Skip to main content

auditai

EU AI Act Deployer Compliance SDK — wrap Claude, GPT, Ollama or any OpenAI-compatible LLM and generate Article 26 reports in minutes.

PyPI License: MIT

Install

pip install auditai-sdk

Quickstart

from auditai import wrap_client
import anthropic

client = wrap_client(anthropic.Anthropic(), project="my-app")

# Your code stays identical — every call is now logged and risk-classified
response = client.messages.create(
    model="claude-haiku-4-5-20251001",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}],
)

Supported providers

Works with any OpenAI-compatible API — including local LLMs:

from openai import OpenAI
from auditai import wrap_client

# OpenAI
client = wrap_client(OpenAI(), project="my-app")

# Ollama (local)
client = wrap_client(
    OpenAI(base_url="http://localhost:11434/v1", api_key="ollama"),
    project="my-app"
)

# LM Studio (local)
client = wrap_client(
    OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio"),
    project="my-app"
)

# vLLM, llama.cpp, Azure OpenAI — same pattern

CLI

# Risk classification wizard (9 questions → EU AI Act category)
auditai classify

# View call stats
auditai stats --project my-app

# Generate Article 26 Deployer Report (PDF)
auditai report --project my-app --company "Acme SL" --email "cto@acme.com"

# Launch Streamlit dashboard
auditai dashboard --project my-app

What gets logged

Every AI call is recorded in a JSONL audit trail:

{
  "call_id": "uuid",
  "timestamp": "2026-05-07T20:00:00Z",
  "provider": "anthropic",
  "model": "claude-haiku-4-5-20251001",
  "input_tokens": 312,
  "output_tokens": 87,
  "input_hash": "sha256...",
  "output_preview": "first 100 chars...",
  "risk_category": "limited",
  "hitl_required": false
}

Generate compliance report

from auditai import generate_report

report_path = generate_report(
    project="my-app",
    company_name="Acme SL",
    contact_email="compliance@acme.com",
    extra_info={
        "system_description": "Customer support chatbot",
        "use_case": "Automated responses to user queries",
    },
)
# → EU_AI_Act_Report_my-app_2026-05-07.pdf

The report covers Art. 26 obligations: risk classification, technical evidence, HITL events, and deployer declaration.

Links

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

auditai_sdk-0.2.2.tar.gz (28.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

auditai_sdk-0.2.2-py3-none-any.whl (29.4 kB view details)

Uploaded Python 3

File details

Details for the file auditai_sdk-0.2.2.tar.gz.

File metadata

  • Download URL: auditai_sdk-0.2.2.tar.gz
  • Upload date:
  • Size: 28.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for auditai_sdk-0.2.2.tar.gz
Algorithm Hash digest
SHA256 b06abc0525935492084b6f56ecbc1e1098fee292e828fca747413996790d9916
MD5 3a3f78db8bcad653d019a7f93f50af8d
BLAKE2b-256 4fd17a89f9a289373db7a6a38f7ad94be46908c0f509812723c475db6a0198d5

See more details on using hashes here.

File details

Details for the file auditai_sdk-0.2.2-py3-none-any.whl.

File metadata

  • Download URL: auditai_sdk-0.2.2-py3-none-any.whl
  • Upload date:
  • Size: 29.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for auditai_sdk-0.2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 39eb8178c5bdf00d92a69743504d2bab28f07348e1eeea5e526acc98d0de799d
MD5 e581224999e2d393e7a086fac6b2d498
BLAKE2b-256 b8a0834c1459572c81cdcdfbe4385bba81aeebb229eb575314b0c95da1ad1799

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page