AI Dataset2023
Provides 52,000 English instruction–response pairs generated by OpenAI's text-davinci-003 for instruction-tuning language models. Released under CC BY-NC 4.0; low-cost synthetic data useful for research but contains model-generated biases and errors.
A multimodal model that accepts image and text inputs and returns text, scoring at human level on professional exams — including a bar exam in the top 10%. Its performance was forecast from models using 1/1000th the compute, showing predictable scaling.
AI Client2023
Self-hosted AI coding assistant you run on your own hardware as an alternative to cloud Copilot. Offers context-aware completion, an in-IDE answer engine and chat, using RAG over your repositories so suggestions match your team's code.
AI API2023
Ensures LLM outputs match precise, schema-defined structures by enforcing Python types, Pydantic models, JSON schemas or grammars at generation time. Provider-agnostic integrations (OpenAI, transformers, vLLM, Ollama, etc.) and function-call style mapping reduce brittle post-processing and make structured generation reliable for production pipelines.
AI Infra2023
Puts OpenAI-, Anthropic- and Ollama-compatible endpoints in front of 60+ inference backends, so existing client code runs unchanged against local models for text, vision, audio, image and embeddings. Runs CPU-only or accelerated, data stays local.
Chatbot2023
Runs open-source LLMs entirely on your own laptop or desktop — no GPU, API key, or cloud required. A cross-platform desktop app with LocalDocs, letting you chat privately over your own files; conversations never leave the machine unless you opt in.
Chatbot2023
Pulls context from your whole codebase via Sourcegraph's search API to power chat, autocomplete, and edits across VS Code, JetBrains, and the CLI. Now ships only inside Sourcegraph Enterprise; the free and Pro tiers are retired.
AI Client2023
Run prompts against OpenAI, Claude, Gemini, and dozens of local or remote models from one terminal command, logging every prompt and response to SQLite. Plugins add new providers, tools, and embeddings; supports schema extraction and function calling.
AI Dataset2023
A 15,000+ English instruction–response corpus for fine-tuning and evaluating LLM instruction-following behavior. Contains human-authored prompts and answers across categories (closed/open QA, summarization, extraction, classification, brainstorming) and is released under CC BY-SA 3.0.
AI Agent2023
Build LLM apps by chaining nodes on a visual canvas — prompts, branching, RAG, agents, tools — and ship the same graph as an API or hosted app. Bundles a plugin marketplace, model routing across hosted and local providers, and built-in observability.
AI Train2023
Streamlines post-training and fine-tuning for large language and multimodal models with a single YAML-driven pipeline. Supports LoRA/QLoRA, full fine-tuning, preference tuning, RL methods, multi-GPU/FSDP/DeepSpeed, and many model backends (Hugging Face, local checkpoints).