Igor Lins e Silva
c35686c9e1
End-user installs now lead with `uv tool install mempalace`, with `pip install mempalace` kept as a fallback. Dev/contributor docs lead with `uv sync --extra dev` and `uv run` for tests/benchmarks/lint, with the equivalent pip recipe kept inline. The shipped `/mempalace:init` skill instructions (mempalace/instructions/init.md) try `uv tool install` first when uv is on PATH, then fall back through the pip variants. Adds a .python-version pin at 3.12 because the lockfile's onnxruntime==1.24.3 only ships wheels for Python >=3.11; without the pin, `uv sync` on a host where uv prefers 3.10 fails with no source distribution available, which would make the documented command a footgun. pyproject's `requires-python = ">=3.9"` is unchanged — pip users on 3.9/3.10 are unaffected. Files updated: README.md, CONTRIBUTING.md, CLAUDE.md, the gemini-cli guide and example, the .claude-plugin / .codex-plugin READMEs, the mempalace SKILL, the openclaw SKILL, tools/save.md, the three benchmarks docs, and the corresponding website mirrors.
96 lines
2.9 KiB
Markdown
96 lines
2.9 KiB
Markdown
# Getting Started
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## Installation
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We recommend [`uv`](https://docs.astral.sh/uv/) — `uv tool install` puts
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the `mempalace` CLI in an isolated environment on your PATH:
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```bash
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uv tool install mempalace
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```
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If you prefer pip, `pip install mempalace` still works.
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::: danger Security Warning
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The domain `mempalace.tech` is a **brand-squatting site** not affiliated with this project. It is known to run ad-redirects and potential malware. The official MemPalace distribution is only available via this [GitHub repository](https://github.com/MemPalace/mempalace) and [PyPI](https://pypi.org/project/mempalace/). Never install binaries or scripts from unofficial domains.
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:::
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### Requirements
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- Python 3.9+
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- `chromadb>=0.5.0` (installed automatically)
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- `pyyaml>=6.0` (installed automatically)
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No API key required for the core local workflow. After installation, the main storage and retrieval path runs locally.
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### From Source
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```bash
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git clone https://github.com/MemPalace/mempalace.git
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cd mempalace
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uv sync --extra dev # or: pip install -e ".[dev]"
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```
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## Quick Start
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Three steps: **init**, **mine**, **search**.
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### 1. Initialize Your Palace
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`mempalace init` requires a project directory to scan. Pass a path,
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or `.` to use the current directory.
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```bash
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mempalace init ~/projects/myapp
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# or, from inside the project:
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mempalace init .
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```
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This scans your project directory and:
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- Detects people and projects from file content
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- Creates rooms from your folder structure
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- Ensures the `~/.mempalace/` config directory exists
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### 2. Mine Your Data
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```bash
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# Mine project files (code, docs, notes)
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mempalace mine ~/projects/myapp
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# Mine conversation exports (Claude, ChatGPT, Slack)
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mempalace mine ~/chats/ --mode convos
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# Mine with auto-classification into memory types
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mempalace mine ~/chats/ --mode convos --extract general
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```
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Two mining modes plus one extraction strategy:
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- **projects** — code and docs, auto-detected rooms
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- **convos** — conversation exports, chunked by exchange pair
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- **general extraction** — an `--extract general` option for conversation mining that classifies content into decisions, preferences, milestones, problems, and emotional context
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### 3. Search
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```bash
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mempalace search "why did we switch to GraphQL"
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```
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That gives you a working local memory index.
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## What Happens Next
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After the one-time setup, you don't run MemPalace commands manually. Your AI uses it for you through [MCP integration](/guide/mcp-integration) or a [Claude Code plugin](/guide/claude-code).
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Ask your AI anything:
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> *"What did we decide about auth last month?"*
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It calls `mempalace_search` automatically, gets verbatim results, and answers you. You never type `mempalace search` again.
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## Next Steps
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- [Mining Your Data](/guide/mining) — deep dive into mining modes
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- [MCP Integration](/guide/mcp-integration) — connect to Claude, ChatGPT, Cursor, Gemini
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- [The Palace](/concepts/the-palace) — understand wings, rooms, halls, and tunnels
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