Memorizz Documentation
Memorizz is a memory-first framework for Python AI agents. The docs in this directory are versioned with the code so examples and API references stay in sync with each release.
Looking For The App UI?
The docs website runs on http://localhost:8000 (MkDocs).
The Memorizz web app UI is separate and runs on http://127.0.0.1:8765.
pip install "memorizz[ui]"
memorizz run local
Open http://127.0.0.1:8765 after starting the command above.
What Memorizz Covers
- Memory architecture: semantic, episodic, procedural, short-term, and shared memory systems.
- Application modes: pre-configured memory stacks for assistant, workflow, and deep research agents.
- Provider abstraction: Oracle, MongoDB, filesystem, or custom
MemoryProvider implementations.
- Agent runtime features: tool calling, semantic cache, context-window stats, and summary generation.
- Optional integrations: internet access providers, sandbox code execution, skills marketplace (Vercel Agent Skills, SkillsMP), and local web UI.
Docs Map
- Getting Started: installation, first agent setup, and the Local UI Guide.
- Memory Types: detailed behavior of each memory subsystem.
- Memory Providers: persistence backend setup and tradeoffs.
- Use Cases: mode-specific patterns for assistants, workflows, and deep research.
- Skills Marketplace: discover and use Vercel Agent Skills or SkillsMP skills at runtime.
- Internet Access + Sandbox: optional runtime capabilities for web research and isolated code execution.
Local Preview
From the project root:
pip install -e ".[docs]"
mkdocs serve
Visit http://localhost:8000.
Before publishing docs changes:
Release Checklist (Docs)
- Ensure
README.md and docs quickstarts reference existing files and valid API names.
- Verify new features are documented under the relevant provider/memory/use-case page.
- Run
mkdocs build --strict to catch broken links/snippets.