AtlasServer‑Core 0.3.5 Release Notes 🚀

Link: https://pypi.org/project/atlasserver/0.3.5/

🎉 Highlights

• New Adapters API
  The BaseAdapter lets you integrate AtlasServer‑Core with any CLI‑driven web framework.
• Customizable Commands
  Define start/stop command templates, environment variables, and extra options to fit your service.
• Plug‑and‑Play
  Add, register, start, and stop your framework in seconds—whether it’s Spring Boot, Vite, Django, Rails, Laravel, or any other.

🌐 Web Interface Integration

• Adapter Discovery
  Once you register() an adapter in your code, it becomes available in the AtlasServer‑Core web UI under New App.
• Select Your Framework
  Choose from your custom adapters alongside built‑in options (Flask, FastAPI, Django) and extras like Ngrok tunneling, etc..

🛠 Breaking Changes

• Database Reset Required
  Drop your existing AtlasServer‑Core database before upgrading to avoid runtime errors.

🚀 Upgrade Instructions

1. Update the package

   pip install --upgrade atlasserver==0.3.5

2. Restart your application

⚙️ Usage Examples

These snippets serve as a template for any CLI‑driven framework. Adapt command_init_tpl, stop_command_tpl, and config as needed.

1. Spring Boot (Java)

from app.adapters import BaseAdapter

spring_adapter = BaseAdapter(
    name="Spring",
    command_init_tpl=[
        "java", "-jar", "{main_file}",
        "server.address={host}",
        "server.port={port}"
    ],
    stop_command_tpl=[
        "java", "-jar", "{main_file}", "--stop"
    ],
    config={"env": {"JAVA_OPTS": "-Xmx512m"}}
)

spring_adapter.register()

2. Vite (JS/TS)

from app.adapters import BaseAdapter

vite_adapter = BaseAdapter(
    name="Vite",
    command_init_tpl=[
        "npx", "vite", "{main_file}",
        "--host", "{host}",
        "--port", "{port}"
    ],
    stop_command_tpl={
        "signal_SIGINT": True
    }
)

vite_adapter.register()

🔧 Tip: For other frameworks—Rails, Laravel, etc.—define your start/stop commands similarly using command_init_tpl and stop_command_tpl (or SIGINT).

🔧 Known Issues & Roadmap

• Some processes may not catch the stop signal properly; we’re working on more robust signal handling.
• Coming soon: automatic child‑process management and health checks.

🙏 Acknowledgements

Thanks for your patience during recent inactivity!
I’m committed to continuing maintenance and improvements for AtlasServer‑Core. 🚀

AtlasServer-Core 0.3.2 Release Notes 🚀

Overview

In this patch release, we address circular import issues and clarify middleware usage without altering existing endpoint contracts. No database migrations or feature changes are required—simply update to 0.3.2 for smoother startup and error-free template loading.

Changes

• Maintain .add_middleware
  We continue using app.add_middleware(SessionMiddleware, ...) in main.py to configure session handling. No changes to middleware registration were needed, ensuring stability and familiarity.

• Fixed Circular Imports for Templates

  • In applications.py and configroutes.py, moved template initializations into their respective modules instead of importing from main.py.
  • Each router module now independently creates its Jinja2Templates instance pointing to the correct template directory, preventing import loops.

Migration & Compatibility

• No Breaking Changes: Public API routes and behaviors remain unchanged.
• No Migrations Needed: Database schema is intact.

Upgrade Instructions

1. Update your dependency:

   pip install --upgrade atlasserver==0.3.2

2. Restart your application.

3. Verify that sessionmiddleware.json is present in your data directory and that routes under /applications and /config render templates without import errors.

Enjoy the fix, and thank you for using AtlasServer-Core!

AtlasServer-Core 0.3.0 Release Notes 🚀

What's New

An improvement in the architecture and structure of the project was necessary, which was raised in this issue #1 :

• All possible routes for APIs or Applications, WebSockets, Configs, etc. Have been moved to a folder called routes with their respective files: routes/api.py, routes/websockets.py, routes/applications.py, routes/configroutes and routes/enviro.py.
• All models have been moved to their dedicated folder and file: models/models.py.
• Database management and creation moved to db/db.py
• The process_manager was refactored as much as possible, removing responsibilities it shouldn't have. It was then moved to services/process_manager.py
• All configuration functions for swagger, ngrok, etc. were moved to configs/configs.py
• All auxiliary functions and functions that AtlasServer-Core needs to run have been moved to utils/utils.py
• The main.py file that runs the application has been refactored as much as possible and removing responsibilities that it shouldn't have, resulting in a 410-line file.

Compatibility Notes

• Due to the project and architecture restructuring, several internal imports have been changed, which are considered Breaking Changes.

• Several functions have been refactored and optimized. Although they perform the same functions and no major changes will be noticeable, it is recommended to update to version 0.3.0.

• Database Migrations: The schema has not changed, so migrations are NOT required; your existing data and tables will work without modification.

• Semantic Versioning: This is a major change to the internal structure and code organization, but with no changes to the public API. Under semver, we've moved to 0.3.0 to signal "new features" and refactoring, without breaking HTTP contracts.

AtlasServer-Core 0.2.6 Release Notes 🚀

We're excited to announce the release of AtlasServer-Core 0.2.6, featuring a significant architectural improvement that makes the AI capabilities optional through a dedicated companion package.

What's New

🧩 Modular Architecture (Major Improvement)

AtlasServer's AI functionality has been moved to a separate package for lighter installations and improved maintainability:

• Core Package: Leaner AtlasServer-Core with reduced dependencies
• Optional AI: AI capabilities now available through the companion AtlasAI-CLI package
• Plugin System: Seamless integration between packages when both are installed

🤖 Enhanced AI Provider Support

AtlasAI-CLI now supports multiple AI providers:

• Ollama: Use local models with Ollama for privacy and offline operation
• OpenAI: Connect to OpenAI's powerful cloud models for advanced analysis
• Provider-specific Configuration: Simple setup for each provider:

# For Ollama (local models)
atlasai ai setup --provider ollama --model llama3:8b

# For OpenAI (cloud models)
atlasai ai setup --provider openai --model gpt-4 --api-key YOUR_API_KEY

🛠️ Technical Improvements

• Reduced Dependencies: Core package no longer requires heavy AI libraries
• Lower Resource Usage: Smaller memory footprint when AI features aren't needed
• Faster Installation: Quicker setup process for basic deployments
• Better Maintainability: Cleaner separation of concerns between components

Technical Details

New Package Structure

AtlasServer now uses a modular approach:

1. AtlasServer-Core: The main package with all core deployment features
2. AtlasAI-CLI: Optional package containing all AI functionality

Integration Mechanism

When both packages are installed, AtlasServer-Core automatically detects and integrates AtlasAI-CLI:

• Commands remain the same (atlasserver ai ...)
• Smooth fallback with helpful messages when AtlasAI-CLI isn't installed
• Zero configuration required for the integration

Installation

Basic Installation (without AI)

pip install atlasserver==0.2.6

Full Installation (with AI capabilities)

pip install atlasserver==0.2.6 atlasai-cli==0.2.0

Upgrade from Previous Version

pip install --upgrade atlasserver
# If you need AI features:
pip install atlasai-cli

Getting Started with the New Structure

1. Install AtlasServer-Core:

pip install atlasserver

2. For AI capabilities, install the companion package:

pip install atlasai-cli

3. Use AI commands as before:

# AtlasAI-CLI will be automatically integrated
atlasserver ai setup --model llama3:8b
atlasserver ai suggest ~/path/to/your/project

Using AtlasAI-CLI as a Standalone Tool

AtlasAI-CLI can also be used independently without AtlasServer-Core:

# Install just the AI CLI
pip install atlasai-cli

# Use AtlasAI commands directly
atlasai ai setup --provider ollama --model llama3:8b
atlasai ai suggest ~/path/to/your/project

Demo

AtlasAI-CLI in Action

Compatibility Notes

• All existing functionality remains backward compatible
• AI commands will prompt for AtlasAI-CLI installation if needed
• Projects previously analyzed will continue to work the same way
• All AtlasAI-CLI commands are identical to previous built-in AI commands

This release represents our commitment to a modular, flexible architecture that gives users more control over their deployment tools.

AtlasServer-Core 0.2.5 Release Notes 🚀

We're excited to announce the release of AtlasServer-Core 0.2.5, introducing AI-powered deployment assistance and several improvements to the core functionality.

What's New

🤖 AI-Powered Deployment (New Feature)

AtlasServer now includes AI capabilities that help analyze projects and suggest optimal deployment configurations:

• Smart Project Analysis: Uses AI to scan project structure, identify frameworks, and determine the best deployment strategy
• Interactive Exploration: Reads key files and automatically detects Flask, FastAPI, Django, and other frameworks
• Context-Aware Suggestions: Recommends appropriate commands, ports, and environment variables based on project structure
• Multilingual Support: Get explanations in English or Spanish with the --language option

# Basic usage
atlasserver ai setup --model llama3:8b
atlasserver ai suggest ~/my-project

# With debugging and language preference
atlasserver ai suggest ~/my-project --debug --language es

🧰 Core Improvements

• Enhanced Error Handling: More robust handling of edge cases and error conditions
• Better Tool Integration: Improved filesystem navigation and command execution
• Performance Optimizations: Reduced latency in processing and analysis
• Streaming Support: Real-time feedback during project analysis

Technical Details

AI Engine

AtlasServer now leverages Ollama to run local AI models for deployment analysis. The system:

1. Scans project structure using filesystem tools
2. Reads key configuration files (requirements.txt, package.json, etc.)
3. Identifies framework patterns in main code files
4. Generates appropriate deployment commands and environment configurations

Framework Detection

The system can detect and generate deployment commands for various frameworks:

• Flask (with Waitress or Gunicorn)
• FastAPI (with Uvicorn)
• Django (with Gunicorn)
• Express.js (with Node.js)
• React/Next.js applications

Installation

New Installation

pip install atlasserver==0.2.5

Upgrade from Previous Version

pip install --upgrade atlasserver

Requirements

• Python 3.8 or higher
• Ollama for AI functionality

Getting Started with AI Capabilities

1. Install and start Ollama:

# Download and start Ollama (instructions vary by platform)
ollama serve

2. Pull your preferred AI model:

ollama pull llama3:8b

3. Configure AtlasServer AI:

atlasserver ai setup --model llama3:8b

4. Analyze a project:

atlasserver ai suggest ~/path/to/your/project

Compatibility Notes

• AI functions work best with models that came out after Llama 3
• All existing AtlasServer functionality remains backward compatible

v0.1.4.1 – Minor Update: Remove Redundant Routes

• Removed all /api/applications/ endpoints, which duplicated existing functionality.
• Switched to the more efficient, consolidated routes to improve code maintainability and API performance.

v0.1.4 - 🔒 API Documentation Security Enhancements

This release adds authentication capabilities to the AtlasServer API documentation, allowing administrators to secure access to Swagger UI and ReDoc interfaces.

New Features

• Protected API Documentation: Administrators can now enable authentication for Swagger UI and ReDoc interfaces
• Flexible Authentication Options:
  • Use existing administrator credentials
  • Configure custom username/password specifically for documentation access
• Integrated Security Controls: All authentication settings are easily configurable through the AtlasServer admin panel

How to Use

1. Access the Settings panel in AtlasServer
2. Navigate to the "API Documentation Security" section
3. Toggle "Protect API documentation" to enable or disable authentication
4. Choose between administrator credentials or custom credentials
5. If using custom credentials, enter your desired username and password
6. Save settings

Screenshot

The new API Documentation Security settings panel in AtlasServer allows administrators to configure access controls for Swagger UI and ReDoc interfaces.

Technical Details

• Implements secure HTTP Basic Authentication for /docs and /redoc routes
• Password comparison uses secure cryptographic comparison functions to prevent timing attacks
• Compatible with all modern browsers that support HTTP Basic Auth

Updates

• Added new configuration storage system for Swagger authentication settings
• Updated documentation to reflect new security features
• Added security validation for API documentation routes

Requirements

This update requires no additional dependencies and is compatible with all existing AtlasServer deployments.

v0.1.3.7 - Release Notes

🔧 Fixes

Configuration File Management

• Important improvement: All configuration files are now stored in the standard operating system path using platformdirs
• Server PID: The atlas_server.pid file is now saved in the user's data directory, avoiding permission issues and improving persistence between restarts
• Ngrok Configuration: The ngrok_config.json file is stored in the same centralized location as the database
• Consistency: This improvement ensures that AtlasServer works correctly on Windows, macOS, and Linux without path issues

Error Handling

• Project creation: Improved validations when creating new applications
• Error messages: Greater clarity in messages to facilitate troubleshooting
• Environment validation: Better detection of Python virtual environments when setting up new applications

🎨 User Interface

HTML Templates

• Corrections: Adjustments to various templates to improve user experience
• Visual consistency: Standardization of styles and components across all pages
• Responsive: Improvements to ensure the interface works correctly on different screen sizes

Application Background

• Improved aesthetics: Background update for a better visual experience
• Performance: Optimization to reduce resource load in the browser

📦 Installation

# Install or update AtlasServer
pip install atlasserver==0.1.3.7

ℹ️ Additional Notes

This update focuses on improving the stability and consistency of AtlasServer. All users are recommended to update to this version to ensure proper storage of configuration files.

Full Changelog: pypi...fix

We have released version 0.1.3.1, with bug fixes and an easier way to install :b !!!