{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "libingzheren-jev-mem--run-offline-memory-demo",
 "repo": "libingzheren/Jev-Mem",
 "repo_url": "https://github.com/libingzheren/Jev-Mem",
 "repo_slug": "libingzheren-jev-mem",
 "title": "Run the offline memory demo in under 15 minutes",
 "page_title": "How to run the offline memory demo in under 15 minutes with Jev Mem",
 "summary": "Install Jev Mem and watch it store observations, retrieve evidence, and print a decision trace with no API keys.",
 "who": "A developer evaluating agent memory who wants to see how the pipeline works before spending money on live model calls.",
 "problem": "Reading about write, connect, retrieve, and assess steps is hard to picture without seeing them run.",
 "outcome": "A printed decision trace from synthetic observations, showing how the memory pipeline behaves on a laptop.",
 "steps": [
  "Clone the repository with `git clone https://github.com/libingzheren/Jev-Mem` and enter it with `cd Jev-Mem`. (inferred, check the README)",
  "Create a virtual environment with `python3.11 -m venv .venv`.",
  "Activate it with `source .venv/bin/activate` (on Windows, use `.venv\\Scripts\\Activate.ps1`).",
  "Install dependencies with `python -m pip install -r requirements.txt`.",
  "Run the demo with `python -m jev_mem.demo` and read the printed decision trace."
 ],
 "agent_prompt": "Clone the Jev-Mem repository from https://github.com/libingzheren/Jev-Mem into <target-folder>, create a Python 3.11 virtual environment, install requirements.txt, and run `python -m jev_mem.demo`. Report the printed decision trace and confirm that no API keys were requested.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "15 minutes",
 "basis": "readme",
 "caveat": "The demo uses deterministic mock decisions and embeddings and does not measure answer quality, so it shows the pipeline rather than the paper's results.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.11 or newer and a terminal",
  "A local copy of the repository (the README assumes you run commands from the repository root)",
  "For live runs: a TypeSafe API key and an OpenAI API key, plus network access, since live runs may incur charges",
  "For benchmarks: the LoCoMo dataset placed at data/locomo10.json, obtained from its original distributor per the data setup guide"
 ],
 "risk": "sensitive",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/libingzheren-jev-mem/run-offline-memory-demo/",
 "md": "https://dedupedai.com/use-cases/libingzheren-jev-mem/run-offline-memory-demo/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/libingzheren-jev-mem--run-offline-memory-demo.json",
 "api_version": "v1"
}