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CODE_OF_CONDUCT.md

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# Code of Conduct
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As contributors and maintainers of NeuronAPI, we pledge to create a welcoming and respectful environment for everyone, regardless of experience level, gender, gender identity and expression, sexual orientation, disability, personal appearance, body size, race, ethnicity, age, religion, or nationality.
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## Our Standards
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Examples of behavior that contributes to creating a positive environment:
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- Using welcoming and inclusive language
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- Being respectful of differing viewpoints and experiences
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- Accepting constructive criticism gracefully
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- Focusing on what is best for the community
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- Showing empathy towards other community members
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Examples of unacceptable behavior:
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- The use of sexualized language or imagery and unwelcome sexual attention or advances
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- Trolling, insulting/derogatory comments, and personal or political attacks
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- Public or private harassment
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- Publishing others' private information, such as physical or electronic addresses, without explicit permission
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- Any other conduct which could reasonably be considered inappropriate in a professional setting
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## Enforcement
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Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any behavior that is deemed unacceptable.
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Project maintainers have the right to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned with this Code of Conduct.
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Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting us at **[email protected]**. All complaints will be reviewed and investigated promptly.
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This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org/), version 2.0.

CONTRIBUTING.md

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# Contributing to NeuronAPI
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First off, thank you for considering contributing to NeuronAPI! We appreciate your time and effort in helping improve the project. Below is a guide on how you can contribute.
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## How to Contribute
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### 1. Fork the Repository
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Fork the repository from [NeuronAPI](https://github.com/doblier/NeuronAPI) to your GitHub account.
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### 2. Create a Branch
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Create a new branch for your feature, bug fix, or enhancement:
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```bash
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git checkout -b feature/my-new-feature
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```
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### 3. Make Changes
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Make your changes in your local repository. Be sure to:
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- Follow the project's existing code style.
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- Write tests for any new functionality.
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- Ensure that the code passes all tests.
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### 4. Commit Changes
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Write clear and concise commit messages explaining your changes:
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```bash
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git commit -m "Add new feature to X"
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```
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### 5. Submit a Pull Request
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Push your changes and submit a pull request to the **main branch** of NeuronAPI:
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```bash
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git push origin feature/my-new-feature
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```
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- Open a pull request on GitHub and explain the changes you’ve made.
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- Include any relevant issues this PR addresses (use `Fixes #issue_number` if applicable).
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## Code Style
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- Follow the existing code structure and formatting.
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- For Python, use **PEP 8** standards.
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## Reporting Bugs
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If you find a bug, please open an issue using the [Bug Report template](./.github/ISSUE_TEMPLATE/bug_report.md).
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## Suggesting Enhancements
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We’re open to new ideas! To suggest an enhancement, use the [Feature Request template](./.github/ISSUE_TEMPLATE/feature_request.md).
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## Join the Discussion
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Feel free to participate in discussions under the [Discussions](https://github.com/doblier/NeuronAPI/discussions) tab to share ideas and suggestions.
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## Contributor License Agreement (CLA)
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https://cla-assistant.io/Doblier/NeuronAPI
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Thank you again for your contribution!

README.md

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# NeuronAPI
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NeuronAPI: A lightweight, AI-driven orchestration framework for building and managing microservices with seamless FastAPI integration.
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NeuronAPI is a lightweight, AI-driven orchestration framework designed to simplify the creation and management of microservices. Built on top of FastAPI and Docker, it enables developers to spin up microservices, integrate LLMs, and orchestrate complex systems with minimal effort.
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## Features
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- Async-first design for scalability.
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- Native integration with FastAPI and Docker.
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- AI-driven code generation and service orchestration.
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- Support for local and cloud-hosted LLMs.
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- Ready-to-use Kafka and Postgres setup via Docker Compose.
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## Getting Started
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1. Clone the repo:
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```bash
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git clone https://github.com/doblier/NeuronAPI.git
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```
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2. Set up the project:
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```bash
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cd NeuronAPI
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python cli.py setup
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docker-compose up
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```
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3. Interact with the generated APIs:
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```bash
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curl http://localhost:8000/api/example
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```
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# Contributing
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Contributions are welcome! Please read our [Code of Conduct]() and [Contributing Guide]() for more information.

SECURITY.md

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# Security Policy
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NeuronAPI takes security seriously, and we appreciate your efforts to responsibly disclose vulnerabilities.
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## Reporting a Vulnerability
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If you discover a security vulnerability, please do the following:
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1. Email the details of the issue to **[email protected]**.
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2. Include as much detail as possible in your report, including the steps to reproduce the vulnerability, the affected versions of NeuronAPI, and any potential impact.
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## Security Response
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- We will acknowledge receipt of your report within **2 business days**.
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- We will investigate the vulnerability and respond with the steps we plan to take, which may include releasing a fix or issuing a patch.
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- We aim to resolve all valid vulnerabilities within **7 days** of the initial report.
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## Supported Versions
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| Version | Supported |
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| -------- | ------------------ |
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| 1.x | ✅ Supported |
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Thank you for helping to keep NeuronAPI secure!

docs/API-Documentation.md

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# API Documentation
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NeuronAPI provides auto-generated API docs via **Swagger** and **ReDoc**.
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Once your services are running, you can access the API documentation:
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- Swagger UI: `http://localhost:8000/docs`
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- ReDoc: `http://localhost:8000/redoc`
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These interfaces allow you to explore and interact with your API endpoints in real time.
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docs/Advanced-Features.md

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# Advanced Features
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## Production Deployment
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NeuronAPI provides built-in support for deploying to production environments using **Docker** and **Terraform**.
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### Deploying with Terraform:
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- You can generate Terraform scripts for AWS, Azure, or Google Cloud using the CLI:
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```bash
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python cli.py deploy production
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```
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This will create the necessary infrastructure files for Kubernetes or serverless environments.
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## CI/CD Integration
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- NeuronAPI works with CI/CD systems like **GitHub Actions** for automated testing, building, and deployment.
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- Example CI/CD pipeline:
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```yaml
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name: NeuronAPI CI
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on:
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push:
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branches:
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- main
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- name: Check out code
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uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: '3.x'
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- name: Install dependencies
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run: |
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pip install -r requirements.txt
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```

docs/Contribution-Guidelines.md

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# Contribution Guidelines
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We welcome contributions to NeuronAPI!
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## How to Contribute:
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1. Fork the repository.
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2. Create a new branch for your feature or fix.
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3. Write clear, concise commit messages.
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4. Open a pull request and explain the changes.
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Please ensure that all changes are properly tested and follow the existing coding standards.
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docs/Installation.md

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# Installation Guide
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Follow these steps to get **NeuronAPI** up and running.
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## Prerequisites:
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- **Python 3.8+** installed
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- **Docker** and **Docker Compose** installed
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- Basic knowledge of FastAPI, Docker, and Kafka
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## Steps:
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1. **Clone the repository**:
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```bash
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git clone https://github.com/doblier/NeuronAPI.git
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cd NeuronAPI
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```
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2. **Create a virtual environment**:
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```bash
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python3 -m venv env
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source env/bin/activate
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```
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3. **Install dependencies**:
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```bash
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pip install -r requirements.txt
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```
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4. **Set up Docker containers**:
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Run the following command to spin up Kafka, Postgres, and the core services:
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```bash
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docker-compose up
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```
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5. **Run the application**:
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Use the CLI to set up your project and start the FastAPI app.
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```bash
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python cli.py setup
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python cli.py up
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```
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That's it! Your NeuronAPI environment is now up and running.

docs/Introduction.md

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# NeuronAPI
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Welcome to **NeuronAPI**, an AI-driven orchestration framework that simplifies the creation and management of microservices.
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## What is NeuronAPI?
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NeuronAPI is a lightweight, async-first framework built on top of FastAPI and Docker to help developers:
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- Easily generate and manage **microservices**.
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- Integrate **Large Language Models (LLMs)** for dynamic service generation.
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- Seamlessly orchestrate complex microservice-based architectures with **Kafka** and **Postgres**.
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## Key Features:
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- **FastAPI Integration**: Leverages FastAPI for high-performance APIs.
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- **AI-Powered Code Generation**: Automatically create microservices with minimal code.
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- **Microservices Orchestration**: Ready-to-use Docker and Kafka setup for asynchronous communication.
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- **Cloud-Ready Deployments**: Built-in support for Terraform and Docker Compose to scale from local to production.
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NeuronAPI is designed for developers and organizations looking to streamline their microservice creation while integrating AI to assist with dynamic code generation.
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docs/LLM-Integration.md

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# LLM Integration
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NeuronAPI allows developers to integrate **Large Language Models (LLMs)** to assist with the dynamic generation and modification of microservices.
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## Using Cloud-hosted LLMs:
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- If you want to use a cloud-hosted LLM, you'll need an API key for the provider.
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- In your `.env` file, add your API key like this:
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```
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LLM_API_KEY=your-api-key-here
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```
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## Running LLM Locally:
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- If you have GPU-enabled hardware, you can run the LLM locally by downloading the necessary open-source models like **LLaMA**.
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## Creating Microservices with LLM:
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Use the following prompt to generate a new microservice:
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```bash
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python cli.py add-microservice "Create a service for real-time notifications with Kafka"
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```
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The LLM will generate the code for the requested microservice, including the routes, Kafka integration, and other required services.

docs/Usage.md

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# Usage Guide
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NeuronAPI allows you to quickly generate microservices and manage them using the integrated CLI.
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## Creating a Microservice
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To create a new microservice, run the following CLI command:
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```bash
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python cli.py add-microservice "Create a microservice for user authentication using JWT and Postgres"
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```
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This command will:
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- Generate a microservice scaffold in the services/ folder.
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- Set up routes, models, and database connections automatically.
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- Add Kafka and Postgres integration.
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## Modifying a Microservice
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After generating a microservice, you can modify it via prompt-driven code generation. Use the CLI:
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```bash
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Copy code
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python cli.py modify-microservice "Add password hashing to the authentication service"
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This will update the code, and you can see changes in real-time.
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```
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## Accessing the APIs
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Once the services are running, you can interact with the API endpoints via the browser or curl commands:
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```bash
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Copy code
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curl http://localhost:8000/api/auth
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```

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