Chatbot2022
Curated, community-maintained collection of ready-to-use prompts — roles like interviewer, translator, and code reviewer — that copy directly into ChatGPT, Claude, Gemini, or local models. Available as CSV, markdown, and a Hugging Face dataset.
AI Others2022
Provides a searchable, community-curated library of prompts for chat and LLM models, with a browsable site, CSV/Hugging Face dataset, an interactive prompting guide, and self-hosting options. Focused on prompt examples and community contributions for ChatGPT and other LLMs.
Chatbot2022
Connect LLMs to major chat platforms so teams can build, deploy, and operate multi-platform AI chatbots and agents. Provides multi-platform adapters, a plugin marketplace, an MCP server and built-in RAG plus production features like access control, rate limiting and monitoring.
AI Dataset2022
Provides human preference comparison pairs and red-team conversation transcripts collected by Anthropic for training preference/reward models and studying harmful model behaviors; intended for RLHF and safety research, not for supervised fine-tuning of dialogue agents.
Chatbot2022
Connects one LLM agent to 15+ chat platforms — QQ, WeChat Work, Feishu, Telegram, Discord, Slack — from a single self-hosted backend. Routes to OpenAI, Anthropic, Gemini, DeepSeek or Ollama, and adds a WebUI, MCP tools, and a 1000+ plugin marketplace.
AI Dataset2022
Community-curated collection of ChatGPT-style prompts mirrored as a Hugging Face dataset; organized by task and model compatibility for quick reuse. Useful for prompt engineering, text-generation prototyping, and building conversational examples across multiple LLMs.
AI Image2022
Web and desktop/mobile WebUI for generating, editing, captioning and processing images and videos with Stable Diffusion and many diffusion models. Key features include automatic model download, SDNQ on-the-fly quantization for VRAM savings, balanced CPU/GPU offload, multi-backend GPU support, and built-in captioning/tagging/upscaling workflows.
AI Train2022
Reproduces GPT-2 (124M) from scratch on OpenWebText in ~4 days on an 8xA100 node, with the whole stack kept to two ~300-line files: train.py for the loop and model.py for the architecture. A char-level Shakespeare run finishes in ~3 minutes on one GPU.
AI Infra2023
Lets you write compositional Python programs that compile into self‑improving LLM pipelines — replacing brittle prompt engineering with a declarative, programmatic approach and built‑in algorithms to optimize prompts and weights for RAG, multi‑stage pipelines, and agent loops.
AI API2023
Routes one API call across hundreds of LLMs from dozens of providers, with credits, fallbacks, pricing comparison, and data-policy controls for teams that need model choice without wiring every provider separately.
AI Agent2023
Turns documents, web pages and audio into a private, searchable knowledge base and builder for AI assistants and agents — supports wide-format ingestion, multi-model (cloud or local) execution, retrieval-augmented responses, and enterprise deployment features like RBAC and SSO.