AI Client2023
Self-hosted browser chat interface for interacting with local or remote LLMs. Supports multiple backends (Ollama, OpenAI-compatible endpoints, llama.cpp), RAG/document chat, plugins/actions, and Docker-based deployment — aimed at teams that need private, customizable LLM UIs.
AI Agent2023
Builds stateful LLM agents whose memory persists across sessions: a tiered, self-editing memory system lets an agent rewrite its own context window so it remembers, learns, and improves over time. Model-agnostic, with Python/TypeScript SDKs.
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AI Client2023
Brings ChatGPT, Claude, Gemini, Perplexity, DeepSeek, Grok and other AI chat services into one desktop app, each in its own isolated session and window. Adds prompt management, multi-window layouts, a built-in terminal, and local-first history.
AI Dataset2023
Benchmark for evaluating general AI assistants with 466 short, real-world questions that require tool use, multimodality and reasoning; provides a public dev set and a withheld test set used for leaderboard evaluation.
AI Dataset2023
Provides a 200k-example filtered conversational dataset derived from UltraChat for supervised fine‑tuning and generation‑ranking of chat models. Stored in parquet with four splits and used as part of Zephyr‑7B‑β training data.
AI Agent2023
Routes LLM and agent decisions through semantic similarity instead of waiting for full generations, useful for intent routing, tool selection, guardrails, and multimodal handling.
AI Client2023
Hands-free voice-first companion with a Live2D avatar for real-time conversations with LLMs. Cross-platform web and desktop clients, runs locally or via cloud APIs, supports local ASR/TTS and modular customization for personas and models.
AI Train2023
Collection of runnable model implementations — LLaMA, Mistral, Stable Diffusion, Whisper, CLIP, plus LoRA fine-tuning — ported to the MLX array framework so they run natively on Apple silicon's unified memory rather than CUDA.
AI Infra2023
A selective State Space Model architecture and PyTorch implementation for linear-time sequence modeling. Hardware-aware, designed for information-dense tasks (e.g. language modeling), with pretrained weights on Hugging Face; requires CUDA-enabled PyTorch.
AI Leaderboard2023
Runs one-command evaluation of vision-language models across 80+ multimodal benchmarks, handling data download, inference, and metric scoring in a single pass. Supports 220+ LMMs; adding a new model means writing one generate_inner() function.
AI Agent2023
Builds realtime voice AI agents that run as server-side participants in WebRTC rooms — mix STT, LLM, and TTS providers or use one realtime model. Adds semantic turn detection, SIP telephony, multi-agent handoffs, and an LLM-judge test harness.