A package for AI Evaluation, RBAC and prompt firewall
Reason this release was yanked:
Bug fix
Project description
ATX Guardrails
Enterprise-Grade AI Guardrails & Evaluation Platform
atx-guardrails is a unified library designed to secure, manage, and evaluate your Large Language Model (LLM) applications. It provides three core pillars of functionality:
- AI Evaluation: State-of-the-art metrics to validate agent performance (Response Relevance, Task Success, Param Correctness, etc.).
- Prompt Firewall: Real-time protection against jailbreaks, harmful content, and PII leakage.
- RBAC (Role-Based Access Control): Secure Retrieval Augmented Generation (RAG) with granular document-level permissioning.
Installation
pip install atx-guardrails
Getting Started
ATX Guardrails is a managed service. To get started:
- Install the library using
pip install atx-guardrails - Contact ATX Labs at hello@atxlabs.ai to receive your authentication credentials and endpoint configuration
- Configure your environment with the provided
.envfile - Start building with the clients provided below
Platform Capabilities
1. AI Evaluation
A comprehensive suite of metrics to validate, benchmark, and monitor the performance of your LLM agents and pipelines.
| Metric | What It Measures |
|---|---|
| Response Relevance | How directly and accurately the output addresses the input query |
| Task Success | Whether the agent successfully completed the requested task |
| Tool Correctness | Whether the agent invoked the right tools in the right sequence |
| Param Correctness | Whether the arguments passed to tools are valid and match user intent |
| G-Eval | Custom criteria evaluation — define your own rubric and scoring logic |
| CEP (Conditional Evaluation Pipeline) | Multi-step, branching evaluation flows for complex agent workflows |
Key Features:
- Agent-level tracking with
agent_nametagging - Automatic server-side logging of all evaluation results
- Configurable thresholds for pass/fail determination
- Support for custom evaluation steps and criteria
2. Prompt Firewall
Real-time protection layer that sits between your users and your LLM, filtering out harmful, malicious, or policy-violating prompts before they reach your model.
Protects Against:
- Prompt injection and jailbreak attempts
- Requests for harmful or dangerous content
- Social engineering and manipulation tactics
- PII leakage and data exfiltration
3. RBAC (Role-Based Access Control)
Secure your Retrieval Augmented Generation (RAG) pipelines with granular, document-level access control. Ensure users only receive answers based on information they are authorized to access.
Key Features:
- Role-based document permissioning via simple YAML configuration
- Automatic document syncing and indexing
- Per-user query filtering based on assigned roles
- Built-in telemetry and access monitoring
Why ATX Guardrails?
- All-in-One Platform — Evaluation, Security, and Access Control in a single library
- Simple Integration — Drop-in Python client, no infrastructure to manage
- Enterprise Ready — Token-based auth, audit logging, role-based access
Contact
For access credentials, or a demo:
License
Proprietary — ATX Labs. All rights reserved.
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