Developer Tool / RAG Framework
An experimental RAG lab for constrained environments, with configurable document classification, chunking, retrieval, reranking, and chat context assembly. It includes Open WebUI integration and emphasizes debugging retrieval and context failures.
The page clearly describes a real AI-building tool: a config-driven RAG framework with document loading, retrieval strategies, reranking, chat interaction, and Open WebUI integration. The README gives enough detail to understand its purpose, workflow, and target users, and it is more than a thin placeholder or generic repo page.
The snapshot does not show installation steps, supported models, licensing/maintenance details, or enough example outputs to judge how easy it is to run and what the system produces in practice.
Last evaluated 35 days ago. Current rank #330. Down 6 spots in the rankings.
WebLLM is a high-performance in-browser LLM inference engine that runs locally in the browser with WebGPU acceleration. It exposes an OpenAI-compatible API, supports streaming and JSON mode, and includes examples for building chat apps and browser extensions.
Self-hosted observability and control plane for production and coding AI agents, with live timelines, fleet-wide feeds, token budgets, MCP allow/block rules, and support for Claude Code plus a Python sensor.
Browser extension that scans pastes for credentials and PII before they reach LLM chat sites, with local on-device inference and no network calls.
Open-source runtime for multi-agent AI systems with job scheduling, DAG orchestration, shared memory, tool execution, and real-time observability.
