generative_ai_project and generative-ai-prompt-engineering

These are complementary tools: one provides a production-ready project scaffold for building generative AI applications, while the other offers sample code and demos focused specifically on prompt engineering techniques to use within those applications.

Maintenance 10/25
Adoption 10/25
Maturity 15/25
Community 25/25
Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 19/25
Stars: 890
Forks: 273
Downloads:
Commits (30d): 0
Language:
License: Apache-2.0
Stars: 36
Forks: 17
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT-0
No Package No Dependents
Stale 6m No Package No Dependents

About generative_ai_project

HeyNina101/generative_ai_project

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

Implements modular subsystems for agents, memory management, multimodal processing (vision/audio), and LLM routing across OpenAI/Anthropic with built-in fallback logic. YAML-based configuration separates model and prompt definitions from code, while dedicated modules handle retrieval, guardrails (PII filtering, validation), caching, rate limiting, and error recovery. Structured for rapid prototyping through notebooks while supporting production deployment via Docker and comprehensive test suites.

About generative-ai-prompt-engineering

build-on-aws/generative-ai-prompt-engineering

Sample code that helps us explore the world of generative AI through prompt engineering. It provides the resources for experimenting with this emerging skill through demos and sample applications such as simple chatbots.

Scores updated daily from GitHub, PyPI, and npm data. How scores work