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How to store and search text facts with Voice Mem with Voice Mem

Save plain text facts in a fact-only mode and retrieve them with a search query.

Who it is forA developer who wants a simple memory store for user facts, without audio processing or emotion tracking.

The problemBuilding a per-user fact store with retrieval from scratch takes time, and the team wants a tested memory engine to start from.

The outcomeA short Python script saves a fact such as a dietary restriction and returns it when asked a matching question.

What you need first

  • Python 3.10 or newer
  • An OpenAI API key, used for fact extraction when memories are written
  • Git and access to GitHub and Hugging Face to clone the repo and download the default models
  • Audio input (a WAV file or a microphone) if you want to ingest speech

Steps

  1. Clone the repo with git clone https://github.com/xzf-thu/VoiceMem.git and install with pip install voicemem.
  2. Download the default models with hf download zhifeixie/VoiceMem_Default_Models_Env --local-dir ./models after running pip install -U huggingface_hub.
  3. In a Python file, create Voice Mem(mode="leftbrain_only", openai_key=...) and call vm.ingest with a text fact.
  4. Call vm.search with a question about that fact and print the result.result_leftbrain field.

Prompt for your agent

In the VoiceMem repo at <repo path>, write a script that creates VoiceMem with mode leftbrain_only, ingests the text <fact text>, and searches with the question <question>. Expected output is the stored fact in result_leftbrain. Verify the search returns the fact after ingest.

Caveat. The README describes this mode as storing factual text without emotion, so it does not replace the full dual-brain setup.

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