Wozway

<p align="center"> <br/> <a href="https://opensource.org/license/apache-2-0"><img src="https://img.shields.io/badge/license-Apache%202.0-blue?color=3F51B5&style=for-the-badge&label=License&logoColor=000000&labelColor=ececec" alt="License: Apache 2.0"></a> <a href="https://discord.com/invite/NBgaCkmJPR"> <img src="https://img.shields.io/discord/1306078130162761799?label=Discord&logo=Discord&style=for-the-badge&logoColor=000000&labelColor=ececec" alt="Discord"/> </a> <a href="https://pypi.org/project/defendai-wozway"> <img src="https://img.shields.io/pypi/v/defendai-wozway?label=PyPi&style=for-the-badge&logoColor=000000&labelColor=ececec" alt="PyPI"/> </a> <a href="https://docs.defendai.tech"><img src="https://img.shields.io/badge/api_docs-1.0.0-blue?color=3F51B5&style=for-the-badge&logoColor=000000&labelColor=ececec" alt="API Docs: 1.0.0"></a> <br/> <br/> </p> <p align="center"> <img src="wozway.png" width="300" title="Wozway"> </p> <h3 align="center">Easily control traffic between Apps and LLM using data security policies</h3> <br/> <a href="https://defendai.tech"> <img src="policy.png" title="Policy Screenshot"> </a> <br/> <br/> <br/>

Integrate quickly using existing openai compatible chat completions api by just changing base url

import openai

api_key = "YOUR_OPENAI_KEY"
client = openai.OpenAI(api_key=api_key,base_url="https://dev.defendai.tech")
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Is this valid SSN 123-45-6789 ?"}
    ],
    stream=False
)
print(response.choices[0].message["content"])

Easily Add policies to Block/Alert/Anonymize Prompts or Responses by App and LLM Model

from defendai_wozway import Wozway
import os
api_key = "YOUR_OPENAI_KEY"
client = Wozway.Client(api_key=api_key,base_url="https://dev.defendai.tech")
policies = [
    {
        "policy_type": "Compliance",
        "direction": "PROMPT",
        "attributes": ["PII", "GDPR"],
        "action": "ALERT",
        "model": "gpt-4o",
        "app": "CopilotApp"
    },
    {
        "policy_type": "Security",
        "direction": "PROMPT",
        "attributes": ["Malware", "Phishing"],
        "action": "BLOCK",
        "model": "deepseek-r1",
        "app": "Global"
    },
    {
        "policy_type": "Privacy",
        "direction": "RESPONSE",
        "attributes": ["SSN"],
        "action": "ANONYMIZE",
        "model": "claude-sonet-3.7",
        "app": "StockAgent"
    }
]
client.apply(policies)

This service allows developers to easily secure requests and responses between their chat apps and LLM cloud services like OpenAI, Groq, Gemini , Anthropic , Perplexity and more using policies through cloud driven UI or APIs available via the wozway sdk

Table of Contents

• Introduction
• Features
• Architecture
• Prerequisites
• Installation
• Usage
• Developer SDK
• Provision Tenant Video
• UI Walkthrough Video
• Support
• License

Introduction

Wozway by DefendAI provides a secure and efficient way to manage communication between your chat client applications and various LLM cloud services. By running a simple script, you can start a tenant that proxies your LLM requests and response through a policy driven llm proxy , adding an extra layer of security and abstraction. Each tenant gets a cloud domain with ability to control traffic through the service

Features

• Secure proxying of requests to Multiple LLM Providers (OpenAI, Groq, etc.)
• Policy based enforcement using API or UI
• Support for Regex , Anonymization , Code , Phishing URL , Prompt and Response detection
• Similarity search with millions of malicious prompts database to block/alery admin
• Incident , Activities and Dashboard for monitoring usage across all Gen AI Apps

Architecture

Wozway runs alongside client apps and intelligently re-routes only LLM bound traffic to DefendAI Cloud for policy enforcement and subsequent forward to LLM Providers like Open AI , Anthropic , Groq etc .. All other traffic is routed without any interference to its intended destination .. Wozway can intercept both prompt and response for running full security check

<p align="center"> <img src="wozway_architecture.png" width="1000" title="Wozway Architecture"> </p>

Prerequisites

• Python 3.7+
• pip package manager
• API keys for the LLM services you intend to use (e.g., OpenAI or GROQ API key)
• Docker

Installation

1. Clone the repository

   git clone https://github.com/Defend-AI-Tech-Inc/wozway.git
   cd wozway
   

2. Install dependencies

   pip install -r requirements.txt
   

Usage

Starting the Tenant

Run the following script to start your tenant:

python start_tenant.py

This script will ask few questions to setup the cloud account and domain . It will start local version of openwebui integrated with wozway to proxy all requests throught the cloud proxy to the LLM Provider . Prompt and Responses are intercepted based on policies configured in cloud console

SDK Installation

The SDK can be installed with either pip package manager.

PIP

pip install defendai-wozway

<!-- End SDK Installation [installation] --> <!-- Start IDE Support [idesupport] -->

SDK Example Usage

Simple Getting Started Example

from defendai_wozway import Wozway
import os

with Wozway(
    bearer_auth=os.getenv("WOZWAY_BEARER_AUTH", ""),
) as s:
    res = s.activities.get_activities()
    if res is not None:
       for activity in res:
          print(activity["prompt"])
      pass

Detailed SDK documentation can be found here SDK Documentation

Installation Video

UI Video Walkthrough

Support

If you encounter any issues or have questions, please open an issue on the GitHub repository or contact our support team at support@defendai.tech.

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.