Runs named-entity recognition, text classification, structured-JSON parsing and relation extraction from one 205M-parameter encoder in a single CPU forward pass, using schemas with per-field regex validators. A larger 1B model is available via API.
Extracts structured data from unstructured text with LLMs, mapping every extraction to its exact character span in the source for visual review. Uses few-shot examples, schema enforcement, and multi-pass chunking to handle long documents.
Runs a six-month live experiment where ChatGPT manages a real-money micro-cap portfolio from $100, trading under strict rules with automated stop-losses. Each trade's rationale is logged; returns are benchmarked against the S&P 500 and Russell 2000.
Bundles Langflow, Docling, and OpenSearch into one installable package so you can ingest messy documents, run agentic retrieval with re-ranking, and chat over your own knowledge base. Ships Python/TS SDKs and a built-in MCP server at /mcp.
An agentic framework that analyzes, plans, and executes multi-step video understanding and editing workflows using multimodal LLM-driven agents—features intent decomposition, graph-based workflow orchestration, and automated shot planning for long-form video tasks.
Detects, segments, and tracks every instance of an open-vocabulary concept in images and video from a text phrase or visual exemplar, not just one object per prompt. An 848M-param model reaching ~75-80% of human accuracy across 270K concepts.
Unifies agentic tasks, reasoning, and coding in a single MoE model with 355B total / 32B active parameters and a switchable thinking mode. A lighter 106B-param Air variant trades scale for efficiency; both ship MIT-licensed.
Closes a learning loop most agents lack: turns experience into reusable skills, refines them mid-task, and full-text searches its own past sessions for recall. Runs from CLI or Telegram/Discord/Slack and schedules unattended cron jobs.
Modular marketplace of focused Claude Code plugins that composes specialized agents and progressive 'agent skills' to orchestrate multi-agent development workflows while minimizing token usage.
Searchable plugin marketplace and curated collections of Claude Code agents, commands, hooks, skills and plugins — lets users discover, browse, and install subagents and tooling via a web UI, plugin commands or a CLI. Indexes community plugins and MCP servers and provides curated packs.
Coordinates specialized AI agents — developer, browser, document, multimodal — running in parallel on your desktop to automate multi-step work. Runs fully local via Ollama, vLLM, or LM Studio, with built-in MCP tools and human-in-the-loop checkpoints.
Parses PDF resumes into structured JSON using LLMs, enriches profiles with GitHub signals, and outputs explainable category scores, evidence, bonuses and deductions. Runs fully local with Ollama or via Google Gemini; designed for reproducible, fairness-constrained resume scoring in hiring workflows.