Merge pull request #1414 from MemPalace/chore/uv-and-3.3.4-housekeeping

chore: housekeeping — sync 3.3.4 version + recommend uv for installs

.claude-plugin/README.md

@@ -23,7 +23,7 @@ claude plugin add /path/to/mempalace
 
 ## Post-Install Setup
 
-After installing the plugin, run the init command to complete setup (pip install, MCP configuration, etc.):
+After installing the plugin, run the init command to complete setup (installs the `mempalace` package via `uv tool` or `pip`, configures MCP, etc.):
 
 ```
 /mempalace:init

.claude-plugin/marketplace.json

@@ -9,7 +9,7 @@
       "name": "mempalace",
       "source": "./.claude-plugin",
       "description": "AI memory system — mine projects and conversations into a searchable palace. 19 MCP tools, auto-save hooks, guided setup.",
-      "version": "3.3.3",
+      "version": "3.3.4",
       "author": {
         "name": "milla-jovovich"
       }

.claude-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "mempalace",
-  "version": "3.3.3",
+  "version": "3.3.4",
   "description": "Give your AI a memory — mine projects and conversations into a searchable palace. 19 MCP tools, auto-save hooks, and guided setup.",
   "author": {
     "name": "milla-jovovich"

.claude-plugin/skills/mempalace/SKILL.md

@@ -16,10 +16,10 @@ Ensure `mempalace` is installed:
 mempalace --version
 ```
 
-If not installed:
+If not installed (uv recommended):
 
 ```bash
-pip install mempalace
+uv tool install mempalace   # or: pip install mempalace
 ```
 
 ## Usage

.codex-plugin/README.md

@@ -6,7 +6,7 @@ Give your AI a persistent memory -- mine projects and conversations into a searc
 
 - Python 3.9+
 - Codex CLI installed and configured
-- `pip install mempalace`
+- `uv tool install mempalace` (recommended) or `pip install mempalace`
 
 ## Installation
 
@@ -39,12 +39,17 @@ git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
 ```
 
-2. Install the Python package:
+2. Install the Python package so the `mempalace-mcp` script lands on
+   your PATH (the bundled `plugin.json` invokes it by bare name):
 
 ```bash
-pip install -e .
+uv tool install --editable .   # or: pip install -e .
 ```
 
+   Plain `uv sync` is **not** enough here — it installs the scripts into
+   `.venv/bin/`, which Codex will not find unless you activate the venv
+   before launching Codex.
+
 3. The `.codex-plugin` directory is already in the repo root. Codex CLI will detect it automatically when you run Codex from inside the repository.
 
 4. Initialize your palace:

.codex-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "mempalace",
-  "version": "3.3.3",
+  "version": "3.3.4",
   "description": "Give your AI a memory — mine projects and conversations into a searchable palace. 19 MCP tools, auto-save hooks, and guided setup.",
   "author": {
     "name": "milla-jovovich"

.python-version

@@ -0,0 +1 @@
+3.12

CLAUDE.md

@@ -36,26 +36,26 @@ We do not accept summarization of user content, cloud storage/sync features, tel
 ## Setup
 
 ```bash
-pip install -e ".[dev]"
+uv sync --extra dev   # recommended; or: pip install -e ".[dev]"
 ```
 
 ## Commands
 
 ```bash
 # Run tests
-python -m pytest tests/ -v --ignore=tests/benchmarks
+uv run pytest tests/ -v --ignore=tests/benchmarks
 
 # Run tests with coverage
-python -m pytest tests/ -v --ignore=tests/benchmarks --cov=mempalace --cov-report=term-missing
+uv run pytest tests/ -v --ignore=tests/benchmarks --cov=mempalace --cov-report=term-missing
 
 # Lint
-ruff check .
+uv run ruff check .
 
 # Format
-ruff format .
+uv run ruff format .
 
 # Format check (CI mode)
-ruff format --check .
+uv run ruff format --check .
 ```
 
 ## Project Structure

CONTRIBUTING.md

@@ -10,13 +10,17 @@ git clone https://github.com/<your-username>/mempalace.git
 cd mempalace
 git remote add upstream https://github.com/MemPalace/mempalace.git
 
-pip install -e ".[dev]"    # installs with dev dependencies (pytest, build, twine)
+# Recommended: uv (https://docs.astral.sh/uv/) handles the venv for you
+uv sync --extra dev
+
+# Or with pip in your own venv:
+# pip install -e ".[dev]"
 ```
 
 ## Running Tests
 
 ```bash
-pytest tests/ -v
+uv run pytest tests/ -v
 ```
 
 All tests must pass before submitting a PR. Tests should run without API keys or network access.
@@ -25,10 +29,10 @@ All tests must pass before submitting a PR. Tests should run without API keys or
 
 ```bash
 # Quick test (20 questions, ~30 seconds)
-python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json --limit 20
+uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json --limit 20
 
 # Full benchmark (500 questions, ~5 minutes)
-python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
+uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
 ```
 
 See [benchmarks/README.md](benchmarks/README.md) for data download instructions and reproduction guide.
@@ -49,7 +53,7 @@ assets/             ← logo + brand
 1. Fork the repo and create a feature branch: `git checkout -b feat/my-thing`
 2. Write your code
 3. Add or update tests if applicable
-4. Run `pytest tests/ -v` — everything must pass
+4. Run `uv run pytest tests/ -v` — everything must pass
 5. Commit with a clear message following [conventional commits](https://www.conventionalcommits.org/):
    - `feat: add Notion export format`
    - `fix: handle empty transcript files`

README.md

@@ -49,11 +49,16 @@ Architecture, concepts, and mining flows:
 
 ## Install
 
+We recommend [`uv`](https://docs.astral.sh/uv/) — `uv tool install` puts
+the `mempalace` CLI in an isolated environment on your PATH:
+
 ```bash
-pip install mempalace
+uv tool install mempalace
 mempalace init ~/projects/myapp
 ```
 
+If you prefer pip, `pip install mempalace` still works.
+
 ## Quickstart
 
 ```bash
@@ -120,9 +125,9 @@ own research page for their published numbers.
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 # see benchmarks/README.md for dataset download commands
-python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
+uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
 ```
 
 ---
@@ -185,7 +190,7 @@ PRs welcome. See [CONTRIBUTING.md](CONTRIBUTING.md).
 MIT — see [LICENSE](LICENSE).
 
 <!-- Link Definitions -->
-[version-shield]: https://img.shields.io/badge/version-3.3.3-4dc9f6?style=flat-square&labelColor=0a0e14
+[version-shield]: https://img.shields.io/badge/version-3.3.4-4dc9f6?style=flat-square&labelColor=0a0e14
 [release-link]: https://github.com/MemPalace/mempalace/releases
 [python-shield]: https://img.shields.io/badge/python-3.9+-7dd8f8?style=flat-square&labelColor=0a0e14&logo=python&logoColor=7dd8f8
 [python-link]: https://www.python.org/

benchmarks/BENCHMARKS.md

@@ -344,7 +344,7 @@ The palace classifies each question into one of 5 halls. Pass 1 searches only wi
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 mkdir -p /tmp/longmemeval-data
 curl -fsSL -o /tmp/longmemeval-data/longmemeval_s_cleaned.json \
   https://huggingface.co/datasets/xiaowu0162/longmemeval-cleaned/resolve/main/longmemeval_s_cleaned.json
@@ -724,8 +724,8 @@ python benchmarks/longmemeval_bench.py /tmp/longmemeval-data/longmemeval_s_clean
 The question: how much of the 96.6% → 99.4% improvement is the heuristics, and how much would come from just using a better embedding model?
 
 ```bash
-pip install fastembed
+uv pip install fastembed   # or: pip install fastembed
-python benchmarks/longmemeval_bench.py /tmp/longmemeval-data/longmemeval_s_cleaned.json \
+uv run python benchmarks/longmemeval_bench.py /tmp/longmemeval-data/longmemeval_s_cleaned.json \
   --mode raw --embed-model bge-large
 ```
 

benchmarks/HYBRID_MODE.md

@@ -198,7 +198,7 @@ python benchmarks/longmemeval_bench.py data/longmemeval_s_cleaned.json --mode hy
 # Setup
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 
 # Download data
 mkdir -p /tmp/longmemeval-data

benchmarks/README.md

@@ -7,7 +7,7 @@ Run the exact same benchmarks we report. Clone, install, run.
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 ```
 
 ## Benchmark 1: LongMemEval (500 questions)

examples/gemini_cli_setup.md

@@ -9,17 +9,24 @@ This guide explains how to set up MemPalace as a permanent memory for the [Gemin
 
 ## 1. Installation
 
-On many Linux systems, installing Python packages globally is restricted. We recommend using a local virtual environment within the MemPalace directory.
+On many Linux systems, installing Python packages globally is restricted. We
+recommend [`uv`](https://docs.astral.sh/uv/), which creates and manages a
+local virtual environment for you.
 
 ```bash
 # Clone the repository (if you haven't already)
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
 
-# Create a virtual environment
+# Create the venv and install MemPalace + dependencies in editable mode
-python3 -m venv .venv
+uv sync
+```
 
-# Install dependencies and MemPalace in editable mode
+This produces a `.venv/` directory inside the repo with everything installed.
+If you prefer plain pip:
+
+```bash
+python3 -m venv .venv
 .venv/bin/pip install -e .
 ```
 
@@ -29,7 +36,7 @@ Set up your "Palace" (the database) and configure your identity.
 
 ```bash
 # Initialize the palace in the current directory
-.venv/bin/python3 -m mempalace init .
+uv run python -m mempalace init .
 ```
 
 ### Identity and Wings (Optional but Recommended)
@@ -86,7 +93,7 @@ Once connected, Gemini CLI will automatically:
 ### Manual Mining
 If you want the AI to learn from your existing code or docs immediately, run the "mine" command:
 ```bash
-.venv/bin/python3 -m mempalace mine /path/to/your/project
+uv run python -m mempalace mine /path/to/your/project
 ```
 
 ### Verification

integrations/openclaw/SKILL.md

@@ -102,10 +102,10 @@ You have access to a local memory palace via MCP tools. The palace stores verbat
 
 ## Setup
 
-Install MemPalace and populate the palace:
+Install MemPalace and populate the palace (uv recommended):
 
 ```bash
-pip install mempalace
+uv tool install mempalace   # or: pip install mempalace
 mempalace init ~/my-convos
 mempalace mine ~/my-convos
 ```

mempalace/instructions/init.md

@@ -11,27 +11,39 @@ tell the user they need Python 3.9+ installed and stop.
 
 ## Step 2: Check if mempalace is already installed
 
-Run `pip show mempalace` to see if the package is already present. If it is,
+Run `mempalace --version`. If it succeeds, the CLI is on PATH — report
-report the installed version and skip to Step 4.
+the installed version and skip to Step 4.
+
+If `mempalace --version` fails, **do not** skip to Step 4 just because
+`pip show mempalace` or `uv tool list` reports the package as installed:
+the package may live inside a venv that isn't activated, in which case
+Step 5 (`mempalace init ...`) will fail with `command not found`. Treat
+that case as not-installed and continue to Step 3, which will (re)install
+into a PATH-visible location via `uv tool install` or `pip`.
 
 ## Step 3: Install mempalace
 
-Run `pip install mempalace`.
+Prefer [`uv`](https://docs.astral.sh/uv/) — it isolates the CLI from system
+Python and avoids most environment-related failures:
 
-### Error handling -- pip failures
+1. If `uv` is on PATH (`uv --version`), run `uv tool install mempalace`.
+2. Otherwise run `pip install mempalace`.
 
-If `pip install mempalace` fails, try these fallbacks in order:
+### Error handling -- install failures
 
-1. Try `pip3 install mempalace`
+If the install command fails, try these fallbacks in order:
-2. Try `python -m pip install mempalace` (or `python3 -m pip install mempalace`)
+
-3. If the error mentions missing build tools or compilation failures (commonly
+1. If `uv tool install` failed, try `pip install mempalace` (or vice versa).
+2. Try `pip3 install mempalace`.
+3. Try `python -m pip install mempalace` (or `python3 -m pip install mempalace`).
+4. If the error mentions missing build tools or compilation failures (commonly
    from chromadb or its native dependencies):
    - On Linux/macOS: suggest `sudo apt-get install build-essential python3-dev`
      (Debian/Ubuntu) or `xcode-select --install` (macOS)
    - On Windows: suggest installing Microsoft C++ Build Tools from
      https://visualstudio.microsoft.com/visual-cpp-build-tools/
    - Then retry the install command
-4. If all attempts fail, report the error clearly and stop.
+5. If all attempts fail, report the error clearly and stop.
 
 ## Step 4: Ask for project directory
 

mempalace/version.py

@@ -1,3 +1,3 @@
 """Single source of truth for the MemPalace package version."""
 
-__version__ = "3.3.3"
+__version__ = "3.3.4"

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "mempalace"
-version = "3.3.3"
+version = "3.3.4"
 description = "Give your AI a memory — mine projects and conversations into a searchable palace. No API key required."
 readme = "README.md"
 requires-python = ">=3.9"

tools/save.md

@@ -23,4 +23,4 @@ Behavior:
    `--wing my_research`).
 4. Report back: how many drawers were filed, into which wing/room.
 
-Requires `mempalace` to be installed (`pip install mempalace`).
+Requires `mempalace` to be installed (`uv tool install mempalace` recommended, or `pip install mempalace`).

uv.lock

@@ -1169,7 +1169,7 @@ wheels = [
 
 [[package]]
 name = "mempalace"
-version = "3.3.3"
+version = "3.3.4"
 source = { editable = "." }
 dependencies = [
     { name = "chromadb" },

website/guide/gemini-cli.md

@@ -9,22 +9,30 @@ MemPalace works natively with [Gemini CLI](https://github.com/google/gemini-cli)
 
 ## Installation
 
+We recommend [`uv`](https://docs.astral.sh/uv/) — it creates and manages the
+virtual environment for you:
+
 ```bash
 # Clone the repository
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
 
-# Create a virtual environment
+# Create the venv and install MemPalace + dependencies
-python3 -m venv .venv
+uv sync
+```
 
-# Install dependencies
+This produces a `.venv/` directory with the project installed in editable
+mode. If you prefer plain pip, the equivalent is:
+
+```bash
+python3 -m venv .venv
 .venv/bin/pip install -e .
 ```
 
 ## Initialize the Palace
 
 ```bash
-.venv/bin/python3 -m mempalace init .
+uv run python -m mempalace init .
 ```
 
 ### Identity and Project Configuration (Optional)
@@ -88,7 +96,7 @@ Once connected, Gemini CLI will automatically:
 
 Mine existing code or docs:
 ```bash
-.venv/bin/python3 -m mempalace mine /path/to/your/project
+uv run python -m mempalace mine /path/to/your/project
 ```
 
 ### Verification

website/guide/getting-started.md

@@ -2,12 +2,15 @@
 
 ## Installation
 
-Install MemPalace from PyPI:
+We recommend [`uv`](https://docs.astral.sh/uv/) — `uv tool install` puts
+the `mempalace` CLI in an isolated environment on your PATH:
 
 ```bash
-pip install mempalace
+uv tool install mempalace
 ```
 
+If you prefer pip, `pip install mempalace` still works.
+
 ::: danger Security Warning
 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.
 :::
@@ -25,7 +28,7 @@ No API key required for the core local workflow. After installation, the main st
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 ```
 
 ## Quick Start

website/reference/benchmarks.md

@@ -113,7 +113,7 @@ Every benchmark runs deterministically from this repository.
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+uv sync --extra dev   # or: pip install -e ".[dev]"
 
 # LongMemEval — raw (96.6%)
 curl -fsSL -o /tmp/longmemeval_s_cleaned.json \

website/reference/contributing.md

@@ -7,13 +7,18 @@ PRs welcome. MemPalace is open source and we welcome contributions of all sizes
 ```bash
 git clone https://github.com/MemPalace/mempalace.git
 cd mempalace
-pip install -e ".[dev]"
+
+# Recommended: uv (https://docs.astral.sh/uv/) manages the venv for you
+uv sync --extra dev
+
+# Or with pip in your own venv:
+# pip install -e ".[dev]"
 ```
 
 ## Running Tests
 
 ```bash
-pytest tests/ -v
+uv run pytest tests/ -v
 ```
 
 All tests must pass before submitting a PR. Tests should run without API keys or network access.
@@ -22,10 +27,10 @@ All tests must pass before submitting a PR. Tests should run without API keys or
 
 ```bash
 # Quick test (20 questions, ~30 seconds)
-python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json --limit 20
+uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json --limit 20
 
 # Full benchmark (500 questions, ~5 minutes)
-python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
+uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json
 ```
 
 See [Benchmarks](/reference/benchmarks) for data download instructions.
@@ -35,7 +40,7 @@ See [Benchmarks](/reference/benchmarks) for data download instructions.
 1. Fork the repo and create a feature branch: `git checkout -b feat/my-thing`
 2. Write your code
 3. Add or update tests if applicable
-4. Run `pytest tests/ -v` — everything must pass
+4. Run `uv run pytest tests/ -v` — everything must pass
 5. Commit with clear [conventional commits](https://www.conventionalcommits.org/):
    - `feat: add Notion export format`
    - `fix: handle empty transcript files`