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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).
GitHub - sapountzis/Unslop: A Web Feed That Deserves You
2026-04-13 · via Hacker News - Newest: "LLM"
Unslop logo

A browser extension that filters AI-generated content from your social feeds. Runs entirely in your browser. Bring your own API key. No account, no backend, no telemetry.

License: MIT Buy Me A Coffee


Unslop classifies posts in your LinkedIn, X, and Reddit feeds using an LLM of your choice. The model returns a direct keep or hide decision for each post. Everything runs locally in the Chrome service worker; only the LLM API calls you configure ever leave your machine.

Install

From source

# Requires Bun v1.3.8+
cd extension
bun install
bun run build
  1. Open Chrome → chrome://extensions/
  2. Enable Developer mode (top right)
  3. Click Load unpacked → select extension/dist/

From releases

Pre-built zips are available on the Releases page.

Setup

Open the extension popup and enter:

Field Example
API Key your key from OpenAI, OpenRouter, etc.
Base URL https://api.openai.com/v1
Model claude-haiku-4-5

Save, flip the toggle, scroll your feed. Done.

Supported platforms

Platform Status
LinkedIn
X / Twitter experimental
Reddit experimental

Supported providers

Any OpenAI-compatible endpoint works:

Provider Base URL
OpenAI https://api.openai.com/v1
OpenRouter https://openrouter.ai/api/v1
Ollama (local) http://localhost:11434/v1
vLLM / LiteLLM your own URL

Recommended model: claude-haiku-4-5 — fast, cheap, accurate for classification. Any model with JSON mode works.

How it works

Each post is classified directly in the Chrome service worker:

post arrives in feed
       ↓
 local classifier (your API key)
       ↓
 keep / hide

Development

cd extension

bun run build          # production build
bun run dev            # watch mode

bun test src/          # full test suite
bunx tsgo --noEmit -p tsconfig.json  # type check

Project structure

extension/src/
├── background/
│   ├── llmClient.ts          # Typed OpenAI-compatible client
│   ├── localClassifier.ts    # Batch classifier with concurrency control
│   ├── storageFacade.ts      # API key + settings (chrome.storage.local)
│   ├── runtimeDiagnostics.ts # LLM endpoint health probe
│   └── handlers.ts           # Message handlers for content scripts
├── lib/
│   ├── prompts.ts            # System + user prompt templates
│   └── config.ts
├── content/                  # Feed DOM observation and rendering
├── platforms/                # LinkedIn, X, Reddit DOM adapters
└── popup/                    # Extension popup UI

Privacy

Post text is sent only to the API endpoint you configure. No analytics, no telemetry, no external requests beyond your own LLM calls. Your API key lives in chrome.storage.local.

Contributing

PRs welcome. Before opening one:

bunx tsgo --noEmit -p tsconfig.json  # must pass
bun test src/                         # must pass

License

MIT