Skip to content

Open source SDKs, benchmarks, and examples for QWED - The Enterprise AI Verification Platform. Model-agnostic verification infrastructure for production AI.

License

Notifications You must be signed in to change notification settings

rahuldass19/qwed-open

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Β 

History

9 Commits
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 
Β 

Repository files navigation

QWED Open Source Ecosystem

PyPI npm License Accuracy Security

The only open-source verification layer for production AI.

Welcome to QWED - The Enterprise Deterministic Verification Engine.

This repository contains the Client SDKs and Benchmarks to help you integrate and independently verify QWED's capabilities.


πŸ€” Why Open Source?

We believe in transparent AI verification. While our core verification engines remain proprietary, we're open-sourcing:

  • βœ… Client SDKs - Integrate QWED into any application
  • βœ… Benchmarks - Independently verify our accuracy claims
  • βœ… Examples - See real-world use cases

Philosophy: "Trust, but verify." We give you the tools to test our claims yourself.


πŸš€ Getting Started

1. Get an API Key

Sign up at qwed.tech to get your API key.

2. Choose Your SDK

  • Python: pip install qwed
  • JavaScript/TypeScript: npm install qwed-sdk

3. Verify Your First Query

from qwed import QwedClient

client = QwedClient(api_key="YOUR_KEY")
result = client.verify_natural_language("What is 10 + 10?")

print(result.final_answer)  # 20.0
print(result.status)        # "VERIFIED"

πŸ“¦ SDKs

Python SDK

Installation

pip install qwed

Advanced Usage

# Verify code security
code_result = client.verify_code("print('Hello World')")

# Verify logic constraints
logic_result = client.verify_logic("x > 5 AND x < 10")

# Verify statistical claims
stats_result = client.verify_stats(csv_data, "Average sales increased by 15%")

JavaScript SDK

Installation

npm install @qwed/sdk

Quick Start

import { QwedClient } from '@qwed/sdk';

const client = new QwedClient("sk_live_...");

const result = await client.verifyNaturalLanguage("What is 15% of $200?");
console.log(result.finalAnswer); // 30.0

οΏ½ Example Use Cases

Use Case 1: FinTech - Verify Loan Calculations

from qwed import QwedClient

client = QwedClient(api_key="YOUR_KEY")

# User queries AI for loan payment
query = "What's the monthly payment for a $500k loan at 3.5% over 30 years?"

# QWED verifies the calculation
result = client.verify_natural_language(query)

if result.status == "VERIFIED":
    print(f"Payment: ${result.final_answer}/month")
    print(f"Proof: {result.verification}")
else:
    print("ERROR: LLM hallucinated")

Use Case 2: HealthTech - Verify Drug Dosages

query = "Calculate pediatric dosage: patient weighs 25kg, adult dose 500mg"
result = client.verify_natural_language(query)

# QWED uses symbolic math to ensure correctness
if result.status == "VERIFIED":
    approve_dosage(result.final_answer)
else:
    flag_for_human_review()

Use Case 3: Code Security - Block Exploits

const code = "os.remove('important.txt')";
const result = await client.verifyCode(code);

if (result.status === "UNSAFE") {
    console.log("Blocked dangerous code:", result.issues);
} else {
    executeCode(code);
}

πŸ“Š Benchmark Results

We tested QWED against raw LLM outputs (GPT-4, Claude) on 1000+ queries.

Test Category Raw LLM Accuracy QWED Accuracy Improvement
Math 83% 99.2% +16.2%
Security 0% (all exploits missed) 100% (all caught) +100%
Logic 67% 98.5% +31.5%
Overall 75% 99.2% +24.2%

How We Test

  • 1000+ queries across 8 domains (Math, Logic, Security, Stats, Facts, SQL, Reasoning, Image)
  • Edge cases included (division by zero, ambiguous queries, code injection)
  • Reproducible (run python benchmarks/api_runner.py yourself)

View Full Results


🀝 Contributing

We welcome contributions to improve the SDKs and benchmarks!

Areas We Need Help

  • Additional language SDKs (Go, Ruby, Java)
  • More benchmark test cases
  • Documentation improvements
  • Example applications

How to Contribute

  1. Fork this repo
  2. Create a feature branch (git checkout -b feature/amazing)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to branch (git push origin feature/amazing)
  5. Open a Pull Request

Code of Conduct

Be kind. We're all learning.


πŸ“œ License

SDKs: MIT License (free to use, modify, distribute)

QWED Core Engines: Proprietary (contact rahul@qwed.tech for licensing)

Benchmarks: CC0 (public domain - use freely)


Built with ❀️ in Pune by Rahul Dass

Questions? β†’ rahul@qwed.tech

About

Open source SDKs, benchmarks, and examples for QWED - The Enterprise AI Verification Platform. Model-agnostic verification infrastructure for production AI.

Topics

Resources

License

Contributing

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published