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What you can do with Voice Mem

VoiceMem is an open source memory system for real-time voice agents that stores facts and emotional context from speech and feeds relevant memories to a reply model.

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xzf-thu/VoiceMem on GitHub

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What do you want to do?

5 use cases

  • Give a custom voice agent long-term memory

    Plug Voice Mem into your own voice model so it recalls user facts and feelings across sessions.

    View prompt
    Using the VoiceMem repo at <repo path>, wire my model <model name> into a reply function with signature my_reply(text, memory_context) and pass it to VoiceMem(reply=my_reply). Confirm the sample script runs and that memory_context is non-empty after I state a fact such as a food allergy.

  • Store and search text facts with Voice Mem

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

    View prompt
    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.

  • Run the LoCoMo benchmark on a memory system

    Score Voice Mem on the LoCoMo dataset and check that the parser reads the data correctly first.

    View prompt
    In the VoiceMem repo at <repo path>, run the LoCoMo sample with evaluation/run.py, then run the full dataset only after the sample passes. Report the overall score, the per-category scores, and median retrieval latency. Verify that the answer model received retrieved memory and not raw conversation history.

  • Run the Voice Mem voice demo in a browser

    Start the local web demo and talk to a voice agent that remembers what you said.

    View prompt
    In the VoiceMem repo at <repo path>, start python web/run.py and open http://localhost:8787. Ask the user to state a fact, then to ask about it. Expected output is a reply that uses the stated fact. Verify the log file in results/logs was written.

  • Fine-tune a Voice Mem model family adapter

    Train your own adapter on the provided training script and reproduce the default configuration.

    View prompt
    In the VoiceMem repo at <repo path>, install ms-swift==4.5.2 and bitsandbytes, then run finetune/train.py with my dataset <dataset path>. Expected output is a trained adapter. Verify the run uses the default parameters described in the README.

How to use Voice Mem

  1. Check you have what it needs: 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.
  2. Open xzf-thu/VoiceMem on GitHub and read the README and license.
  3. Clone the repo with git clone https://github.com/xzf-thu/VoiceMem.git and enter the folder with cd VoiceMem.
  4. Install the memory system with pip install voicemem.
  5. Download the default local models with pip install -U huggingface_hub and then hf download zhifeixie/VoiceMem_Default_Models_Env --local-dir ./models.
  6. Set your key with export OPENAI_API_KEY=sk-....

These steps come from our top use case, Give a custom voice agent long-term memory, which also has a copy-paste agent prompt.

Voice Mem alternatives · Best AI repos for Software and DevOps

About this repo

  • Who it is forDevelopers building voice assistants or agents who need long-term, user-specific memory, and AI agents that set up or evaluate such systems.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/xzf-thu/VoiceMem · Back to Hot repos

Requirements

  • 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
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Questions about Voice Mem

What is Voice Mem?

VoiceMem is an open source memory system for real-time voice agents that stores facts and emotional context from speech and feeds relevant memories to a reply model. It is an open-source project on GitHub: https://github.com/xzf-thu/VoiceMem.

Who is Voice Mem for?

Developers building voice assistants or agents who need long-term, user-specific memory, and AI agents that set up or evaluate such systems.

What can I do with Voice Mem?

5 use cases so far, for example: Give a custom voice agent long-term memory; Store and search text facts with Voice Mem; Run the LoCoMo benchmark on a memory system. Each has steps and a copy-paste agent prompt.

What do I need to run Voice Mem?

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.

What are alternatives to Voice Mem?

Other hot AI repos in Software and DevOps: Harness2, iFixAi, Orca, Diagram Design, AI Memory.

Is Voice Mem safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.