28 lines
2.3 KiB
Markdown
28 lines
2.3 KiB
Markdown
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# Example projects
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Full, working projects you can clone, run, and tear apart. They're not lessons — they're more like worked examples. The point is to give you something concrete to look at when you're trying to imagine what your own project could look like (or to copy-paste from when one of them does roughly what you need).
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These are intentionally on equal footing — there's no "beginner / intermediate / advanced" tier. Pick whichever interests you.
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## Index
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| Project | What it is | What you'll see in it |
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|---------|------------|-----------------------|
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| [`image_meaning_db/`](image_meaning_db/) | Search a folder of images by meaning, not filename. Drop in a query image, get back the closest matches. | CLIP embeddings, ChromaDB, FastAPI, a tiny browser UI, all in one Docker container. |
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| [`audio_meaning_db/`](audio_meaning_db/) | Search spoken audio by what's said in it. Drop in a clip, get back the closest segments from your library. | Whisper transcription, sentence embeddings, segment chunking, FastAPI, Docker. |
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| [`everything_function/`](everything_function/) | Ten Python functions — arithmetic, prime factorization, sentiment, translation, OCR, photo→recipe — all backed by the same one-line call to a local AI model. Browser UI + terminal REPLs. | A local Qwen vision-language model in Ollama, FastAPI, Docker Compose, and the realization that a "function" can have a prompt for a body. |
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More will be added over time.
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## How to use these
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Three reasonable modes, in increasing order of effort:
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1. **Just run one.** Each project's README has a `docker compose up -d --build` line. Try it. Poke at the UI. Get a feel for what's possible.
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2. **Read the code.** The backends are deliberately small — a single `main.py` per project. Open it, ask AI to walk you through any part you don't understand. This is one of the best ways to *see* how a complete small thing fits together.
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3. **Fork and modify.** Copy the folder somewhere of your own, change things, see what breaks. Swap the embedding model. Change the seed images. Add a "delete by ID" endpoint. This is where it stops being an example and starts being a project.
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## Prerequisites
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Both current examples need Docker. See [`../reference/docker/`](../reference/docker/) for the basics; each project's README also links the official install guides.
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