pyrecall-cli 0.4.0

Local project memory and correction learning for Python workflows

PyRecall

Local project memory and correction learning for Python workflows.

PyRecall keeps durable notes about your repository, turns corrections into reusable skills, and serves them back through a CLI or a stdio tool bridge that compatible coding tools can call.

No cloud account. No network calls for recall. Everything stays in .pyrecall/ inside your project.

Replay the same ~30s learn → recall session locally:

# Unix
bash examples/demo.sh

# Windows PowerShell
./examples/demo.ps1

Recording tips: docs/DEMO.md

Why

Coding tools forget project preferences between sessions. You correct the same mistake twice. PyRecall records the correction once and surfaces it the next time the same topic comes up — especially for Python testing, typing, packaging, and style conventions.

Install

pip install pyrecall-cli

This installs the pyrecall command and the pyrecall Python package.

If pyrecall is not found on Windows after install:

python -m pyrecall doctor
python -m pyrecall --help

Or add your user Scripts folder to PATH, then open a new terminal.

For local development:

pip install -e ".[dev]"

Requires Python 3.10+.

Quick start

cd your-python-project
pyrecall init
pyrecall harvest
pyrecall index
pyrecall setup-host
pyrecall learn --rejected "unittest.TestCase" --preferred "pytest assert + fixtures" --reason "Repo standard"
pyrecall recall "how should tests be written"

Free-form corrections

pyrecall learn --blob "os.path.join => Path / 'name'"
pyrecall learn --blob "avoid: bare except | prefer: except ValueError as exc"

Commands

Command	Purpose
pyrecall init	Create .pyrecall/, seed defaults, host rules + workflow
pyrecall harvest	Turn README / CONTRIBUTING / AGENTS bullets into conventions
pyrecall index	Index docs and Python module signals
pyrecall watch	Re-index when docs/config/Python files change
pyrecall remember	Store a decision / convention / note
pyrecall learn	Distill a correction into a skill
pyrecall recall	Search memories and skills (--tag, --why)
pyrecall skills	List learned skills
pyrecall forget	Deactivate a skill
pyrecall packs	List/install stack packs (fastapi, django, …)
pyrecall setup-host	Write host rules, bridge JSON, AGENTS.md section
pyrecall workflow	Print or write the before/after-edit checklist
pyrecall doctor	Check PATH / store health
pyrecall playbook	Write SKILLS.md from active skills
pyrecall stats	Show store counts
pyrecall export / import-data	Backup and restore JSON
pyrecall serve	Run the stdio tool bridge

Skill packs

pyrecall packs list
pyrecall packs install fastapi
pyrecall packs install django
pyrecall packs install sqlalchemy
pyrecall packs install ruff

Keep memory fresh

# one-shot
pyrecall index

# poll and re-index on change (side terminal)
pyrecall watch

Sticky workflow for hosts

pyrecall setup-host        # HOST_RULES.md + bridge JSON + AGENTS.md
pyrecall workflow          # print checklist
pyrecall harvest           # import conventions from project docs

setup-host writes .pyrecall/HOST_RULES.md (required get_context before edits, learn_correction on user fixes) and ready-to-copy bridge configs with your project cwd.

Stdio tool bridge

Compatible coding tools that speak JSON-RPC over stdio can attach PyRecall as a local tool server.

Full guide: docs/BRIDGE.md

Quick connect

pip install pyrecall-cli
cd your-python-project
pyrecall init
pyrecall serve

Add this to your host tool config (restart the host afterward):

{
  "pyrecall": {
    "command": "pyrecall",
    "args": ["serve"],
    "cwd": "/absolute/path/to/your/python-project"
  }
}

Windows / PATH-safe variant:

{
  "pyrecall": {
    "command": "python",
    "args": ["-m", "pyrecall", "serve"],
    "cwd": "C:/Users/you/projects/myapp"
  }
}

Ready-made files: bridge.client.json · bridge.mcp.json · bridge.windows.json

Tools exposed

Tool	Purpose
get_context	Required before edits — conventions + skills (+ why)
search_memory	Ranked search; optional tags filter
learn_correction	Required on user corrections — durable skill
add_memory	Store a decision / convention / note
list_skills	List active skills
install_pack	Install fastapi / django / sqlalchemy / ruff pack
harvest_docs	Import convention bullets from project docs
project_stats	Store counts

How learning works

1. You provide a rejected approach and a preferred approach.
2. PyRecall stores the correction and distills a named skill.
3. Later recall / get_context ranks that skill into the result set with BM25 + overlap scoring.
4. Skill hit counts increase when they are retrieved, so useful rules rise over time.

All ranking is local. There are no model downloads and no external APIs.

Storage layout

.pyrecall/
  config.json
  store.db
  WORKFLOW.md
  HOST_RULES.md
  bridge.mcp.json
  bridge.client.json
  bridge.python.json
  index/

Add .pyrecall/store.db to .gitignore if you do not want binary state in git. Export JSON when you want a reviewable backup.

Python defaults

pyrecall init seeds practical skills such as:

• prefer pytest over unittest
• type-hint public APIs
• pathlib over os.path
• context managers for I/O
• no bare except:
• pyproject-first configuration

Optional packs add FastAPI, Django, SQLAlchemy, and ruff conventions via pyrecall packs install ….

Development

pip install -e ".[dev]"
pytest
ruff check src tests

See CHANGELOG.md for release history, docs/LAUNCH.md for the public launch checklist, and docs/SPONSORS.md for funding setup.

License

MIT