-
@@ -20,33 +20,34 @@ >[!IMPORTANT] ->This repository leverages [SourceSage](https://github.com/Sunwood-ai-labs/SourceSage). Approximately 90% of the release notes, README, and commit messages are generated using [SourceSage](https://github.com/Sunwood-ai-labs/SourceSage) and [claude.ai](https://claude.ai/). +>This repository utilizes [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 in a separate EC2 instance using Docker Compose, enabling 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 in an independent EC2 instance using Docker Compose, making deployment with Terraform significantly easier. -[Image Placeholder - The link provided points to a user attachment and cannot be displayed here.] +https://github.com/user-attachments/assets/90f382c2-6b4a-42c4-9543-887ecc67b6eb -## 🔒 Security-Focused Design Philosophy +## 🔒 Security-Focused Design -AMATERASU is a private AI platform foundation developed specifically for Japanese enterprises with stringent security requirements. It enables the secure use of LLMs based on AWS Bedrock: +AMATERASU is a private AI platform infrastructure specifically developed for Japanese enterprises with stringent security requirements. It enables the secure use of LLMs based on AWS Bedrock: -- **Secure LLM Foundation with AWS Bedrock**: +- **Secure LLM Infrastructure with AWS Bedrock**: - Supports the Claude-3 model, optimized for enterprise use. - Leverages AWS's enterprise-grade security. - - Granular access control using IAM roles. + - Granular access control based on IAM roles. -- **Operation in a Completely Closed Environment**: +- **Operation in a Fully Closed Environment**: - Operates only within the internal network. - Supports private cloud/on-premises deployments. - **Enterprise-Grade Security**: - - IP whitelist access control. + - IP whitelisting for access control (directly specified in security group settings). - HTTPS/TLS encrypted communication. - Network segmentation using AWS Security Groups. - IAM role management based on the principle of least privilege. + ## ✨ Key Features ### 1. Secure ChatGPT-like Interface (Open WebUI) @@ -60,14 +61,15 @@ AMATERASU is a private AI platform foundation developed specifically for Japanes - Load balancing and rate limiting of requests. - Centralized API key management. -### 3. Cost Management and Monitoring Foundation (Langfuse) +### 3. Cost Management and Monitoring Infrastructure (Langfuse) - Visualizes token usage. - Aggregates costs by department. - Analyzes usage patterns. + ## 🏗️ System Architecture -### Secure 3-Tier Architecture based on AWS Bedrock +### Secure 3-Tier Architecture Based on AWS Bedrock ```mermaid %%{init:{'theme':'base'}}%% @@ -118,27 +120,27 @@ Recommended Configuration: - Network: Public/Private subnet -## 💼 Use Cases in Enterprises +## 💼 Enterprise Use Cases 1. **Development Department** - Code review assistance - - Improved bug analysis efficiency + - Bug analysis efficiency improvement - Document generation 2. **Business Departments** - - Report creation assistance + - Report generation assistance - Data analysis support - - Meeting minutes creation + - Meeting minute creation 3. **Customer Support** - - Improved efficiency of inquiry response + - Improved efficiency in handling inquiries - Automatic FAQ generation - Improved quality of reply text -## 🔧 Installation and Operation +## 🔧 Deployment and Operation -### Setup Procedure +### Setup Instructions ```bash # 1. Clone the repository git clone https://github.com/Sunwood-ai-labs/AMATERASU.git @@ -146,18 +148,24 @@ cd AMATERASU # 2. Set environment variables cp .env.example .env -# Edit the .env file and set credentials +# Edit the .env file and set your credentials -# 3. Deploy infrastructure +# 3. Deploy the infrastructure cd spellbook/base-infrastructure terraform init && terraform apply cd ../open-webui/terraform/main-infrastructure terraform init && terraform apply -# 4. Start services -# Langfuse (Monitoring foundation) -cd ../../langfuse +cd ../../litellm/terraform/main-infrastructure +terraform init && terraform apply + +cd ../../langfuse/terraform/main-infrastructure +terraform init && terraform apply + +# 4. Start the services +# Langfuse (Monitoring infrastructure) +cd ../../../langfuse docker-compose up -d # LiteLLM (API proxy) @@ -167,61 +175,69 @@ docker-compose up -d # Open WebUI (User interface) cd ../open-webui docker-compose up -d + ``` ## 📚 Detailed Documentation -- [Spellbook Infrastructure Construction Guide](spellbook/README.md) +- [Spellbook Infrastructure Setup Guide](spellbook/README.md) - [LiteLLM Configuration Guide](spellbook/litellm/README.md) - [Langfuse Setup Guide](spellbook/langfuse/README.md) -## 🆕 Latest Information - -### v0.6.1 Update Notes - -- Updated documentation and added important information to the README file. -- Updated English and Japanese READMEs. -- Added information about the development process using SourceSage and claude.ai. -- Simplified descriptions related to security. - - -### v0.6.0 Update Notes - -- Removed unnecessary resources due to the removal of the CloudFront infrastructure. -- Simplified the code to improve maintainability. -- Added application HTTPS and HTTP URLs to the output. -- Enabled easy modification of the environment variable file and setup script paths in `terraform.tfvars`. -- Removed unnecessary variable definitions. -- Simplified the setup script. +## 🆕 What's New + +### v1.0.0 Update Contents + +- 🎉 Added Langfuse integrated filter pipeline (`langfuse_litellm_filter_pipeline.py`): Integrates with the Langfuse API for conversation tracing and monitoring. +- 🎉 Added conversation turn limit filter (`conversation_turn_limit_filter.py`): Limits the number of conversation turns. +- 🎉 Added convenient Terraform commands: `terraform destroy -auto-approve ; terraform init ; terraform plan ; terraform apply -auto-approve` +- 🚀 README.md updated: Added links and corrected line breaks. +- 🚀 Setup script corrected: Changed the execution order of `docker-compose up`. +- 🚀 Docker Compose configuration corrected: Added `extra_hosts` option. +- 🚀 English README updated. +- 🚀 README updated after release. +- 🚀 Header image updated. +- ⚠️ Removed whitelist CSV file and changed to direct description in security group settings. +- ⚠️ Corrected security group output. +- ⚠️ Removed security group module and changed to direct settings. +- ⚠️ Docker Compose configuration corrected. +- ⚠️ Changed the development environment URL to the production environment URL. +- ⚠️ Whitelist for access restriction to the LitleLLM development environment. +- ⚠️ Terraform variable configuration file for the LitleLLM development environment. +- ⚠️ Creation of a setup script for the LitleLLM development environment. +- ⚠️ Added output value definition for the LitleLLM development environment. +- ⚠️ Terraform module configuration for building the LitleLLM development environment. +- ⚠️ Added definition of Terraform variables for the LitleLLM development environment. ## 💰 Cost Management -Provides detailed cost analysis and management functionality through Langfuse: -- Tracks usage costs for each model. +Provides detailed cost analysis and management capabilities through Langfuse: +- Tracks usage costs per model. - Allows setting budget alerts. - Visualizes usage. + ## 👏 Acknowledgements Thanks to iris-s-coon and Maki for their contributions. ## 📄 License -This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. +This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. ## 🤝 Contributions -1. Fork this repository -2. Create a new branch (`git checkout -b feature/amazing-feature`) -3. Commit your changes (`git commit -m 'Add amazing feature'`) -4. Push the branch (`git push origin feature/amazing-feature`) -5. Create a pull request +1. Fork this repository. +2. Create a new branch (`git checkout -b feature/amazing-feature`). +3. Commit your changes (`git commit -m 'Add amazing feature'`). +4. Push the branch (`git push origin feature/amazing-feature`). +5. Create a pull request. ## 📧 Support For questions or feedback, please feel free to contact us: -- Create an Issue: [GitHub Issues](https://github.com/Sunwood-ai-labs/AMATERASU/issues) +- Create an issue: [GitHub Issues](https://github.com/Sunwood-ai-labs/AMATERASU/issues) - Email: support@sunwoodai.com ---