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Tutorials

Interactive Jupyter notebooks covering Director-AI from first principles to production deployment. Every notebook runs in Google Colab with zero local setup.

Learning Path

graph LR
    A[00 Quickstart] --> B[01 Coherence Engine]
    B --> C[09 Production Guardrails]
    B --> D[02 Streaming Oversight]
    C --> E[10 Vector RAG]
    C --> F[12 Domain Presets]
    D --> G[11 Streaming Deep Dive]
    E --> H[06 Medical RAG]
    F --> I[13 Batch Processing]
    I --> J[14 Enterprise]
    J --> K[15 Fine-Tuning]

Getting Started

Start here. These two notebooks teach the core concepts in under 30 minutes.

# Notebook What You Learn Time Colab
00 Quickstart Install, score, guard, stream, presets 5 min Colab
01 Coherence Engine CoherenceScorer, SafetyKernel, CoherenceAgent, dual-entropy formula 15 min Colab

Core Features

Deep dives into the four pillars of Director-AI.

# Notebook What You Learn Time Colab
09 Production Guardrails guard() for OpenAI / Anthropic / Bedrock / Gemini / Cohere, failure modes, streaming guards 20 min Colab
10 Vector RAG Pipeline Semantic retrieval, ChromaDB, pluggable backends, reranking, multi-tenant KB 25 min Colab
11 Streaming Halt Deep Dive Hard limit, sliding window, trend detection, async, per-token visualization 20 min Colab
12 Domain Presets & Config 8 profiles, env vars, YAML, backends, strict mode, multi-GPU, LLM-as-judge 15 min Colab

Domain Applications

Real-world integrations and domain-specific patterns.

# Notebook What You Learn Time Colab
02 Streaming Oversight StreamingKernel basics, token-by-token monitoring 10 min Colab
03 Vector Store VectorGroundTruthStore, InMemoryBackend, fact ingestion 10 min Colab
05 SSGF Geometry Self-similar geometry foundation concepts 10 min Colab
06 Medical RAG Chatbot Healthcare-specific guardrails, high thresholds, evidence citations 20 min Colab
07 LangChain Integration CoherenceCallbackHandler, chain integration, output parsing 15 min Colab
08 Provider Adapters OpenAI, Anthropic, Bedrock, Gemini, Cohere adapter patterns 10 min Colab

Enterprise & Production

Scale, evaluate, fine-tune, and deploy.

# Notebook What You Learn Time Colab
04 End-to-End Benchmark Full benchmark suite, latency profiling, accuracy metrics 15 min Colab
13 Batch Processing & Evaluation BatchProcessor, evaluation pipelines, claim attribution, regression gates 20 min Colab
14 Enterprise Multi-Tenant Tenant isolation, REST/gRPC servers, Docker, Kubernetes, monitoring 25 min Colab
15 Custom Fine-Tuning JSONL data prep, validation, training, anti-forgetting, ONNX export, REST API 30 min Colab

Prerequisites

All notebooks run on Python 3.11+ with pip install director-ai.

Notebooks requiring optional extras note this in their first cell:

Extra Install Notebooks
NLI scoring pip install director-ai[nli] 01, 04, 06, 09–15
Vector store pip install director-ai[vector] 10, 14
Fine-tuning pip install director-ai[finetune] 15
Server pip install director-ai[server] 14
gRPC pip install director-ai[grpc] 14

Running Locally

git clone https://github.com/anulum/director-ai.git
cd director-ai
pip install -e ".[dev,nli]"
jupyter lab notebooks/