AI API Playbook v1.0.0 — Initial Research Release

AI API Playbook v1.0.0

The first public research and engineering release of AI API Playbook by Faramarz Kowsari.

This repository provides a reproducible and production-oriented reference for designing, testing, securing, evaluating, and commercializing modern AI API applications.

Highlights

• Reusable Python architecture for provider-aware AI applications
• OpenAI, Google Gemini, Anthropic Claude, and Microsoft Foundry examples
• Function calling and Model Context Protocol patterns
• Retrieval-Augmented Generation workflows
• Image generation, OCR, speech, video, and realtime examples
• Hugging Face, Cohere, Pinecone, Replicate, Runway, Deepgram, and ElevenLabs integrations
• Model routing, retry handling, cost estimation, evaluation, and safety utilities
• TypeScript WebRTC realtime client
• Commercial AI product blueprints
• Google Colab-compatible notebook
• Docker and GitHub Actions support
• Tested with Python 3.11, 3.12, and 3.13
• Citation and Zenodo metadata
• 100-page infographic book production map

Reproducibility

The repository includes an offline mock mode, automated tests, strict type checking, CI validation, documented environment variables, and provider-specific implementation examples. Live provider calls require the user's own API credentials.

Author

Faramarz Kowsari
Author, Software Engineer, and AI Researcher

• ORCID: https://orcid.org/0000-0003-1692-0453
• Google Scholar: https://scholar.google.com/citations?user=G7tP5WMAAAAJ&hl=en
• GitHub: https://github.com/FaramarzKowsari
• LinkedIn: https://www.linkedin.com/in/faramarzkowsari
• Wikidata: https://www.wikidata.org/wiki/Q140389378
• Google Books: https://play.google.com/store/search?q=Faramarz_Kowsari&c=books

License

Software source code is released under the MIT License. Book text, diagrams, and the visual prompt manuscript are licensed under CC BY 4.0 unless otherwise stated.