AEP: AI Enhanced Platform

Welcome to AEP, your comprehensive solution for integrating Generative AI workflows into your build system. Enhance your DevOps processes with AI-driven pull request summarization, code reviews, and more.

Get your API key and revolutionize your DevOps journey with AI-powered insights and assistance today. 🚀

Website: AEP Docs

Features of AEP

AEP currently offers the following features:

• AI-Driven Pull Request Summary: Automatically generate summaries of your pull requests using AI.
• AI-Driven Pull Request Insights: Obtain AI-driven insights on DevOps tasks and identify potential vulnerabilities.
• Custom AI-Driven Prompts: Customize prompts for specific needs using tailored system and user prompts for precise model guidance.

Usage

Authentication

AEP provides secure access through flexible authentication mechanisms:

1. Local Authentication:

   • Use the .env file to set the 'system' user API key when running the API locally.
   • If X-API-CONSUMER is 'system', the local API key will be used.

2. Azure Authentication:

   • When running the API in Azure, it retrieves the API key from the Azure Key Vault.
   • If X-API-CONSUMER is not 'system', the Azure Key Vault is used, with the X-API-CONSUMER acting as the identifier.

Endpoints

GET /

Returns a list of available system prompts with their descriptions.

POST /predefined

Retrieve prompts based on predefined types, with parameters for customized assessment:

• prompt_type: The predefined prompt to use.
• prompt: The content for the model to assess based on the predefined prompt type.

POST /custom

Customize prompts for specific needs using system and user prompts:

• system_prompt: Directs the model towards a desired output.
• user_prompt: Specifies the desired action for the prompt.
• prompt: The content for the model to assess based on the custom prompt.
• compression_enabled (optional): Compresses the input prompt to reduce token count (default: false).
• model (optional): The model to use, currently available options are ["gpt-4-turbo", "gpt-35-turbo"] (default: 'gpt-35-turbo').

Local Development

Secrets Setup

Create a .env file in the root of the project with the following content:

OPENAI_API_KEY=<your_openai_api_key>
SYSTEM_API_KEY=<your_system_api_key>
AZURE_VAULT_ID=<your_azure_key_vault_id>

Local Setup

Install the required dependencies and start the server using the following commands:

Requirements

To install the dependencies:

make build-local

Dependencies include:

• fastapi
• uvicorn
• requests
• pytest
• openai
• python-dotenv
• azure-identity
• azure-keyvault-secrets
• starlette
• tiktoken
• prometheus_fastapi_instrumentator
• pydantic-core

Start Server

To start the server:

make run-local

Docker

To run the API using Docker, use the following commands:

Build and Run

make build
make run

Terraform Setup and Usage

This project uses Terraform to manage infrastructure. Terraform scripts are located in the terraform/envs/stable directory.

Prerequisites

• Terraform >= 0.14
• Azure CLI
• Make

Environment Variables

Set the following environment variables:

ARM_CLIENT_ID
ARM_CLIENT_SECRET
ARM_SUBSCRIPTION_ID
ARM_TENANT_ID
BACKEND_RESOURCE_GROUP
BACKEND_STORAGE_ACCOUNT
BACKEND_CONTAINER_NAME
OPENAI_API_KEY
SYSTEM_API_KEY
AZURE_VAULT_ID

Linting

Lint your Terraform scripts to catch syntax or formatting issues:

make tf-lint

To automatically fix some issues:

make tf-fmt

Initialization

Initialize your Terraform working directory:

make tf-init

Planning

Create an execution plan to see the actions Terraform will perform:

make tf-plan

Applying

Apply the changes to reach the desired state:

make tf-apply

Destroying

Destroy all resources managed by Terraform:

make tf-destroy

Note: This command will remove all resources in your Azure subscription managed by Terraform.

Continuous Deployment

This project uses GitHub Actions for continuous deployment. The workflow is defined in .github/workflows/deploy-terraform.yml. On each push to the main branch, the workflow lints, initializes, plans, and applies Terraform changes. Ensure required environment variables are set in your GitHub repository secrets.

Metrics and Monitoring

The application is instrumented with Prometheus FastAPI Instrumentator. Enable metrics collection by setting the ENABLE_METRICS environment variable to True. Metrics can then be scraped from the /metrics path.

Contributing

We welcome contributions to AEP! To contribute, please follow these steps:

1. Fork the repository: Create a fork of the repository on GitHub.

2. Clone the repository: Clone your fork locally.

   git clone https://github.com/your-username/ai-enhanced-platform.git
   

3. Create a branch: Create a new branch for your feature or bugfix.

   git checkout -b feature/your-feature-name
   

4. Make your changes: Implement your changes and commit them with descriptive messages.

   git commit -m "Add feature/your-feature-name: description of changes"
   

5. Push to GitHub: Push your changes to your forked repository.

   git push origin feature/your-feature-name
   

6. Create a Pull Request: Open a pull request against the main repository. Provide a detailed description of your changes and any relevant context.

7. Review Process: Your pull request will be reviewed by project maintainers. Please be responsive to feedback and make any necessary adjustments.

8. Merge: Once approved, your pull request will be merged into the main branch.

Thank you for contributing to AEP!