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README.md

Outline

Ancilis Examples

Runnable examples showing how to integrate Ancilis SDK in common AI agent patterns.

Example Framework Description Difficulty
minimal-quickstart Python Fastest path to first scan — 10 lines Beginner
certification-driven Python One config line to AIUC-1 readiness Beginner
data-classification Python Declare data types, get HIPAA/GDPR/SOC 2 controls Beginner
cover-mcp-gap-assessment MCP Map business language to Ancilis setup and evidence gaps Beginner
auto-register Any auto_register — instantiate one producer per installed SDK Beginner
openai-assistant OpenAI Wrap chat.completions.create with OpenAIActionProducer.wrap_create Intermediate
langchain-chatbot LangChain / LangGraph Drop-in LangChainCallbackHandler for any Runnable, Chain, or LLM Intermediate
crewai-research-crew CrewAI step_callback / task_callback / crew_callback — per-agent attribution Intermediate
autogen-group-chat AutoGen / AG2 producer.attach(agent) — auto-wire send + receive hooks Intermediate
mcp-middleware MCP Intercept MCP tool calls with Ancilis middleware Intermediate
cli-agent Python CLI agent with HTTP producer Intermediate

Quick start

pip install ancilis
cd examples/minimal-quickstart
python main.py
ancilis scan --config ancilis.yaml

Prerequisites

All Python examples require:

pip install ancilis

Framework examples

Framework examples (LangChain, CrewAI, AutoGen, OpenAI) drive the producers directly with framework-shape arguments, so they run without an API key or any of the framework SDKs installed — the producers are duck-typed. Once you wire a real Runnable/Crew/Agent/Client into the same producer instance, the same observations are produced for free.

Set OPENAI_API_KEY for the OpenAI example to swap the fake transport for a real chat.completions.create call.

License

AGPL-3.0-or-later — see LICENSE.

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