shareGPT - permenent links to your conversations vs Browser Use

The Chrome extension injects a share button into the ChatGPT DOM, then uses content script injection to traverse the conversation tree structure and extract all message pairs (user prompts and assistant responses) with metadata (timestamps, model info). It serializes this data into a JSON payload that preserves conversation structure and formatting for transmission to the backend API.

Unique: Uses content script injection directly into ChatGPT's DOM rather than relying on OpenAI's official API, enabling extraction without API credentials and capturing the exact rendered conversation state including formatting and UI elements

vs alternatives: Faster and simpler than building a ChatGPT API client because it works with the existing web interface without authentication overhead, but more fragile than API-based approaches due to DOM dependency

The web application generates a unique slug or ID for each submitted conversation and stores it in PlanetScale MySQL database, then serves the conversation via a permanent URL (sharegpt.com/share/{id}). The URL structure enables direct linking, bookmarking, and social sharing without requiring user authentication or session management.

Unique: Generates immutable, publicly-accessible URLs for conversations without requiring user accounts or authentication, using a simple slug-based routing pattern in Next.js that maps directly to database records

vs alternatives: Simpler than Slack's shared message links because it doesn't require workspace membership, but lacks access controls and audit trails that enterprise tools provide

The application defines a relational data model with tables for conversations (storing extracted ChatGPT data), users (storing authentication info), comments (storing user feedback), and favorites (storing user-conversation relationships). The schema uses foreign keys to maintain referential integrity and enable efficient queries across related entities.

Unique: Designs a normalized relational schema that separates conversations, users, comments, and favorites into distinct tables with foreign key relationships, enabling efficient queries and maintaining data integrity

vs alternatives: More queryable than document-based storage because SQL enables complex joins and aggregations, but requires more upfront schema design than schemaless databases

The application uses Next.js API routes (files in /api directory) to handle HTTP requests for conversation submission, retrieval, commenting, and favoriting. Each route is a serverless function that receives a request object, queries the database, and returns a JSON response. The routing is file-based — /api/conversations/[id].js maps to GET /api/conversations/{id}.

Unique: Leverages Next.js file-based API routing to create REST endpoints as serverless functions, eliminating the need for a separate backend framework while keeping API logic colocated with frontend code

vs alternatives: Simpler than Express.js because routing is automatic, but less flexible because it's tied to Next.js and Vercel deployment

The web application provides a sharegpt.com/explore page that queries the PlanetScale database for recently shared conversations and renders them in a browsable feed or grid. The interface uses Next.js server-side rendering to fetch conversations and Tailwind CSS for responsive UI, enabling users to discover shared examples without authentication.

Unique: Provides unauthenticated public discovery of conversations through a simple feed interface, leveraging Next.js SSR to render conversation previews server-side rather than client-side, reducing initial page load time

vs alternatives: More discoverable than direct URL sharing because conversations are indexed in a central feed, but less powerful than search engines because it lacks full-text indexing and semantic search

The web application uses NextAuth.js for user authentication and stores user-specific favorite/bookmark relationships in the PlanetScale database. When authenticated, users can mark conversations as favorites, which are persisted to their user profile and accessible via a dedicated /favorites page. The system maintains a many-to-many relationship between users and conversations.

Unique: Integrates NextAuth.js for session management and stores favorites in a relational database, enabling persistent user-specific collections without building custom auth infrastructure

vs alternatives: More persistent than browser bookmarks because favorites sync across devices, but less flexible than local file storage because it requires account creation and internet connectivity

The web application provides a commenting system on shared conversations where authenticated users can post replies, questions, or feedback. Comments are stored in the PlanetScale database with references to both the conversation and the commenting user, enabling threaded discussion around shared examples.

Unique: Adds lightweight social features to conversation sharing by storing comments in the same database as conversations, enabling discussion without requiring a separate comment platform or third-party service

vs alternatives: Simpler than integrating Disqus or similar because comments stay within the platform, but less feature-rich because it lacks moderation, threading, and notifications

The extension uses the Chrome Extension API (manifest.json v3) to inject content scripts into chatgpt.com, register message passing between the extension popup and content script, and handle permissions for DOM access. It leverages chrome.runtime.sendMessage for async communication between the extension background and content script, enabling the share button to trigger conversation extraction.

Unique: Uses Chrome Extension Manifest v3 with content script injection and message passing to integrate with ChatGPT without modifying the ChatGPT codebase, relying on DOM traversal rather than React state access

vs alternatives: More maintainable than Manifest v2 because it follows current Chrome security standards, but more complex than direct API integration because it requires async message passing and DOM parsing

browser-use/browser-use | DeepWiki Loading... Index your code with Devin DeepWiki DeepWiki browser-use/browser-use Index your code with Devin Edit Wiki Share Loading... Last indexed: 17 May 2026 ( 933e28 ) Overview System Architecture Installation and Setup Quick Start Examples Agent System Agent Core and Execution Loop Message Manager and Prompt Construction Agent State and History Management System Prompts and Output Formats Skills Integration Agent Configuration and Settings Loop Detection and Behavioral Nudges Message Compaction System Memory and Follow-up Tasks Judge System and Trace Evaluation Browser Session Management BrowserSession Lifecycle Browser Profile Configuration SessionManager and CDP Session Pool Target and Frame Management Navigation and Tab Control Event-Driven Architecture Event System Overview Event Types Reference Watchdog Pattern and Base Classes Core Watchdog Implementations DOM Processing Engine DOM Tree Construction DOM Serialization Pipeline Interactive Element Detection Visibility Calculation and Coordinate Transformation Screenshot Highlighting System Browser State Summary Markdown Extraction and HTML Serialization Tools and Action System Tools Registry and Action Models Built-in Actions Reference Action Execution Pipeline Custom Tools and Extensions Click Action Deep Dive Input Action and Autocomplete Detection FileSystem Integration Br

System Architecture | browser-use/browser-use | DeepWiki Loading... Index your code with Devin DeepWiki DeepWiki browser-use/browser-use Index your code with Devin Edit Wiki Share Loading... Last indexed: 17 May 2026 ( 933e28 ) Overview System Architecture Installation and Setup Quick Start Examples Agent System Agent Core and Execution Loop Message Manager and Prompt Construction Agent State and History Management System Prompts and Output Formats Skills Integration Agent Configuration and Settings Loop Detection and Behavioral Nudges Message Compaction System Memory and Follow-up Tasks Judge System and Trace Evaluation Browser Session Management BrowserSession Lifecycle Browser Profile Configuration SessionManager and CDP Session Pool Target and Frame Management Navigation and Tab Control Event-Driven Architecture Event System Overview Event Types Reference Watchdog Pattern and Base Classes Core Watchdog Implementations DOM Processing Engine DOM Tree Construction DOM Serialization Pipeline Interactive Element Detection Visibility Calculation and Coordinate Transformation Screenshot Highlighting System Browser State Summary Markdown Extraction and HTML Serialization Tools and Action System Tools Registry and Action Models Built-in Actions Reference Action Execution Pipeline Custom Tools and Extensions Click Action Deep Dive Input Action and Autocomplete Detection FileS

Agent System | browser-use/browser-use | DeepWiki Loading... Index your code with Devin DeepWiki DeepWiki browser-use/browser-use Index your code with Devin Edit Wiki Share Loading... Last indexed: 17 May 2026 ( 933e28 ) Overview System Architecture Installation and Setup Quick Start Examples Agent System Agent Core and Execution Loop Message Manager and Prompt Construction Agent State and History Management System Prompts and Output Formats Skills Integration Agent Configuration and Settings Loop Detection and Behavioral Nudges Message Compaction System Memory and Follow-up Tasks Judge System and Trace Evaluation Browser Session Management BrowserSession Lifecycle Browser Profile Configuration SessionManager and CDP Session Pool Target and Frame Management Navigation and Tab Control Event-Driven Architecture Event System Overview Event Types Reference Watchdog Pattern and Base Classes Core Watchdog Implementations DOM Processing Engine DOM Tree Construction DOM Serialization Pipeline Interactive Element Detection Visibility Calculation and Coordinate Transformation Screenshot Highlighting System Browser State Summary Markdown Extraction and HTML Serialization Tools and Action System Tools Registry and Action Models Built-in Actions Reference Action Execution Pipeline Custom Tools and Extensions Click Action Deep Dive Input Action and Autocomplete Detection FileSystem I

browser-use/browser-use | DeepWiki Loading... Index your code with Devin DeepWiki DeepWiki browser-use/browser-use Index your code with Devin Edit Wiki Share Loading... Last indexed: 17 May 2026 ( 933e28 ) Overview System Architecture Installation and Setup Quick Start Examples Agent System Agent Core and Execution Loop Message Manager and Prompt Construction Agent State and History Management System Prompts and Output Formats Skills Integration Agent Configuration and Settings Loop Detection and Behavioral Nudges Message Compaction System Memory and Follow-up Tasks Judge System and Trace Evaluation Browser Session Management BrowserSession Lifecycle Browser Profile Configuration SessionManager and CDP Session Pool Target and Frame Management Navigation and Tab Control Event-Driven Architecture Event System Overview Event Types Reference Watchdog Pattern and Base Classes Core Watchdog Implementations DOM Processing Engine DOM Tree Construction DOM Serialization Pipeline Interactive Element Detection Visibility Calculation and Coordinate Transformation Screenshot Highlighting System Browser Sta