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📖 [docs] 英語READMEの自動更新 #81

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93 changes: 58 additions & 35 deletions docs/README.en.md
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Expand Up @@ -8,17 +8,17 @@
<a href="https://github.com/Sunwood-ai-labs/AMATERASU/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/Sunwood-ai-labs/AMATERASU?color=green"></a>
</p>

<h2 align="center">Enterprise-Grade Private AI Platform (v1.21.0)</h2>
<h2 align="center">Enterprise-Grade Private AI Platform (🚀 AMATERASU v1.22.0)</h2>

>[!IMPORTANT]
>This repository leverages [SourceSage](https://github.com/Sunwood-ai-labs/SourceSage). Approximately 90% of the release notes, README, and commit messages were generated using [SourceSage](https://github.com/Sunwood-ai-labs/SourceSage) and [claude.ai](https://claude.ai/).

>[!NOTE]
>AMATERASU is the successor project to [MOA](https://github.com/Sunwood-ai-labs/MOA). It has evolved to run each AI service as an independent EC2 instance using Docker Compose, allowing for easy deployment with Terraform.
>AMATERASU is the successor project to [MOA](https://github.com/Sunwood-ai-labs/MOA). It has evolved to run each AI service as an independent EC2 instance using Docker Compose, and deployment is simplified using Terraform.

## 🚀 Project Overview

AMATERASU is an enterprise-grade private AI platform. Built on AWS Bedrock and Google Vertex AI, it enables the development and operation of LLM-based applications in a secure and scalable environment. Integration with GitLab streamlines version control, CI/CD pipelines, and project management. This repository acts as a "Spellbook" for managing multiple AI-related projects. Each project is structured as an independent folder for deploying and managing specific AI services or functionalities.
AMATERASU is an enterprise-grade private AI platform. Built on AWS Bedrock and Google Vertex AI, it enables the development and operation of LLM-based applications in a secure and scalable environment. Integration with GitLab streamlines version control, CI/CD pipelines, and project management. This repository serves as a "spellbook" for managing multiple AI-related projects. Each project is structured as a separate folder for deploying and managing specific AI services or functionalities.


## ✨ Key Features
Expand All @@ -28,25 +28,25 @@ AMATERASU is an enterprise-grade private AI platform. Built on AWS Bedrock and G
- Operation in a completely closed environment
- Enterprise-grade security

### Microservice Architecture
### Microservices Architecture
- Independent service components
- Container-based deployment
- Flexible scaling

### Infrastructure as Code
- Fully automated deployment using Terraform
- Environment-specific configuration management
- Version-controlled infrastructure
- Fully automated deployment with Terraform
- Configuration management for each environment
- Version-controlled configuration

### GitLab Integration
- Enhanced version control, CI/CD pipelines, and project management
- Improved version control, CI/CD pipelines, and project management
- Integration with self-hosted GitLab instances
- LLM-powered merge request analysis
- Automated labeling using GitLab webhooks
- Automated labeling using GitLab Webhooks

### Project Exploration Feature
### Project Exploration Functionality
- Automatic detection of Terraform projects and generation of `terraform.tfvars` files
- Simplified configuration using the `amaterasu` command-line tool
- Simplified configuration via the `amaterasu` command-line tool


## 🏗️ System Architecture
Expand All @@ -63,10 +63,12 @@ graph TB
CD["Coder<br/>Cloud Development Environment"]
GR["Gradio LLM Tester"]
ST["Streamlit LLM Tester"]
MEU["Marp Editable UI<br/>Presentation Editing"]
AGS["App Gallery Showcase<br/>Project Showcase"]
end

subgraph "Fargate-based Service"
PP["Prompt Pandora<br/>Prompt Generation Support"]
PP["Prompt Pandora<br/>Prompt Generation Assistance"]
ECS["ECS Fargate Cluster"]
end
end
Expand All @@ -89,6 +91,8 @@ graph TB
CD --> CF
GR --> CF
ST --> CF
MEU --> CF
AGS --> CF
PP --> ECS

CF --> WAF
Expand All @@ -101,7 +105,7 @@ graph TB
end
```

## 📦 Component Structure
## 📦 Component Composition

### 1. Open WebUI (Frontend)
- Chat-based user interface
Expand All @@ -125,7 +129,7 @@ graph TB
### 4. GitLab (Version Control)
- Self-hosted GitLab instance
- Project and code management
- CI pipeline and runner configuration
- CI pipeline and Runner configuration
- Backup and restore functionality

### 5. FG-prompt-pandora (Fargate Sample Application)
Expand All @@ -147,28 +151,28 @@ graph TB

### 8. Dify Beta (AI Application Development Platform)
- Beta version of Dify including new and experimental features
- Advanced configuration of vector databases and sandbox environments
- Advanced settings for vector databases and sandbox environments
- [Details here](./spellbook/dify-beta1/README.md)

### 9. Open WebUI Pipeline
- Pipeline features enhancing integration with Open WebUI
- Pipeline functions to enhance integration with Open WebUI
- Filter processing such as conversation turn limits and Langfuse integration
- [Details here](./spellbook/open-webui-pipeline/README.md)

### 10. Amaterasu Tool (Terraform Variable Generator)
- Automates the generation of `terraform.tfvars` files using a command-line tool
- Generates configuration values for each project in the spellbook
- [Details here](./spellbook/amaterasu-tool-ui/README.md)
- Generates settings for each project in the spellbook
- [Details here](./spellbook/amaterasu-tool-ui/README.md)

### 11. Kotaemon (Document and Chat RAG UI Tool)
- RAG UI tool for document and chat access
- RAG UI tool for document and chat interaction
- Provides Docker environment and Terraform configuration
- Data persistence and customizable environment settings
- Data persistence and customizable settings
- Secure authentication system implemented
- [Details here](./spellbook/kotaemon/README.md)

### 12. Bolt DIY (AI Chat Interface)
- Modern AI chat interface
- State-of-the-art AI chat interface
- Supports multiple AI providers (OpenAI, Anthropic, Google, etc.)
- Provides a Docker containerized environment
- CloudFront infrastructure configuration
Expand All @@ -184,21 +188,31 @@ graph TB
- Various parameter settings and debug information display
- [Details here](./spellbook/ee-llm-tester-st/README.md)

### 15. Marp Editable UI (Markdown Presentation Editing Tool)
- Web application for creating and editing presentations in Markdown format
- Provides a Docker containerized environment
- [Details here](./spellbook/ee-marp-editable-ui/README.md)

### 16. App Gallery Showcase (Project Showcase Web Application)
- Web application for visually showcasing projects
- Provides a Docker containerized environment
- [Details here](./spellbook/app-gallery-showcase/README.md)


## 🔧 Usage

Refer to the respective README files for instructions on using each component. For instructions on using the `amaterasu` command-line tool, refer to `spellbook/amaterasu-tool-ui/README.md`.
Refer to the respective README files for instructions on using each component. For instructions on using the `amaterasu` command-line tool, see `spellbook/amaterasu-tool-ui/README.md`.


## 📦 Installation
## 📦 Installation Instructions

1. Clone the repository.
```bash
git clone https://github.com/Sunwood-ai-labs/AMATERASU.git
cd AMATERASU
```
2. Follow the instructions in each project's README to install dependencies and deploy the application.
3. Enter the necessary settings in the `terraform.tfvars` file. You can also use the `amaterasu` tool to generate it automatically.
3. Enter the necessary settings in the `terraform.tfvars` file. You can also use the `amaterasu` tool to generate this automatically.


## 📦 Dependencies
Expand All @@ -223,18 +237,27 @@ Thanks to iris-s-coon and Maki for their contributions.

## 🆕 What's New

### AMATERASU v1.21.0 (Latest Release)
### AMATERASU v1.22.0 (Latest Release)

<img src="https://raw.githubusercontent.com/Sunwood-ai-labs/AMATERASU/refs/heads/main/docs/release_notes/header_image/release_header_v1.21.0.png" width="100%">
- **🔄 Enhanced OpenRouter API Integration**: LiteLLM's OpenRouter API integration has been enhanced and updated to the latest version.
- **🧪 Improved UI Testing Tools**: The ECS infrastructure has been optimized to an EC2 instance-based architecture, enabling more stable operation.
- **📊 Added Marp Editable UI**: A new containerized tool providing a Markdown presentation editing environment has been added.
- **🖼️ Integrated App Gallery Showcase**: A web application for beautifully showcasing projects has been added.
- **🐳 Updated Docker Images**: Several components have been updated to the latest versions, including Langfuse 3.26.
- **📐 Enhanced Architecture Visualization**: A system-wide architecture diagram has been added to clearly show the relationships between components.
- **🔍 Enhanced RAG Functionality in Open WebUI**: Added Web content loading functionality through Playwright integration.
- 🖥️ ECS task deployment has been optimized to an EC2 instance-based configuration, enabling more stable operation.
- 🔗 Docker Compose configuration improvements and standardization have strengthened inter-container collaboration.
- 🛡️ Enhanced WAF security settings and improved CSV file-based IP whitelisting management.
- 📄 Added `.env.example` files to each component for standardized and documented configuration files.
- 🧩 Improved sharing and reusability of Terraform modules.
- 🔤 Standardized environment variables to ensure consistency across different environments.

- **Expanded LLM Tester Functionality**: Added two interfaces based on Gradio and Streamlit. Displays IP address information and detailed debugging information.
- **Enhanced LiteLLM Functionality**: Integrated OpenRouter API and standardized model names.
- **Infrastructure Improvements**: Optimized Docker environment, strengthened inter-container communication, and updated NextAuth URL settings for Langfuse3.
- **Addition of New Presentation Tool**: Added Marp Editable UI. Provides a containerized Markdown presentation editing environment.
- **Enhanced Security**: Improved WAF settings, CSV file management for IP whitelists, and flexible security rule settings.
- **Improved Configuration Management**: Added `.env.example` files for each component to standardize and document configuration files.

- 📝 Notes:
- Existing configuration files need to be updated due to LiteLLM configuration changes.
- The WAF IP whitelist needs to be migrated to the new CSV format.
- Check environment variable settings and update as needed.
- 🔄 Due to changes in LiteLLM configuration, existing configuration files need to be updated.
- 📋 The WAF IP whitelist needs to be migrated to the new CSV format.
- 🔍 Check the environment variable settings and update them as needed.
- 📚 When using new components, refer to their respective READMEs for proper configuration.

This release enhances the functionality of the enterprise-grade AI platform, providing a more stable infrastructure and expanded UI tools. ✨