features with hosted frontier models for text, code, vision, audio, images, and agents. The platform pairs model APIs with tools, SDKs, safety controls, and enterprise options.
AI API2024
Runnable starter projects for the Claude API you fork and adapt: a knowledge-base customer support agent, a financial analyst that charts results in chat, plus computer-use, browser-use, and autonomous-coding-agent reference implementations.
AI Client2025
Manages provider configs for seven coding CLIs (Claude Code, Codex, Gemini CLI, OpenCode and more) from one desktop app, so switching API endpoints no longer means hand-editing JSON, TOML, or .env files. Adds tray quick-switch and cloud sync.
AI Train2015
Builds and trains deep learning models from one Python API across JAX, TensorFlow, PyTorch, and OpenVINO inference. Its real value is portability: model code, custom layers, and data pipelines can move across backends instead of locking into one stack.
AI API2023
Lets developers call Gemini, Nano Banana, Veo, and other Google AI models from apps through SDKs or REST. It is fastest for teams that want hosted multimodal generation without running model infrastructure.
AI Train2023
Patches Hugging Face Transformers and TRL with hand-written Triton kernels to fine-tune LLMs on a single consumer GPU up to 30x faster with about 90% less memory. Does LoRA, QLoRA, and full fine-tuning across 500+ models, exporting to GGUF and Safetensors.
AI Infra2010
The N-dimensional array (ndarray) underpinning Python's scientific stack — pandas, scikit-learn, and SciPy build directly on it. Vectorized math, broadcasting, and a C/Fortran bridge move numeric work out of Python loops into compiled code.
AI API2012
Provides a collaborative API development platform for designing, testing, documenting, and monitoring APIs — with sharable Collections, mock servers, CLI, and AI-driven features (Agent Mode, AI Agent Builder, MCP Server) to automate API workflows.