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🧠 Generative AI Project Template

A production-ready template to help you kickstart and organize your Generative AI projects with clarity and scalability in mind.
Designed to reduce chaos in early development and support long-term maintainability with proven structure and practices.

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📋 Project Overview

A production-ready template for building scalable Generative AI apps — structured, maintainable, and built on real-world best practices.


🔧 Key Components

  • config/ – Configuration outside the code
  • src/ – Structured source with modular logic
  • data/ – Organized repository for various data types
  • examples/ – Implementations for guidance
  • notebooks/ – Interactive exploration and analysis

⚡ Best Practices

  • Track prompt versions and results
  • Separate configs using YAML files
  • Structure code by clear module boundaries
  • Cache responses to reduce latency and cost
  • Handle errors with custom exceptions
  • Use notebooks for rapid testing and iteration
  • Monitor API usage and set rate limits
  • Keep code and docs in sync

🧭 Getting Started

  1. Clone the repo
  2. Install via requirements.txt
  3. Set up model configs
  4. Check sample code
  5. Begin in notebooks

💡 Development Tips

  • Use modular structure
  • Test components early
  • Track with version control
  • Keep datasets fresh
  • Monitor API usage

📁 Core Files

  • requirements.txt – Package dependencies
  • README.md – Project overview and usage
  • Dockerfile – Container build instructions

📄 License

This project is licensed under the Apache 2.0 License.
You are free to use, modify, and distribute with minimal restriction.


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A production-ready template to kickstart your Generative AI projects with structure and scalability in mind.

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