From ab417d4c41720219eb4381c0ca186aaf1773f7cf Mon Sep 17 00:00:00 2001 From: Oskar Hane Date: Fri, 26 Apr 2024 14:17:38 +0200 Subject: [PATCH] Update README (#20) --- .gitignore | 2 +- README.md | 2 +- docs/build/.buildinfo | 4 - docs/build/.doctrees/README.doctree | Bin 23822 -> 0 bytes docs/build/.doctrees/api.doctree | Bin 87181 -> 0 bytes docs/build/.doctrees/environment.pickle | Bin 336006 -> 0 bytes docs/build/.doctrees/index.doctree | Bin 5081 -> 0 bytes docs/build/.doctrees/neo4j_genai.doctree | Bin 60246 -> 0 bytes docs/build/.doctrees/retrieval.doctree | Bin 62026 -> 0 bytes docs/build/README.html | 311 ------ docs/build/_sources/README.md.txt | 170 ---- docs/build/_sources/api.rst.txt | 43 - docs/build/_sources/index.rst.txt | 21 - docs/build/_static/basic.css | 925 ------------------ docs/build/_static/css/neo4j.css | 642 ------------ docs/build/_static/css/nunito-sans.css | 200 ---- docs/build/_static/css/site.css | 8 - docs/build/_static/doctools.js | 156 --- 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src/neo4j_genai/queries.py diff --git a/.gitignore b/.gitignore index c5ed14b25..16c7907ed 100644 --- a/.gitignore +++ b/.gitignore @@ -6,4 +6,4 @@ dist/ htmlcov/ .idea/ .env -docs/build +docs/build/ diff --git a/README.md b/README.md index 8272e13ca..10096a060 100644 --- a/README.md +++ b/README.md @@ -80,7 +80,7 @@ create_vector_index( ### Populating the Neo4j Vector Index -This library does not write to the database, that is up to you. +This library does not write to the database, that is up to you. See below for how to write using Cypher via the Neo4j driver. Assumption: Neo4j running with a defined vector index diff --git a/docs/build/.buildinfo b/docs/build/.buildinfo deleted file mode 100644 index 7fc617e3a..000000000 --- a/docs/build/.buildinfo +++ /dev/null @@ -1,4 +0,0 @@ -# Sphinx build info version 1 -# This file hashes the configuration used when building these files. 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z$0lIo^>%nE0)_<EW%bOco7EJr4TkXL4}fVgRux^>?9;$^Q>!(UMi^`7;+-3 zL`nXO9!d&_y%dK&i4yofFB2j!^LWhJ*q315h0k(H!ZyL t))Zo3+_`{8gh&9h@z#WUs=2p1UbEe65lgX5l=ftcxH#M!V2jTB{|EA^s}}$O diff --git a/docs/build/README.html b/docs/build/README.html deleted file mode 100644 index 870d01cd4..000000000 --- a/docs/build/README.html +++ /dev/null @@ -1,311 +0,0 @@ - - - - - - - - Neo4j GenAI package for Python — neo4j-genai-python documentation - - - - - - - - - - - - - -
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Neo4j GenAI package for Python

-

This repository contains the official Neo4j GenAI features for Python.

-

The purpose of this package is to provide a first party package to developers, -where Neo4j can guarantee long term commitment and maintenance as well as being -fast to ship new features and high performing patterns and methods.

-

Docs are coming soon!

-
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Usage

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Installation

-

This package requires Python (>=3.8.1).

-

To install the latest stable version, use:

-
pip install neo4j-genai
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Examples

-

While the library has more retrievers than shown here, the following examples should be able to get you started.

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Creating a vector index

-

When creating a vector index, make sure you match the number of dimensions in the index with the number of dimensions the embeddings have.

-

Assumption: Neo4j running

-
from neo4j import GraphDatabase
-from neo4j_genai.indexes import create_vector_index
-
-URI = "neo4j://localhost:7687"
-AUTH = ("neo4j", "password")
-
-INDEX_NAME = "chunk-index"
-
-# Connect to Neo4j database
-driver = GraphDatabase.driver(URI, auth=AUTH)
-
-# Creating the index
-create_vector_index(
-    driver,
-    INDEX_NAME,
-    label="Document",
-    property="textProperty",
-    dimensions=1536,
-    similarity_fn="euclidean",
-)
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Populating the Neo4j Vector Index

-

This library does not write to the database, that is up to you. -See below for how to write using Cypher via the Neo4j driver.

-

Assumption: Neo4j running with a defined vector index

-
from neo4j import GraphDatabase
-from random import random
-
-URI = "neo4j://localhost:7687"
-AUTH = ("neo4j", "password")
-
-# Connect to Neo4j database
-driver = GraphDatabase.driver(URI, auth=AUTH)
-
-# Upsert the vector
-vector = [random() for _ in range(DIMENSION)]
-insert_query = (
-    "MERGE (n:Document {id: $id})"
-    "WITH n "
-    "CALL db.create.setNodeVectorProperty(n, 'textProperty', $vector)"
-    "RETURN n"
-)
-parameters = {
-    "id": 0,
-    "vector": vector,
-}
-driver.execute_query(insert_query, parameters)
-
-
-
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-

Development

-
-

Install dependencies

-
poetry install
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Getting started

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Issues

-

If you have a bug to report or feature to request, first -search to see if an issue already exists. -If a related issue doesn’t exist, please raise a new issue using the relevant -issue form.

-

If you’re a Neo4j Enterprise customer, you can also reach out to Customer Support.

-

If you don’t have a bug to report or feature request, but you need a hand with -the library; community support is available via Neo4j Online Community -and/or Discord.

-
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-

Make changes

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    -

  1. Fork the repository.

    2. -

  2. Install Python and Poetry. For more information, see the development guide.

    3. -

  3. Create a working branch from main and start with your changes!

    4. -
-
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-

Pull request

-

When you’re finished with your changes, create a pull request, also known as a PR.

-
    -

  • Ensure that you have signed the CLA.

    • -

  • Ensure that the base of your PR is set to main.

    • -

  • Don’t forget to link your PR to an issue -if you are solving one.

    • -

  • Enable the checkbox to allow maintainer edits -so that maintainers can make any necessary tweaks and update your branch for merge.

    • -

  • Reviewers may ask for changes to be made before a PR can be merged, either using -suggested changes -or normal pull request comments. You can apply suggested changes directly through -the UI, and any other changes can be made in your fork and committed to the PR branch.

    • -

  • As you update your PR and apply changes, mark each conversation as resolved.

    • -
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Run tests

-

Open a new virtual environment and then run the tests.

-
poetry shell
-pytest
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Further information

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- -
-
- - - - - - \ No newline at end of file diff --git a/docs/build/_sources/README.md.txt b/docs/build/_sources/README.md.txt deleted file mode 100644 index 10096a060..000000000 --- a/docs/build/_sources/README.md.txt +++ /dev/null @@ -1,170 +0,0 @@ -# Neo4j GenAI package for Python - -This repository contains the official Neo4j GenAI features for Python. - -The purpose of this package is to provide a first party package to developers, -where Neo4j can guarantee long term commitment and maintenance as well as being -fast to ship new features and high performing patterns and methods. - -Docs are coming soon! - -# Usage - -## Installation - -This package requires Python (>=3.8.1). - -To install the latest stable version, use: - -```shell -pip install neo4j-genai -``` - -## Examples - -While the library has more retrievers than shown here, the following examples should be able to get you started. - -### Performing a similarity search - -Assumption: Neo4j running with populated vector index in place. - -```python -from neo4j import GraphDatabase -from neo4j_genai import VectorRetriever - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "embedding-name" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Initialize the retriever -retriever = VectorRetriever(driver, INDEX_NAME) - -# Run the similarity search -query_text = "How do I do similarity search in Neo4j?" -response = retriever.search(query_text=query_text, top_k=5) -``` - -### Creating a vector index - -When creating a vector index, make sure you match the number of dimensions in the index with the number of dimensions the embeddings have. - -Assumption: Neo4j running - -```python -from neo4j import GraphDatabase -from neo4j_genai.indexes import create_vector_index - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "chunk-index" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Creating the index -create_vector_index( - driver, - INDEX_NAME, - label="Document", - property="textProperty", - dimensions=1536, - similarity_fn="euclidean", -) - -``` - -### Populating the Neo4j Vector Index - -This library does not write to the database, that is up to you. -See below for how to write using Cypher via the Neo4j driver. - -Assumption: Neo4j running with a defined vector index - -```python -from neo4j import GraphDatabase -from random import random - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Upsert the vector -vector = [random() for _ in range(DIMENSION)] -insert_query = ( - "MERGE (n:Document {id: $id})" - "WITH n " - "CALL db.create.setNodeVectorProperty(n, 'textProperty', $vector)" - "RETURN n" -) -parameters = { - "id": 0, - "vector": vector, -} -driver.execute_query(insert_query, parameters) -``` - -# Development - -## Install dependencies - -```bash -poetry install -``` - -## Getting started - -### Issues - -If you have a bug to report or feature to request, first -[search to see if an issue already exists](https://docs.github.com/en/github/searching-for-information-on-github/searching-on-github/searching-issues-and-pull-requests#search-by-the-title-body-or-comments). -If a related issue doesn't exist, please raise a new issue using the relevant -[issue form](https://github.com/neo4j/neo4j-genai-python/issues/new/choose). - -If you're a Neo4j Enterprise customer, you can also reach out to [Customer Support](http://support.neo4j.com/). - -If you don't have a bug to report or feature request, but you need a hand with -the library; community support is available via [Neo4j Online Community](https://community.neo4j.com/) -and/or [Discord](https://discord.gg/neo4j). - -### Make changes - -1. Fork the repository. -2. Install Python and Poetry. For more information, see [the development guide](./docs/contributing/DEVELOPING.md). -3. Create a working branch from `main` and start with your changes! - -### Pull request - -When you're finished with your changes, create a pull request, also known as a PR. - -- Ensure that you have [signed the CLA](https://neo4j.com/developer/contributing-code/#sign-cla). -- Ensure that the base of your PR is set to `main`. -- Don't forget to [link your PR to an issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue) - if you are solving one. -- Enable the checkbox to [allow maintainer edits](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/allowing-changes-to-a-pull-request-branch-created-from-a-fork) - so that maintainers can make any necessary tweaks and update your branch for merge. -- Reviewers may ask for changes to be made before a PR can be merged, either using - [suggested changes](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/reviewing-changes-in-pull-requests/incorporating-feedback-in-your-pull-request) - or normal pull request comments. You can apply suggested changes directly through - the UI, and any other changes can be made in your fork and committed to the PR branch. -- As you update your PR and apply changes, mark each conversation as [resolved](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request#resolving-conversations). - -## Run tests - -Open a new virtual environment and then run the tests. - -```bash -poetry shell -pytest -``` - -## Further information - -- [The official Neo4j Python driver](https://github.com/neo4j/neo4j-python-driver) -- [Neo4j GenAI integrations](https://neo4j.com/docs/cypher-manual/current/genai-integrations/) diff --git a/docs/build/_sources/api.rst.txt b/docs/build/_sources/api.rst.txt deleted file mode 100644 index 7e46f2f40..000000000 --- a/docs/build/_sources/api.rst.txt +++ /dev/null @@ -1,43 +0,0 @@ -.. _api-documentation: - -API Documentation -################# - -************************************ -Retrieval-Augmented Generation (RAG) -************************************ -RAG is a technique that enhances Large Language Model (LLM) responses by retrieving -source information from external data stores to augment generated responses. - -This package enables Python developers to use perform RAG using Neo4j. - -********** -Retrievers -********** - -VectorRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.vector.VectorRetriever - :members: - - -VectorCypherRetriever -===================== - -.. autoclass:: neo4j_genai.retrievers.vector.VectorCypherRetriever - :members: - - -HybridRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.hybrid.HybridRetriever - :members: - - -HybridCypherRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.hybrid.HybridCypherRetriever - :members: diff --git a/docs/build/_sources/index.rst.txt b/docs/build/_sources/index.rst.txt deleted file mode 100644 index bec1b20ee..000000000 --- a/docs/build/_sources/index.rst.txt +++ /dev/null @@ -1,21 +0,0 @@ -.. neo4j-genai-python documentation master file, created by - sphinx-quickstart on Tue Apr 9 16:36:43 2024. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - -Welcome to neo4j-genai-python's documentation! -============================================== - -.. toctree:: - :maxdepth: 2 - :caption: Contents: - - api.rst - - -Indices and tables -================== - -* :ref:`genindex` -* :ref:`modindex` -* :ref:`search` diff --git a/docs/build/_static/basic.css b/docs/build/_static/basic.css deleted file mode 100644 index 30fee9d0f..000000000 --- a/docs/build/_static/basic.css +++ /dev/null @@ -1,925 +0,0 @@ -/* - * basic.css - * ~~~~~~~~~ - * - * Sphinx stylesheet -- basic theme. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -/* -- main layout ----------------------------------------------------------- */ - 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#indexlinklabel { - margin: 0.8rem 0 0.5rem; -} - -body.sphinx #searchlabel, -body.sphinx #indexlinklabel { - margin: 0.8rem 0 0.5rem; -} - -body.sphinx #searchbox .search, -body.sphinx .content .search { - display: block; - opacity: 1; - position: relative; - background: initial; -} - -@media screen and (min-width: 1024px) { - - body.sphinx .toolbar { - background: initial; - box-shadow: none; - height: 0; - } - - .navbar-item, .navbar-link { - -webkit-box-align: center; - -ms-flex-align: center; - align-items: center; - display: -webkit-box; - display: -ms-flexbox; - display: flex; - } - - body.sphinx .nav-container { - border: none; - } - - body.sphinx .nav, - body.sphinx .nav-panel-menu { - height: auto; - background: initial; - } - - body.sphinx .sphinxsidebar { - background: #f5f7fa; - position: static; - } - - body.sphinx .sphinxsidebarwrapper { - position: sticky; - top: 3.77778rem; - height: calc(100vh - 3.77778rem); - overflow-y: auto; - } - - body.sphinx .nav-panel-menu:not(.is-active)::after { - background: initial; - } - - body.sphinx .navbar-start { - display: -webkit-box; - display: -ms-flexbox; - display: flex; - max-width: 63.11111rem; - -webkit-box-flex: 1; - -ms-flex-positive: 1; - flex-grow: 1; - -webkit-box-align: center; - -ms-flex-align: center; - align-items: center; - margin-right: 2rem; - } - - body.sphinx .navbar-start .navbar-link { - margin-left: auto; - } -} - -.navbar-item, .navbar-link { - color: #4a5568; - line-height: 1.8; - padding: 0.5rem 1rem; - position: relative; -} - -@media screen and (min-width: 769px) { - .doc>.sect-header>h1.page:first-child { - margin-top: 2.5rem; - } -} - -.doc>section>h1:first-child { - font-size: 2rem; - margin: 1.5rem 0.5rem 1.5rem 0; - -webkit-box-flex: 1; - -ms-flex-positive: 1; - flex-grow: 1; -} -.doc h1, .doc h2, .doc h3, .doc h4, .doc h5, .doc h6 { - color: #4a5568; - font-weight: 400; - -webkit-hyphens: none; - -ms-hyphens: none; - hyphens: none; - line-height: 1.3; - margin: 2rem 0 1rem; -} - -.doc a.headerlink { - visibility: hidden; - margin-left: 0.5rem; -} - -h1:hover > a.headerlink, -h2:hover > a.headerlink, -h3:hover > a.headerlink, -h4:hover > a.headerlink, -h5:hover > a.headerlink, -h6:hover > a.headerlink, -dt:hover > a.headerlink, -caption:hover > a.headerlink, -p.caption:hover > a.headerlink, -div.code-block-caption:hover > a.headerlink { - visibility: visible; -} - -.nav-menu .caption { - padding: 0.5rem 1.5rem; - font-size: 1.5rem; -} - -.nav-menu ul { - padding-left: 0; -} - - - -.nav-menu li.toctree-l1 { - list-style: none; - position: relative; -} - -.nav-menu .toctree-l1>a, -.nav-menu .toctree-l1>span { - padding-left: 1.5rem; -} - -.nav-menu .toctree-l1>a, -.nav-menu .toctree-l1>span { - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.nav-menu .toctree-l1 a:hover, -.nav-menu .toctree-l1 span:hover { - background-color: #e6e9ee; -} - -.nav-menu .toctree-l1>a.current { - background-color: #e6f8ff; - color: #0056b3; -} - -.nav-menu .toctree-l1>a.current::before { - content: ""; - width: 4px; - height: 100%; - position: absolute; - left: 0; - top: 0; - background: #0056b3; - border-radius: 4px; -} - -.toctree-l1>a, .toctree-l1>span { - position: relative; - padding-right: 2rem; -} - -.nav-menu li.toctree-l2 { - list-style: none; - position: relative; -} - -.nav-menu .toctree-l2>a, -.nav-menu .toctree-l2>span { - padding-left: 2.5rem; -} - -.nav-menu .toctree-l2>a, -.nav-menu .toctree-l2>span { - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.nav-menu .toctree-l2 a:hover, -.nav-menu .toctree-l2 span:hover { - background-color: #e6e9ee; -} - -.nav-menu .toctree-l2>a.current { - background-color: #e6f8ff; - color: #0056b3; -} - -.nav-menu .toctree-l2>a.current::before { - content: ""; - width: 4px; - height: 100%; - position: absolute; - left: 0; - top: 0; - background: #0056b3; - border-radius: 4px; -} - -.toctree-l2>a, .toctree-l2>span { - position: relative; - padding-right: 2rem; -} - -.nav-menu li.toctree-l3 { - list-style: none; - position: relative; -} - -.nav-menu .toctree-l3>a, -.nav-menu .toctree-l3>span { - padding-left: 3.5rem; -} - -.nav-menu .toctree-l3>a, -.nav-menu .toctree-l3>span { - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.nav-menu .toctree-l3 a:hover, -.nav-menu .toctree-l3 span:hover { - background-color: #e6e9ee; -} - -.nav-menu .toctree-l3>a.current { - background-color: #e6f8ff; - color: #0056b3; -} - -.nav-menu .toctree-l3>a.current::before { - content: ""; - width: 4px; - height: 100%; - position: absolute; - left: 0; - top: 0; - background: #0056b3; - border-radius: 4px; -} - -.toctree-l3>a, .toctree-l3>span { - position: relative; - padding-right: 2rem; -} - - -.nav-menu li a code { - font-family: inherit -} - -.is-current-page>.nav-link, -.is-current-page>.nav-text { - font-weight: 400; -} - -.nav-menu a, .nav-text { - color: #535b66; - font-weight: 400; - display: block; - padding: 0.25rem 0; -} - -/* lists */ - -body.sphinx .doc ul li{ - margin-bottom: 0; -} - -/* functions */ - -body.sphinx .doc dl.py.function { - padding: 0 1rem; - /* border-top: 2px dotted #eee; */ -} - -/* deprecated */ - -body.sphinx .deprecated::after, -body.sphinx .deprecated > *::after { - content: unset; -} - -body.sphinx .doc dl.deprecated dt:first-of-type span.sig-prename, -body.sphinx .doc dl.deprecated dt:first-of-type span.sig-name { - border-bottom: 1px solid #f6ad55; - /* color: #702459; */ - /* background-color: #fed7e2; */ -} - -body.sphinx .doc dl.deprecated { - margin-bottom: 0; - padding-bottom: 0; -} - -body.sphinx .doc div.deprecated { - padding: 1rem 1rem 0.75rem; - margin: 0.5rem 1.5rem; - /* color: #702459; */ - border-left: 4px solid #f6ad55; - border-radius: .25rem; - background-color: #fffaf0; -} - -.sphinx .doc .deprecated > :first-child { - margin-top: 0; -} - -.sphinx .doc .deprecated > :last-child { - margin-bottom: 0; -} - -b, strong { - font-weight: 800; -} - -dt { - font-weight: initial; -} - -.sphinx .doc .admonition { - margin: 0.5rem 1.5rem; - border-left: 4px solid #2d3748; - border-radius: .25rem; - padding: 1rem 1rem 0.75rem; - font-size: .88889rem -} - -.sphinx .doc .admonition .admonition-title:after { - content: ":"; -} - -.sphinx .doc .admonition .admonition-title, -.sphinx .doc .admonition .admonition-title + p { - display: inline; -} - -.sphinx .doc .admonition > :last-child { - margin-bottom: 0; -} - -.sphinx .doc .admonition > table { - border-collapse: collapse; - table-layout: fixed; - position: relative; - width: 100% -} - -.sphinx .doc .admonition .content { - padding: 1rem 1rem .75rem; - width: 100% -} - -.sphinx .doc .admonition .listingblock .content { - padding: 0 -} - -.sphinx .doc .admonition .icon { - display: none -} - -.sphinx .doc .admonition a.btn { - display: inline-block; - background: #000; - color: #fff !important; - padding: .5rem 2rem; - border-radius: .5rem -} - -.sphinx .doc .admonition a.btn::after { - display: none !important -} - -.sphinx .doc .admonition.warning { - background-color: #fed7d7; - color: #742a2a; - border-left-color: #e53e3e -} - -.sphinx .doc .admonition.warning pre { - background-color: #fff5f5; - color: #c53030 -} - -.sphinx .doc .admonition.warning a.btn { - background-color: #e53e3e -} - -.sphinx .doc .admonition.warning a { - color: #f56565 -} - -.sphinx .doc .admonition.caution { - background-color: #feebc8; - color: #7b341e; - border-left-color: #dd6b20 -} - -.sphinx .doc .admonition.caution a { - color: #ed8936 -} - -.sphinx .doc .admonition.caution a:hover { - color: #f6ad55 -} - -.sphinx .doc .admonition.caution a.btn { - background-color: #dd6b20 -} - -.sphinx .doc .admonition.caution pre { - background-color: #fffaf0; - color: #c05621 -} - -.sphinx .doc .admonition.tip, .sphinx .doc .admonition.note { - background-color: #bee3f8; - color: #2a4365; - border-left-color: #3182ce -} - -.sphinx .doc .admonition.tip a, .sphinx .doc .admonition.note a { - color: #3182ce -} - -.sphinx .doc .admonition.tip a:hover, .sphinx .doc .admonition.note a:hover { - color: #4299e1 -} - -.sphinx .doc .admonition.tip a.btn, .sphinx .doc .admonition.note a.btn { - background-color: #3182ce -} - -.sphinx .doc .admonition.tip pre, .sphinx .doc .admonition.note pre { - background-color: #ebf8ff; - color: #2b6cb0 -} - -.sphinx .doc .admonition.seealso { - background-color: #edf2f7; - color: #1a202c; - border-left-color: #718096 -} - -.sphinx .doc .admonition.seealso a { - color: #718096 -} - -.sphinx .doc .admonition.seealso a:hover { - color: #a0aec0 -} - -.sphinx .doc .admonition.seealso a.btn { - background-color: #718096 -} - -.sphinx .doc .admonition.important { - background-color: #e9d8fd; - color: #44337a; - border-left-color: #805ad5 -} - -.sphinx .doc .admonition.important a { - color: #805ad5 -} - -.sphinx .doc .admonition.important a:hover { - color: #9f7aea -} - -.sphinx .doc .admonition.important a.btn { - background-color: #805ad5 -} - -dd > :first-child { - margin-top: 0; -} - -.field-list p { - margin: 0; -} - -dl.field-list { - display: grid; - grid-template-columns: fit-content(30%) auto; -} - -dl.field-list > dt { - font-weight: bold; - /*word-break: break-word;*/ - padding-left: 0.5em; - padding-right: 5px; -} - - -dl.field-list > dd { - padding-left: 0.5em; - margin-left: 0; -} - -dl > dd:last-child, -dl > dd:last-child > :last-child { - margin-bottom: 0; -} - -dl.field-list > dd > ul, -dl.field-list > dd > ol { - padding-left: 1.9em; - margin-left: 0; -} - -.content ol li > p:first-of-type, -.content ul li > p:first-of-type { - margin-top: 0; -} - -.content ol li > p:last-of-type, -.content ul li > p:last-of-type { - margin-bottom: 0; -} - - -table.docutils { - margin-top: 10px; - margin-bottom: 10px; - border: 0; - border-collapse: collapse; -} - -table.docutils td, table.docutils th { - padding: 1px 8px 1px 5px; - border: 0; -} - -table.docutils > tbody > tr:not(:last-child) > td, -table.docutils > tbody > tr:not(:last-child) > td, -table.docutils > thead > tr:not(:last-child) > td, -table.docutils > thead > tr:not(:last-child) > td, -table.docutils > tr:not(:last-child) > td, -table.docutils > tr:not(:last-child) > td { - border-bottom: 1px solid #aaa; -} - -th > :first-child, -td > :first-child { - margin-top: 0; -} - -th > :last-child, -td > :last-child { - margin-bottom: 0; -} - -.sig-name, code.descname { - font-weight: bold; -} - -.sig-paren { - font-size: larger; -} - -.versionmodified { - font-style: italic; -} \ No newline at end of file diff --git a/docs/build/_static/css/nunito-sans.css b/docs/build/_static/css/nunito-sans.css deleted file mode 100644 index dfd39b79d..000000000 --- a/docs/build/_static/css/nunito-sans.css +++ /dev/null @@ -1,200 +0,0 @@ -/* cyrillic-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic-ext.woff2) format('woff2'); - unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; -} -/* cyrillic */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic.woff2) format('woff2'); - unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; -} -/* vietnamese */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-vietnamese.woff2) format('woff2'); - unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; -} -/* latin-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin-ext.woff2) format('woff2'); - unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF; -} -/* latin */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin.woff2) format('woff2'); - unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; -} -/* cyrillic-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic-ext.woff2) format('woff2'); - unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; -} -/* cyrillic */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic.woff2) format('woff2'); - unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; -} -/* vietnamese */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-vietnamese.woff2) format('woff2'); - unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; -} -/* latin-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin-ext.woff2) format('woff2'); - unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF; -} -/* latin */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin.woff2) format('woff2'); - unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; -} -/* cyrillic-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 600; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic-ext.woff2) format('woff2'); - unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; -} -/* cyrillic */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 600; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic.woff2) format('woff2'); - unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; -} -/* vietnamese */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 600; - font-stretch: 100%; - font-display: swap; 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e.preventDefault() - } - var topOffset = toolbar ? toolbar.getBoundingClientRect().bottom : headerNavigationBar.getBoundingClientRect().bottom - - if (cheatSheet) { - var scrollTarget = this.closest('div') - var selectorsTop = document.querySelector('.nav-container .selectors').querySelector('div').getBoundingClientRect().top - if (this.tagName === 'H3') topOffset = selectorsTop - window.scrollTo(0, computePosition(scrollTarget, 0) - topOffset) - } else { - window.scrollTo(0, computePosition(this, 0) - topOffset) - } - } - - window.addEventListener('load', function jumpOnLoad (e) { - var fragment, target - if ((fragment = decodeFragment(window.location.hash)) && (target = document.getElementById(fragment))) { - jumpToAnchor.bind(target)() - setTimeout(jumpToAnchor.bind(target), 0) - } - window.removeEventListener('load', jumpOnLoad) - }) - - Array.prototype.slice.call(document.querySelectorAll('a[href^="#"]')).forEach(function (el) { - var fragment, target - if ((fragment = decodeFragment(el.hash)) && (target = document.getElementById(fragment))) { - el.addEventListener('click', jumpToAnchor.bind(target)) - } - }) -})() diff --git a/docs/build/_static/language_data.js b/docs/build/_static/language_data.js deleted file mode 100644 index 250f5665f..000000000 --- a/docs/build/_static/language_data.js +++ /dev/null @@ -1,199 +0,0 @@ -/* - * language_data.js - * ~~~~~~~~~~~~~~~~ - * - * This script contains the language-specific data used by searchtools.js, - * namely the list of stopwords, stemmer, scorer and splitter. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; - - -/* Non-minified version is copied as a separate JS file, is available */ - -/** - * Porter Stemmer - */ -var Stemmer = function() { - - var step2list = { - ational: 'ate', - tional: 'tion', - enci: 'ence', - anci: 'ance', - izer: 'ize', - bli: 'ble', - alli: 'al', - entli: 'ent', - eli: 'e', - ousli: 'ous', - ization: 'ize', - ation: 'ate', - ator: 'ate', - alism: 'al', - iveness: 'ive', - fulness: 'ful', - ousness: 'ous', - aliti: 'al', - iviti: 'ive', - biliti: 'ble', - logi: 'log' - }; - - var step3list = { - icate: 'ic', - ative: '', - alize: 'al', - iciti: 'ic', - ical: 'ic', - ful: '', - ness: '' - }; - - var c = "[^aeiou]"; // consonant - var v = "[aeiouy]"; // vowel - var C = c + "[^aeiouy]*"; // consonant sequence - var V = v + "[aeiou]*"; // vowel sequence - - var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 - var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 - var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 - var s_v = "^(" + C + ")?" + v; // vowel in stem - - this.stemWord = function (w) { - var stem; - var suffix; - var firstch; - var origword = w; - - if (w.length < 3) - return w; - - var re; - var re2; - var re3; - var re4; - - firstch = w.substr(0,1); - if (firstch == "y") - w = firstch.toUpperCase() + w.substr(1); - - // Step 1a - re = /^(.+?)(ss|i)es$/; - re2 = /^(.+?)([^s])s$/; - - if (re.test(w)) - w = w.replace(re,"$1$2"); - else if (re2.test(w)) - w = w.replace(re2,"$1$2"); - - // Step 1b - re = /^(.+?)eed$/; - re2 = /^(.+?)(ed|ing)$/; - if (re.test(w)) { - var fp = re.exec(w); - re = new RegExp(mgr0); - if (re.test(fp[1])) { - re = /.$/; - w = w.replace(re,""); - } - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1]; - re2 = new RegExp(s_v); - if (re2.test(stem)) { - w = stem; - re2 = /(at|bl|iz)$/; - re3 = new RegExp("([^aeiouylsz])\\1$"); - re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re2.test(w)) - w = w + "e"; - else if (re3.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - else if (re4.test(w)) - w = w + "e"; - } - } - - // Step 1c - re = /^(.+?)y$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(s_v); - if (re.test(stem)) - w = stem + "i"; - } - - // Step 2 - re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step2list[suffix]; - } - - // Step 3 - re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step3list[suffix]; - } - - // Step 4 - re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; - re2 = /^(.+?)(s|t)(ion)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - if (re.test(stem)) - w = stem; - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1] + fp[2]; - re2 = new RegExp(mgr1); - if (re2.test(stem)) - w = stem; - } - - // Step 5 - re = /^(.+?)e$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - re2 = new RegExp(meq1); - re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) - w = stem; - } - re = /ll$/; - re2 = new RegExp(mgr1); - if (re.test(w) && re2.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - - // and turn initial Y back to y - if (firstch == "y") - w = firstch.toLowerCase() + w.substr(1); - return w; - } -} - diff --git a/docs/build/_static/menu.svg b/docs/build/_static/menu.svg deleted file mode 100644 index 1cc79e63c..000000000 --- a/docs/build/_static/menu.svg +++ /dev/null @@ -1 +0,0 @@ - diff --git a/docs/build/_static/minus.png b/docs/build/_static/minus.png deleted file mode 100644 index d96755fdaf8bb2214971e0db9c1fd3077d7c419d..0000000000000000000000000000000000000000 GIT binary patch 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* ~~~~~~~~~~~~~~~~ - * - * Sphinx JavaScript utilities for the full-text search. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ -"use strict"; - -/** - * Simple result scoring code. - */ -if (typeof Scorer === "undefined") { - var Scorer = { - // Implement the following function to further tweak the score for each result - // The function takes a result array [docname, title, anchor, descr, score, filename] - // and returns the new score. - /* - score: result => { - const [docname, title, anchor, descr, score, filename] = result - return score - }, - */ - - // query matches the full name of an object - objNameMatch: 11, - // or matches in the last dotted part of the object name - objPartialMatch: 6, - // Additive scores depending on the priority of the object - objPrio: { - 0: 15, // used to be importantResults - 1: 5, // used to be objectResults - 2: -5, // used to be unimportantResults - }, - // Used when the priority is not in the mapping. - objPrioDefault: 0, - - // query found in title - title: 15, - partialTitle: 7, - // query found in terms - term: 5, - partialTerm: 2, - }; -} - -const _removeChildren = (element) => { - while (element && element.lastChild) element.removeChild(element.lastChild); -}; - -/** - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping - */ -const _escapeRegExp = (string) => - string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string - -const _displayItem = (item, searchTerms, highlightTerms) => { - const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; - const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; - const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; - const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; - const contentRoot = document.documentElement.dataset.content_root; - - const [docName, title, anchor, descr, score, _filename] = item; - - let listItem = document.createElement("li"); - let requestUrl; - let linkUrl; - if (docBuilder === "dirhtml") { - // dirhtml builder - let dirname = docName + "/"; - if (dirname.match(/\/index\/$/)) - dirname = dirname.substring(0, dirname.length - 6); - else if (dirname === "index/") dirname = ""; - requestUrl = contentRoot + dirname; - linkUrl = requestUrl; - } else { - // normal html builders - requestUrl = contentRoot + docName + docFileSuffix; - linkUrl = docName + docLinkSuffix; - } - let linkEl = listItem.appendChild(document.createElement("a")); - linkEl.href = linkUrl + anchor; - linkEl.dataset.score = score; - linkEl.innerHTML = title; - if (descr) { - listItem.appendChild(document.createElement("span")).innerHTML = - " (" + descr + ")"; - // highlight search terms in the description - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - } - else if (showSearchSummary) - fetch(requestUrl) - .then((responseData) => responseData.text()) - .then((data) => { - if (data) - listItem.appendChild( - Search.makeSearchSummary(data, searchTerms) - ); - // highlight search terms in the summary - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - }); - Search.output.appendChild(listItem); -}; -const _finishSearch = (resultCount) => { - Search.stopPulse(); - Search.title.innerText = _("Search Results"); - if (!resultCount) - Search.status.innerText = Documentation.gettext( - "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." - ); - else - Search.status.innerText = _( - `Search finished, found ${resultCount} page(s) matching the search query.` - ); -}; -const _displayNextItem = ( - results, - resultCount, - searchTerms, - highlightTerms, -) => { - // results left, load the summary and display it - // this is intended to be dynamic (don't sub resultsCount) - if (results.length) { - _displayItem(results.pop(), searchTerms, highlightTerms); - setTimeout( - () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), - 5 - ); - } - // search finished, update title and status message - else _finishSearch(resultCount); -}; - -/** - * Default splitQuery function. Can be overridden in ``sphinx.search`` with a - * custom function per language. - * - * The regular expression works by splitting the string on consecutive characters - * that are not Unicode letters, numbers, underscores, or emoji characters. - * This is the same as ``\W+`` in Python, preserving the surrogate pair area. - */ -if (typeof splitQuery === "undefined") { - var splitQuery = (query) => query - .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) - .filter(term => term) // remove remaining empty strings -} - -/** - * Search Module - */ -const Search = { - _index: null, - _queued_query: null, - _pulse_status: -1, - - htmlToText: (htmlString) => { - const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); - htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() }); - const docContent = htmlElement.querySelector('[role="main"]'); - if (docContent !== undefined) return docContent.textContent; - console.warn( - "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." - ); - return ""; - }, - - init: () => { - const query = new URLSearchParams(window.location.search).get("q"); - document - .querySelectorAll('input[name="q"]') - .forEach((el) => (el.value = query)); - if (query) Search.performSearch(query); - }, - - loadIndex: (url) => - (document.body.appendChild(document.createElement("script")).src = url), - - setIndex: (index) => { - Search._index = index; - if (Search._queued_query !== null) { - const query = Search._queued_query; - Search._queued_query = null; - Search.query(query); - } - }, - - hasIndex: () => Search._index !== null, - - deferQuery: (query) => (Search._queued_query = query), - - stopPulse: () => (Search._pulse_status = -1), - - startPulse: () => { - if (Search._pulse_status >= 0) return; - - const pulse = () => { - Search._pulse_status = (Search._pulse_status + 1) % 4; - Search.dots.innerText = ".".repeat(Search._pulse_status); - if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); - }; - pulse(); - }, - - /** - * perform a search for something (or wait until index is loaded) - */ - performSearch: (query) => { - // create the required interface elements - const searchText = document.createElement("h2"); - searchText.textContent = _("Searching"); - const searchSummary = document.createElement("p"); - searchSummary.classList.add("search-summary"); - searchSummary.innerText = ""; - const searchList = document.createElement("ul"); - searchList.classList.add("search"); - - const out = document.getElementById("search-results"); - Search.title = out.appendChild(searchText); - Search.dots = Search.title.appendChild(document.createElement("span")); - Search.status = out.appendChild(searchSummary); - Search.output = out.appendChild(searchList); - - const searchProgress = document.getElementById("search-progress"); - // Some themes don't use the search progress node - if (searchProgress) { - searchProgress.innerText = _("Preparing search..."); - } - Search.startPulse(); - - // index already loaded, the browser was quick! - if (Search.hasIndex()) Search.query(query); - else Search.deferQuery(query); - }, - - /** - * execute search (requires search index to be loaded) - */ - query: (query) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - const allTitles = Search._index.alltitles; - const indexEntries = Search._index.indexentries; - - // stem the search terms and add them to the correct list - const stemmer = new Stemmer(); - const searchTerms = new Set(); - const excludedTerms = new Set(); - const highlightTerms = new Set(); - const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); - splitQuery(query.trim()).forEach((queryTerm) => { - const queryTermLower = queryTerm.toLowerCase(); - - // maybe skip this "word" - // stopwords array is from language_data.js - if ( - stopwords.indexOf(queryTermLower) !== -1 || - queryTerm.match(/^\d+$/) - ) - return; - - // stem the word - let word = stemmer.stemWord(queryTermLower); - // select the correct list - if (word[0] === "-") excludedTerms.add(word.substr(1)); - else { - searchTerms.add(word); - highlightTerms.add(queryTermLower); - } - }); - - if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js - localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) - } - - // console.debug("SEARCH: searching for:"); - // console.info("required: ", [...searchTerms]); - // console.info("excluded: ", [...excludedTerms]); - - // array of [docname, title, anchor, descr, score, filename] - let results = []; - _removeChildren(document.getElementById("search-progress")); - - const queryLower = query.toLowerCase(); - for (const [title, foundTitles] of Object.entries(allTitles)) { - if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { - for (const [file, id] of foundTitles) { - let score = Math.round(100 * queryLower.length / title.length) - results.push([ - docNames[file], - titles[file] !== title ? `${titles[file]} > ${title}` : title, - id !== null ? "#" + id : "", - null, - score, - filenames[file], - ]); - } - } - } - - // search for explicit entries in index directives - for (const [entry, foundEntries] of Object.entries(indexEntries)) { - if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { - for (const [file, id] of foundEntries) { - let score = Math.round(100 * queryLower.length / entry.length) - results.push([ - docNames[file], - titles[file], - id ? "#" + id : "", - null, - score, - filenames[file], - ]); - } - } - } - - // lookup as object - objectTerms.forEach((term) => - results.push(...Search.performObjectSearch(term, objectTerms)) - ); - - // lookup as search terms in fulltext - results.push(...Search.performTermsSearch(searchTerms, excludedTerms)); - - // let the scorer override scores with a custom scoring function - if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item))); - - // now sort the results by score (in opposite order of appearance, since the - // display function below uses pop() to retrieve items) and then - // alphabetically - results.sort((a, b) => { - const leftScore = a[4]; - const rightScore = b[4]; - if (leftScore === rightScore) { - // same score: sort alphabetically - const leftTitle = a[1].toLowerCase(); - const rightTitle = b[1].toLowerCase(); - if (leftTitle === rightTitle) return 0; - return leftTitle > rightTitle ? -1 : 1; // inverted is intentional - } - return leftScore > rightScore ? 1 : -1; - }); - - // remove duplicate search results - // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept - let seen = new Set(); - results = results.reverse().reduce((acc, result) => { - let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); - if (!seen.has(resultStr)) { - acc.push(result); - seen.add(resultStr); - } - return acc; - }, []); - - results = results.reverse(); - - // for debugging - //Search.lastresults = results.slice(); // a copy - // console.info("search results:", Search.lastresults); - - // print the results - _displayNextItem(results, results.length, searchTerms, highlightTerms); - }, - - /** - * search for object names - */ - performObjectSearch: (object, objectTerms) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const objects = Search._index.objects; - const objNames = Search._index.objnames; - const titles = Search._index.titles; - - const results = []; - - const objectSearchCallback = (prefix, match) => { - const name = match[4] - const fullname = (prefix ? prefix + "." : "") + name; - const fullnameLower = fullname.toLowerCase(); - if (fullnameLower.indexOf(object) < 0) return; - - let score = 0; - const parts = fullnameLower.split("."); - - // check for different match types: exact matches of full name or - // "last name" (i.e. last dotted part) - if (fullnameLower === object || parts.slice(-1)[0] === object) - score += Scorer.objNameMatch; - else if (parts.slice(-1)[0].indexOf(object) > -1) - score += Scorer.objPartialMatch; // matches in last name - - const objName = objNames[match[1]][2]; - const title = titles[match[0]]; - - // If more than one term searched for, we require other words to be - // found in the name/title/description - const otherTerms = new Set(objectTerms); - otherTerms.delete(object); - if (otherTerms.size > 0) { - const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); - if ( - [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) - ) - return; - } - - let anchor = match[3]; - if (anchor === "") anchor = fullname; - else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; - - const descr = objName + _(", in ") + title; - - // add custom score for some objects according to scorer - if (Scorer.objPrio.hasOwnProperty(match[2])) - score += Scorer.objPrio[match[2]]; - else score += Scorer.objPrioDefault; - - results.push([ - docNames[match[0]], - fullname, - "#" + anchor, - descr, - score, - filenames[match[0]], - ]); - }; - Object.keys(objects).forEach((prefix) => - objects[prefix].forEach((array) => - objectSearchCallback(prefix, array) - ) - ); - return results; - }, - - /** - * search for full-text terms in the index - */ - performTermsSearch: (searchTerms, excludedTerms) => { - // prepare search - const terms = Search._index.terms; - const titleTerms = Search._index.titleterms; - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - - const scoreMap = new Map(); - const fileMap = new Map(); - - // perform the search on the required terms - searchTerms.forEach((word) => { - const files = []; - const arr = [ - { files: terms[word], score: Scorer.term }, - { files: titleTerms[word], score: Scorer.title }, - ]; - // add support for partial matches - if (word.length > 2) { - const escapedWord = _escapeRegExp(word); - Object.keys(terms).forEach((term) => { - if (term.match(escapedWord) && !terms[word]) - arr.push({ files: terms[term], score: Scorer.partialTerm }); - }); - Object.keys(titleTerms).forEach((term) => { - if (term.match(escapedWord) && !titleTerms[word]) - arr.push({ files: titleTerms[word], score: Scorer.partialTitle }); - }); - } - - // no match but word was a required one - if (arr.every((record) => record.files === undefined)) return; - - // found search word in contents - arr.forEach((record) => { - if (record.files === undefined) return; - - let recordFiles = record.files; - if (recordFiles.length === undefined) recordFiles = [recordFiles]; - files.push(...recordFiles); - - // set score for the word in each file - recordFiles.forEach((file) => { - if (!scoreMap.has(file)) scoreMap.set(file, {}); - scoreMap.get(file)[word] = record.score; - }); - }); - - // create the mapping - files.forEach((file) => { - if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1) - fileMap.get(file).push(word); - else fileMap.set(file, [word]); - }); - }); - - // now check if the files don't contain excluded terms - const results = []; - for (const [file, wordList] of fileMap) { - // check if all requirements are matched - - // as search terms with length < 3 are discarded - const filteredTermCount = [...searchTerms].filter( - (term) => term.length > 2 - ).length; - if ( - wordList.length !== searchTerms.size && - wordList.length !== filteredTermCount - ) - continue; - - // ensure that none of the excluded terms is in the search result - if ( - [...excludedTerms].some( - (term) => - terms[term] === file || - titleTerms[term] === file || - (terms[term] || []).includes(file) || - (titleTerms[term] || []).includes(file) - ) - ) - break; - - // select one (max) score for the file. - const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); - // add result to the result list - results.push([ - docNames[file], - titles[file], - "", - null, - score, - filenames[file], - ]); - } - return results; - }, - - /** - * helper function to return a node containing the - * search summary for a given text. keywords is a list - * of stemmed words. - */ - makeSearchSummary: (htmlText, keywords) => { - const text = Search.htmlToText(htmlText); - if (text === "") return null; - - const textLower = text.toLowerCase(); - const actualStartPosition = [...keywords] - .map((k) => textLower.indexOf(k.toLowerCase())) - .filter((i) => i > -1) - .slice(-1)[0]; - const startWithContext = Math.max(actualStartPosition - 120, 0); - - const top = startWithContext === 0 ? "" : "..."; - const tail = startWithContext + 240 < text.length ? "..." : ""; - - let summary = document.createElement("p"); - summary.classList.add("context"); - summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; - - return summary; - }, -}; - -_ready(Search.init); diff --git a/docs/build/_static/sphinx_highlight.js b/docs/build/_static/sphinx_highlight.js deleted file mode 100644 index 8a96c69a1..000000000 --- a/docs/build/_static/sphinx_highlight.js +++ /dev/null @@ -1,154 +0,0 @@ -/* Highlighting utilities for Sphinx HTML documentation. */ -"use strict"; - -const SPHINX_HIGHLIGHT_ENABLED = true - -/** - * highlight a given string on a node by wrapping it in - * span elements with the given class name. - */ -const _highlight = (node, addItems, text, className) => { - if (node.nodeType === Node.TEXT_NODE) { - const val = node.nodeValue; - const parent = node.parentNode; - const pos = val.toLowerCase().indexOf(text); - if ( - pos >= 0 && - !parent.classList.contains(className) && - !parent.classList.contains("nohighlight") - ) { - let span; - - const closestNode = parent.closest("body, svg, foreignObject"); - const isInSVG = closestNode && closestNode.matches("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.classList.add(className); - } - - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - const rest = document.createTextNode(val.substr(pos + text.length)); - parent.insertBefore( - span, - parent.insertBefore( - rest, - node.nextSibling - ) - ); - node.nodeValue = val.substr(0, pos); - /* There may be more occurrences of search term in this node. So call this - * function recursively on the remaining fragment. - */ - _highlight(rest, addItems, text, className); - - if (isInSVG) { - const rect = document.createElementNS( - "http://www.w3.org/2000/svg", - "rect" - ); - const bbox = parent.getBBox(); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute("class", className); - addItems.push({ parent: parent, target: rect }); - } - } - } else if (node.matches && !node.matches("button, select, textarea")) { - node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); - } -}; -const _highlightText = (thisNode, text, className) => { - let addItems = []; - _highlight(thisNode, addItems, text, className); - addItems.forEach((obj) => - obj.parent.insertAdjacentElement("beforebegin", obj.target) - ); -}; - -/** - * Small JavaScript module for the documentation. - */ -const SphinxHighlight = { - - /** - * highlight the search words provided in localstorage in the text - */ - highlightSearchWords: () => { - if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight - - // get and clear terms from localstorage - const url = new URL(window.location); - const highlight = - localStorage.getItem("sphinx_highlight_terms") - || url.searchParams.get("highlight") - || ""; - localStorage.removeItem("sphinx_highlight_terms") - url.searchParams.delete("highlight"); - window.history.replaceState({}, "", url); - - // get individual terms from highlight string - const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); - if (terms.length === 0) return; // nothing to do - - // There should never be more than one element matching "div.body" - const divBody = document.querySelectorAll("div.body"); - const body = divBody.length ? divBody[0] : document.querySelector("body"); - window.setTimeout(() => { - terms.forEach((term) => _highlightText(body, term, "highlighted")); - }, 10); - - const searchBox = document.getElementById("searchbox"); - if (searchBox === null) return; - searchBox.appendChild( - document - .createRange() - .createContextualFragment( - '

' + - '' + - _("Hide Search Matches") + - "

" - ) - ); - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords: () => { - document - .querySelectorAll("#searchbox .highlight-link") - .forEach((el) => el.remove()); - document - .querySelectorAll("span.highlighted") - .forEach((el) => el.classList.remove("highlighted")); - localStorage.removeItem("sphinx_highlight_terms") - }, - - initEscapeListener: () => { - // only install a listener if it is really needed - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; - - document.addEventListener("keydown", (event) => { - // bail for input elements - if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; - // bail with special keys - if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; - if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { - SphinxHighlight.hideSearchWords(); - event.preventDefault(); - } - }); - }, -}; - -_ready(() => { - /* Do not call highlightSearchWords() when we are on the search page. - * It will highlight words from the *previous* search query. - */ - if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); - SphinxHighlight.initEscapeListener(); -}); diff --git a/docs/build/api.html b/docs/build/api.html deleted file mode 100644 index de7c3c3e9..000000000 --- a/docs/build/api.html +++ /dev/null @@ -1,295 +0,0 @@ - - - - - - - - API Documentation — neo4j-genai-python documentation - - - - - - - - - - - - - - -
- -
- - -
- - -
- -
-
- -
-

API Documentation

-
-

Retrieval-Augmented Generation (RAG)

-

RAG is a technique that enhances Large Language Model (LLM) responses by retrieving -source information from external data stores to augment generated responses.

-

This package enables Python developers to use perform RAG using Neo4j.

-
-
-

Retrievers

-
-

VectorRetriever

-
-
-class neo4j_genai.retrievers.vector.VectorRetriever(driver: Driver, index_name: str, embedder: Embedder | None = None, return_properties: list[str] | None = None)
-

Provides retrieval method using vector search over embeddings. -If an embedder is provided, it needs to have the required Embedder type.

-
-
-search(query_vector: list[float] | None = None, query_text: str | None = None, top_k: int = 5) → list[VectorSearchRecord]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -See the following documentation for more details:

- -
-
Args:

query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -query_text (Optional[str], optional): The text to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[VectorSearchRecord]: The top_k neighbors found in vector search with their nodes and scores.

-
-
-
- -
- -
-
-

VectorCypherRetriever

-
-
-class neo4j_genai.retrievers.vector.VectorCypherRetriever(driver: Driver, index_name: str, retrieval_query: str, embedder: Embedder | None = None)
-

Provides retrieval method using vector similarity and custom Cypher query. -If an embedder is provided, it needs to have the required Embedder type.

-
-
-search(query_vector: list[float] | None = None, query_text: str | None = None, top_k: int = 5, query_params: dict[str, Any] | None = None) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -See the following documentation for more details:

- -
-
Args:

query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -query_text (Optional[str], optional): The text to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5. -query_params (Optional[dict[str, Any]], optional): Parameters for the Cypher query. Defaults to None.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[Record]: The results of the search query

-
-
-
- -
- -
-
-

HybridRetriever

-
-
-class neo4j_genai.retrievers.hybrid.HybridRetriever(driver: Driver, vector_index_name: str, fulltext_index_name: str, embedder: Embedder | None = None, return_properties: list[str] | None = None)
-
-
-search(query_text: str, query_vector: list[float] | None = None, top_k: int = 5) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -Both query_vector and query_text can be provided. -If query_vector is provided, then it will be preferred over the embedded query_text -for the vector search.

-

See the following documentation for more details:

- -
-
Args:

query_text (str): The text to get the closest neighbors of. -query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[Record]: The results of the search query

-
-
-
- -
- -
-
-

HybridCypherRetriever

-
-
-class neo4j_genai.retrievers.hybrid.HybridCypherRetriever(driver: Driver, vector_index_name: str, fulltext_index_name: str, retrieval_query: str, embedder: Embedder | None = None)
-
-
-search(query_text: str, query_vector: list[float] | None = None, top_k: int = 5, query_params: dict[str, Any] | None = None) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -Both query_vector and query_text can be provided. -If query_vector is provided, then it will be preferred over the embedded query_text -for the vector search.

-

See the following documentation for more details:

- -
-
Args:

query_text (str): The text to get the closest neighbors of. -query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5. -query_params (Optional[dict[str, Any]], optional): Parameters for the Cypher query. Defaults to None.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[Record]: The results of the search query

-
-
-
- -
- -
-
-
- - - -
-
- -
-
- - - - - - \ No newline at end of file diff --git a/docs/build/doctrees/README.doctree b/docs/build/doctrees/README.doctree deleted file mode 100644 index facf220e3b49f8867e3a09ee1429a409cad3e013..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 23822 zcmeHPTWlQHd6q1Z5|3hUv{SsXizhm6h*yl(j;gbzZeP7Hhn0N0xfz?o78CwxGwt8KD0*Nq6Yd>peWEF zLBIc8=FHCSl1qsW62OMJ+CBIG{-6K+=X|>FSNGi9#s5nVh7H^C)+SBM@_dVh&1Apj zSK>PJqUIaT@t<$rYK|oXfw>y`aZq8+WEWagY{#_%<~47ka+umjjvG$O0rrKg5;?w? z_P6`&etRF<+5<^nf7&Yy~$v`=U$=;LnOHgK$y{_Z2=4`xZCIvH!0%tLffC2(}k7I=Z zFWFad%`ikEzV~@%U3}Yb#SQ&q5sMC3mD)9U=2;}i45G6f)DM!cbtVuoo{ogj=*8$|1A8#J)k3UmDiNHS4awOPOQ)L8Fe5w0@=I@<_L{d=DPInB6GZ@Le<2Km?N~EhT*YQ zBgHdywVfr~z{KG0I$C2<5oQ3H__z%0ZiRvhWA?FRc4uL2YI00v$$^=67dEN9y2Ciy zWU5Z<03(cC-Ua4AmR#Hk>~_Hd+mb2!x-#X_OAuTG+J;z#=oHCR-X@`=p{lI#*~Sw9H6kLFh3qk$a>j8dMUg zH2Wb{kn~*-p}`gO@|T7->K$5Apo0?HSGJybXvPa8({)X5e7M;-mb4b?Wqf9P%QzsH z@tRzQ)<|c$?o}!%V6Vgusa0XTjImEmJu>;kkIOz**sP|?vuvT}^hafV__BTLZ 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- - - - - - \ No newline at end of file diff --git a/docs/build/html/.buildinfo b/docs/build/html/.buildinfo deleted file mode 100644 index 7fc617e3a..000000000 --- a/docs/build/html/.buildinfo +++ /dev/null @@ -1,4 +0,0 @@ -# Sphinx build info version 1 -# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 98edc6100e73e280e52569a33c93b947 -tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/docs/build/html/README.html b/docs/build/html/README.html deleted file mode 100644 index 870d01cd4..000000000 --- a/docs/build/html/README.html +++ /dev/null @@ -1,311 +0,0 @@ - - - - - - - - Neo4j GenAI package for Python — neo4j-genai-python documentation - - - - - - - - - - - - - -
- -
- - -
- - -
- -
-
- -
-

Neo4j GenAI package for Python

-

This repository contains the official Neo4j GenAI features for Python.

-

The purpose of this package is to provide a first party package to developers, -where Neo4j can guarantee long term commitment and maintenance as well as being -fast to ship new features and high performing patterns and methods.

-

Docs are coming soon!

-
-
-

Usage

-
-

Installation

-

This package requires Python (>=3.8.1).

-

To install the latest stable version, use:

-
pip install neo4j-genai
-
-
-
-
-

Examples

-

While the library has more retrievers than shown here, the following examples should be able to get you started.

- -
-

Creating a vector index

-

When creating a vector index, make sure you match the number of dimensions in the index with the number of dimensions the embeddings have.

-

Assumption: Neo4j running

-
from neo4j import GraphDatabase
-from neo4j_genai.indexes import create_vector_index
-
-URI = "neo4j://localhost:7687"
-AUTH = ("neo4j", "password")
-
-INDEX_NAME = "chunk-index"
-
-# Connect to Neo4j database
-driver = GraphDatabase.driver(URI, auth=AUTH)
-
-# Creating the index
-create_vector_index(
-    driver,
-    INDEX_NAME,
-    label="Document",
-    property="textProperty",
-    dimensions=1536,
-    similarity_fn="euclidean",
-)
-
-
-
-
-
-

Populating the Neo4j Vector Index

-

This library does not write to the database, that is up to you. -See below for how to write using Cypher via the Neo4j driver.

-

Assumption: Neo4j running with a defined vector index

-
from neo4j import GraphDatabase
-from random import random
-
-URI = "neo4j://localhost:7687"
-AUTH = ("neo4j", "password")
-
-# Connect to Neo4j database
-driver = GraphDatabase.driver(URI, auth=AUTH)
-
-# Upsert the vector
-vector = [random() for _ in range(DIMENSION)]
-insert_query = (
-    "MERGE (n:Document {id: $id})"
-    "WITH n "
-    "CALL db.create.setNodeVectorProperty(n, 'textProperty', $vector)"
-    "RETURN n"
-)
-parameters = {
-    "id": 0,
-    "vector": vector,
-}
-driver.execute_query(insert_query, parameters)
-
-
-
-
-
-
-

Development

-
-

Install dependencies

-
poetry install
-
-
-
-
-

Getting started

-
-

Issues

-

If you have a bug to report or feature to request, first -search to see if an issue already exists. -If a related issue doesn’t exist, please raise a new issue using the relevant -issue form.

-

If you’re a Neo4j Enterprise customer, you can also reach out to Customer Support.

-

If you don’t have a bug to report or feature request, but you need a hand with -the library; community support is available via Neo4j Online Community -and/or Discord.

-
-
-

Make changes

-
    -

  1. Fork the repository.

    2. -

  2. Install Python and Poetry. For more information, see the development guide.

    3. -

  3. Create a working branch from main and start with your changes!

    4. -
-
-
-

Pull request

-

When you’re finished with your changes, create a pull request, also known as a PR.

-
    -

  • Ensure that you have signed the CLA.

    • -

  • Ensure that the base of your PR is set to main.

    • -

  • Don’t forget to link your PR to an issue -if you are solving one.

    • -

  • Enable the checkbox to allow maintainer edits -so that maintainers can make any necessary tweaks and update your branch for merge.

    • -

  • Reviewers may ask for changes to be made before a PR can be merged, either using -suggested changes -or normal pull request comments. You can apply suggested changes directly through -the UI, and any other changes can be made in your fork and committed to the PR branch.

    • -

  • As you update your PR and apply changes, mark each conversation as resolved.

    • -
-
-
-
-

Run tests

-

Open a new virtual environment and then run the tests.

-
poetry shell
-pytest
-
-
-
-
-

Further information

- -
-
- - - -
-
- -
-
- - - - - - \ No newline at end of file diff --git a/docs/build/html/_sources/README.md.txt b/docs/build/html/_sources/README.md.txt deleted file mode 100644 index 10096a060..000000000 --- a/docs/build/html/_sources/README.md.txt +++ /dev/null @@ -1,170 +0,0 @@ -# Neo4j GenAI package for Python - -This repository contains the official Neo4j GenAI features for Python. - -The purpose of this package is to provide a first party package to developers, -where Neo4j can guarantee long term commitment and maintenance as well as being -fast to ship new features and high performing patterns and methods. - -Docs are coming soon! - -# Usage - -## Installation - -This package requires Python (>=3.8.1). - -To install the latest stable version, use: - -```shell -pip install neo4j-genai -``` - -## Examples - -While the library has more retrievers than shown here, the following examples should be able to get you started. - -### Performing a similarity search - -Assumption: Neo4j running with populated vector index in place. - -```python -from neo4j import GraphDatabase -from neo4j_genai import VectorRetriever - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "embedding-name" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Initialize the retriever -retriever = VectorRetriever(driver, INDEX_NAME) - -# Run the similarity search -query_text = "How do I do similarity search in Neo4j?" -response = retriever.search(query_text=query_text, top_k=5) -``` - -### Creating a vector index - -When creating a vector index, make sure you match the number of dimensions in the index with the number of dimensions the embeddings have. - -Assumption: Neo4j running - -```python -from neo4j import GraphDatabase -from neo4j_genai.indexes import create_vector_index - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "chunk-index" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Creating the index -create_vector_index( - driver, - INDEX_NAME, - label="Document", - property="textProperty", - dimensions=1536, - similarity_fn="euclidean", -) - -``` - -### Populating the Neo4j Vector Index - -This library does not write to the database, that is up to you. -See below for how to write using Cypher via the Neo4j driver. - -Assumption: Neo4j running with a defined vector index - -```python -from neo4j import GraphDatabase -from random import random - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Upsert the vector -vector = [random() for _ in range(DIMENSION)] -insert_query = ( - "MERGE (n:Document {id: $id})" - "WITH n " - "CALL db.create.setNodeVectorProperty(n, 'textProperty', $vector)" - "RETURN n" -) -parameters = { - "id": 0, - "vector": vector, -} -driver.execute_query(insert_query, parameters) -``` - -# Development - -## Install dependencies - -```bash -poetry install -``` - -## Getting started - -### Issues - -If you have a bug to report or feature to request, first -[search to see if an issue already exists](https://docs.github.com/en/github/searching-for-information-on-github/searching-on-github/searching-issues-and-pull-requests#search-by-the-title-body-or-comments). -If a related issue doesn't exist, please raise a new issue using the relevant -[issue form](https://github.com/neo4j/neo4j-genai-python/issues/new/choose). - -If you're a Neo4j Enterprise customer, you can also reach out to [Customer Support](http://support.neo4j.com/). - -If you don't have a bug to report or feature request, but you need a hand with -the library; community support is available via [Neo4j Online Community](https://community.neo4j.com/) -and/or [Discord](https://discord.gg/neo4j). - -### Make changes - -1. Fork the repository. -2. Install Python and Poetry. For more information, see [the development guide](./docs/contributing/DEVELOPING.md). -3. Create a working branch from `main` and start with your changes! - -### Pull request - -When you're finished with your changes, create a pull request, also known as a PR. - -- Ensure that you have [signed the CLA](https://neo4j.com/developer/contributing-code/#sign-cla). -- Ensure that the base of your PR is set to `main`. -- Don't forget to [link your PR to an issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue) - if you are solving one. -- Enable the checkbox to [allow maintainer edits](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/allowing-changes-to-a-pull-request-branch-created-from-a-fork) - so that maintainers can make any necessary tweaks and update your branch for merge. -- Reviewers may ask for changes to be made before a PR can be merged, either using - [suggested changes](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/reviewing-changes-in-pull-requests/incorporating-feedback-in-your-pull-request) - or normal pull request comments. You can apply suggested changes directly through - the UI, and any other changes can be made in your fork and committed to the PR branch. -- As you update your PR and apply changes, mark each conversation as [resolved](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request#resolving-conversations). - -## Run tests - -Open a new virtual environment and then run the tests. - -```bash -poetry shell -pytest -``` - -## Further information - -- [The official Neo4j Python driver](https://github.com/neo4j/neo4j-python-driver) -- [Neo4j GenAI integrations](https://neo4j.com/docs/cypher-manual/current/genai-integrations/) diff --git a/docs/build/html/_sources/api.rst.txt b/docs/build/html/_sources/api.rst.txt deleted file mode 100644 index 7e46f2f40..000000000 --- a/docs/build/html/_sources/api.rst.txt +++ /dev/null @@ -1,43 +0,0 @@ -.. _api-documentation: - -API Documentation -################# - -************************************ -Retrieval-Augmented Generation (RAG) -************************************ -RAG is a technique that enhances Large Language Model (LLM) responses by retrieving -source information from external data stores to augment generated responses. - -This package enables Python developers to use perform RAG using Neo4j. - -********** -Retrievers -********** - -VectorRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.vector.VectorRetriever - :members: - - -VectorCypherRetriever -===================== - -.. autoclass:: neo4j_genai.retrievers.vector.VectorCypherRetriever - :members: - - -HybridRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.hybrid.HybridRetriever - :members: - - -HybridCypherRetriever -=============== - -.. autoclass:: neo4j_genai.retrievers.hybrid.HybridCypherRetriever - :members: diff --git a/docs/build/html/_sources/index.rst.txt b/docs/build/html/_sources/index.rst.txt deleted file mode 100644 index bec1b20ee..000000000 --- a/docs/build/html/_sources/index.rst.txt +++ /dev/null @@ -1,21 +0,0 @@ -.. neo4j-genai-python documentation master file, created by - sphinx-quickstart on Tue Apr 9 16:36:43 2024. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - -Welcome to neo4j-genai-python's documentation! -============================================== - -.. toctree:: - :maxdepth: 2 - :caption: Contents: - - api.rst - - -Indices and tables -================== - -* :ref:`genindex` -* :ref:`modindex` -* :ref:`search` diff --git a/docs/build/html/_static/basic.css b/docs/build/html/_static/basic.css deleted file mode 100644 index 30fee9d0f..000000000 --- a/docs/build/html/_static/basic.css +++ /dev/null @@ -1,925 +0,0 @@ -/* - * basic.css - * ~~~~~~~~~ - * - * Sphinx stylesheet -- basic theme. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -/* -- main layout 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margin: 2px 0 0 30px; - text-align: left; -} - -ul.keywordmatches li.goodmatch a { - font-weight: bold; -} - -/* -- index page ------------------------------------------------------------ */ - -table.contentstable { - width: 90%; - margin-left: auto; - margin-right: auto; -} - -table.contentstable p.biglink { - line-height: 150%; -} - -a.biglink { - font-size: 1.3em; -} - -span.linkdescr { - font-style: italic; - padding-top: 5px; - font-size: 90%; -} - -/* -- general index --------------------------------------------------------- */ - -table.indextable { - width: 100%; -} - -table.indextable td { - text-align: left; - vertical-align: top; -} - -table.indextable ul { - margin-top: 0; - margin-bottom: 0; - list-style-type: none; -} - -table.indextable > tbody > tr > td > ul { - padding-left: 0em; -} - -table.indextable tr.pcap { - height: 10px; -} - -table.indextable tr.cap { - margin-top: 10px; - background-color: #f2f2f2; -} - -img.toggler { - margin-right: 3px; - margin-top: 3px; - 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td.linenos { - padding-right: 0.5em; -} - -table.highlighttable td.code { - flex: 1; - overflow: hidden; -} - -.highlight .hll { - display: block; -} - -div.highlight pre, -table.highlighttable pre { - margin: 0; -} - -div.code-block-caption + div { - margin-top: 0; -} - -div.code-block-caption { - margin-top: 1em; - padding: 2px 5px; - font-size: small; -} - -div.code-block-caption code { - background-color: transparent; -} - -table.highlighttable td.linenos, -span.linenos, -div.highlight span.gp { /* gp: Generic.Prompt */ - user-select: none; - -webkit-user-select: text; /* Safari fallback only */ - -webkit-user-select: none; /* Chrome/Safari */ - -moz-user-select: none; /* Firefox */ - -ms-user-select: none; /* IE10+ */ -} - -div.code-block-caption span.caption-number { - padding: 0.1em 0.3em; - font-style: italic; -} - -div.code-block-caption span.caption-text { -} - -div.literal-block-wrapper { - margin: 1em 0; -} - -code.xref, a code { - background-color: transparent; - font-weight: bold; -} - -h1 code, h2 code, h3 code, h4 code, h5 code, h6 code { - background-color: transparent; -} - -.viewcode-link { - float: right; -} - -.viewcode-back { - float: right; - font-family: sans-serif; -} - -div.viewcode-block:target { - margin: -1px -10px; - padding: 0 10px; -} - -/* -- math display ---------------------------------------------------------- */ - -img.math { - vertical-align: middle; -} - -div.body div.math p { - text-align: center; -} - -span.eqno { - float: right; -} - -span.eqno a.headerlink { - position: absolute; - z-index: 1; -} - -div.math:hover a.headerlink { - visibility: visible; -} - -/* -- printout stylesheet --------------------------------------------------- */ - -@media print { - div.document, - div.documentwrapper, - div.bodywrapper { - margin: 0 !important; - width: 100%; - } - - div.sphinxsidebar, - div.related, - div.footer, - #top-link { - display: none; - } -} \ No newline at end of file diff --git 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.toctree-l2>span { - position: relative; - padding-right: 2rem; -} - -.nav-menu li.toctree-l3 { - list-style: none; - position: relative; -} - -.nav-menu .toctree-l3>a, -.nav-menu .toctree-l3>span { - padding-left: 3.5rem; -} - -.nav-menu .toctree-l3>a, -.nav-menu .toctree-l3>span { - padding-top: 0.5rem; - padding-bottom: 0.5rem; -} - -.nav-menu .toctree-l3 a:hover, -.nav-menu .toctree-l3 span:hover { - background-color: #e6e9ee; -} - -.nav-menu .toctree-l3>a.current { - background-color: #e6f8ff; - color: #0056b3; -} - -.nav-menu .toctree-l3>a.current::before { - content: ""; - width: 4px; - height: 100%; - position: absolute; - left: 0; - top: 0; - background: #0056b3; - border-radius: 4px; -} - -.toctree-l3>a, .toctree-l3>span { - position: relative; - padding-right: 2rem; -} - - -.nav-menu li a code { - font-family: inherit -} - -.is-current-page>.nav-link, -.is-current-page>.nav-text { - font-weight: 400; -} - -.nav-menu a, .nav-text { - color: #535b66; - font-weight: 400; - display: block; - padding: 0.25rem 0; -} - -/* lists */ - -body.sphinx .doc ul li{ - margin-bottom: 0; -} - -/* functions */ - -body.sphinx .doc dl.py.function { - padding: 0 1rem; - /* border-top: 2px dotted #eee; */ -} - -/* deprecated */ - -body.sphinx .deprecated::after, -body.sphinx .deprecated > *::after { - content: unset; -} - -body.sphinx .doc dl.deprecated dt:first-of-type span.sig-prename, -body.sphinx .doc dl.deprecated dt:first-of-type span.sig-name { - border-bottom: 1px solid #f6ad55; - /* color: #702459; */ - /* background-color: #fed7e2; */ -} - -body.sphinx .doc dl.deprecated { - margin-bottom: 0; - padding-bottom: 0; -} - -body.sphinx .doc div.deprecated { - padding: 1rem 1rem 0.75rem; - margin: 0.5rem 1.5rem; - /* color: #702459; */ - border-left: 4px solid #f6ad55; - border-radius: .25rem; - background-color: #fffaf0; -} - -.sphinx .doc .deprecated > :first-child { - margin-top: 0; -} - -.sphinx .doc .deprecated > :last-child { - margin-bottom: 0; -} - -b, strong { - font-weight: 800; -} - -dt { - font-weight: initial; -} - -.sphinx .doc .admonition { - margin: 0.5rem 1.5rem; - border-left: 4px solid #2d3748; - border-radius: .25rem; - padding: 1rem 1rem 0.75rem; - font-size: .88889rem -} - -.sphinx .doc .admonition .admonition-title:after { - content: ":"; -} - -.sphinx .doc .admonition .admonition-title, -.sphinx .doc .admonition .admonition-title + p { - display: inline; -} - -.sphinx .doc .admonition > :last-child { - margin-bottom: 0; -} - -.sphinx .doc .admonition > table { - border-collapse: collapse; - table-layout: fixed; - position: relative; - width: 100% -} - -.sphinx .doc .admonition .content { - padding: 1rem 1rem .75rem; - width: 100% -} - -.sphinx .doc .admonition .listingblock .content { - padding: 0 -} - -.sphinx .doc .admonition .icon { - display: none -} - -.sphinx .doc .admonition a.btn { - display: inline-block; - background: #000; - color: #fff !important; - padding: .5rem 2rem; - border-radius: .5rem -} - -.sphinx .doc .admonition a.btn::after { - display: none !important -} - -.sphinx .doc .admonition.warning { - background-color: #fed7d7; - color: #742a2a; - border-left-color: #e53e3e -} - -.sphinx .doc .admonition.warning pre { - background-color: #fff5f5; - color: #c53030 -} - -.sphinx .doc .admonition.warning a.btn { - background-color: #e53e3e -} - -.sphinx .doc .admonition.warning a { - color: #f56565 -} - -.sphinx .doc .admonition.caution { - background-color: #feebc8; - color: #7b341e; - border-left-color: #dd6b20 -} - -.sphinx .doc .admonition.caution a { - color: #ed8936 -} - -.sphinx .doc .admonition.caution a:hover { - color: #f6ad55 -} - -.sphinx .doc .admonition.caution a.btn { - background-color: #dd6b20 -} - -.sphinx .doc .admonition.caution pre { - background-color: #fffaf0; - color: #c05621 -} - -.sphinx .doc .admonition.tip, .sphinx .doc .admonition.note { - background-color: #bee3f8; - color: #2a4365; - border-left-color: #3182ce -} - -.sphinx .doc .admonition.tip a, .sphinx .doc .admonition.note a { - color: #3182ce -} - -.sphinx .doc .admonition.tip a:hover, .sphinx .doc .admonition.note a:hover { - color: #4299e1 -} - -.sphinx .doc .admonition.tip a.btn, .sphinx .doc .admonition.note a.btn { - background-color: #3182ce -} - -.sphinx .doc .admonition.tip pre, .sphinx .doc .admonition.note pre { - background-color: #ebf8ff; - color: #2b6cb0 -} - -.sphinx .doc .admonition.seealso { - background-color: #edf2f7; - color: #1a202c; - border-left-color: #718096 -} - -.sphinx .doc .admonition.seealso a { - color: #718096 -} - -.sphinx .doc .admonition.seealso a:hover { - color: #a0aec0 -} - -.sphinx .doc .admonition.seealso a.btn { - background-color: #718096 -} - -.sphinx .doc .admonition.important { - background-color: #e9d8fd; - color: #44337a; - border-left-color: #805ad5 -} - -.sphinx .doc .admonition.important a { - color: #805ad5 -} - -.sphinx .doc .admonition.important a:hover { - color: #9f7aea -} - -.sphinx .doc .admonition.important a.btn { - background-color: #805ad5 -} - -dd > :first-child { - margin-top: 0; -} - -.field-list p { - margin: 0; -} - -dl.field-list { - display: grid; - grid-template-columns: fit-content(30%) auto; -} - -dl.field-list > dt { - font-weight: bold; - /*word-break: break-word;*/ - padding-left: 0.5em; - padding-right: 5px; -} - - -dl.field-list > dd { - padding-left: 0.5em; - margin-left: 0; -} - -dl > dd:last-child, -dl > dd:last-child > :last-child { - margin-bottom: 0; -} - -dl.field-list > dd > ul, -dl.field-list > dd > ol { - padding-left: 1.9em; - margin-left: 0; -} - -.content ol li > p:first-of-type, -.content ul li > p:first-of-type { - margin-top: 0; -} - -.content ol li > p:last-of-type, -.content ul li > p:last-of-type { - margin-bottom: 0; -} - - -table.docutils { - margin-top: 10px; - margin-bottom: 10px; - border: 0; - border-collapse: collapse; -} - -table.docutils td, table.docutils th { - padding: 1px 8px 1px 5px; - border: 0; -} - -table.docutils > tbody > tr:not(:last-child) > td, -table.docutils > tbody > tr:not(:last-child) > td, -table.docutils > thead > tr:not(:last-child) > td, -table.docutils > thead > tr:not(:last-child) > td, -table.docutils > tr:not(:last-child) > td, -table.docutils > tr:not(:last-child) > td { - border-bottom: 1px solid #aaa; -} - -th > :first-child, -td > :first-child { - margin-top: 0; -} - -th > :last-child, -td > :last-child { - margin-bottom: 0; -} - -.sig-name, code.descname { - font-weight: bold; -} - -.sig-paren { - font-size: larger; -} - -.versionmodified { - font-style: italic; -} \ No newline at end of file diff --git a/docs/build/html/_static/css/nunito-sans.css b/docs/build/html/_static/css/nunito-sans.css deleted file mode 100644 index dfd39b79d..000000000 --- a/docs/build/html/_static/css/nunito-sans.css +++ /dev/null @@ -1,200 +0,0 @@ -/* cyrillic-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic-ext.woff2) format('woff2'); - unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; -} -/* cyrillic */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic.woff2) format('woff2'); - unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; -} -/* vietnamese */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-vietnamese.woff2) format('woff2'); - unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; -} -/* latin-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin-ext.woff2) format('woff2'); - unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF; -} -/* latin */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 300; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin.woff2) format('woff2'); - unicode-range: U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+0304, U+0308, U+0329, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD; -} -/* cyrillic-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic-ext.woff2) format('woff2'); - unicode-range: U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F; -} -/* cyrillic */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-cyrillic.woff2) format('woff2'); - unicode-range: U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116; -} -/* vietnamese */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-vietnamese.woff2) format('woff2'); - unicode-range: U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+0300-0301, U+0303-0304, U+0308-0309, U+0323, U+0329, U+1EA0-1EF9, U+20AB; -} -/* latin-ext */ -@font-face { - font-family: 'Nunito Sans'; - font-style: normal; - font-weight: 400; - font-stretch: 100%; - font-display: swap; - src: url(../fonts/nunito-sans-latin-ext.woff2) format('woff2'); - unicode-range: U+0100-02AF, U+0304, U+0308, U+0329, U+1E00-1E9F, U+1EF2-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF; -} -/* latin */ -@font-face { - 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this.id - e.preventDefault() - } - var topOffset = toolbar ? toolbar.getBoundingClientRect().bottom : headerNavigationBar.getBoundingClientRect().bottom - - if (cheatSheet) { - var scrollTarget = this.closest('div') - var selectorsTop = document.querySelector('.nav-container .selectors').querySelector('div').getBoundingClientRect().top - if (this.tagName === 'H3') topOffset = selectorsTop - window.scrollTo(0, computePosition(scrollTarget, 0) - topOffset) - } else { - window.scrollTo(0, computePosition(this, 0) - topOffset) - } - } - - window.addEventListener('load', function jumpOnLoad (e) { - var fragment, target - if ((fragment = decodeFragment(window.location.hash)) && (target = document.getElementById(fragment))) { - jumpToAnchor.bind(target)() - setTimeout(jumpToAnchor.bind(target), 0) - } - window.removeEventListener('load', jumpOnLoad) - }) - - Array.prototype.slice.call(document.querySelectorAll('a[href^="#"]')).forEach(function (el) { - var fragment, target - if ((fragment = decodeFragment(el.hash)) && (target = document.getElementById(fragment))) { - el.addEventListener('click', jumpToAnchor.bind(target)) - } - }) -})() diff --git a/docs/build/html/_static/language_data.js b/docs/build/html/_static/language_data.js deleted file mode 100644 index 250f5665f..000000000 --- a/docs/build/html/_static/language_data.js +++ /dev/null @@ -1,199 +0,0 @@ -/* - * language_data.js - * ~~~~~~~~~~~~~~~~ - * - * This script contains the language-specific data used by searchtools.js, - * namely the list of stopwords, stemmer, scorer and splitter. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ - -var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; - - -/* Non-minified version is copied as a separate JS file, is available */ - -/** - * Porter Stemmer - */ -var Stemmer = function() { - - var step2list = { - ational: 'ate', - tional: 'tion', - enci: 'ence', - anci: 'ance', - izer: 'ize', - bli: 'ble', - alli: 'al', - entli: 'ent', - eli: 'e', - ousli: 'ous', - ization: 'ize', - ation: 'ate', - ator: 'ate', - alism: 'al', - iveness: 'ive', - fulness: 'ful', - ousness: 'ous', - aliti: 'al', - iviti: 'ive', - biliti: 'ble', - logi: 'log' - }; - - var step3list = { - icate: 'ic', - ative: '', - alize: 'al', - iciti: 'ic', - ical: 'ic', - ful: '', - ness: '' - }; - - var c = "[^aeiou]"; // consonant - var v = "[aeiouy]"; // vowel - var C = c + "[^aeiouy]*"; // consonant sequence - var V = v + "[aeiou]*"; // vowel sequence - - var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 - var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 - var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 - var s_v = "^(" + C + ")?" + v; // vowel in stem - - this.stemWord = function (w) { - var stem; - var suffix; - var firstch; - var origword = w; - - if (w.length < 3) - return w; - - var re; - var re2; - var re3; - var re4; - - firstch = w.substr(0,1); - if (firstch == "y") - w = firstch.toUpperCase() + w.substr(1); - - // Step 1a - re = /^(.+?)(ss|i)es$/; - re2 = /^(.+?)([^s])s$/; - - if (re.test(w)) - w = w.replace(re,"$1$2"); - else if (re2.test(w)) - w = w.replace(re2,"$1$2"); - - // Step 1b - re = /^(.+?)eed$/; - re2 = /^(.+?)(ed|ing)$/; - if (re.test(w)) { - var fp = re.exec(w); - re = new RegExp(mgr0); - if (re.test(fp[1])) { - re = /.$/; - w = w.replace(re,""); - } - } - else if (re2.test(w)) { - var fp = re2.exec(w); - stem = fp[1]; - re2 = new RegExp(s_v); - if (re2.test(stem)) { - w = stem; - re2 = /(at|bl|iz)$/; - re3 = new RegExp("([^aeiouylsz])\\1$"); - re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); - if (re2.test(w)) - w = w + "e"; - else if (re3.test(w)) { - re = /.$/; - w = w.replace(re,""); - } - else if (re4.test(w)) - w = w + "e"; - } - } - - // Step 1c - re = /^(.+?)y$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(s_v); - if (re.test(stem)) - w = stem + "i"; - } - - // Step 2 - re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step2list[suffix]; - } - - // Step 3 - re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - suffix = fp[2]; - re = new RegExp(mgr0); - if (re.test(stem)) - w = stem + step3list[suffix]; - } - - // Step 4 - re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; - re2 = /^(.+?)(s|t)(ion)$/; - if (re.test(w)) { - var fp = re.exec(w); - stem = fp[1]; - re = new RegExp(mgr1); - if (re.test(stem)) - w = stem; - } - else if (re2.test(w)) { 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mode 100644 index 7918c3fab..000000000 --- a/docs/build/html/_static/searchtools.js +++ /dev/null @@ -1,574 +0,0 @@ -/* - * searchtools.js - * ~~~~~~~~~~~~~~~~ - * - * Sphinx JavaScript utilities for the full-text search. - * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. - * :license: BSD, see LICENSE for details. - * - */ -"use strict"; - -/** - * Simple result scoring code. - */ -if (typeof Scorer === "undefined") { - var Scorer = { - // Implement the following function to further tweak the score for each result - // The function takes a result array [docname, title, anchor, descr, score, filename] - // and returns the new score. - /* - score: result => { - const [docname, title, anchor, descr, score, filename] = result - return score - }, - */ - - // query matches the full name of an object - objNameMatch: 11, - // or matches in the last dotted part of the object name - objPartialMatch: 6, - // Additive scores depending on the priority of the object - objPrio: { - 0: 15, // used to be importantResults - 1: 5, // used to be objectResults - 2: -5, // used to be unimportantResults - }, - // Used when the priority is not in the mapping. - objPrioDefault: 0, - - // query found in title - title: 15, - partialTitle: 7, - // query found in terms - term: 5, - partialTerm: 2, - }; -} - -const _removeChildren = (element) => { - while (element && element.lastChild) element.removeChild(element.lastChild); -}; - -/** - * See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions#escaping - */ -const _escapeRegExp = (string) => - string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string - -const _displayItem = (item, searchTerms, highlightTerms) => { - const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; - const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; - const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; - const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; - const contentRoot = document.documentElement.dataset.content_root; - - const [docName, title, anchor, descr, score, _filename] = item; - - let listItem = document.createElement("li"); - let requestUrl; - let linkUrl; - if (docBuilder === "dirhtml") { - // dirhtml builder - let dirname = docName + "/"; - if (dirname.match(/\/index\/$/)) - dirname = dirname.substring(0, dirname.length - 6); - else if (dirname === "index/") dirname = ""; - requestUrl = contentRoot + dirname; - linkUrl = requestUrl; - } else { - // normal html builders - requestUrl = contentRoot + docName + docFileSuffix; - linkUrl = docName + docLinkSuffix; - } - let linkEl = listItem.appendChild(document.createElement("a")); - linkEl.href = linkUrl + anchor; - linkEl.dataset.score = score; - linkEl.innerHTML = title; - if (descr) { - listItem.appendChild(document.createElement("span")).innerHTML = - " (" + descr + ")"; - // highlight search terms in the description - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - } - else if (showSearchSummary) - fetch(requestUrl) - .then((responseData) => responseData.text()) - .then((data) => { - if (data) - listItem.appendChild( - Search.makeSearchSummary(data, searchTerms) - ); - // highlight search terms in the summary - if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js - highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); - }); - Search.output.appendChild(listItem); -}; -const _finishSearch = (resultCount) => { - Search.stopPulse(); - Search.title.innerText = _("Search Results"); - if (!resultCount) - Search.status.innerText = Documentation.gettext( - "Your search did not match any documents. Please make sure that all words are spelled correctly and that you've selected enough categories." - ); - else - Search.status.innerText = _( - `Search finished, found ${resultCount} page(s) matching the search query.` - ); -}; -const _displayNextItem = ( - results, - resultCount, - searchTerms, - highlightTerms, -) => { - // results left, load the summary and display it - // this is intended to be dynamic (don't sub resultsCount) - if (results.length) { - _displayItem(results.pop(), searchTerms, highlightTerms); - setTimeout( - () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), - 5 - ); - } - // search finished, update title and status message - else _finishSearch(resultCount); -}; - -/** - * Default splitQuery function. Can be overridden in ``sphinx.search`` with a - * custom function per language. - * - * The regular expression works by splitting the string on consecutive characters - * that are not Unicode letters, numbers, underscores, or emoji characters. - * This is the same as ``\W+`` in Python, preserving the surrogate pair area. - */ -if (typeof splitQuery === "undefined") { - var splitQuery = (query) => query - .split(/[^\p{Letter}\p{Number}_\p{Emoji_Presentation}]+/gu) - .filter(term => term) // remove remaining empty strings -} - -/** - * Search Module - */ -const Search = { - _index: null, - _queued_query: null, - _pulse_status: -1, - - htmlToText: (htmlString) => { - const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); - htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() }); - const docContent = htmlElement.querySelector('[role="main"]'); - if (docContent !== undefined) return docContent.textContent; - console.warn( - "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." - ); - return ""; - }, - - init: () => { - const query = new URLSearchParams(window.location.search).get("q"); - document - .querySelectorAll('input[name="q"]') - .forEach((el) => (el.value = query)); - if (query) Search.performSearch(query); - }, - - loadIndex: (url) => - (document.body.appendChild(document.createElement("script")).src = url), - - setIndex: (index) => { - Search._index = index; - if (Search._queued_query !== null) { - const query = Search._queued_query; - Search._queued_query = null; - Search.query(query); - } - }, - - hasIndex: () => Search._index !== null, - - deferQuery: (query) => (Search._queued_query = query), - - stopPulse: () => (Search._pulse_status = -1), - - startPulse: () => { - if (Search._pulse_status >= 0) return; - - const pulse = () => { - Search._pulse_status = (Search._pulse_status + 1) % 4; - Search.dots.innerText = ".".repeat(Search._pulse_status); - if (Search._pulse_status >= 0) window.setTimeout(pulse, 500); - }; - pulse(); - }, - - /** - * perform a search for something (or wait until index is loaded) - */ - performSearch: (query) => { - // create the required interface elements - const searchText = document.createElement("h2"); - searchText.textContent = _("Searching"); - const searchSummary = document.createElement("p"); - searchSummary.classList.add("search-summary"); - searchSummary.innerText = ""; - const searchList = document.createElement("ul"); - searchList.classList.add("search"); - - const out = document.getElementById("search-results"); - Search.title = out.appendChild(searchText); - Search.dots = Search.title.appendChild(document.createElement("span")); - Search.status = out.appendChild(searchSummary); - Search.output = out.appendChild(searchList); - - const searchProgress = document.getElementById("search-progress"); - // Some themes don't use the search progress node - if (searchProgress) { - searchProgress.innerText = _("Preparing search..."); - } - Search.startPulse(); - - // index already loaded, the browser was quick! - if (Search.hasIndex()) Search.query(query); - else Search.deferQuery(query); - }, - - /** - * execute search (requires search index to be loaded) - */ - query: (query) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - const allTitles = Search._index.alltitles; - const indexEntries = Search._index.indexentries; - - // stem the search terms and add them to the correct list - const stemmer = new Stemmer(); - const searchTerms = new Set(); - const excludedTerms = new Set(); - const highlightTerms = new Set(); - const objectTerms = new Set(splitQuery(query.toLowerCase().trim())); - splitQuery(query.trim()).forEach((queryTerm) => { - const queryTermLower = queryTerm.toLowerCase(); - - // maybe skip this "word" - // stopwords array is from language_data.js - if ( - stopwords.indexOf(queryTermLower) !== -1 || - queryTerm.match(/^\d+$/) - ) - return; - - // stem the word - let word = stemmer.stemWord(queryTermLower); - // select the correct list - if (word[0] === "-") excludedTerms.add(word.substr(1)); - else { - searchTerms.add(word); - highlightTerms.add(queryTermLower); - } - }); - - if (SPHINX_HIGHLIGHT_ENABLED) { // set in sphinx_highlight.js - localStorage.setItem("sphinx_highlight_terms", [...highlightTerms].join(" ")) - } - - // console.debug("SEARCH: searching for:"); - // console.info("required: ", [...searchTerms]); - // console.info("excluded: ", [...excludedTerms]); - - // array of [docname, title, anchor, descr, score, filename] - let results = []; - _removeChildren(document.getElementById("search-progress")); - - const queryLower = query.toLowerCase(); - for (const [title, foundTitles] of Object.entries(allTitles)) { - if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { - for (const [file, id] of foundTitles) { - let score = Math.round(100 * queryLower.length / title.length) - results.push([ - docNames[file], - titles[file] !== title ? `${titles[file]} > ${title}` : title, - id !== null ? "#" + id : "", - null, - score, - filenames[file], - ]); - } - } - } - - // search for explicit entries in index directives - for (const [entry, foundEntries] of Object.entries(indexEntries)) { - if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { - for (const [file, id] of foundEntries) { - let score = Math.round(100 * queryLower.length / entry.length) - results.push([ - docNames[file], - titles[file], - id ? "#" + id : "", - null, - score, - filenames[file], - ]); - } - } - } - - // lookup as object - objectTerms.forEach((term) => - results.push(...Search.performObjectSearch(term, objectTerms)) - ); - - // lookup as search terms in fulltext - results.push(...Search.performTermsSearch(searchTerms, excludedTerms)); - - // let the scorer override scores with a custom scoring function - if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item))); - - // now sort the results by score (in opposite order of appearance, since the - // display function below uses pop() to retrieve items) and then - // alphabetically - results.sort((a, b) => { - const leftScore = a[4]; - const rightScore = b[4]; - if (leftScore === rightScore) { - // same score: sort alphabetically - const leftTitle = a[1].toLowerCase(); - const rightTitle = b[1].toLowerCase(); - if (leftTitle === rightTitle) return 0; - return leftTitle > rightTitle ? -1 : 1; // inverted is intentional - } - return leftScore > rightScore ? 1 : -1; - }); - - // remove duplicate search results - // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept - let seen = new Set(); - results = results.reverse().reduce((acc, result) => { - let resultStr = result.slice(0, 4).concat([result[5]]).map(v => String(v)).join(','); - if (!seen.has(resultStr)) { - acc.push(result); - seen.add(resultStr); - } - return acc; - }, []); - - results = results.reverse(); - - // for debugging - //Search.lastresults = results.slice(); // a copy - // console.info("search results:", Search.lastresults); - - // print the results - _displayNextItem(results, results.length, searchTerms, highlightTerms); - }, - - /** - * search for object names - */ - performObjectSearch: (object, objectTerms) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const objects = Search._index.objects; - const objNames = Search._index.objnames; - const titles = Search._index.titles; - - const results = []; - - const objectSearchCallback = (prefix, match) => { - const name = match[4] - const fullname = (prefix ? prefix + "." : "") + name; - const fullnameLower = fullname.toLowerCase(); - if (fullnameLower.indexOf(object) < 0) return; - - let score = 0; - const parts = fullnameLower.split("."); - - // check for different match types: exact matches of full name or - // "last name" (i.e. last dotted part) - if (fullnameLower === object || parts.slice(-1)[0] === object) - score += Scorer.objNameMatch; - else if (parts.slice(-1)[0].indexOf(object) > -1) - score += Scorer.objPartialMatch; // matches in last name - - const objName = objNames[match[1]][2]; - const title = titles[match[0]]; - - // If more than one term searched for, we require other words to be - // found in the name/title/description - const otherTerms = new Set(objectTerms); - otherTerms.delete(object); - if (otherTerms.size > 0) { - const haystack = `${prefix} ${name} ${objName} ${title}`.toLowerCase(); - if ( - [...otherTerms].some((otherTerm) => haystack.indexOf(otherTerm) < 0) - ) - return; - } - - let anchor = match[3]; - if (anchor === "") anchor = fullname; - else if (anchor === "-") anchor = objNames[match[1]][1] + "-" + fullname; - - const descr = objName + _(", in ") + title; - - // add custom score for some objects according to scorer - if (Scorer.objPrio.hasOwnProperty(match[2])) - score += Scorer.objPrio[match[2]]; - else score += Scorer.objPrioDefault; - - results.push([ - docNames[match[0]], - fullname, - "#" + anchor, - descr, - score, - filenames[match[0]], - ]); - }; - Object.keys(objects).forEach((prefix) => - objects[prefix].forEach((array) => - objectSearchCallback(prefix, array) - ) - ); - return results; - }, - - /** - * search for full-text terms in the index - */ - performTermsSearch: (searchTerms, excludedTerms) => { - // prepare search - const terms = Search._index.terms; - const titleTerms = Search._index.titleterms; - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - - const scoreMap = new Map(); - const fileMap = new Map(); - - // perform the search on the required terms - searchTerms.forEach((word) => { - const files = []; - const arr = [ - { files: terms[word], score: Scorer.term }, - { files: titleTerms[word], score: Scorer.title }, - ]; - // add support for partial matches - if (word.length > 2) { - const escapedWord = _escapeRegExp(word); - Object.keys(terms).forEach((term) => { - if (term.match(escapedWord) && !terms[word]) - arr.push({ files: terms[term], score: Scorer.partialTerm }); - }); - Object.keys(titleTerms).forEach((term) => { - if (term.match(escapedWord) && !titleTerms[word]) - arr.push({ files: titleTerms[word], score: Scorer.partialTitle }); - }); - } - - // no match but word was a required one - if (arr.every((record) => record.files === undefined)) return; - - // found search word in contents - arr.forEach((record) => { - if (record.files === undefined) return; - - let recordFiles = record.files; - if (recordFiles.length === undefined) recordFiles = [recordFiles]; - files.push(...recordFiles); - - // set score for the word in each file - recordFiles.forEach((file) => { - if (!scoreMap.has(file)) scoreMap.set(file, {}); - scoreMap.get(file)[word] = record.score; - }); - }); - - // create the mapping - files.forEach((file) => { - if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1) - fileMap.get(file).push(word); - else fileMap.set(file, [word]); - }); - }); - - // now check if the files don't contain excluded terms - const results = []; - for (const [file, wordList] of fileMap) { - // check if all requirements are matched - - // as search terms with length < 3 are discarded - const filteredTermCount = [...searchTerms].filter( - (term) => term.length > 2 - ).length; - if ( - wordList.length !== searchTerms.size && - wordList.length !== filteredTermCount - ) - continue; - - // ensure that none of the excluded terms is in the search result - if ( - [...excludedTerms].some( - (term) => - terms[term] === file || - titleTerms[term] === file || - (terms[term] || []).includes(file) || - (titleTerms[term] || []).includes(file) - ) - ) - break; - - // select one (max) score for the file. - const score = Math.max(...wordList.map((w) => scoreMap.get(file)[w])); - // add result to the result list - results.push([ - docNames[file], - titles[file], - "", - null, - score, - filenames[file], - ]); - } - return results; - }, - - /** - * helper function to return a node containing the - * search summary for a given text. keywords is a list - * of stemmed words. - */ - makeSearchSummary: (htmlText, keywords) => { - const text = Search.htmlToText(htmlText); - if (text === "") return null; - - const textLower = text.toLowerCase(); - const actualStartPosition = [...keywords] - .map((k) => textLower.indexOf(k.toLowerCase())) - .filter((i) => i > -1) - .slice(-1)[0]; - const startWithContext = Math.max(actualStartPosition - 120, 0); - - const top = startWithContext === 0 ? "" : "..."; - const tail = startWithContext + 240 < text.length ? "..." : ""; - - let summary = document.createElement("p"); - summary.classList.add("context"); - summary.textContent = top + text.substr(startWithContext, 240).trim() + tail; - - return summary; - }, -}; - -_ready(Search.init); diff --git a/docs/build/html/_static/sphinx_highlight.js b/docs/build/html/_static/sphinx_highlight.js deleted file mode 100644 index 8a96c69a1..000000000 --- a/docs/build/html/_static/sphinx_highlight.js +++ /dev/null @@ -1,154 +0,0 @@ -/* Highlighting utilities for Sphinx HTML documentation. */ -"use strict"; - -const SPHINX_HIGHLIGHT_ENABLED = true - -/** - * highlight a given string on a node by wrapping it in - * span elements with the given class name. - */ -const _highlight = (node, addItems, text, className) => { - if (node.nodeType === Node.TEXT_NODE) { - const val = node.nodeValue; - const parent = node.parentNode; - const pos = val.toLowerCase().indexOf(text); - if ( - pos >= 0 && - !parent.classList.contains(className) && - !parent.classList.contains("nohighlight") - ) { - let span; - - const closestNode = parent.closest("body, svg, foreignObject"); - const isInSVG = closestNode && closestNode.matches("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.classList.add(className); - } - - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - const rest = document.createTextNode(val.substr(pos + text.length)); - parent.insertBefore( - span, - parent.insertBefore( - rest, - node.nextSibling - ) - ); - node.nodeValue = val.substr(0, pos); - /* There may be more occurrences of search term in this node. So call this - * function recursively on the remaining fragment. - */ - _highlight(rest, addItems, text, className); - - if (isInSVG) { - const rect = document.createElementNS( - "http://www.w3.org/2000/svg", - "rect" - ); - const bbox = parent.getBBox(); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute("class", className); - addItems.push({ parent: parent, target: rect }); - } - } - } else if (node.matches && !node.matches("button, select, textarea")) { - node.childNodes.forEach((el) => _highlight(el, addItems, text, className)); - } -}; -const _highlightText = (thisNode, text, className) => { - let addItems = []; - _highlight(thisNode, addItems, text, className); - addItems.forEach((obj) => - obj.parent.insertAdjacentElement("beforebegin", obj.target) - ); -}; - -/** - * Small JavaScript module for the documentation. - */ -const SphinxHighlight = { - - /** - * highlight the search words provided in localstorage in the text - */ - highlightSearchWords: () => { - if (!SPHINX_HIGHLIGHT_ENABLED) return; // bail if no highlight - - // get and clear terms from localstorage - const url = new URL(window.location); - const highlight = - localStorage.getItem("sphinx_highlight_terms") - || url.searchParams.get("highlight") - || ""; - localStorage.removeItem("sphinx_highlight_terms") - url.searchParams.delete("highlight"); - window.history.replaceState({}, "", url); - - // get individual terms from highlight string - const terms = highlight.toLowerCase().split(/\s+/).filter(x => x); - if (terms.length === 0) return; // nothing to do - - // There should never be more than one element matching "div.body" - const divBody = document.querySelectorAll("div.body"); - const body = divBody.length ? divBody[0] : document.querySelector("body"); - window.setTimeout(() => { - terms.forEach((term) => _highlightText(body, term, "highlighted")); - }, 10); - - const searchBox = document.getElementById("searchbox"); - if (searchBox === null) return; - searchBox.appendChild( - document - .createRange() - .createContextualFragment( - '

' + - '' + - _("Hide Search Matches") + - "

" - ) - ); - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords: () => { - document - .querySelectorAll("#searchbox .highlight-link") - .forEach((el) => el.remove()); - document - .querySelectorAll("span.highlighted") - .forEach((el) => el.classList.remove("highlighted")); - localStorage.removeItem("sphinx_highlight_terms") - }, - - initEscapeListener: () => { - // only install a listener if it is really needed - if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) return; - - document.addEventListener("keydown", (event) => { - // bail for input elements - if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; - // bail with special keys - if (event.shiftKey || event.altKey || event.ctrlKey || event.metaKey) return; - if (DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS && (event.key === "Escape")) { - SphinxHighlight.hideSearchWords(); - event.preventDefault(); - } - }); - }, -}; - -_ready(() => { - /* Do not call highlightSearchWords() when we are on the search page. - * It will highlight words from the *previous* search query. - */ - if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); - SphinxHighlight.initEscapeListener(); -}); diff --git a/docs/build/html/api.html b/docs/build/html/api.html deleted file mode 100644 index de7c3c3e9..000000000 --- a/docs/build/html/api.html +++ /dev/null @@ -1,295 +0,0 @@ - - - - - - - - API Documentation — neo4j-genai-python documentation - - - - - - - - - - - - - - -
- -
- - -
- - -
- -
-
- -
-

API Documentation

-
-

Retrieval-Augmented Generation (RAG)

-

RAG is a technique that enhances Large Language Model (LLM) responses by retrieving -source information from external data stores to augment generated responses.

-

This package enables Python developers to use perform RAG using Neo4j.

-
-
-

Retrievers

-
-

VectorRetriever

-
-
-class neo4j_genai.retrievers.vector.VectorRetriever(driver: Driver, index_name: str, embedder: Embedder | None = None, return_properties: list[str] | None = None)
-

Provides retrieval method using vector search over embeddings. -If an embedder is provided, it needs to have the required Embedder type.

-
-
-search(query_vector: list[float] | None = None, query_text: str | None = None, top_k: int = 5) → list[VectorSearchRecord]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -See the following documentation for more details:

- -
-
Args:

query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -query_text (Optional[str], optional): The text to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[VectorSearchRecord]: The top_k neighbors found in vector search with their nodes and scores.

-
-
-
- -
- -
-
-

VectorCypherRetriever

-
-
-class neo4j_genai.retrievers.vector.VectorCypherRetriever(driver: Driver, index_name: str, retrieval_query: str, embedder: Embedder | None = None)
-

Provides retrieval method using vector similarity and custom Cypher query. -If an embedder is provided, it needs to have the required Embedder type.

-
-
-search(query_vector: list[float] | None = None, query_text: str | None = None, top_k: int = 5, query_params: dict[str, Any] | None = None) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -See the following documentation for more details:

- -
-
Args:

query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -query_text (Optional[str], optional): The text to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5. -query_params (Optional[dict[str, Any]], optional): Parameters for the Cypher query. Defaults to None.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[Record]: The results of the search query

-
-
-
- -
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HybridRetriever

-
-
-class neo4j_genai.retrievers.hybrid.HybridRetriever(driver: Driver, vector_index_name: str, fulltext_index_name: str, embedder: Embedder | None = None, return_properties: list[str] | None = None)
-
-
-search(query_text: str, query_vector: list[float] | None = None, top_k: int = 5) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -Both query_vector and query_text can be provided. -If query_vector is provided, then it will be preferred over the embedded query_text -for the vector search.

-

See the following documentation for more details:

- -
-
Args:

query_text (str): The text to get the closest neighbors of. -query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
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Returns:

list[Record]: The results of the search query

-
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HybridCypherRetriever

-
-
-class neo4j_genai.retrievers.hybrid.HybridCypherRetriever(driver: Driver, vector_index_name: str, fulltext_index_name: str, retrieval_query: str, embedder: Embedder | None = None)
-
-
-search(query_text: str, query_vector: list[float] | None = None, top_k: int = 5, query_params: dict[str, Any] | None = None) → list[Record]
-

Get the top_k nearest neighbor embeddings for either provided query_vector or query_text. -Both query_vector and query_text can be provided. -If query_vector is provided, then it will be preferred over the embedded query_text -for the vector search.

-

See the following documentation for more details:

- -
-
Args:

query_text (str): The text to get the closest neighbors of. -query_vector (Optional[list[float]], optional): The vector embeddings to get the closest neighbors of. Defaults to None. -top_k (int, optional): The number of neighbors to return. Defaults to 5. -query_params (Optional[dict[str, Any]], optional): Parameters for the Cypher query. Defaults to None.

-
-
Raises:

ValueError: If validation of the input arguments fail. -ValueError: If no embedder is provided.

-
-
Returns:

list[Record]: The results of the search query

-
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- - - - - - \ No newline at end of file diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html deleted file mode 100644 index 360c0f451..000000000 --- a/docs/build/html/genindex.html +++ /dev/null @@ -1,190 +0,0 @@ - - - - - - - Index — neo4j-genai-python documentation - - - - - - - - - - - - - -
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Index

- -
- H - | S - | V - -
-

H

- - - -
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S

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V

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- - - - - - \ No newline at end of file diff --git a/docs/build/html/index.html b/docs/build/html/index.html deleted file mode 100644 index 4d520f87a..000000000 --- a/docs/build/html/index.html +++ /dev/null @@ -1,166 +0,0 @@ - - - - - - - - Welcome to neo4j-genai-python’s documentation! — neo4j-genai-python documentation - - - - - - - - - - - - - - -
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- - - - - - \ No newline at end of file diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv deleted file mode 100644 index a4db56716..000000000 --- a/docs/build/html/objects.inv +++ /dev/null @@ -1,7 +0,0 @@ -# Sphinx inventory version 2 -# Project: neo4j-genai-python -# Version: -# The remainder of this file is compressed using zlib. -xڭN0 } -#&$NUl!eYi%DoǓ&hvrdќ?oQ3I'qӪ8)U Э*ffUL݋zdWe2?!;i<Goc8fy8dgZ/j >0 R&vu7 .QXƟ8(KgX9C^0|W,I8umP-gm!&3hFwxA/HlÄ$bmPH+#v -{QYTDrIse ;|z \ No newline at end of file diff --git a/docs/build/html/search.html b/docs/build/html/search.html deleted file mode 100644 index 6eb5eaf24..000000000 --- a/docs/build/html/search.html +++ /dev/null @@ -1,166 +0,0 @@ - - - - - - - Search — neo4j-genai-python documentation - - - - - - - - - - - - - - - - - - - -
- -
- - -
- - -
- -
-
- -

Search

- - - - -

- Searching for multiple words only shows matches that contain - all words. -

- - -
- - - -
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- -
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-
- - - - - - \ No newline at end of file diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js deleted file mode 100644 index 7f9ba351b..000000000 --- a/docs/build/html/searchindex.js +++ /dev/null @@ -1 +0,0 @@ -Search.setIndex({"docnames": ["README", "api", "index"], "filenames": ["README.md", "api.rst", "index.rst"], "titles": ["Neo4j GenAI package for Python", "API Documentation", "Welcome to neo4j-genai-python\u2019s documentation!"], "terms": {"thi": [0, 1], "repositori": 0, "contain": 0, "offici": 0, "featur": 0, "The": [0, 1], "purpos": 0, "i": [0, 1], "provid": [0, 1], "first": 0, "parti": 0, "where": 0, "can": [0, 1], "guarante": 0, "long": 0, "term": 0, "commit": 0, "mainten": 0, "well": 0, "being": 0, "fast": 0, "ship": 0, "new": 0, "high": 0, "pattern": 0, "method": [0, 1], "doc": 0, "ar": 0, "come": 0, "soon": 0, "requir": [0, 1], "3": 0, "8": 0, "1": 0, "To": 0, "latest": 0, "stabl": 0, "version": 0, "us": [0, 1], "pip": 0, "while": 0, "librari": 0, 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- -
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- - - - - - \ No newline at end of file diff --git a/docs/build/objects.inv b/docs/build/objects.inv deleted file mode 100644 index a4db56716..000000000 --- a/docs/build/objects.inv +++ /dev/null @@ -1,7 +0,0 @@ -# Sphinx inventory version 2 -# Project: neo4j-genai-python -# Version: -# The remainder of this file is compressed using zlib. -xڭN0 } -#&$NUl!eYi%DoǓ&hvrdќ?oQ3I'qӪ8)U Э*ffUL݋zdWe2?!;i<Goc8fy8dgZ/j >0 R&vu7 .QXƟ8(KgX9C^0|W,I8umP-gm!&3hFwxA/HlÄ$bmPH+#v -{QYTDrIse ;|z \ No newline at end of file diff --git a/docs/build/search.html b/docs/build/search.html deleted file mode 100644 index 6eb5eaf24..000000000 --- a/docs/build/search.html +++ /dev/null @@ -1,166 +0,0 @@ - - - - - - - Search — neo4j-genai-python documentation - - - - - - - - - - - - - - - - - - - -
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- Searching for multiple words only shows matches that contain - all words. -

- - -
- - - -
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- - - - - - \ No newline at end of file diff --git a/docs/build/searchindex.js b/docs/build/searchindex.js deleted file mode 100644 index 7f9ba351b..000000000 --- a/docs/build/searchindex.js +++ /dev/null @@ -1 +0,0 @@ -Search.setIndex({"docnames": ["README", "api", "index"], "filenames": ["README.md", "api.rst", "index.rst"], "titles": ["Neo4j GenAI package for Python", "API Documentation", "Welcome to neo4j-genai-python\u2019s documentation!"], "terms": {"thi": [0, 1], "repositori": 0, "contain": 0, "offici": 0, "featur": 0, "The": [0, 1], "purpos": 0, "i": [0, 1], "provid": [0, 1], "first": 0, "parti": 0, "where": 0, "can": [0, 1], "guarante": 0, "long": 0, "term": 0, "commit": 0, "mainten": 0, "well": 0, "being": 0, "fast": 0, "ship": 0, "new": 0, "high": 0, "pattern": 0, "method": [0, 1], "doc": 0, "ar": 0, "come": 0, "soon": 0, "requir": [0, 1], "3": 0, "8": 0, "1": 0, "To": 0, "latest": 0, "stabl": 0, "version": 0, "us": [0, 1], "pip": 0, "while": 0, "librari": 0, "ha": 0, 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"neo4j_genai.retrievers.vector.VectorCypherRetriever.search"]], "search() (neo4j_genai.retrievers.vector.vectorretriever method)": [[1, "neo4j_genai.retrievers.vector.VectorRetriever.search"]]}}) \ No newline at end of file diff --git a/docs/source/README.md b/docs/source/README.md index 10096a060..5e995465e 100644 --- a/docs/source/README.md +++ b/docs/source/README.md @@ -1,170 +1,14 @@ -# Neo4j GenAI package for Python +# Sphinx Documentation -This repository contains the official Neo4j GenAI features for Python. +Building the docs requires Python 3.8.1+ -The purpose of this package is to provide a first party package to developers, -where Neo4j can guarantee long term commitment and maintenance as well as being -fast to ship new features and high performing patterns and methods. - -Docs are coming soon! - -# Usage - -## Installation - -This package requires Python (>=3.8.1). - -To install the latest stable version, use: - -```shell -pip install neo4j-genai -``` - -## Examples - -While the library has more retrievers than shown here, the following examples should be able to get you started. - -### Performing a similarity search - -Assumption: Neo4j running with populated vector index in place. - -```python -from neo4j import GraphDatabase -from neo4j_genai import VectorRetriever - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "embedding-name" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Initialize the retriever -retriever = VectorRetriever(driver, INDEX_NAME) - -# Run the similarity search -query_text = "How do I do similarity search in Neo4j?" -response = retriever.search(query_text=query_text, top_k=5) -``` - -### Creating a vector index - -When creating a vector index, make sure you match the number of dimensions in the index with the number of dimensions the embeddings have. - -Assumption: Neo4j running - -```python -from neo4j import GraphDatabase -from neo4j_genai.indexes import create_vector_index - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -INDEX_NAME = "chunk-index" - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Creating the index -create_vector_index( - driver, - INDEX_NAME, - label="Document", - property="textProperty", - dimensions=1536, - similarity_fn="euclidean", -) +Ensure the dev dependencies in `pyproject.toml` are installed. +From the root directory ``` - -### Populating the Neo4j Vector Index - -This library does not write to the database, that is up to you. -See below for how to write using Cypher via the Neo4j driver. - -Assumption: Neo4j running with a defined vector index - -```python -from neo4j import GraphDatabase -from random import random - -URI = "neo4j://localhost:7687" -AUTH = ("neo4j", "password") - -# Connect to Neo4j database -driver = GraphDatabase.driver(URI, auth=AUTH) - -# Upsert the vector -vector = [random() for _ in range(DIMENSION)] -insert_query = ( - "MERGE (n:Document {id: $id})" - "WITH n " - "CALL db.create.setNodeVectorProperty(n, 'textProperty', $vector)" - "RETURN n" -) -parameters = { - "id": 0, - "vector": vector, -} -driver.execute_query(insert_query, parameters) +make -C docs html ``` -# Development - -## Install dependencies - -```bash -poetry install ``` - -## Getting started - -### Issues - -If you have a bug to report or feature to request, first -[search to see if an issue already exists](https://docs.github.com/en/github/searching-for-information-on-github/searching-on-github/searching-issues-and-pull-requests#search-by-the-title-body-or-comments). -If a related issue doesn't exist, please raise a new issue using the relevant -[issue form](https://github.com/neo4j/neo4j-genai-python/issues/new/choose). - -If you're a Neo4j Enterprise customer, you can also reach out to [Customer Support](http://support.neo4j.com/). - -If you don't have a bug to report or feature request, but you need a hand with -the library; community support is available via [Neo4j Online Community](https://community.neo4j.com/) -and/or [Discord](https://discord.gg/neo4j). - -### Make changes - -1. Fork the repository. -2. Install Python and Poetry. For more information, see [the development guide](./docs/contributing/DEVELOPING.md). -3. Create a working branch from `main` and start with your changes! - -### Pull request - -When you're finished with your changes, create a pull request, also known as a PR. - -- Ensure that you have [signed the CLA](https://neo4j.com/developer/contributing-code/#sign-cla). -- Ensure that the base of your PR is set to `main`. -- Don't forget to [link your PR to an issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue) - if you are solving one. -- Enable the checkbox to [allow maintainer edits](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/allowing-changes-to-a-pull-request-branch-created-from-a-fork) - so that maintainers can make any necessary tweaks and update your branch for merge. -- Reviewers may ask for changes to be made before a PR can be merged, either using - [suggested changes](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/reviewing-changes-in-pull-requests/incorporating-feedback-in-your-pull-request) - or normal pull request comments. You can apply suggested changes directly through - the UI, and any other changes can be made in your fork and committed to the PR branch. -- As you update your PR and apply changes, mark each conversation as [resolved](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/commenting-on-a-pull-request#resolving-conversations). - -## Run tests - -Open a new virtual environment and then run the tests. - -```bash -poetry shell -pytest +python -m sphinx -b html docs/source docs/build/html ``` - -## Further information - -- [The official Neo4j Python driver](https://github.com/neo4j/neo4j-python-driver) -- [Neo4j GenAI integrations](https://neo4j.com/docs/cypher-manual/current/genai-integrations/) diff --git a/docs/source/api.rst b/docs/source/api.rst index 7e46f2f40..c2921b908 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -37,7 +37,7 @@ HybridRetriever HybridCypherRetriever -=============== +===================== .. autoclass:: neo4j_genai.retrievers.hybrid.HybridCypherRetriever :members: diff --git a/src/neo4j_genai/queries.py b/src/neo4j_genai/queries.py deleted file mode 100644 index 752677d5f..000000000 --- a/src/neo4j_genai/queries.py +++ /dev/null @@ -1,56 +0,0 @@ -# Copyright (c) "Neo4j" -# Neo4j Sweden AB [https://neo4j.com] -# # -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# # -# https://www.apache.org/licenses/LICENSE-2.0 -# # -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -from typing import Optional - -from neo4j_genai.types import SearchType - - -def get_search_query( - search_type: SearchType, - return_properties: Optional[list[str]] = None, - retrieval_query: Optional[str] = None, -): - query_map = { - SearchType.VECTOR: ( - "CALL db.index.vector.queryNodes($index_name, $top_k, $query_vector) " - ), - SearchType.HYBRID: ( - "CALL { " - "CALL db.index.vector.queryNodes($vector_index_name, $top_k, $query_vector) " - "YIELD node, score " - "RETURN node, score UNION " - "CALL db.index.fulltext.queryNodes($fulltext_index_name, $query_text, {limit: $top_k}) " - "YIELD node, score " - "WITH collect({node:node, score:score}) AS nodes, max(score) AS max " - "UNWIND nodes AS n " - "RETURN n.node AS node, (n.score / max) AS score " - "} " - "WITH node, max(score) AS score ORDER BY score DESC LIMIT $top_k " - ), - } - - base_query = query_map[search_type] - additional_query = "" - - if retrieval_query: - additional_query += retrieval_query - elif return_properties: - return_properties_cypher = ", ".join([f".{prop}" for prop in return_properties]) - additional_query += "YIELD node, score " - additional_query += f"RETURN node {{{return_properties_cypher}}} as node, score" - else: - additional_query += "RETURN node, score" - - return base_query + additional_query
- -