OpenAI Rust SDK

A comprehensive Rust SDK for the OpenAI API with integrated YARA-X rule validation testing. This library provides complete access to all OpenAI APIs including Chat, Assistants, Batch processing, and more, with special capabilities for testing AI models' ability to generate valid YARA rules.

Developed by Wyatt Roersma and Claude Code.

Features

✅ Complete OpenAI API Support

• Create, retrieve, cancel, and list batch jobs
• JSONL format support for batch requests
• Automatic retry and error handling
• Type-safe API interactions

✅ YARA-X Integration

• Real-time YARA rule validation using yara-x
• Feature detection (hex patterns, strings, regex, metadata)
• Performance metrics and complexity scoring
• Pattern testing against sample data

✅ Testing Framework

• Generate batch jobs with YARA-specific questions
• Validate AI-generated rules for correctness
• Built-in test suite with various rule types
• Comprehensive error reporting

Installation

Add to your Cargo.toml:

[dependencies]
openai_rust_sdk = "0.1.0"

Quick Start

Environment Setup

export OPENAI_API_KEY=your_api_key_here

Generate a Batch Job

cargo run -- generate-batch basic output.jsonl

Validate a YARA Rule

cargo run -- validate-rule rule.yar

Run Test Suite

cargo run -- run-tests

Usage Examples

Full Integration Example

use openai_rust_sdk::testing::{
    batch_generator::BatchJobGenerator,
    yara_validator::YaraValidator,
};

fn main() {
    // Generate batch job
    let generator = BatchJobGenerator::new(Some("gpt-5-nano".to_string()));
    let batch_file = std::path::Path::new("test_batch.jsonl");
    generator.generate_test_suite(batch_file, "basic").unwrap();
    
    // Validate a YARA rule
    let rule = r#"
    rule DetectMalware {
        strings:
            $a = "malware"
        condition:
            $a
    }
    "#;
    
    let validator = YaraValidator::new();
    let result = validator.validate_rule(rule).unwrap();
    
    if result.is_valid {
        println!("✓ Rule is valid!");
    }
}

Batch Processing Workflow

1. Prepare Questions: Generate JSONL file with YARA-related questions
2. Upload File: Use OpenAI Files API to upload the JSONL
3. Create Batch: Submit batch job with file ID
4. Monitor Progress: Poll for completion (up to 24 hours)
5. Download Results: Retrieve generated YARA rules
6. Validate Rules: Use yara-x validator to test correctness

Modern Responses API

The SDK now ships with a native client for the /v1/responses endpoints. You can access the full feature set--including conversations, background execution, and structured outputs--through the new builder and client helpers:

use futures::StreamExt;
use openai_rust_sdk::{
    CreateResponseRequest, OpenAIClient,
    ResponsesApiServiceTier as ServiceTier,
};

# tokio_test::block_on(async {
let client = OpenAIClient::new(std::env::var("OPENAI_API_KEY")?)?;

let request = CreateResponseRequest::new_text("gpt-4o-mini", "Summarize Rust ownership")
    .with_service_tier(ServiceTier::Auto)
    .with_store(true);

let response = client.create_response_v2(&request).await?;
println!("Summary: {}", response.output_text());

// Stream events with strong typing
let mut stream = client.stream_response_v2(&request).await?;
while let Some(event) = stream.next().await {
    match event? {
        openai_rust_sdk::ResponseStreamEvent::OutputTextDelta { delta, .. } => {
            print!("{}", delta);
        }
        openai_rust_sdk::ResponseStreamEvent::ResponseCompleted { .. } => println!("\nDone!"),
        _ => {}
    }
}
# Ok::<(), Box<dyn std::error::Error>>(())
# })?;

Compatibility helpers such as generate_text, create_chat_completion, and create_custom_response automatically route through the Responses API to maintain the existing interface while unlocking new functionality.

Test Suites

The SDK includes three test suites for different complexity levels:

Basic Suite

• Simple string detection rules
• Basic PE file detection
• Error/warning pattern matching

Malware Suite

• Ransomware detection patterns
• Trojan indicators
• Cryptominer signatures
• Advanced malware techniques

Comprehensive Suite

• Complex multi-condition rules
• External variable usage
• Iterator patterns
• Module imports
• Performance-optimized rules

Project Structure

openai_rust_sdk/
├── src/
│   ├── lib.rs              # Library entry point
│   ├── main.rs             # CLI application
│   └── testing/
│       ├── mod.rs          # Testing module exports
│       ├── yara_validator.rs    # YARA-X validation
│       ├── test_cases.rs       # Built-in test cases
│       └── batch_generator.rs  # Batch job generation
├── examples/
│   └── full_integration.rs # Complete usage example
├── test_data/
│   ├── yara_x_questions.jsonl # Sample questions
│   └── simple_batch.jsonl     # Basic test batch
└── tests/
    └── integration_test.rs # Integration tests

CLI Commands

# Validate a single YARA rule
cargo run -- validate-rule path/to/rule.yar

# Run the built-in test suite
cargo run -- run-tests

# Generate batch job for basic testing
cargo run -- generate-batch basic output.jsonl

# Generate batch job for malware detection
cargo run -- generate-batch malware output.jsonl

# Generate comprehensive test batch
cargo run -- generate-batch comprehensive output.jsonl

Testing with GPT-5-Nano

The SDK is configured to use gpt-5-nano for testing, which provides fast and cost-effective rule generation. Example batch request:

{
  "custom_id": "yara_001",
  "method": "POST",
  "url": "/v1/chat/completions",
  "body": {
    "model": "gpt-5-nano",
    "messages": [
      {
        "role": "system",
        "content": "You are an expert YARA rule developer."
      },
      {
        "role": "user",
        "content": "Create a YARA rule to detect UPX-packed PE files."
      }
    ],
    "max_tokens": 1000,
    "temperature": 0.3
  }
}

Validation Metrics

The validator provides comprehensive metrics:

• Compilation Status: Whether the rule compiles successfully
• Feature Detection: Identifies rule components (strings, hex, regex, etc.)
• Performance Metrics: Compilation time and complexity scoring
• Pattern Testing: Tests rules against sample data
• Error Reporting: Detailed error messages for invalid rules

Development

Building

cargo build --release

Running Tests

cargo test

Formatting & Linting

cargo fmt
cargo clippy -- -D warnings

License

MIT

Contributing

Contributions are welcome! Please ensure all tests pass and code is properly formatted before submitting PRs.

Requirements

• Rust 1.89.0 or later
• OpenAI API key for batch processing
• yara-x crate for rule validation