Live transcription and natural, LLM-powered translation for macOS — focused on meaning, not just words.
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Updated
Sep 10, 2026 - Swift
Live transcription and natural, LLM-powered translation for macOS — focused on meaning, not just words.
An intelligent document reasoning system with a Matrix-themed interface. Now fully private on your device! (no API keys or online deployment).
A Linux Chinese IME that helps you learn English while typing, built with Fcitx5, Rime, and Ollama.
Deterministic agent effect-execution kernel with bounded tools, durable effects, recovery, replay, tracing, MCP, and multi-agent orchestration.
A Dart client for interacting with the Ollama API. This package provides methods to interact with the Ollama API, including chat, model management, embeddings, and more.
Chat with any document Text files (.txt, .md), PDF files (.pdf), Word documents (.docx, .doc), JSON files (.json), GeoJSON files (.geojson) using RAG
AI-powered competitive intelligence tool that scrapes company websites, uses LLMs for dynamic page selection and extraction, and generates executive prospectus reports.
A tiny proxy that sits in front of any OpenAI-compatible LLM backend (Ollama, LiteLLM, etc.) and forces conversation-history compaction before the context window fills up, so local-model coding CLIs don't hard-die from context overflow.
Production-grade, 100% local implementations of SOTA AI & Agentic research papers. Features interactive visual web UIs, rigorous test suites, and local LLM integrations (Ollama / Qwen / Gemma).
AI-powered personal telemetry operating system for unified life tracking, agent orchestration, and semantic behavioral analysis.
Enterprise-grade distributed IoT energy tracking & AI recommendations platform built with Spring Boot 4, Java 21, Apache Kafka, InfluxDB, Keycloak OAuth2 security, Ollama local LLMs (Spring AI), Prometheus/Grafana observability, and Testcontainers.
A minimal RAG pipeline with a labelled retrieval eval set, testing whether query rewriting and routing actually improve retrieval. They didn't.
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