{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "libingzheren-jev-mem--build-memory-over-own-observations",
 "repo": "libingzheren/Jev-Mem",
 "repo_url": "https://github.com/libingzheren/Jev-Mem",
 "repo_slug": "libingzheren-jev-mem",
 "title": "Build and query Jev Mem over your own observations",
 "page_title": "How to build and query Jev Mem over your own observations with Jev Mem",
 "summary": "Load your JSON notes into a Jev Mem cache with live models and ask questions answered from retrieved evidence.",
 "who": "A developer building a persistent assistant that must remember user preferences across sessions and recall them later.",
 "problem": "The assistant forgets details from earlier conversations, and the team needs memory that keeps original observations with timestamps and provenance.",
 "outcome": "A local memory cache built from your observations, plus an answer to a question about a stored preference, produced by the OpenAI-compatible model.",
 "steps": [
  "Create a `.env` file in the repository root with `TYPESAFE_API_KEY=your-typesafe-key` and `OPENAI_API_KEY=your-openai-key`.",
  "Format your data as a JSON list of strings or objects with `content`, an optional ISO 8601 `timestamp`, and optional `metadata`.",
  "Build the cache with `python -m jev_mem --mode build --input examples/observations.json --jev-config config/jev_mem.json --cache-dir ./jev_mem_cache/app`, replacing the input path with your file. (inferred, check the README)",
  "Query it with `python -m jev_mem --mode query --question \"What reminder does Mira prefer?\" --jev-config config/jev_mem.json --cache-dir ./jev_mem_cache/app`, replacing the question with your own. (inferred, check the README)"
 ],
 "agent_prompt": "In the Jev-Mem repository at <target-folder>, build a cache from <input-json-file> using `python -m jev_mem --mode build` with config/jev_mem.json, then query it with `--mode query` using the question <question>. Return the answer and confirm that the cache folder was created locally.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "Live runs send your text to the configured providers and may incur charges, and the README says to keep keys, conversations, and caches local, so review SECURITY.md before using private data.",
 "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": [
  {
   "tag": "credentials",
   "notice": "The .env file holds provider API keys, so keep it local and out of version control, and avoid pasting keys into agent prompts or logs."
  }
 ],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/libingzheren-jev-mem/build-memory-over-own-observations/",
 "md": "https://dedupedai.com/use-cases/libingzheren-jev-mem/build-memory-over-own-observations/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--build-memory-over-own-observations.json",
 "api_version": "v1"
}