atx-guardrails 0.0.1

A package for AI-powered RBAC, prompt firewall, PII detection/masking and AI Evaluation

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:

1. AI Evaluation: State-of-the-art metrics to validate agent performance (Response Relevance, Task Success, Param Correctness, etc.).
2. Prompt Firewall: Real-time protection against jailbreaks, harmful content, and PII leakage.
3. RBAC (Role-Based Access Control): Secure Retrieval Augmented Generation (RAG) with granular document-level permissioning.

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Installation

pip install atx-guardrails

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Getting Started

ATX Guardrails is a managed service. To get started:

1. Install the library using pip install atx-guardrails
2. Contact ATX Labs at [e-mail] to receive your authentication credentials and endpoint configuration
3. Configure your environment with the provided .env file
4. Start building with the clients provided below

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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_name tagging
• Automatic server-side logging of all evaluation results
• Configurable thresholds for pass/fail determination
• Support for custom evaluation steps and criteria

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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

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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

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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

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Contact

For access credentials, or a demo:

📧 [e-mail]

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License

Proprietary — ATX Labs. All rights reserved.