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Hacker News - Newest: "LLM"

GitHub - lechmazur/position_bias: A benchmark for testing whether LLM judges keep the same preference when two lightly edited versions of the same story are shown in opposite orders. Flex routing (EU and EFTA) Dark Factories: Retooling for LLM Velocity Ask HN: What would be the impact of a LLM output injection attack? GitHub - AronDaron/dataset-generator: No-code desktop app for generating high-quality synthetic datasets to fine-tune LLMs — plan-then-execute pipeline, LLM-as-judge, HuggingFace upload. GitHub - Oaklight/llm-rosetta: Production-ready LLM API translation layer for Python — bidirectional conversion between OpenAI, Anthropic & Google formats via hub-and-spoke IR. Optional API gateway. Streaming & non-streaming. Zero core deps. Contributions welcome! GitHub - browser-use/browser-harness: Self-healing browser harness that enables LLMs to complete any task. GitHub - moeen-mahmud/remen: Remen turns thoughts into something you can return to Analyzing 156 LLM Launch Posts on Hacker News ChatGPT vs Gemini vs Claude: The Best LLM Subscription You Should Buy GitHub - salaamalykum/quran-semantic-search: High-density RAG Semantic Search Engine & Quran Corpus (GEO/SEO Architecture) GitHub - NVIDIA/TensorRT-LLM: TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way. The State of LLM Bug Bounties in 2026 Operational Readiness Criteria for Tool-Using LLM Agents Meshcore: Architecture for a Decentralized P2P LLM Inference Network How an LLM becomes more coherent as we train it GitHub - seetrex-ai/laimark GitHub - Jossifresben/BibCrit: AI-assited biblical textual criticism GitHub - wastedcode/memex: File system based wiki, maintained by Claude 99helpers.com GitHub - cliver-project/AITrigram GitHub - unbody-io/adapt: A self-evolving memory layer for AI agents. GitHub - hb20007/awesome-gen-ai-fails: A list of incidents where reliance on generative AI and LLMs resulted in harm to companies, individuals, or society GitHub - nevenkordic/localmind: Run any local LLM with persistent memory and context. CLI agent over Ollama with SQLite-backed hybrid recall. No cloud. Ask HN: What are the machine requirements for a LLM like Llama-3.1-8B? Faster LLM Inference via Sequential Monte Carlo grpo explained: group relative policy optimization for llm finetuning - cgft Stop comparing price per million tokens: the hidden LLM API costs · TensorZero Andrej Karpathy's LLM Wiki Is a Bad Idea GitHub - GG-QandV/mnemostroma: Offline RAM-first cognitive leer/coprocessor for AI agents and robotics. Solves "Context Abandonment" with 20-80ms latency using a dual-thread biomimetic memory architecture (ONNX + SQLite WAL). mempalace/agent at agent · skorotkiewicz/mempalace GitHub - Nyquest-ai/nyquest-rust-fullstack-pub: Nyquest — Semantic Compression Proxy for LLMs. 350+ rules, local LLM stage, 15-75% token savings. Full Rust stack. GitHub - TheoV823/mneme: Enforce architectural decisions in AI-assisted development. GitHub - klemenvod/TokenBrawl: A 1v1 Bomberman-style game where two LLM agents play autonomously against each other. No human plays — you watch the AIs fight. Each agent receives a text description of the board state, reasons about it, and outputs a move as JSON. The game engine executes it. Introducing the Common AI Provider: LLM and AI Agent Support for Apache Airflow Power Circuit AI: Designing Power Electronic Circuits for Motor Drives with Generative Artificial Intelligence Ask HN: How to program with IDE and LLM on CPU locally? Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis Bonsai 1-bit WebGPU - a Hugging Face Space by webml-community The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows Ask HN: Simple tooling for local LLM code critique without IDE integration? Can a General LLM Diagnose a DICOM Slice? A 10-Case Public Benchmark Charts-of-Thought: Enhancing LLM Visualization Literacy (PDF, 2026) GitHub - Mesh-LLM/mesh-llm: Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. 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Open the Black Box with the Arthur Engine Milla Jovovich's New Open Source LLM Memory App and the Dark Code Problem Your intuition of LLM token usage might be wrong Show HN: Bloomberg Terminal for LLM ops – free and open source GitHub - 0xchamin/mcptube: Transform YouTube videos into a compounding knowledge base with transcripts, vision analysis, and agentic search. Works as an MCP server for Claude, Copilot & more. Show HN: Open KB: Open LLM Knowledge Base Your LLM is a compiler, not a runtime GitHub - sapountzis/Unslop: A Web Feed That Deserves You crates.io: Rust Package Registry Beyond Karpathy's LLM-Wiki: The Necessity of Cognitive Governance GitHub - amitshekhariitbhu/llm-internals: Learn LLM internals step by step - from tokenization to attention to inference optimization. GitHub - parallem-ai/parallem: An expressive library for running agents with the Batch API. GitHub - stfurkan/pi-llm LLM-Wiki Show HN: Formal – Formal verification for AI-generated code using Lean 4 LRTS – Regression testing for LLM prompts (open source, local-first) LLM Wiki Skill: Build a Second Brain with Claude Code and Obsidian I built an LLM Wiki and RAG solution: here's a demo for a security KB The biggest advance in AI since the LLM Predict-Rlm: The LLM Runtime That Lets Models Write Their Own Control Flow the-synthetic-library/the-synthetic-mind at main · joshferrer1/the-synthetic-library GitHub - yisding/reviewwiggum GitHub - Donnyb369/mcp-spine: Context Minifier & State Guard — Local-first MCP middleware proxy GitHub - Beledarian/wgpu-llm: A from-scratch LLM inference engine that uses wgpu (the cross-platform WebGPU implementation) to dispatch WGSL compute shaders for every math operation a Transformer needs. No CUDA. No Python. No massive framework dependencies. Just Rust, raw shaders, and your GPU. GitHub - anitiue/Hindsight: An experience-driven self-improvement framework for LLM agents — 基于经验的 LLM Agent 自我改进框架 GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. GitHub - alainnothere/AmdPerformanceTesting: Amd Performance Testing Ask HN: Is a purely Markdown-based CRM a terrible idea? Optimized for LLM agents Context Engineering - LLM Memory and Retrieval for AI Agents | Weaviate little_helper_tui/letter.md at main · sleepyeldrazi/little_helper_tui GitHub - EvanZhouDev/umr: The Unified Model Registry for all your local AI apps. GitHub - JordanCT/VigIA-Orchestrator Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain A Taxonomy of RL Environments for LLM Agents Llama LLM Network Feture GitHub - genedeng-ca/ai-mac-migration: AI-powered Mac-to-Mac migration tool - replace Apple Migration Assistant with intelligent, selective transfer using local LLMs GitHub - lunargate-ai/gateway: High-performance self-hosted AI gateway (OpenAI-compatible) with routing, retries, and streaming GitHub - AuthBits/webmcp: A lightweight, prompt-driven MCP web research server for high-quality LLM powered information extraction. Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception High-Stakes Personalization: Rethinking LLM Customization for Individual Investor Decision-Making From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization TIDE: Token-Informed Depth Execution for Per-Token Early Exit in LLM Inference Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
GitHub - trentisiete/endy: Multi-agent control plane for coding CLIs (Codex, OpenCode, CommandCode, Hermes) with one tmux session, one .logs/ source of truth, terminal + web frontends.
trentisiete · 2026-05-11 · via Hacker News - Newest: "LLM"

A tmux control plane that hands a coding task from one CLI agent to another when one runs out of tier.

endy handoff: opencode runs out, cmd picks up mid-task

Recording script: docs/demo.md.

Why

I kept hitting my paid agent's weekly cap on a Thursday afternoon, with a task half done in a tmux window I couldn't extend. The other CLIs I had installed — Gemini, OpenCode, CommandCode, Hermes — were idle, on free tiers, perfectly capable of continuing the work. They just didn't know about each other.

endy is the layer that makes them know.

What it does

One command:

endy handoff <task-id> --to <next-agent>

reads the original prompt, tails the previous agent's output, opens a new tmux window with a different CLI, and tells it:

Here is what was being done. Here is the full output of what your predecessor wrote. The previous agent stopped because of <reason>. Continue.

The new agent picks up. The chain is recorded in the task's meta file (handoff_from=…, handoff_chain=…), so taskA(opencode) → taskB(cmd) → taskC(hermes) is fully traceable. Same .logs/ directory, same web dashboard, same endy watch family of commands.

If you set ENDY_HANDOFF_RESOLVER to a script that prints an agent name (for example a wrapper around multiplexor), the --to flag becomes optional and routing happens automatically when one tier runs dry.

The stack

Layer Agent Tier Notes
Orchestrator codex paid Long context, good at planning. You pay only for the conductor.
Worker opencode free (multiple backends) Default for refactors, tests, fast edits
Worker cmd (CommandCode / Kimi K2.6) ~€1 buys a lot of work Strong taste reviewer; cheapest paid option
Worker hermes (Nous Research) depends on backend (configurable per provider, incl. Copilot) Tool-heavy agentic work
Worker gemini (Google Gemini CLI) free daily quota Wide reach
Smoke testing bash (offline stub) free Spawns a no-op window so you can rehearse handoff chains without burning real-agent credits

You only install the ones you want. endy doctor shows what is wired up and authenticated.

Local models (Ollama, LM Studio, …)

endy does not spawn a local model directly — endy spawn ollama is deliberately not wired. Local inference is better treated as a backend behind an existing agent than as a peer-level CLI:

  • Via hermes. Hermes supports user-defined providers in ~/.hermes/config.yaml pointing at any OpenAI-compatible endpoint, including ollama's http://localhost:11434/v1. Add the provider once, then endy spawn hermes --model "ollama/llama3.2" (or whichever model you've pulled) routes through hermes to your local ollama.
  • Via /model inside a CLI that supports it. cmd, codex, and others expose local providers in their /model picker (codex has --oss --local-provider ollama / --local-provider lmstudio; cmd has an Ollama provider you can pick interactively). When the picker opens, browse to the local provider, pick a pulled model, and the CLI sends to your local daemon for that session.

multiplexor also knows ollama as a local fallback at the routing layer — multiplexor delegate "task" may pick it when free tiers are exhausted — but the multiplexor-next-provider resolver used by endy handoff does NOT return ollama (endy can't drive it headlessly as a peer agent). The local-model story lives inside hermes and the /model slash command, not in endy's spawn surface.

Quickstart

Prereqs (macOS or Linux): tmux, python3, and at least one of codex / opencode / cmd / hermes / claude / gemini on PATH.

npm install -g @noetiklab/endy
endy install                     # idempotent: symlinks, completion, PATH,
                                 # AND bootstraps multiplexor from PyPI
                                 # (the routing policy — see below)
exec "$SHELL" -l
endy doctor

Or from source:

git clone https://github.com/trentisiete/endy.git
cd endy && ./scripts/install.sh --yes
exec "$SHELL" -l

The 60-second demo

cd ~/work/my-project
endy start                                            # tmux session for this dir

endy spawn opencode -- "refactor src/auth/ to use the new IdentityProvider interface, then run npm test"

endy watch tree                                       # see it running
# (opencode hits a rate limit, log shows "RESOURCE_EXHAUSTED")

endy handoff <task-id> --to cmd --reason "rate limited" --stop-parent
# → new cmd window opens, reads the original prompt + the FULL log of what
#   opencode produced, and continues from where opencode stopped. Add
#   --stop-parent to close the rate-limited window in the same shot.
#   (Use --lines N to truncate if you're handing off to a small-context
#   target like gemini free.)

Want to rehearse the loop without burning any real-agent credit? Use the offline bash stub:

endy spawn bash -- "pretend to be doing work"
endy handoff <task-id> --to bash --reason "smoke test"
endy watch tree

You get a real handoff chain in .logs/ and a real new tmux window — the agent just doesn't call out to a real model. Useful for testing the dashboard, the tree view, and your demo recording.

That is the loop. Everything else in endy exists to make this one command not feel magical:

  • endy spawn writes a strict .logs/task-<id>.{log,meta,prompt.md} contract so any frontend can read it.
  • endy watch shows the chain across tmux sessions, web dashboard, and your phone over Tailscale.
  • endy chat, endy ask, endy watch followup cover same-agent continuation, interactive takeover, and one-shot questions.

Status

Honest table — what is shippable today, what is on the roadmap. Phase labels match docs/roadmap.md.

Phase Feature Status
0 README + docs repositioning + LICENSE + PyPI metadata shipped
1 endy spawn / ask / chat / watch basic stack shipped
1 endy handoff <id> --to <agent> (manual handoff) shipped
1 Web dashboard + Tailscale mobile shipped
1 Per-directory tmux sessions + global endy overview shipped
1 endy watch tree / list render the ↪ handoff from X chain shipped
1 Web dashboard cards show ↪ from <short> + full chain panel shipped
2 endy install bootstraps multiplexor from PyPI automatically shipped
2 ENDY_HANDOFF_RESOLVER auto-routing (no --to needed) shipped
2 multiplexor next-provider + multiplexor status --json shipped
3 endy state snapshot + auto-prepended environment block shipped
3 codex/skills/endy-state Codex skill shipped
4 Auto-detection of exhaustion (CLI stderr → auto-handoff) shipped
5 Git worktree per spawned task (parallel isolation) planned
6 npm 0.6.0+ stable surface, real demo GIF, public launch planned

The loop now closes itself. When an agent task exits non-zero with a known exhaustion signal in its log (Gemini's RESOURCE_EXHAUSTED, opencode's ProviderModelNotFoundError, cmd's Reached maximum conversation turns, claude's usage_limit_exceeded, hermes's model_not_supported, etc.), endy invokes endy handoff automatically and multiplexor picks the next eligible agent. Disable per-task with --no-auto-handoff, globally with ENDY_AUTO_HANDOFF=0, per-project with a .endy/no-auto-handoff marker. Chain depth is capped at 5 to prevent runaway loops.

Multiplexor

multiplexor is the routing layer. It knows which CLIs you have installed, scores them by priority + tier_bonus, and picks the best one. When you wire it as ENDY_HANDOFF_RESOLVER, every endy handoff without an explicit --to calls multiplexor for the next eligible agent.

You do not install it separately: endy install already pulls endy-multiplexor from PyPI (via pipx / uv tool / pip --user, in that order of preference) and exports ENDY_HANDOFF_RESOLVER=multiplexor-next-provider into your shell startup. Pass --no-multiplexor to endy install if you want to skip it.

The two repos are independent — you can use either alone — but they are designed to compose. endy is the runtime; multiplexor is the policy.

A note on terms of service

endy executes each CLI under its own contract. You are responsible for using each provider within the terms you agreed to — including any limits on automation, free-tier eligibility, or use as a backing model for other applications. endy does not bypass quotas, scrape balances, or store credentials. It moves work between CLIs you have already authenticated yourself.

Documentation

  • docs/kickoff.md — onboarding for a new agent or contributor: architecture, conventions, design principles to preserve, anti-patterns we've already burned on
  • docs/operations.md — full command reference, manager workflows, the endy watch family, the .logs/ contract, web dashboard internals
  • docs/cli-gotchas.md — per-CLI quirks (opencode --dir, cmd --max-turns, hermes -Q, tmux specifics)
  • docs/demo.md — script for recording the handoff GIF, beat-by-beat
  • docs/roadmap.md — phases 0-6 with closing commits and what's coming next

endy help prints top-level usage. endy help <agent> (where <agent> is one of opencode, cmd, hermes, claude, gemini, bash, tmux) prints the relevant section of the gotchas doc.

Related

License

MIT.