Python

Open-source package collection for BetterDB’s Valkey/Redis-based AI infrastructure, including semantic cache, agent memory, retrieval, monitoring, CLI, and an MCP server for assistants.

HALO is an open-source local debugger and optimizer for AI agent traces. It collects execution traces, analyzes recurring failure modes with an RLM-based engine, and feeds findings into a coding agent to improve the harness.

An open-source 26M parameter function-calling model designed to run on very small devices, with a local quickstart, Python usage, and a playground for testing and finetuning.

A framework-agnostic checkpointing tool that helps AI agents resume work after context loss or session death. It saves goals, constraints, decisions, touched files, and token usage, then rebuilds a structured resume prompt for continuation.

A finite volume solver for the 1D Saint-Venant (shallow water) system with topography, using a kinetic scheme with reflections and a comparison Rusanov scheme.

A local sandbox for running LLM-generated code from Python or Node with no cloud, no daemon, and strong isolation controls.

Open-source execution runtime for production agents. It records tool and LLM calls as durable steps, supports resume after interruption, and lets teams allow, deny, or approve steps with human oversight.

Bastiontrace is a Python library for analyzing AI agent tool-call traces to locate prompt injections, identify where they landed, and map the resulting blast radius.

Reference implementation for building and understanding AI evaluation systems, including rule-based evaluation, human review, LLM-as-a-Judge, online evaluation, and experiment comparison for a flight search app.

A two-part self-study course for building a tiny LLM stack from scalar autograd to a working chat assistant, with modules covering transformers, pretraining, instruction tuning, retrieval, tool use, and agent loops.

A Python framework for building AI agents as Python objects, with typed methods, stateful fields, and LLM-driven agentic methods. The repo includes installation steps, a quick start, examples, and notes on supported models and safety boundaries.

fenic is an open-source Python framework for semantic DataFrames, letting you use LLM-powered operators like extract, classify, summarize, and embed inside query pipelines.

A local-first Python tool that audits Git history to quantify rework in AI-generated engineering work, including PR correction rates, churn clusters, superseded work, and line survival.

Subarr is an open-source coordination layer for the *arr subtitle stack. It adds subtitle coverage tracking, audio-language verification, provider success tracking, queue management, Whisper tuning, and post-transcription quality checks for Bazarr/Subgen workflows.

A Python CLI that packages data science repositories and data-heavy project files into LLM-friendly prompts, with sampling for CSV, SQL, Excel, and notebooks.

A Python framework for building OAuth 2.0 authorization servers for MCP servers, with token storage, PKCE, device flow, introspection, and rate limiting.

Python package for recording real LLM API responses and replaying them in tests so LLM-driven code can run deterministically without live API calls.

Semble is a local-first code search tool for agents. It offers natural-language search, an MCP server, bash/AGENTS.md integration, and a Python API, with claims of faster indexing and much lower token usage than grep+read.

Hyperset is a local-first debugging tool for coding agents that captures runtime evidence from your app and feeds it back into the agent. It supports Node.js, Python, and Go, and can work with its own agent or tools like Claude Code, Codex, and OpenCode.

Self-hosted voice agent runtime that streams speech-to-text, LLM output, and text-to-speech together in one process. The page shows quickstart commands, a minimal agent example, browser/client embedding, authentication notes, and performance benchmarks.

Anypick is an open library for selecting the best LLM across providers using filters for capabilities, pricing, and benchmarks. It includes Python and TypeScript implementations, provider support for OpenRouter and Vercel AI Gateway, and examples showing how to pick a model by constraints and strategy.

Codeknow turns a codebase into a queryable knowledge graph for architecture analysis, impact detection, drift tracking, onboarding tours, and refactoring guidance. It runs without LLM keys, supports 25+ languages, and exposes a broad CLI plus export formats and interactive views.

Self-hosted multiplayer AI workspace in Python for team-based agent collaboration, with governed actions, real-time shared rooms, and a tamper-evident audit log.

Open-source agent skill and Python service for stripping AI provenance marks from text and files. It supports multiple hosts, includes install scripts, hooks, and a service-backed workflow for cleaning watermarks across many file types.