OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
RAG & Knowledge Systems

Treesearch

Treesearch is a Python document-retrieval library with Python and Rust command-line tools. It searches codebases and structured documents using SQLite FTS5 keyword matching over document tree structures, without vector embeddings or chunk splitting.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Treesearch — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when keyword-based retrieval over structured files is a fit and preserving document hierarchy matters, especially for codebases, technical documentation and papers.

Who it is for

  • Developers searching source code and repository documentation.
  • Teams adding retrieval to Python scripts, backend services or data pipelines.
  • Builders creating RAG systems over structured documents.

Documented uses

  • Find matching code or documentation across directories, files and glob patterns.
  • Retrieve ranked sections from papers and technical documents while retaining their heading relationships.
  • Add a structure-aware retrieval component to a RAG system or a custom repository search interface.
Before you choose

Requirements & limits

The README specifies Python 3.10 or later for the Python package. It also documents a Rust CLI and prebuilt binaries for listed macOS, Linux and Windows targets.

  • Retrieval uses SQLite FTS5 keyword matching rather than embeddings or chunk splitting.
  • Tree mode returns traversal paths in addition to ranked nodes; the default mode selects based on document type.
  • In-memory indexes are discarded when the process exits; a database path supports persistent, incremental indexing.
  • The Python library and CLI require a Python environment; the Rust CLI is documented as a standalone option.
  • Respect for .gitignore depends on installing the optional pathspec package.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install the Python package and prepare a search

Install TreeSearch for use in Python scripts, services or data pipelines.

Before you start

  • Python 3.10 or later.
  • A Python environment with package installation available.

Steps

  1. Install or upgrade the package with the command below.

    Documented command
    pip install -U pytreesearch

  2. Import the library with from treesearch import TreeSearch.

Expected outcome

The package is installed and its TreeSearch class can be imported for use in Python code.

Guide limitations

  • These steps cover installation and import, not a complete search workflow.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Retrieval-augmented applications

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
TreesearchFind matching code or documentation across directories, files and glob patterns.Linux, macOS, WindowsThe README specifies Python 3.10 or later for the Python package. It also documents a Rust CLI and prebuilt binaries for listed macOS, Linux and Windows targets.
LangsearchCrawl website or local data for a knowledge base.CLI, Self-hosted, Server
Hybrid Search RagCombine document retrieval and language-model generation in a configurable workflow.
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
12 October 2026
Original website title
shibing624/TreeSearch · Official homepage title · retained in its source language
How we review sourcesSuggest a correction