Enhance Your AI Models with Giskard: A Comprehensive Evaluation & Testing Framework
In the realm of Artificial Intelligence (AI) and Machine Learning (ML), ensuring the robustness, fairness, and security of models is paramount. With the increasing complexity of AI applications, it's crucial to have robust evaluation and testing frameworks in place to control risks associated with performance, bias, and security issues. This is where Giskard steps in – an open-source evaluation and testing framework designed specifically for Language Model-based applications (LLMs) and ML models.
Unveiling Giskard 🐢
Giskard is more than just a tool; it's a solution to the pressing challenges faced by developers, researchers, and practitioners in the AI domain. With its easy installation process via PyPi and seamless integration with Python 3.9, 3.10, and 3.11, Giskard empowers users to take control of their AI models' performance, bias, and security.
Delving into Giskard's Capabilities ⤵️
Automated Assessment with Scan
Giskard's scanning capabilities are nothing short of revolutionary. By automatically detecting issues such as hallucinations, harmful content generation, prompt injection, robustness issues, sensitive information disclosure, stereotypes, and discrimination, Giskard provides users with comprehensive insights into their models' vulnerabilities.
RAG Evaluation Toolkit (RAGET)
For those working with RAG (Retrieval-Augmented Generation) applications, Giskard's RAGET comes to the rescue. This toolkit enables users to automatically generate evaluation datasets and assess RAG application answers with unparalleled depth and accuracy. With RAGET, users can evaluate various components of the RAG agent, including the generator, retriever, rewriter, router, and knowledge base.
Seamless Integration with Favorite Tools
Giskard is designed to seamlessly integrate with your favorite tools and environments, ensuring a smooth and hassle-free experience for users across different platforms.
Quickstart Guide 🤸♀️
1. Build a LLM Agent
Giskard makes it easy to build LLM agents tailored to your specific needs. Whether you're answering questions about climate change or tackling complex queries, Giskard provides the tools and resources you need to get started.
2. Scan Your Model for Issues
Once your model is up and running, it's time to scan it for potential issues. With Giskard's magical scan, you can identify and address performance, bias, and security issues with ease.
3. Automatically Generate an Evaluation Dataset
In the event that issues are detected, Giskard enables you to automatically generate an evaluation dataset based on the issues found. This allows for thorough testing and validation, ensuring that your AI models meet the highest standards of quality and reliability.
Join the Giskard Community 👋
At Giskard, we believe in the power of community-driven innovation. We welcome contributions from the AI community and invite you to join our thriving community on Discord. By leaving us a star on GitHub or considering sponsorship, you can help support our mission to build powerful, open-source tools for the AI community.
Conclusion
With Giskard, the journey to building robust, fair, and secure AI models becomes a reality. By harnessing the power of cutting-edge evaluation and testing frameworks, developers and researchers can unlock new possibilities in the field of AI. Whether you're a seasoned AI practitioner or just getting started, Giskard is your trusted partner in enhancing the performance, fairness, and security of your AI models.
