# PAS2

## Docs

- [Feedback storage system](https://mintlify.wiki/serhanylmz/pas2/advanced/feedback-system.md): Understand PAS2's SQLite-based feedback storage, data persistence, and how to collect and analyze user feedback on hallucination detection results.
- [Performance optimization](https://mintlify.wiki/serhanylmz/pas2/advanced/performance-tuning.md): Optimize PAS2's performance through parallel processing, connection pooling, progress callbacks, and resource management for faster hallucination detection.
- [Visualization tools and techniques](https://mintlify.wiki/serhanylmz/pas2/advanced/visualization.md): Learn how to use PAS2's visualization system to display analysis results, track progress, and create interactive UI components with Gradio.
- [detect_hallucination method](https://mintlify.wiki/serhanylmz/pas2/api/detect-hallucination.md): Main method for detecting hallucinations by analyzing responses to paraphrased queries
- [HallucinationDetectorApp class](https://mintlify.wiki/serhanylmz/pas2/api/detector-app.md): Gradio application wrapper for PAS2 with database storage and UI integration
- [generate_paraphrases method](https://mintlify.wiki/serhanylmz/pas2/api/generate-paraphrases.md): Generate semantically equivalent paraphrases of a query using the Mistral API
- [HallucinationJudgment class](https://mintlify.wiki/serhanylmz/pas2/api/hallucination-judgment.md): Pydantic model representing the judgment result from hallucination detection analysis
- [judge_hallucination method](https://mintlify.wiki/serhanylmz/pas2/api/judge-hallucination.md): Use a judge model to evaluate responses for hallucinations and factual inconsistencies
- [PAS2 class](https://mintlify.wiki/serhanylmz/pas2/api/pas2-class.md): Core class implementing the Paraphrase-based Approach for Scrutinizing Systems using model-as-judge methodology
- [Changelog](https://mintlify.wiki/serhanylmz/pas2/changelog.md): Version history and updates for the PAS2 hallucination detection system
- [Hallucination detection](https://mintlify.wiki/serhanylmz/pas2/concepts/hallucination-detection.md): Understand how PAS2 detects hallucinations by analyzing response consistency across semantically equivalent queries
- [Model-as-judge approach](https://mintlify.wiki/serhanylmz/pas2/concepts/model-as-judge.md): Learn how PAS2 uses OpenAI's o3-mini model as an independent judge to evaluate response consistency and detect hallucinations
- [Paraphrasing technique](https://mintlify.wiki/serhanylmz/pas2/concepts/paraphrasing.md): Learn how PAS2 uses semantic paraphrases to test response consistency and detect potential hallucinations
- [Contributing](https://mintlify.wiki/serhanylmz/pas2/contributing.md): Guidelines for contributing to the PAS2 hallucination detection system
- [Basic usage](https://mintlify.wiki/serhanylmz/pas2/examples/basic-usage.md): Get started with PAS2 for hallucination detection using simple examples
- [Batch processing](https://mintlify.wiki/serhanylmz/pas2/examples/batch-processing.md): Process multiple queries efficiently with parallel execution and batch operations
- [Custom configuration](https://mintlify.wiki/serhanylmz/pas2/examples/custom-configuration.md): Configure PAS2 with custom models, callbacks, and advanced settings
- [FAQ](https://mintlify.wiki/serhanylmz/pas2/faq.md): Frequently asked questions about the PAS2 hallucination detection system
- [API key setup](https://mintlify.wiki/serhanylmz/pas2/guides/api-keys.md): Configure Mistral AI and OpenAI API keys for PAS2
- [Benchmarking and evaluation](https://mintlify.wiki/serhanylmz/pas2/guides/benchmarking.md): Evaluate PAS2's hallucination detection accuracy using benchmark datasets
- [Configuration](https://mintlify.wiki/serhanylmz/pas2/guides/configuration.md): Configure PAS2 settings and environment variables for optimal performance
- [Deploying to Hugging Face Spaces](https://mintlify.wiki/serhanylmz/pas2/guides/huggingface-spaces.md): Deploy PAS2 hallucination detection system to Hugging Face Spaces with persistent storage
- [Installation](https://mintlify.wiki/serhanylmz/pas2/guides/installation.md): Learn how to install PAS2 and set up your development environment
- [Local deployment options](https://mintlify.wiki/serhanylmz/pas2/guides/local-deployment.md): Run PAS2 hallucination detection system on your local machine for development and testing
- [Using PAS2 as a Python library](https://mintlify.wiki/serhanylmz/pas2/guides/python-library.md): Integrate hallucination detection into your Python applications using the PAS2 library
- [Using the web interface](https://mintlify.wiki/serhanylmz/pas2/guides/web-interface.md): Learn how to use the Gradio web interface for interactive hallucination detection
- [How it works](https://mintlify.wiki/serhanylmz/pas2/how-it-works.md): Understanding the paraphrase-based hallucination detection system and model-as-judge approach
- [Welcome to PAS2](https://mintlify.wiki/serhanylmz/pas2/introduction.md): A sophisticated hallucination detection system using paraphrase-based approach with model-as-judge verification
- [Quick start](https://mintlify.wiki/serhanylmz/pas2/quickstart.md): Get up and running with PAS2 hallucination detection in under 5 minutes