A project gallery of full end-to-end applications built with SIE. Each project lives in its own subdirectory. Clone it, run it, learn from it.
New to SIE? Start with the quickstart notebook 
Use this table to pick the right starting point. "Runnable" means the example has code, sample data or data-fetch instructions, and a documented local path. "Advanced" examples may require a custom SIE image or third-party service keys.
| Example | Best for | SIE primitives | Setup | Status |
|---|---|---|---|---|
| Self-hosted product search in 5 min | Showing the fastest local product-search path with extraction, embeddings, and reranking | extract, encode, score |
Local SIE Docker image, Python or TypeScript app | Runnable |
| Find the best retrieval strategy for your RAG | Picking a production RAG retrieval pipeline by evals on real financial documents | encode, score |
SIE endpoint, Turbopuffer key, optional SIE API key for auth-enabled clusters | Runnable benchmark |
| Find SOTA embedding models by MTEB task | Searching ~14K HF embedding models ranked by task-specific MTEB scores | encode, score |
Backend seed script plus Vite frontend; falls back without a live SIE endpoint | Runnable |
| Private fine-tuned compliance RAG | Hot-loading a domain LoRA encoder and a custom token-pruning adapter on SIE | encode, score, extract |
Custom SIE Docker image, GPU recommended | Advanced runnable example |
| Build a multimodal wine recommender with OCR | Combining preference-based retrieval with OCR-driven label detection in one UI | encode, score, extract |
Docker Compose app plus local SIE endpoint; API key optional for unauthenticated SIE | Runnable demo |
| Build a multi-modal product classifier with embeddings | Evaluating text, image, NLI, and reranking approaches for hierarchical product taxonomy classification | extract, encode, score |
SIE endpoint, Shopify dataset prep via uv run scripts, standalone uv project |
Runnable evaluation example |
| Swap an OCR model with one identifier change | Driving recognition (VLM-OCR), structured extraction (Donut), and zero-shot NER (GLiNER) through the same extract call by swapping the model ID |
extract |
Docker Compose plus Node UI, no API key required, hosted version on Hugging Face Spaces | Runnable demo |
| A Stripe Link checkout with an SIE fraud-risk gate | Wiring all three SIE primitives into a pre-authorization fraud-risk gate that runs in the same round-trip as the Stripe PaymentIntent | extract, encode, score |
Docker Compose plus Node UI; Stripe test-mode keys optional (runs in mock mode without them) | Runnable demo |
| Vision-first document RAG | Retrieving and answering questions over a multi-tenant page corpus by looking at page images (including scanned drawings) with OCR kept out of the score path | encode, chat/completions, score (optional) |
GPU SIE deployment required: ColQwen2.5 retriever + Qwen3.5-4B answer model (runs on the generation bundle) | Runnable demo |
| Multi-model contract review with the OpenAI Agents SDK | Running an OpenAI Agents SDK agent whose every model call (triage, orchestration, vision, OCR, embeddings, rerank, entity extraction, text-to-SQL, reasoning, and a safety guardrail) is served by one SIE cluster, each step on the right catalog model, with per-model observability | chat/completions, encode, score, extract |
GPU SIE deployment required; standalone uv project; real contracts fetched from CUAD (CC BY 4.0) |
Runnable demo |
For docs publishing, lead with the quickest runnable demos, then use the benchmark and evaluation examples for deeper technical users.
We welcome contributions. To add your project to the gallery:
- Create a subdirectory with a short, descriptive name (e.g.
wikipedia-search/,pdf-rag/) - Include a README that covers:
- What the project does
- How to run it (
docker compose up, a script, etc.) - Which SIE features it uses (encode, score, extract, cluster, etc.)
- Keep it self-contained - include a
requirements.txtorpackage.json, a docker-compose if needed, and sample data or instructions to fetch it - Open a PR against
main
Projects can be anything: a search engine, a RAG pipeline, a benchmark, a migration guide, a CLI tool. If it uses SIE, it belongs here.