streaming

A lightweight React Markdown renderer with built-in LaTeX, syntax highlighting, streaming-safe rendering, and security-focused defaults.

Go SDK for building AI-backed apps and endpoints with streaming, tool calling, structured output, and React frontend compatibility.

A minimal, provider-agnostic agent loop for building custom AI agents with swappable memory, model, tools, and stop-condition seams.

A Ruby gem that encodes the Vercel AI SDK Data Stream protocol for Rails and Rack backends, so Ruby apps can stream text, reasoning, tool calls, and data parts to useChat/useObject.

Self-hosted OpenAI-compatible mock server for testing LLM integrations without exposing API keys. Includes a hosted instance, local setup, Docker support, streaming, and deterministic responses.

Blocks.ai is an infrastructure and network layer for AI agents, offering outbound-only connectivity, routing, auth, billing, streaming, and a marketplace/network for builders and callers.

A lightweight Flask-based LLM proxy that forwards Ollama, OpenAI, and llama.cpp-style requests to NVIDIA’s OpenAI-compatible API, with streaming support, retries, caching, auth, and usage stats.

A type-safe Go runtime for building tool-using LLM agents across multiple providers, with streaming, memory, and OpenTelemetry support.

Wallie is an open-source, self-hosted AI streamer that can watch and hear your screen, speak in a custom persona, and now play Minecraft autonomously while narrating its actions. The repo shows a live-streaming workflow with vision, hearing, TTS, avatars, OBS integration, and dashboard-driven setup.

A TypeScript markdown parser built for incremental streaming, aimed at parsing LLM markdown output on the server or client. It exposes a typed AST, supports CommonMark and GFM tables, and includes examples for full and streaming parsing.

PicoMQ is a developer tool for durable real-time streams over HTTP, backed by S3-compatible object storage. The page highlights unlimited streams, a zero-disk architecture, and high-throughput deployment goals.