Topics Covered:

Worker Chat: Text, image, URL input and chat export (PDF/DOCX)
Workers Launchpad: Central hub for users
Session Management: Auto-titled sessions, history, context, and persistence
File Upload & Management: Temporary vs persistent file handling
Search & Filtering: Tag-based and semantic search

Worker Chat

The primary interaction interface where Users communicate with AI Workers.

Supports text, image, and URL input
Users can view the Worker's skills and knowledge sources
Displays the Worker's thinking trace (collapsed chain-of-thought) for transparency
Custom welcome messages can be configured per Worker to greet users
Chat controls:
- Enter to send
- Shift + Enter for new lines
- Paste URLs inline
- Attach files and images in chat

Chat Export

Export your conversation history in multiple formats:

PDF Export: Download the chat as a formatted PDF document
DOCX Export: Download the chat as a Microsoft Word document

Exports include the full conversation history with messages, responses, and formatting preserved.

Session Management

Each new conversation with a Worker creates a dedicated session with its own memory, settings, and context.

All sessions are automatically titled (based on summary + timestamp)
Users can:
- Rename, search, or delete sessions
- Enable/disable memory or skills for a specific session
- See a list of previous sessions in the left-hand panel
Planned: Graph-based session navigation (jump from old message threads into new sessions)

File Upload & Management

Users can upload documents to provide additional context during conversations.

In-chat uploads are temporary (valid only during the session)
Persistent files are uploaded via the Session Settings panel, becoming part of session memory
Supported formats : You can upload the following file types in chat or session context:

.pdf, .docx, .doc, .txt, .md, .rtf, .xlsx, .csv ⚠️ Only text-based PDF files are supported. Images and scanned PDFs cannot be processed at this time.
Files are embedded into vector memory and used for response generation when enabled

Search & Filtering

Users can easily discover and navigate content through search and tag systems.

Tag-based filters on the Worker list (customizable by Builder)
Semantic search in memory items, session names, and chat logs
Planned enhancements:
- Search by Worker capabilities (e.g., "find Workers that connect to Salesforce")
- Combined filters (e.g., tags + activity status)

Summary

EverWorker's user experience is built around clarity, control, and context continuity. From rich, multi-modal chat to evolving session intelligence and personalized launchpads, the interface aims to make advanced AI interactions feel familiar, productive, and trustworthy - especially for non-technical users.