Turns heterogeneous traces (chats, docs, emails, transcripts) into versioned, inspectable agent 'Skills' that capture both Persona and Work behaviors; supports multi-source collection, incremental merges and corrections, and installation across multiple agent hosts.
Self-hosted web and mobile interface for running and managing a Hermes autonomous agent — chat, persistent sessions, workspace file browsing, task scheduling, and tools with near-1:1 parity to the CLI. Designed for self-hosted homelab or VPS deployments; depends on a running Hermes Agent.
Turns natural-language instructions into runnable trading research: data loaders, strategy generation, backtests, reports, and optional broker connectors. Focuses on a tool-driven agent model (36+ MCP tools, 77 finance skills) and an Alpha Zoo of 452 pre-built alphas for reproducible research and gated agentic trading.
Provides a lightweight Python harness that turns LLMs into working agents with tool-use, skills, persistent memory, permission controls and multi-agent coordination. Ships with a CLI/React TUI, 43+ built-in tools, a plugin/skill system and the ohmo personal-agent for chat gateways. Best for developers prototyping agent workflows and multi-agent experiments.
Turns a repo's code, docs, PDFs, images, and videos into a queryable multimodal knowledge graph for AI coding assistants. Uses deterministic AST extraction for code and LLM-based semantic extraction for other assets, exporting interactive HTML, JSON, and a human-readable audit report.
Maps a codebase plus docs, PDFs, media and configs into a local, queryable knowledge graph; parses code with a local tree-sitter AST (no LLM), uses configurable backends for semantic extraction of non-code, and outputs graph.json, graph.html and a brief report.
Compiles raw documents into a persistent, interlinked Markdown wiki that LLMs can query; uses PageIndex for vectorless, reasoning-based retrieval of long documents, supports native multi-modality, bundled web Workbench, and skill distillation.
Stores conversation history verbatim and retrieves it via local semantic search with a structured index (wings/rooms/drawers). Pluggable vector backends and a local-first default mean high recall (benchmarked) without cloud or API keys—useful for agent memory and private RAG.
Runs local speech-to-text inference for a wide range of ASR model families using GGUF models on the ggml runtime. Supports Metal, Vulkan, and CUDA GPU backends plus a tinyBLAS-accelerated CPU path, prebuilt GGUFs on Hugging Face, and a quantization tool.
Provides a CLI and skill suite that lets coding assistants scaffold, evaluate, and deploy ADK-based AI agents on Google Cloud. Integrates eval pipelines (generate/grade), deployment infra and CI/CD scaffolds, observability, and Gemini Enterprise publishing workflows.
Local-first voice workflows for cloning, multi-engine TTS/ASR, video dubbing, dictation, transcription and audiobook production across 646 languages. Desktop app with a local OpenAI-compatible API, engine catalogue (TTS/ASR/LLM), and explicit opt-ins for remote features to keep audio and projects on-device.
Desktop app for local voice cloning, real-time dictation, and end-to-end video dubbing using zero-shot TTS across 600+ languages; features multi-engine TTS/ASR, speaker diarization, vocal isolation, batch pipelines, and invisible audio watermarking — all run fully offline.