Skip to main content

basemode-loom

Persistent branching exploration for LLM continuations.

basemode-loom lets you generate multiple continuations, navigate a tree of alternatives, and keep everything in a local SQLite store so you can resume later.

Install

pip install basemode-loom

Quickstart

# Create a new tree with 3 branches
basemode-loom run "The ship rounded the headland and" -n 3 -m gpt-4o-mini

# Open the interactive explorer
basemode-loom view

# Continue from selected branch
basemode-loom continue -b 2 -n 3

Core Commands

basemode-loom --help
basemode-loom view --help
basemode-loom run --help
basemode-loom continue --help
basemode-loom stats --help
basemode-loom serve --help

Useful commands:

  • basemode-loom view: interactive TUI tree explorer
  • basemode-loom run: create a new tree from a prompt
  • basemode-loom continue: branch from current/selected node
  • basemode-loom nodes|active|show|children: inspect stored trees
  • basemode-loom stats: analyze tree depth/branching/model usage
  • basemode-loom export|import: move trees in/out as JSON/Markdown
  • basemode-loom serve: run REST/WebSocket API for frontend usage

Tree Search

The TUI tree picker (Tab) supports live metadata filtering, category/domain/ source/model facets, ID lookup, FTS5 keyword search, and semantic search when the selected database contains a compatible vector index.

Guardian Angel corpora use the optional MLX search dependencies:

pip install 'basemode-loom[embed-mlx]'
basemode-loom view --db /path/to/corpus.sqlite

Press / in the tree picker, enter a query, and press Enter to rank matching trees. Build or update an embedding index directly with:

basemode-loom embed --db /path/to/corpus.sqlite --model mlx
basemode-loom embed --db /path/to/corpus.sqlite --model mlx --incremental

The MLX model is downloaded lazily on first use. Embedding dependencies remain isolated in the optional embed and embed-mlx installation extras.

Model Selection

  • TUI model picker is available via m.
  • Picker can consume verified model metadata from basemode when available.
  • Session state supports model-plan metadata for multi-model generation workflows.
  • Force OpenRouter passthrough for new/unknown IDs with -m "or:vendor/model" (or openrouter:vendor/model), e.g. -m "or:moonshotai/kimi-k2.6".

Storage

By default, data is stored in a local SQLite DB under your user data directory. Use --db /path/to/file.sqlite to choose a custom location.

Docs

Project docs live in docs/ (MkDocs):

make docs
make docs-serve

Then open http://localhost:8001.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

basemode_loom-0.5.1.tar.gz (398.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

basemode_loom-0.5.1-py3-none-any.whl (100.6 kB view details)

Uploaded Python 3

File details

Details for the file basemode_loom-0.5.1.tar.gz.

File metadata

  • Download URL: basemode_loom-0.5.1.tar.gz
  • Upload date:
  • Size: 398.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.12.5 {"installer":{"name":"uv","version":"0.12.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for basemode_loom-0.5.1.tar.gz
Algorithm Hash digest
SHA256 59af7de88158992f0ad04a53701534653df1dc2d5f6afcb69d906b819597f7ab
MD5 5f934986b1be8a998fea850f7adf1d9c
BLAKE2b-256 5b33d99d86c5b56291dd5b404a9930fae3c61856c1c4994fab3b990196701718

See more details on using hashes here.

File details

Details for the file basemode_loom-0.5.1-py3-none-any.whl.

File metadata

  • Download URL: basemode_loom-0.5.1-py3-none-any.whl
  • Upload date:
  • Size: 100.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.12.5 {"installer":{"name":"uv","version":"0.12.5","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for basemode_loom-0.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 2079c68cf0d7cad09bd62dd863f1c3a3cc1cc92a331d7b3c9c1ae2586cfba99d
MD5 9e7a7485c722bd11a26381dc38778316
BLAKE2b-256 dad096f1fe808f900d7d41a42c859ed00b4cef6290b935698e1767d9bad3f532

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.5.1 This release

2 files

0.5.0

2 files

0.4.1

2 files

0.3.0

2 files

0.2.1

2 files

0.2.0

2 files

0.1.3

2 files

0.1.2

2 files

0.1.1

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page