Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.egisai.co/llms.txt

Use this file to discover all available pages before exploring further.

Production guardrails for Python AI applications. Install the SDK, call egisai.init(), and continue using OpenAI, Anthropic, Google Gemini, or plain HTTP clients as you do today — policy evaluation and audit logging wrap those calls automatically. This site is the canonical SDK guide for the egisai package on PyPI.

Quickstart

Install, initialize, and make your first governed call in five minutes.

How it works

Understand how policy evaluation slots into your model call path.

API reference

Detailed reference for init(), set_context(), and policy types.

Troubleshooting

Common symptoms, what they mean, and how to fix them.

​
Overview

CapabilityWhat it means for you
Central policiesOperators configure rules in the EgisAI dashboard. The SDK loads them at runtime and refreshes them continuously — no redeploy to tighten controls.
Transparent integrationNo proxy layer and no wrapper objects you must remember to use. Supported libraries are patched in-process when your application imports them after egisai.init().
Audit trailGoverned calls emit structured events to your org so teams can review verdicts, latency, and usage in one place.
Local-first sensitive checksPattern-based PII handling and other deterministic rules run entirely inside your process before traffic leaves your environment.

​
What you need

  1. Python 3.11+
  2. An EgisAI account and an SDK API key (dashboard → API Keys → create). Keys look like egis_live_….
  3. The AI SDK(s) you already use (openai, anthropic, google-generativeai, …).

​
Installation

pip install "egisai[all]"
Optional extras (smaller installs): 
pip install "egisai[openai]"
pip install "egisai[anthropic]"
pip install "egisai[google]"
Only frameworks present in your environment are activated at runtime. See the installation guide for more options.

​
Getting started

1

Initialize once per process

Call egisai.init() as early as possible in your application lifecycle — for example, right after loading configuration. Use your SDK API key from the dashboard.
import egisai

egisai.init(
    api_key="egis_live_…",   # or set EGISAI_API_KEY in the environment
    app="customer-support-bot",
    env="production",
)
2

Use your LLM client normally

No changes to your calling convention — the SDK intercepts supported APIs after initialization.
from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4.1",
    messages=[{"role": "user", "content": "Hello"}],
)
3

Review activity

Open Dashboard → Requests to see governed calls, verdicts, and supporting metadata for your organization.

​
How governance fits your call path

  1. Evaluation — Before the upstream model runs, the SDK applies your organization’s active policies (cached locally). Rules such as PII detection, regex denylists, model allowlists, and intent-oriented policies are evaluated in a fixed order defined by the product.
  2. Outcomes — A call may be allowed, sanitized (payload adjusted per policy, then forwarded), or blocked. Blocked calls never reach the provider when enforcement raises or returns a stub, depending on configuration.
  3. Telemetry — Non-blocking delivery of audit metadata to EgisAI so your dashboard stays current without slowing customer-facing inference.
Sensitive pattern detection intended to catch regulated data is performed locally so raw values are not sent to third-party models as part of governance. Intent-oriented policies operate only after applicable local checks have run on the text that will be judged. Read How it works for the full call-path diagram.

​
When a call is blocked

on_blockBehavior
"raise" (default)Raises PermissionError if a policy blocks the call.
"stub"Returns a framework-shaped refusal object so applications that cannot tolerate exceptions keep running; the refusal is clearly identifiable in your logs and on the dashboard.
Configure at init: 
egisai.init(..., on_block="stub")
See Blocking behavior for guidance on when to choose each mode.

​
Configuration at a glance

ParameterDefaultDescription
api_key—Required unless EGISAI_API_KEY is set. Your EgisAI SDK key (egis_live_…).
app"default"Logical application name; appears as an Agent in the dashboard for attribution.
env"production"Environment label (for example staging, prod). Free-form string for your own segmentation.
base_urlHosted control planeOverride only when directed by EgisAI (for example dedicated regions or enterprise deployments).
on_block"raise""raise" or "stub" — see above.
refresh_interval_seconds10How often to poll for policy updates if live streaming is unavailable.
enable_sseTrueSubscribe to live policy and configuration updates when supported.
enable_http_fallbackTrueOptional patching of httpx / requests for broader HTTP visibility where enabled.
quietFalseSet True to suppress the one-line startup banner on stderr.
VariablePurpose
EGISAI_API_KEYSDK API key if not passed as api_key=.
EGISAI_BASE_URLControl plane base URL override when supplied by EgisAI.
Treat API keys as secrets — use environment variables or a secrets manager, never commit them to source control.
The full reference lives in Configuration and the init API reference.

​
Policies (operator concepts)

Organizations configure policies in the dashboard. Typical categories include:
CategoryPurpose (high level)
PII & secretsDetect and block or mask categories such as government identifiers, payment data, and credential-shaped strings before model calls.
Content patternsAllow or deny prompts or outputs matching operator-defined patterns.
Models & sizeRestrict which model names may be called or cap prompt size.
IntentBlock requests that match dangerous or out-of-scope intent even when phrased obliquely or in another language.
Tools & connectorsRestrict tool, shell, or integration use when the model returns structured tool or command requests.
Exact rule shape and ordering are managed in the product; the SDK consumes the published configuration and does not require you to embed policy documents in your repository. See Policies for the SDK-side picture.

​
Advanced: explicit context (optional)

For multi-tenant or test scenarios, you may override auto-detected context (for example agent identity) with egisai.set_context(**kwargs) as described in the set_context reference. This is optional — the default path fingerprints agents from your application’s behavior. See Multi-agent context for patterns.

​
Performance and availability

  • Steady-state overhead is designed to stay on the order of a fraction of a millisecond for policy lookup per call after initialization and cache warm-up.
  • Control plane connectivity — If the SDK cannot reach EgisAI at startup, your process can still run; policy enforcement may be limited until a successful connection and policy fetch. Local checks remain in force where the engine can evaluate them. For your specific deployment’s behavior, refer to your contract and SECURITY.md.
  • Audit delivery is asynchronous so network latency does not sit on the critical path of every model call.

​
Privacy and security

  • Do not embed secrets in repository copies of this README.
  • For vulnerability reporting, see SECURITY.md — please use the disclosed channel rather than public issues for security-sensitive matters.
A short summary suitable for architecture reviews:
  • Governance evaluates prompts with respect to your organization’s policies before upstream invocation where applicable.
  • Sensitive-content handling is architected so that raw regulated values are not sent to third-party LLMs as part of policy enforcement workflows described here.

​
Supported Python libraries

LibraryNotes
openai ≥ 1.40Chat Completions, Responses API, streaming where supported by the adapter.
anthropic ≥ 0.40Messages API, streaming.
google-generativeai ≥ 0.8GenerativeModel.generate_content, streaming.
httpx / requestsOptional broad HTTP capture when the fallback is enabled.
Minimum versions are guidance; pin in your own requirements.txt for reproducible builds. Per-library walkthroughs:

OpenAI

Anthropic

Google Gemini

httpx / requests

​
Resources

ResourceURL
Websiteegisai.co
Documentationdocs.egisai.co
Dashboardapp.egisai.co
PyPIpypi.org/project/egisai
Repository & issuesgithub.com/EgisLabs/egisai-sdk
ChangelogCHANGELOG.md on GitHub
SecuritySECURITY.md on GitHub

​
License

Apache License 2.0 — see the LICENSE file in the source repository.
EgisAI — runtime governance for AI agents.