# Release Notes

Epizo is currently in **Beta**.\
These releases represent rapid iteration toward a stable offline-first platform.

***

### 🚀 Version 1.31.1 — April 27, 2026 (Current Beta)

#### Status

**Open Beta — Publicly Available**

This version represents the current public beta of Epizo, focused on stability, security, and improving the offline AI experience.

***

#### 🐞 Bug Fixes

* **AI Module**
  * Fixed model download cancellation and improved progress UI consistency
  * Resolved crash when model metadata was missing required fields
  * Fixed document embedding queue issues causing excessive logging
  * Fixed incorrect batch handling for large dataset embeddings
  * Improved content extraction from offline knowledge sources (more complete indexing)
* **Downloads System**
  * Added `.tmp` staging for safer downloads (prevents corruption)
  * Improved handling of partial/range requests
  * Fixed duplicate logging and improved error handling
  * Better detection and handling of corrupted files
* **Storage & System**
  * Improved disk and network storage reporting accuracy
* **UI**
  * Fixed Content Explorer pagination issue
  * Fixed incorrect storage type labeling
* **Security**
  * Patched potential SSRF vulnerability in map downloads
  * Improved backend error sanitization to prevent data leakage

***

#### ⚡ Improvements

* **AI Module**
  * Improved response consistency by using active model for system tasks
  * Better handling of remote vs local AI runtime configuration
* **Privacy**
  * Disabled telemetry in vector database by default (new installs)
* **System**
  * Dependency updates for improved stability and security
* **Documentation**
  * Added Community Add-Ons section

***

***

### 🧪 Version 1.3.0 — April 2026

#### Status

**First Public Beta Release**

This version marks the first time Epizo was made available for public testing.

***

#### Highlights

* Initial public release of Epizo
* Core Command Center interface introduced
* Offline Knowledge system (Wikipedia via local storage)
* Basic AI module (local model execution)
* Content download system
* Maps module (initial version)
* Local network access (multi-device support)

***

#### Notes

This release focused on validating:

* Offline-first architecture
* Local AI usability
* Real-world hardware compatibility

***

### 🔧 Version 1.2.0 — Pre-Beta Development

#### Status

**Closed Testing**

***

#### Highlights

* Integration of AI module with local inference engines
* Knowledge Base (document upload + semantic search)
* Initial Docker-based modular system
* Early UI structure for Command Center
* Content management system (ZIM + datasets)

***

### ⚙️ Version 1.1.0 — Early Prototype

#### Status

**Internal Development**

***

#### Highlights

* Basic offline content serving
* Initial system architecture design
* Early experiments with:
  * Offline Wikipedia
  * Local services orchestration
* Foundational system scripts

***

### 🧱 Version 1.0.0 — Foundation Build

#### Status

**Concept & Core Build**

***

#### Highlights

* Core idea: Offline-first knowledge + AI system
* Initial proof-of-concept:
  * Local server setup
  * Static offline content
* Early testing on Ubuntu/Debian systems

***

### 📌 About the Beta

Epizo is still evolving.

During Beta:

* Features may change rapidly
* Performance depends on hardware
* Bugs and edge cases are expected

***

### 🔭 What’s Next

Planned improvements include:

* Expanded hardware support (Windows, ARM, Raspberry Pi)
* Improved AI performance and model management
* Easier installation and onboarding
* Better offline maps and dataset coverage
* System optimization for low-resource environments

***

### 🌐 Learn More

Official website: <https://projectepizo.com>


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.projectepizo.com/epizo-app-overview/release-notes.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
