In this exciting video, software engineer Kaylynn Watson from Focused Labs dives into the world of AI and demonstrates the automation of testing and debugging processes for Retrieve and Generate (RAG) applications. Using cutting-edge technologies like Python, LangChain, and LCEL, Kaylynn showcases the creation of a tool to streamline the demo and documentation creation process for stakeholders.
By ingesting PowerPoint documentation and leveraging the power of the vector database, Kaylynn showcases how to automate the testing of a chatbot, making the entire process quicker and more efficient. With mentions of AI, RAG, Python, LangChain, and LCEL, this video is a must-watch for anyone looking to beef up their testing and debugging skills.
Don't forget to like, subscribe, and provide feedback to help Kaylin create more helpful content in the future. Join the journey of automating AI testing and debugging and discover the power of these buzzworthy technologies!
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Chapters
0:00 - Intro to Automating Testing and Debugging: Streamlining Demo Creation and Documentation
07:32 - Optimizing Data Analysis: The Advantages of Saving Content to CSVs
19:34 - Focusing on Factual Answer Accuracy: Foundations and Future Directions
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Keywords
AI, RAG (Retrieve and Generate), Testing, Debugging, Automation, Software engineer, Python, Vector database, Chatbot, Documentation, @LangChain , @OpenAI , PowerPoint, @unstructuredio
