A project named Baker, a smart recipe app, showcases the rapid evolution of AI capabilities in data extraction. Initially, using MistralAI’s open-mixtral-8x7b, the app struggled with parsing recipes, failing to extract data from 89 out of 360 recipes due to JSON inconsistencies. However, with the adoption of the newer and more advanced GPT-4o model, Baker achieved a 100% success rate in parsing all 360 recipes. This improvement highlights the significant strides AI has made in handling complex data tasks. The app, built almost entirely in Python, uses a simple three-tier architecture with FastAPI for backend and Streamlit for frontend, demonstrating how modern tools can accelerate development. Baker’s open-source nature on GitHub encourages collaboration and innovation, while its deployment on free-tier services like Streamlit Cloud and Koyeb makes it accessible to a broader audience. Despite its current limitations, such as a small recipe database and basic search functionality, Baker’s development journey illustrates the potential of AI in transforming unstructured data into practical, user-friendly applications.
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