Audit logging for Azure/go-workflow — records every step execution event with timestamped events, export to JSON, NDJSON, diagrams, and an interactive HTML dashboard.
BM25 full-text search that actually finds what you type — fuzzy substrings across token boundaries, accent-insensitive, with byte-offset highlights. Python + Rust, built for hybrid search with vector DBs.
DocDag reads a directory of Markdown documents with YAML frontmatter, extracts a typed directed graph from it, enforces DAG invariants on that graph, and answers queries about it.
🧠 Local-first LLM state branching & debugging. Capture, visualize, branch, and regression-test LLM calls as a DAG. Free & local via Ollama, any OpenAI-compatible API, MCP for agents. Zero config.
Orchestration for Python data pipelines, without the platform. A fast Rust core drives flows, schedules, backfills, retries, and a live UI. Agentic-ready: MCP tools, agent-attributed runs, human-in-the-loop approvals. One wheel, no runtime dependencies.
Deterministic-first execution engine for agent workflows in Go: the LLM extracts at the edge, a deterministic state machine decides. Zero dependencies, no-code JSON plugins, replayable runs.
Supergroup brings extreme convenience and understandability to the manipulation of Javascript data collections, especially in the context of D3.js visualization programming.
HTML · JavaScript · TypeScript★ 89↓ 2,328/月2026年10月21日
Lightweight self-hosted workflow scheduler in a single Go binary — an open-source Airflow/Azkaban alternative. Embedded SQLite, DAGs (cron + dependencies + backfill), polyglot tasks (shell/Python/SQL/JAR/HTTP), web console, REST API, and a built-in MCP server for AI agents. Linux & macOS.
Incremental computation engine for Go with live what-if worlds: fork the graph into N scenarios that pin some inputs and track the rest live, all updated by one stabilization. Data-shaped topology (Bind), per-key diff collections, O(divergence) scenario cost.