Cognigy.AI OData Analytics Endpoint - Cognigy Documentation

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Updated in 2026.14 Open Data Protocol (OData) is a standard for building and using RESTful APIs. This protocol simplifies data access for web clients by providing a consistent way to describe data models and perform CRUD operations (create, read, update, delete) using standard HTTP methods and URLs.Based on the OData protocol version 4, Cognigy.AI offers an OData Analytics endpoint to retrieve raw data using GET requests. This endpoint meets all your enterprise analytics needs, enabling you to make fine-grained queries in your spreadsheets or build rich dashboards for AI Agents with your favorite data visualization tool.Watch this video to get a quick overview of what the OData Analytics endpoint is, how it works, and in which scenarios you can use it:

Cognigy Sessions: Cognigy Insights & OData - YouTube

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Cognigy Sessions: Cognigy Insights & OData NiCE Cognigy

NiCE Cognigy2.97K subscribers

To analyze your AI Agent’s performance, you can use the built-in Insights reports as an alternative to OData or in addition to it.

​ Limitations

OData Endpoint Field Size and Length Limitations

• By default, the OData endpoint fields have the following limitations by data type:

• The OData endpoint fields in the following table have a maximum length that differs from the default limitations:

​ Restrictions

• The Cognigy.AI OData endpoint supports only the OData protocol version 4.
• The Cognigy.AI OData endpoint only supports GET requests and doesn’t support any other request types, such as PATCH, DELETE, or POST.
• The data retrieved through the Cognigy.AI OData endpoint isn’t updated in real time and may not reflect the current state.
• The Cognigy.AI OData endpoint supports a limited set of system query options, operators, and query functions. For detailed information about the query syntax, refer to the OData Query Syntax section.

​ Supported Versions

​ Data Protection

You can control the data available through the OData endpoint at the Endpoint, Flow, and Node levels:

• Endpoint — go to the Data Protection & Analytics section in the Endpoint settings:

• If you disable the Collect Analytics setting, no analytics data is logged or available in OData.

  • If you enable the Mask Sensitive Analytics setting, the inputText and inputData fields are masked.

• Flow — add a Blind Mode Node to your Flow. This Node disables or masks analytics data available to the OData endpoint.

• Node — use the Mask and keep analytics data parameter in the Delete Profile Node and the Keep analytics records, mask personal data option in the Deactivate Profile Node. These Nodes can mask personal data while including analytics data across the Analytics, Conversations, and Sessions collections. By default, rows with masked personal data in these collections are included in OData results. To exclude rows where personal data has been masked:

• For SaaS installations, contact Cognigy technical support.

  • For on-premises installations, set ODATA_FILTER_MASKED_ROWS=true in values.yaml.

​ OData Endpoint Access

You can access the OData endpoint through a different domain than the one from Cognigy.AI:

• Cognigy

• NiCE CXone

Depending on the type of Cognigy installation you have, the OData endpoint domain is as follows:

• Trial — https://odata-trial.cognigy.ai.
• Shared SaaS — https://odata-<your-domain>.cognigy.ai.
• Dedicated SaaS — contact your Customer Success Manager or Cognigy.AI Support to get the OData endpoint URL.
• On-premises — https://odata-<backend-url>, where <backend-url> refer to the URL assigned to the BACKEND_BASE_URL_WITH_PROTOCOL in values.yaml.

Use the following pattern: https://cognigy-odata-<region>.nicecxone.com, where <region> matches your NiCE CXone cluster. For example:

• https://cognigy-odata-na1.nicecxone.com
• https://cognigy-odata-na3.nicecxone.com
• https://cognigy-odata-eu1.nicecxone.com

For a full list of available regions, refer to NiCE CXone Shared SaaS.

​ Authentication

To connect to the OData endpoint, you need to have the odata global role and an API Key.To authenticate your API requests to the OData endpoint, you need the following parameters:

• The Cognigy.AI OData base domain. It is the root URL where your OData service is hosted.
• The API version of the Cognigy.AI OData endpoint. Currently, Cognigy.AI supports OData 2.3 and 2.4.
• The collection in the OData service you want to access.
• The API key that authenticates and authorizes the API access. Generate the API key in your profile.

​ Authentication Methods

You can use the following methods to authenticate your requests to the OData endpoint:

• HTTP Headers — this method provides more security to access the OData endpoint. HTTP header authentication prevents API keys from exposure in the URL, server access logs, and other security risks. This method doesn’t support Microsoft Excel and Power BI integrations.
• Query Parameters — allows for Microsoft Excel and Power BI integrations. For this method, ensure appropriate access controls and security measures to prevent security risks.

​ Examples

The following examples use the following parameters:

• Cognigy.AI OData base domain — odata-trial.cognigy.ai

• Cognigy.AI OData endpoint version — v2.4

• OData collection — Analytics

• API key — 123abc

• HTTP Headers

• Query Parameters

cURL

JavaScript

Python

Node.js

curl -H "apikey: 123abc" \
"https://odata-trial.cognigy.ai/v2.4/Analytics"

fetch('https://odata-trial.cognigy.ai/v2.4/Analytics', {
  headers: {
    'apikey': '123abc'
  }
});

import requests
requests.get('https://odata-trial.cognigy.ai/v2.4/Analytics', headers={'apikey': '123abc'})

const axios = require('axios');
axios.get('https://odata-trial.cognigy.ai/v2.4/Analytics', { headers: { 'apikey': '123abc' } });

https://odata-trial.cognigy.ai/v2.4/Analytics?apikey=123abc

If you are using the query parameters method to authenticate your requests to the OData endpoint, you can migrate to the HTTP headers method without breaking changes as follows:

Migrate from Query Parameters to HTTP Headers

If you currently use query parameters authentication with https://odata-trial.cognigy.ai/v2.4/Analytics?apikey=123abc, you can migrate to HTTP headers authentication by using the following HTTP headers:

cURL

JavaScript

Python

Node.js

curl -H "apikey: 123abc" \
"https://odata-trial.cognigy.ai/v2.4/Analytics"

fetch('https://odata-trial.cognigy.ai/v2.4/Analytics', {
  headers: {
    'apikey': '123abc'
  }
});

import requests
requests.get('https://odata-trial.cognigy.ai/v2.4/Analytics', headers={'apikey': '123abc'})

const axios = require('axios');
axios.get('https://odata-trial.cognigy.ai/v2.4/Analytics', { headers: { 'apikey': '123abc' } });

​ Authentication for Microsoft Excel and Power BI

When using Microsoft Excel and Power BI, you might be prompted to authenticate. In this case, select Anonymous Authentication.

​ OData Query Syntax

The following rules define how OData queries must be structured when using system query options, operators, and string functions.These syntax requirements ensure that requests are valid, predictable, and compatible with the OData v4 protocol. They apply to all Cognigy.AI OData endpoint Collections and must be followed when creating query expressions.

List of Requirements

​ System Query Options

The Cognigy.AI OData endpoint supports a limited set of system query options:

​ Supported Operators and Query Functions

The Cognigy.AI OData endpoint supports a limited set of operators and query functions that you can use in the $filter system query option to create more complex queries.

Comparison Operators

These operators allow you to compare field values against specific criteria to filter your data effectively.

Logical Operators

These operators allow you to combine multiple conditions for creating complex queries.

The not logical operator isn’t supported in the Cognigy.AI OData endpoint. Expressions such as not startswith(field, 'value'), not contains(field, 'value'), or startswith(field, 'value') eq false won’t work.

Query Functions

These functions allow you to perform complex filtering based on string patterns.

• Query functions may affect the performance of your requests. Use them with caution, especially on large datasets.
• Query functions don’t work in fields of type text[] (array of text values). Use exact match filtering (eq) or filter in a different supported field.

​ Examples

The tables contain examples of requests using system query options and operators. Select the OData endpoint version compatible with your Cognigy.AI version.

• OData 2.4

• OData 2.3

For a full reference, refer to the extensive collection of resources at OData.org and the Oasis OData URL Convention documentation.

​ Cognigy.AI OData Collections

The OData endpoint provides access to several data collections containing information about your interactions and workflows. A collection is similar to a database table or a set of entities containing data. The set of collections varies depending on which version you are using:

• Version 2.4

• Version 2.3

The current version of the OData endpoint is v2.4. In this version, the following OData collections are available:

• Analytics (/Analytics)
• Conversations (/Conversations)
• Steps (/Steps)
• ExecutedSteps (/ExecutedSteps)
• Sessions (/Sessions)
• LiveAgentEscalations (/LiveAgentEscalations)
• Goals (/Goals)
• GoalSteps (/GoalSteps)
• GoalStepMetrics (/GoalStepMetrics)
• GoalEvents (/GoalEvents)

The URL for accessing the OData endpoint 2.4 is as follows: https://<odata-domain>/v2.4/<collection>?apikey=<your-api-key>

The previous version of the OData endpoint is 2.3. In this version, the following OData collections are available:

The URL for accessing the OData endpoint 2.3 is as follows: https://<odata-domain>/v2.3/<collection>?apikey=<your-api-key>

Each collection can be filtered by its fields, which are often retrieved directly from the Input object results.

​ Analytics

The Analytics collection offers a log of comprehensive details such as organizational information, Project identifiers, Flow specifics, and essential performance metrics. Each chat or voice AI Agent session in Cognigy.AI creates an Analytics record for an interaction. Each interaction is logged as a single record. The information is saved only after the end of the session. You can change this data using the Overwrite Analytics Node.RequestsSelect an API request to extract data from the collection. The API version in the request must match your Cognigy.AI version.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/Analytics?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/Analytics?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

The Analytics step label can be updated from the Cognigy.AI UI at any time. Therefore, to ensure compatibility between past and future data records, the entityReferenceId field is used. This field corresponds to either the Node ID or Intent ID assigned as an Analytics step. The current Analytics step label can be retrieved by mapping the entityReferenceID field to the Steps record.

​ Conversations

The Conversations collection offers a log of all session messages, including messages from the end user, AI Agent, and human agent. Each time one of these sources sends a message to a Flow, Cognigy.AI creates a record to log the interaction. Each interaction is logged as a single record.RequestsSelect an API request to extract data from the collection. The API version in the request must match your Cognigy.AI version.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/Conversations?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/Conversations?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ Steps

The Steps collection provides a list of all entities, which are either Nodes or Intents, assigned as Analytics Steps within any Flow. An Analytics step appear in this OData collection only after it has been triggered at least once in a session within the Flow. Each step is logged as a single record.RequestsSelect an API request to extract data from the collection. The API version in the request must match your Cognigy.AI version.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/Steps?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/Steps?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

The Step Monitoring with OData article explains how these records can be manipulated in BI software to build insightful session path analytics.

​ ExecutedSteps

The ExecutedSteps collection logs all step events in sessions, including a reference to the prior (parent) step. Whenever a Node or Intent with an assigned step is executed, the collection creates a record for that step. Each step is logged as a single record.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/ExecutedSteps?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/ExecutedSteps?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ Sessions

The Sessions collection contains a list of all sessions that have occurred. The primary objective of this collection is to provide a list of the Analytics steps that took place in any given session, along with the order of execution. This information is included as a comma-separated list within a field called stepPath. Each session is logged as a single record.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/Sessions?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/Sessions?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ LiveAgentEscalations

The LiveAgentEscalations collection contains records from Cognigy Live Agent and includes the related data about handovers to Live Agent. Each handover (escalation) is logged as a single record.

• OData 2.4

• OData 2.3

https://odata-trial.cognigy.ai/v2.4/LiveAgentEscalations?apikey=<your-api-key>

https://odata-trial.cognigy.ai/v2.3/LiveAgentEscalations?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ Goals

The Goals collection contains records from goals. Each goal is logged as a single record.

• OData 2.4

https://odata-trial.cognigy.ai/v2.4/Goals?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ GoalSteps

The GoalSteps collection contains records about a specific Goal step from goals. Each goal is logged as a single record.

• OData 2.4

https://odata-trial.cognigy.ai/v2.4/GoalSteps?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ GoalStepMetrics

The GoalStepMetrics collection contains records about specific goal-related events from goals. Each metric is logged as a single record.

• OData 2.4

https://odata-trial.cognigy.ai/v2.4/GoalStepMetrics?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ GoalEvents

The GoalEvents collection contains records about specific goal-related events from goals. Each event is logged as a single record.

• OData 2.4

https://odata-trial.cognigy.ai/v2.4/GoalEvents?apikey=<your-api-key>

ResponseWhen retrieving this collection, the endpoint returns the following fields:

Response Fields

​ Cognigy.AI OData Collections: Entity Relationship Diagram (ERD)

The Entity Relationship Diagram (ERD) describes the relationships between the collection entities.

logs messages

executes

summarized by

escalates via

tracks goals via

executed as

parentStep (self)

has

measured by

tracked by

measured by

Sessions

string

id

PK

string

sessionId

UK

string

userId

string

goals

string

stepPath

number

stepsCount

datetime

startedAt

string

projectId

string

organisationId

string

more

...

Conversations

string

id

PK

string

sessionId

FK

string

inputId

string

type

string

source

string

inputText

datetime

timestamp

string

projectId

string

organisation

string

more

...

ExecutedSteps

string

id

PK

string

sessionId

FK

string

parentStep

FK

string

entityReferenceId

FK

string

flowReferenceId

string

stepLabel

datetime

timestamp

string

projectId

string

organisationId

string

more

...

Analytics

string

id

PK

string

sessionId

FK

string

flowReferenceId

string

organisation

string

projectId

string

intent

string

completedGoalsList

datetime

timestamp

number

executionTime

string

more

...

LiveAgentEscalations

string

id

PK

string

sessionId

FK

string

organisationId

string

projectId

string

status

string

teamName

string

agentName

datetime

timestamp

string

more

...

GoalEvents

string

id

PK

string

goalId

FK

string

sessionId

FK

string

stepId

string

goalCycleId

string

version

datetime

timestamp

string

projectId

string

organisationId

string

more

...

Steps

string

id

PK

string

entityReferenceId

UK

string

flowReferenceId

string

label

string

type

string

flowName

string

projectName

string

more

...

Goals

string

goalId

PK

string

name

string

version

string

referenceId

string

projectId

string

organisationId

datetime

createdAt

string

more

...

GoalSteps

string

goalStepId

PK

string

goalId

FK

string

name

string

type

int

order

string

projectId

string

organisationId

string

more

...

GoalStepMetrics

string

goalStepMetricId

PK

string

goalId

FK

string

goalStepId

FK

string

name

string

type

int

value

string

projectId

string

organisationId

string

more

...

Legend

string

info

One-to-Many: ||--o{ (1..*)

string

info2

One-to-One: O--O (1..1)

string

info3

Many-to-Many: }o--o{ ( ..)

string

info4

Optional-to-One: |o--|| (0..1)

string

info5

Strong One-to-One: ||--||

string

abbr

PK=Primary Key, FK=Foreign Key, UK=Unique Key

​ Integrations

The Cognigy.AI OData endpoint can integrate with all tools compatible with the OData protocol version 4. The table outlines popular integration tools, including data visualization tools, recommended for integration.

If you want to use another tool not listed in the table, verify its compatibility with the OData endpoint on the OData website and in the tool’s documentation before integrating. For example, the data visualization tool Tableau can’t be used for integration because it doesn’t support the OData protocol version 4 on which the OData endpoint is based.

​ Keyset Pagination

Keyset pagination is a more efficient way to retrieve data from large datasets where you need to set $skip to high values, such as 10000. To use keyset pagination, follow these steps:

Keyset Pagination

1. Retrieve the first page with the $top and $orderby query options, for example, https://odata-trial.cognigy.ai/v2.4/Conversations?apikey=<your-api-key>&$top=10000&$orderby=timestamp asc.
2. Use the last timestamp value from the previous page in the next page request, for example, https://odata-trial.cognigy.ai/v2.4/Conversations?apikey=<your-api-key>&$filter=timestamp gt <LAST_TIMESTAMP_FROM_PREVIOUS_PAGE>&$top=10000&$orderby=timestamp asc.
3. Repeat step 2 until you have retrieved all the records.

​ More Information

• Collecting Data
• Insights

1: Microsoft Excel and Power BI do not support for the $count query. Use Postman or other options. To perform this query, consider using tools such as Postman or other applications that support advanced API querying.

Last modified onJune 29, 2026

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// Batch style updates Object.assign(viewer.style, { display: 'none', visibility: 'hidden', position: 'absolute', width: '1px', height: '1px', overflow: 'hidden', opacity: '0', pointerEvents: 'none', margin: '0', padding: '0' });

viewer.setAttribute('data-initialized', 'true'); viewer.setAttribute('data-viewer-replaced', 'true');

processedAny = true; invalidateQueryCache();

requestAnimationFrame(function() { updateIframeDimensions(iframeWrapper, scaleDiv, iframe, zoom); }); } } catch (e) { isInitializing = false; return; } });

if (processedAny) { const currentUrl = window.location.href; processedUrls.add(currentUrl); lastUrl = currentUrl; invalidateQueryCache(); }

isInitializing = false; }

// Wait for content area to be available function waitForContentArea(callback, maxAttempts, attempt) { attempt = attempt || 0; maxAttempts = maxAttempts || 20;

const contentArea = document.querySelector('#content-area') || document.querySelector('.mdx-content');

if (contentArea && document.contains(contentArea)) { cachedContentArea = contentArea; callback(); } else if (attempt < maxAttempts) { setTimeout(function() { waitForContentArea(callback, maxAttempts, attempt + 1); }, 500); } else { cachedContentArea = document.body; callback(); } }

// Optimized: Initialize with better state management function initialize() { const currentUrl = window.location.href; if (lastUrl !== currentUrl && lastUrl !== null) { lastUrl = currentUrl; processedUrls.clear(); invalidateQueryCache(); }

if (typeof window !== 'undefined') { window.__lastFullUrl = window.location.href; }

if (lastThemeClass === null && document.documentElement) { lastThemeClass = document.documentElement.className; }

if (!themeObserver && document.documentElement) { themeObserver = new MutationObserver(function(mutations) { for (let i = 0; i < mutations.length; i++) { const mutation = mutations[i]; if (mutation.type === 'attributes' && mutation.attributeName === 'class') { const currentThemeClass = document.documentElement.className; if (lastThemeClass !== null && lastThemeClass !== currentThemeClass) { themeToggleInProgress = true;

// Optimized: Lock containers synchronously const contentArea = getContentArea(); if (contentArea) { const containers = getContainers(true); containers.forEach(function(container) { if (container.getAttribute('data-position-locked') !== 'true') { const rect = container.getBoundingClientRect(); Object.assign(container.style, { position: 'fixed', top: rect.top + 'px', left: rect.left + 'px', width: rect.width + 'px', zIndex: '9999', margin: '0' }); container.setAttribute('data-position-locked', 'true'); containerPositions.set(container, { top: rect.top, left: rect.left, width: rect.width, height: rect.height }); } }); }

let repositionAttempts = 0; const maxRepositionAttempts = 30;

const repositionInterval = setInterval(function() { repositionAttempts++; repositionContainersAfterThemeToggleCore(); // Use core function for immediate repositioning if (repositionAttempts >= maxRepositionAttempts) { clearInterval(repositionInterval); } }, 100);

setTimeout(function() { clearInterval(repositionInterval); themeToggleInProgress = false; repositionContainersAfterThemeToggleCore(); // Use core function for final repositioning unlockContainers(); }, 3000); } lastThemeClass = currentThemeClass; } } });

themeObserver.observe(document.documentElement, { attributes: true, attributeFilter: ['class'] }); }

if (typeof MutationObserver !== 'undefined') { setupObserver(); }

waitForContentArea(function() { setTimeout(function() { initSinglePageViewers(); setTimeout(function() { const remaining = getUninitializedViewers(true); if (remaining.length > 0) { initSinglePageViewers(); } }, INIT_DELAY); }, INIT_DELAY); }); }

// Optimized: Lock/unlock containers function lockContainersInPlace() { const contentArea = getContentArea(); if (!contentArea) return;

const containers = getContainers(true); containerPositions.clear();

requestAnimationFrame(function() { containers.forEach(function(container) { if (container.getAttribute('data-position-locked') !== 'true') { const rect = container.getBoundingClientRect(); Object.assign(container.style, { position: 'fixed', top: rect.top + 'px', left: rect.left + 'px', width: rect.width + 'px', zIndex: '9999', margin: '0' }); container.setAttribute('data-position-locked', 'true'); containerPositions.set(container, { top: rect.top, left: rect.left, width: rect.width, height: rect.height }); } }); }); }

function unlockContainers() { const contentArea = getContentArea(); if (!contentArea) return;

const containers = Array.from( contentArea.querySelectorAll('.single-page-viewer-container[data-position-locked="true"]') );

containers.forEach(function(container) { Object.assign(container.style, { position: '', top: '', left: '', width: '', zIndex: '', margin: '' }); container.removeAttribute('data-position-locked'); // Clean up container position from Map to prevent memory leak containerPositions.delete(container); });

containerPositions.clear(); }

// Optimized: Reposition containers with better DOM operations // Core repositioning function (not debounced for immediate use) function repositionContainersAfterThemeToggleCore() { const contentArea = getContentArea(); if (!contentArea) return;

const containers = getContainers(true);

containers.forEach(function(container) { const viewerId = container.getAttribute('data-viewer-id'); if (!viewerId) return;

let viewer = document.getElementById(viewerId);

if (!viewer) { const iframe = container.querySelector('iframe'); if (iframe && iframe.src) { const allViewers = contentArea.querySelectorAll('[data-single-page-viewer]'); for (let i = 0; i < allViewers.length; i++) { const v = allViewers[i]; if (v.getAttribute('data-src') === iframe.src) { viewer = v; viewer.id = viewerId; viewer.setAttribute('data-viewer-id', viewerId); Object.assign(viewer.style, { display: 'none', visibility: 'hidden', position: 'absolute', width: '1px', height: '1px', overflow: 'hidden', opacity: '0', pointerEvents: 'none', margin: '0', padding: '0' }); viewer.setAttribute('data-initialized', 'true'); viewer.setAttribute('data-viewer-replaced', 'true'); break; } } } }

if (viewer && viewer.parentNode) { if (container.getAttribute('data-position-locked') === 'true') { unlockContainers(); }

const viewerIndex = Array.from(viewer.parentNode.children).indexOf(viewer); const containerIndex = Array.from(viewer.parentNode.children).indexOf(container);

if (containerIndex !== viewerIndex + 1) { // CRITICAL: Check if container is actually a child before removing if (container.parentNode && container.parentNode.contains(container)) { try { container.parentNode.removeChild(container); } catch (e) { return; // Skip repositioning if removal failed } } if (viewer.nextSibling) { viewer.parentNode.insertBefore(container, viewer.nextSibling); } else { viewer.parentNode.appendChild(container); } } else if (container.parentNode !== viewer.parentNode) { // CRITICAL: Check if container is actually a child before removing if (container.parentNode && container.parentNode.contains(container)) { try { container.parentNode.removeChild(container); } catch (e) { return; // Skip repositioning if removal failed } } if (viewer.nextSibling) { viewer.parentNode.insertBefore(container, viewer.nextSibling); } else { viewer.parentNode.appendChild(container); } } } });

invalidateQueryCache(); }

// Debounced version for non-critical repositioning const repositionContainersAfterThemeToggle = debounce(repositionContainersAfterThemeToggleCore, REPOSITION_DEBOUNCE);

// Optimized: Observer setup with better filtering let observer = null; let containerPositionObserver = null; let fallbackObserver = null; // Track fallback observer for cleanup

function setupContainerPositionObserver() { if (typeof MutationObserver === 'undefined') return;

const contentArea = getContentArea(); if (!contentArea || !document.contains(contentArea)) { setTimeout(setupContainerPositionObserver, 500); return; }

if (containerPositionObserver) { containerPositionObserver.disconnect(); }

containerPositionObserver = new MutationObserver(function(mutations) { if (themeToggleInProgress) { // Use core function (not debounced) for immediate repositioning during theme toggle requestAnimationFrame(repositionContainersAfterThemeToggleCore); return; }

let needsReposition = false; for (let i = 0; i < mutations.length && !needsReposition; i++) { if (mutations[i].type === 'childList') { needsReposition = true; } }

if (needsReposition) { clearTimeout(containerPositionObserver._timeout); containerPositionObserver._timeout = setTimeout(repositionContainersAfterThemeToggle, REPOSITION_DEBOUNCE); } });

containerPositionObserver.observe(contentArea, { childList: true, subtree: true, attributes: false, characterData: false });

containerPositionObserver._timeout = null; }

// Optimized: Main observer with better early exits function setupObserver() { if (typeof MutationObserver === 'undefined') return;

const contentArea = getContentArea(); if (!contentArea || !document.contains(contentArea)) { setTimeout(setupObserver, 500); return; }

if (contentArea === document.documentElement || contentArea === document.body) { return; }

if (observer) { const currentObserved = observer._observedElement; if (currentObserved === contentArea && document.contains(contentArea)) { return; } if (currentObserved) { observer.disconnect(); } observer = null; }

observer = new MutationObserver(function(mutations) { if (themeToggleInProgress) return;

let hasNewViewer = false; for (let i = 0; i < mutations.length && !hasNewViewer; i++) { const mutation = mutations[i]; if (mutation.addedNodes && mutation.addedNodes.length > 0) { for (let j = 0; j < mutation.addedNodes.length && !hasNewViewer; j++) { const node = mutation.addedNodes[j]; if (node.nodeType === 1 && node.hasAttribute && node.hasAttribute('data-single-page-viewer') && !node.hasAttribute('data-initialized') && !node.hasAttribute('data-viewer-replaced')) { hasNewViewer = true; } } } }

if (hasNewViewer) { // Use core function for immediate repositioning when new viewer detected repositionContainersAfterThemeToggleCore(); setTimeout(repositionContainersAfterThemeToggleCore, 10); setTimeout(repositionContainersAfterThemeToggleCore, 50); setTimeout(repositionContainersAfterThemeToggleCore, 200); }

clearTimeout(observerTimeout); observerTimeout = setTimeout(function() { if (themeToggleInProgress) return;

let hasNewViewer = false; for (let i = 0; i < mutations.length && !hasNewViewer; i++) { const mutation = mutations[i];

if (mutation.target === document.documentElement || mutation.target === document.body) { continue; }

if (mutation.type === 'attributes' && mutation.attributeName === 'class' && mutation.target === document.documentElement) { continue; }

if (mutation.type === 'attributes' && mutation.attributeName === 'data-initialized') { const target = mutation.target; if (target && target.hasAttribute && target.hasAttribute('data-single-page-viewer') && !target.hasAttribute('data-initialized')) { hasNewViewer = true; } }

if (mutation.addedNodes && mutation.addedNodes.length > 0) { for (let j = 0; j < mutation.addedNodes.length && !hasNewViewer; j++) { const node = mutation.addedNodes[j]; if (node.nodeType === 1 && node.hasAttribute && node.hasAttribute('data-single-page-viewer') && !node.hasAttribute('data-initialized')) { hasNewViewer = true; } } } }

if (hasNewViewer) { invalidateQueryCache(); initSinglePageViewers(); } }, OBSERVER_DEBOUNCE); });

observer.observe(contentArea, { childList: true, subtree: true, attributes: true, attributeFilter: ['data-initialized'], characterData: false });

observer._observedElement = contentArea; setupContainerPositionObserver(); }

function start() { setupObserver(); initialize(); }

function checkAndInitialize() { if (isInitializing) return;

const currentUrl = window.location.href; if (currentUrl === lastUrl && lastUrl !== null) { return; }

const contentArea = document.querySelector('#content-area') || document.querySelector('.mdx-content'); if (contentArea) { const viewers = getUninitializedViewers(true); if (viewers.length > 0) { cachedContentArea = contentArea; setupObserver(); initialize(); } } }

if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', start); } else { setTimeout(start, 100); }

if (typeof window !== 'undefined' && window.next) { let initialLoadAttempts = 0; const maxInitialAttempts = 4; const attemptDelays = [200, 500, 1000, 2000]; const initialUrl = window.location.href;

attemptDelays.forEach(function(delay) { setTimeout(function() { if (initialLoadAttempts < maxInitialAttempts) { initialLoadAttempts++; if (window.location.href === initialUrl) { checkAndInitialize(); } } }, delay); }); }

window.addEventListener('popstate', function(e) { const currentUrl = window.location.href; if (currentUrl !== lastUrl) { handleNavigation(); } });

if (typeof window !== 'undefined') { if (window.next && window.next.router && window.next.router.events) { window.next.router.events.on('routeChangeComplete', function(url) { lastUrl = window.location.href; isInitializing = false; pendingInitCall = false; if (navigationTimeout) { clearTimeout(navigationTimeout); navigationTimeout = null; } invalidateContentAreaCache(); invalidateQueryCache(); setTimeout(function() { setupObserver(); initialize(); }, 300); });

window.next.router.events.on('routeChangeStart', function(url) { isInitializing = false; pendingInitCall = false; }); }

if (!window.next || !window.next.router) { const originalPushState = history.pushState; const originalReplaceState = history.replaceState;

history.pushState = function() { originalPushState.apply(history, arguments); setTimeout(function() { if (window.location.href !== lastUrl) { handleNavigation(); } }, 0); };

history.replaceState = function() { originalReplaceState.apply(history, arguments); setTimeout(function() { if (window.location.href !== lastUrl) { handleNavigation(); } }, 0); }; } }

document.addEventListener('visibilitychange', function() { if (!document.hidden) { isInitializing = false; startPeriodicCheck(); if (!pendingInitCall) { pendingInitCall = true; setTimeout(function() { pendingInitCall = false; initSinglePageViewers(); }, INIT_DELAY / 2); } } });

function startPeriodicCheck() { if (periodicCheckInterval) return;

periodicCheckInterval = setInterval(function() { const uninitialized = getUninitializedViewers(true); if (uninitialized.length === 0) { clearInterval(periodicCheckInterval); periodicCheckInterval = null; } else if (!isInitializing) { initSinglePageViewers(); } }, 2000); }

setTimeout(startPeriodicCheck, INIT_DELAY * 2);

window.__singlePageViewerInit = function() { const currentUrl = window.location.href; if (currentUrl === lastUrl) { return; }

isInitializing = false; pendingInitCall = false; lastUrl = currentUrl; invalidateContentAreaCache(); invalidateQueryCache(); setupObserver(); initialize(); };

window.__singlePageViewerCheck = function() { invalidateQueryCache(); initSinglePageViewers(); }; })();

// Optimized: Second IIFE for navigation handling (function() { 'use strict';

let lastPathname = window.location.pathname; let lastInitializedPathname = window.location.pathname;

function checkAndInit() { const currentPathname = window.location.pathname; if (currentPathname === lastInitializedPathname) { return; }

lastInitializedPathname = currentPathname; if (typeof window !== 'undefined') { window.__lastFullUrl = window.location.href; }

if (window.__singlePageViewerInit) { window.__singlePageViewerInit(); } }

function runInit() { if (window.__singlePageViewerInit) { setTimeout(checkAndInit, 100); } else { let attempts = 0; const maxAttempts = 50; const checkInterval = setInterval(function() { attempts++; if (window.__singlePageViewerInit) { clearInterval(checkInterval); setTimeout(checkAndInit, 100); } else if (attempts >= maxAttempts) { clearInterval(checkInterval); } }, 100); } }

if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', runInit); } else { setTimeout(runInit, 100); }

if (typeof window !== 'undefined' && window.next && window.next.router && window.next.router.events) { window.next.router.events.on('routeChangeComplete', function(url) { lastPathname = window.location.pathname; setTimeout(checkAndInit, 300); }); }

setInterval(function() { const currentPathname = window.location.pathname; if (currentPathname !== lastPathname) { lastPathname = currentPathname; setTimeout(checkAndInit, 300); } }, 500);

if (typeof MutationObserver !== 'undefined') { let fallbackObserverTimeout = null; // Store in outer scope for cleanup tracking fallbackObserver = new MutationObserver(function(mutations) { if (fallbackObserverTimeout) { clearTimeout(fallbackObserverTimeout); } fallbackObserverTimeout = setTimeout(function() { const contentArea = document.querySelector('#content-area'); if (contentArea) { const uninitialized = contentArea.querySelectorAll( '[data-single-page-viewer]:not([data-initialized]):not(.single-page-viewer-container [data-single-page-viewer])' ); if (uninitialized.length > 0) { const currentPathname = window.location.pathname; if (currentPathname !== lastInitializedPathname) { setTimeout(checkAndInit, 200); } } } }, 500); });

if (document.body) { fallbackObserver.observe(document.body, { childList: true, subtree: true }); } else { document.addEventListener('DOMContentLoaded', function() { if (document.body) { fallbackObserver.observe(document.body, { childList: true, subtree: true }); } }); } } })();