genai-starter-kit 0.2.0

🚀 完整的生成式AI开发工具包，支持RAG、LLM和多模态AI功能

🌟 GenerativeAI-Starter-Kit

🚀 A comprehensive, beginner-friendly Generative AI development toolkit

Welcome to GenerativeAI-Starter-Kit! This repository provides everything you need to get started with Generative AI—from basic concepts to production-ready applications. Perfect for learning, rapid prototyping, and real-world deployment.

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🧠 What's Included

• RAG (Retrieval-Augmented Generation): Build intelligent document Q&A systems
• Multimodal Applications: Work with text, images, and cross-modal tasks
• Model Fine-tuning: Adapt pre-trained models for specific domains
• Production-Ready APIs: FastAPI servers with full documentation

🛠️ Development Tools

• One-Click Setup: Automated environment configuration
• Interactive Notebooks: Step-by-step Jupyter tutorials
• Configuration Management: Easy YAML-based settings
• Testing Framework: Comprehensive test suites

📚 Learning Resources

• Multi-language Docs: Complete guides in English and Chinese
• Progressive Tutorials: From beginner to advanced
• Best Practices: Industry-standard approaches
• Research Examples: Latest techniques and methods

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📦 Installation

✅ From PyPI (Recommended)

pip install genai-starter-kit

from genai_starter_kit import chains, utils

response = chains.run_rag_query("What is retrieval-augmented generation?")
print(response)

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🧪 From Source (Development Mode)

git clone https://github.com/YY-Nexus/GenerativeAI-Starter-Kit.git
cd GenerativeAI-Starter-Kit
pip install .

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🚀 Quick Start

1️⃣ Clone & Setup

git clone https://github.com/YY-Nexus/GenerativeAI-Starter-Kit.git
cd GenerativeAI-Starter-Kit
./automation/setup.sh
source venv/bin/activate

2️⃣ Try the Examples

# RAG System Demo

python examples/rag/simple_rag.py

# Multimodal Web App

python examples/multimodal/image_text_app.py --web

# Fine-tuning Demo

python examples/fine-tuning/text_classification_tuning.py

# Start API Server

python automation/api_server.py

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📚 Batch Run All Notebooks

pip install jupyter nbconvert
find RAG/notebooks -name "*.ipynb" -exec jupyter nbconvert --to notebook --execute --inplace {} \;

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🗂️ Directory Structure

docs/ # Documentation and usage guides (with Chinese docs in docs-zh) RAG/ # Retrieval-Augmented Generation module community/ # Community contributions and experimental resources examples/ # Example scripts and demos scripts/ # Automation and lint/test/release scripts tests/ # Unit tests automation/ # Setup and API server scripts setup.py # Build configuration

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🔧 Core Features

• End-to-end RAG examples (basic & advanced)
• Multimodal and industry-specific AI agents (text, speech, image, healthcare, finance, security)
• Model fine-tuning, training, evaluation, and safety (Llama, NeMo, Nemotron)
• Community resources, open-source contributions, and tutorials
• Comprehensive documentation (Chinese & English), one-click scripts, batch notebook execution

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💼 Typical Use Cases

• Intelligent Q&A, knowledge retrieval, document analysis
• Multimodal interaction (speech, image, text)
• Industry-specific agents (healthcare, finance, security)
• Large model fine-tuning and safety evaluation

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❓ FAQ & Help

• Dependency install failed? Check Python version or use a local mirror.
• API service won't start? Check port usage or run python main.py --help for options.
• Notebooks won't batch run? Ensure Jupyter and nbconvert are installed.

📖 See docs/README.md or open a GitHub Issue for more help.

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🤝 Contributing & Feedback

• Pull Requests welcome for code, docs, or examples
• Report issues with clear steps and environment details
• All contributions must comply with the LICENSE

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📐 Standardization & Usability Commitment

• Unified script and doc formats with clear comments and step-by-step instructions
• Modular directory structure for easy navigation and extension
• Chinese and English documentation for global accessibility
• Continuous improvement—feedback is welcome!

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This project is committed to making generative AI development easy for everyone.

Join our community and start building today!

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