memori: a tiny FOSS memory layer (CRUD + reflection + gap detection) you can run today

Most agents and chatbots today can store and recall facts. But they rarely reflect or detect when something important is missing or outdated. This leads to brittle behavior: repeated mistakes, stale knowledge, and “I never learned that” failures.

This talk introduces memori, an open-source Python library that adds a minimal but powerful meta-memory layer to any app. At its core, memori provides:

• A clean CRUD API for memory records (add, get, update, delete).

• A lightweight reflection mechanism that merges duplicates and flags stale facts.

• Gap detection so agents can say, “I don’t know your project name, teach me?” instead of hallucinating.

On top of the library, we’ll demo a simple FastAPI+HTMX journaling bot that lets you edit memories live, press “reflect,” and watch the agent’s behavior change instantly. It is self-hosted, Apache-licensed, and runs with Docker in minutes.

By the end, you’ll see how a few hundred lines of Python and Postgres/Valkey can turn static recall into a reflective memory system.

• Why CRUD + reflection + gap detection are the features that make memory systems actually useful.

• How to run memori locally and try the journaling bot in minutes.

• A practical open-source blueprint for adding reflection and gap awareness to your own apps or agents.

• Roadmap ideas: provenance, forgetting policies, vector backends, and integrations with LangChain/LlamaIndex.