What are the best prototype showcase galleries for learning how to build AI apps with real code examples?

Here are some of the best prototype/showcase galleries and code-first examples for learning how to build AI apps:

1) OpenAI Cookbook

• Why it’s great: Practical, code-heavy examples for prompts, function calling, structured outputs, embeddings, RAG, agents, evals, and more.
• Best for: Learning patterns you can directly adapt into production code.
• Languages: Mostly Python, some JS.
• Link: https://cookbook.openai.com/

2) Vercel AI SDK Examples

• Why it’s great: Excellent for building modern AI web apps with React/Next.js.
• Best for: Chat UIs, tool calling, streaming responses, image generation, and multi-step workflows.
• Languages: TypeScript / Next.js.
• Link: https://sdk.vercel.ai/docs

3) LangChain Templates / LangGraph Examples

• Why it’s great: Good for agentic workflows, retrieval, tool use, and multi-step app patterns.
• Best for: Learning app structure for orchestration-heavy AI systems.
• Languages: Python / TypeScript.
• Link: https://github.com/langchain-ai/langchain/tree/master/templates
  https://langchain-ai.github.io/langgraph/

4) Hugging Face Spaces

• Why it’s great: Massive gallery of live demos with source code often available.
• Best for: Seeing real AI product ideas, then inspecting implementations.
• Languages: Python, Gradio, Streamlit, JS.
• Link: https://huggingface.co/spaces

5) Gradio Gallery / Examples

• Why it’s great: Fast way to build and study model demos and UI prototypes.
• Best for: Rapid prototyping for ML/LLM interfaces.
• Languages: Python.
• Link: https://www.gradio.app/guides/gallery

6) Streamlit Gallery

• Why it’s great: Strong for quick interactive AI app prototypes.
• Best for: Dashboards, data apps, internal tools, model exploration.
• Languages: Python.
• Link: https://streamlit.io/gallery

7) Replicate Examples / Demo Apps

• Why it’s great: Useful for image, audio, video, and multimodal AI prototypes.
• Best for: Apps that call hosted models and need fast iteration.
• Languages: Mostly JS/Python examples.
• Link: https://replicate.com/docs

8) Firebase AI / Google AI Studio Samples

• Why it’s great: Good for production-oriented AI app examples with auth, hosting, and data integration.
• Best for: Full-stack AI apps.
• Link:
  https://ai.google.dev/examples
  https://firebase.google.com/docs/ai-logic

9) Microsoft Azure AI Samples

• Why it’s great: Enterprise-friendly sample apps and reference architectures.
• Best for: RAG, agents, secure deployment patterns.
• Link: https://github.com/Azure-Samples

10) Anthropic Cookbook / Examples

• Why it’s great: Solid examples for Claude, tool use, structured outputs, and agent workflows.
• Best for: Learning model-specific best practices.
• Link: https://docs.anthropic.com/

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If you want the most useful combo

For learning to build AI apps with real code, I’d start with:

1. OpenAI Cookbook — core patterns
2. Vercel AI SDK examples — modern app/UI patterns
3. Hugging Face Spaces — gallery of real prototypes
4. LangGraph examples — agent workflows

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Good “gallery-style” places to browse ideas

• Product Hunt AI category — to see current AI app patterns
• Hugging Face Spaces — live prototype browsing
• GitHub topic searches like ai-app, rag, llm-app, nextjs-ai, gradio, streamlit

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If you want, I can also give you:

• a ranked list by easiest to learn from
• a list specifically for Next.js/React AI apps
• or a list of the best open-source AI app repos with full code