Notebook Gallery¶
Use this gallery to choose a runnable Director-AI notebook by buyer problem, implementation track, and required optional extras. Each row links to the local notebook in the repository and the matching Google Colab launcher.
If you are evaluating commercial fit before opening a notebook, start with Applications and Market Map, then read Product Overview. If you are running a governed pilot, pair the notebook path with Evaluation Onboarding so the pilot produces useful evidence instead of a demo-only result.
Choose The Notebook By Outcome¶
| Outcome | Notebook path |
|---|---|
| First guarded response | Quickstart, then Coherence Engine |
| Streaming halt proof | Streaming Oversight, then Streaming Halt Deep Dive |
| Private-fact grounding | Vector Store, then Vector RAG Pipeline |
| SDK or framework integration | Provider Adapters, LangChain Integration, Production Guardrails |
| Domain or regulated example | Medical RAG Chatbot, Domain Presets, Verification Gems |
| Enterprise pilot evidence | Batch Processing, Enterprise Multi-Tenant, Custom Fine-Tuning |
Notebook-To-Market Map¶
| Market question | Notebook path | Evidence produced |
|---|---|---|
| Can the guard reject a known false answer? | Quickstart, Coherence Engine | Approved/rejected pair with score and evidence |
| Can it protect streamed output? | Streaming Oversight, Streaming Halt Deep Dive | Halt metadata for a completed contradictory claim |
| Can it ground private knowledge? | Vector Store, Vector RAG Pipeline | Retrieved chunks tied to a verdict |
| Can it fit an existing stack? | Provider Adapters, LangChain Integration, Production Guardrails | Wrapped SDK/framework call path |
| Can it support a governed pilot? | Batch Processing, Enterprise Multi-Tenant, Custom Fine-Tuning | Threshold, tenant, deployment, and adaptation evidence |
| Track | Notebook | Audience | Use Case | Time | Extras | Colab |
|---|---|---|---|---|---|---|
| Foundations | Protect any LLM in 10 lines | First evaluation | Install Director-AI, understand the guarded workflow, score a response, wrap an SDK client, and inspect halt metadata. | 5 min | base | Open |
| Foundations | Coherence Engine Quick Start | Technical evaluator | Understand CoherenceScorer, SafetyKernel, CoherenceAgent, and dual-entropy scoring. | 15 min | nli | Open |
| Streaming Safety | Streaming Token-by-Token Oversight | Application engineer | Monitor streamed tokens and inspect contradiction-halt metadata before completion. | 10 min | base | Open |
| Retrieval | Vector Store and Semantic Retrieval | RAG engineer | Load facts into a vector-backed ground-truth store and retrieve evidence for scoring. | 10 min | vector | Open |
| Evaluation | End-to-End Guardrail Benchmark | ML evaluation lead | Run benchmark examples, profile latency, and interpret catch-rate metrics. | 15 min | nli | Open |
| Domain Applications | Medical RAG Chatbot | Healthcare evaluator | Apply high-threshold medical guardrails with retrieval evidence and clinical disclaimers. | 20 min | nli, vector | Open |
| Integrations | LangChain Integration | LangChain developer | Wire Director-AI into LangChain callbacks and chain output parsing. | 15 min | langchain | Open |
| Integrations | Multi-Provider SDK Guard | Platform engineer | Compare commercial SDK adapters, cloud-runtime adapters, agent frameworks, Guardrails AI, and Vercel AI SDK adapter patterns. | 10 min | base | Open |
| Production | Production Guardrails | Application engineer | Wrap production SDK calls, choose failure modes, and keep streamed-response checks evidence-bound. | 20 min | nli | Open |
| Retrieval | Vector RAG Pipeline | RAG engineer | Build a semantic fact retrieval pipeline with ChromaDB, pluggable backends, reranking, and tenant-aware knowledge. | 25 min | nli, vector | Open |
| Streaming Safety | Streaming Halt Deep Dive | Runtime engineer | Compare hard limits, sliding windows, trend detection, async streams, and per-token visualization. | 20 min | base | Open |
| Configuration | Domain Presets and Configuration | Solutions engineer | Apply profiles, environment variables, YAML config, strict mode, multi-GPU settings, and LLM-as-judge options. | 15 min | nli | Open |
| Evaluation | Batch Processing and Evaluation Pipelines | Evaluation engineer | Run batch scoring, claim attribution, dataset evaluation, and regression gates. | 20 min | nli | Open |
| Enterprise | Enterprise Multi-Tenant Deployment | Enterprise platform team | Inspect tenant isolation, REST and gRPC services, Docker, Kubernetes, and monitoring patterns. | 25 min | server, grpc, vector | Open |
| Model Adaptation | Custom Fine-Tuning | ML engineer | Prepare JSONL data, validate training examples, measure forgetting risk, export ONNX, and package held-out evidence before any tuning claim. | 30 min | finetune, nli | Open |
| Verification | Verification Gems | Safety engineer | Exercise numeric, reasoning, temporal, consensus, conformal, feedback-loop, agentic, and REST verification modules. | 15 min | base | Open |
| Demo | Streaming Halt Live Demo | First-touch evaluator | Open a focused Colab demo that shows opt-in streaming contradiction behavior without a local setup. | 8 min | base | Open |
Local Execution¶
The manifest at notebooks/gallery.toml is the source of truth. The gallery
validator fails if a notebook is added without a manifest entry or if this page
omits a notebook link.