Examples

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 : encode, score, and extract in 5 minutes, then pick a project below.

Gallery

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
Rank exact primary-source passages	Testing a reranker on verbatim SEC, CMS, NTSB, and Supreme Court excerpts	score	SIE endpoint with Qwen3 Reranker; standalone uv project	Runnable verified example
Extract custom entities from primary sources	Changing zero-shot labels across financial, healthcare, rail-safety, and legal text	extract	SIE endpoint with GLiNER; standalone uv project	Runnable verified example
Search licensed images with text	Recomputing a six-image hard-negative ranking from full SigLIP vectors	encode	SIE endpoint with SigLIP; standalone uv project	Runnable verified example
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	encode, score, generate	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	generate, encode, score, extract	GPU SIE deployment required; standalone uv project; real contracts fetched from CUAD (CC BY 4.0)	Runnable demo
Turn difficult PDFs into Markdown	Preserving tables, reading order, headings, and form labels across real financial, academic, and government PDFs	extract	SIE endpoint with docling; standalone uv project; source PDFs fetched at run time	Runnable evaluation example
Review a published flood-insurance appeal	Separating FEMA's covered stone-removal scope from excluded barge, handling, disposal, and yard costs	extract, score, generate	GPU SIE deployment; standalone uv project; bundled public FEMA appeal and policy	Runnable agent example
Trace a restated filing figure	Following one reported figure through an original filing, corrective notice, and restatement while preserving source status	extract, encode, score	SIE endpoint; standalone uv project; public SEC facts and saved verified evidence	Runnable agent example
Reproduce CMS's L1851 documentation finding	Tracing a published six-month requirement against a seven-month face-to-face encounter and CMS's recoupment result	extract, encode, score	SIE endpoint; standalone uv project; exact CMS published example	Runnable agent example
Reconstruct a bearing failure	Turning the NTSB's three East Palestine detector readings into a cited temperature and alert sequence without adding a new causal claim	extract, encode, score	SIE endpoint; standalone uv project; exact NTSB illustrated report spread	Runnable agent example
Make a shelf gap auditable	Detecting one empty facing, deriving its notice and shelf-label crops by geometry, then preserving OCR evidence	extract	GPU SIE deployment; standalone uv project; CC0 supermarket shelf image and recorded direct-checkpoint evidence included	Runnable evaluation example
A behavioural gate that catches hijacked AI agents by their actions, not their credentials	Judging a proposed AI agent action against that agent's own learned baseline in real time, before it reaches a downstream system	encode, score, extract	Docker Compose (gate + self-hosted SIE + n8n + mock downstream), no API key required	Runnable demo

For docs publishing, lead with the quickest runnable demos, then use the benchmark and evaluation examples for deeper technical users.

Submit your project

We welcome contributions. To add your project to the gallery:

1. Create a subdirectory with a short, descriptive name (e.g. wikipedia-search/, pdf-rag/)
2. 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.)
3. Keep it self-contained - include a requirements.txt or package.json, a docker-compose if needed, and sample data or instructions to fetch it
4. Open a PR against main

Review workflow

Maintainers apply the coderabbit-direct label to eligible PRs that change content under examples/** or the root README.md. The label opts the PR into CodeRabbit review and allows CodeRabbit to formally approve it once review comments are resolved and required checks pass.

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.

Links

• SIE overview
• API reference
• Deployment guide
• All models