Building Agentic AI Apps: Vector Database Interaction & Docker Deployment
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In this riveting episode by Krish Naik, the stage is set for the development of an agentic AI application that delves into the realm of Vector databases. The mission? To create a platform where agents can seamlessly interact with these databases to extract precise responses. As the narrative unfolds, viewers are urged to rally behind the channel, with a target of 1200 likes and 150 comments to fuel the fire for more exhilarating content.
The plot thickens as the protagonist encounters a hurdle involving open API keys, swiftly maneuvering through viewer feedback to incorporate suggested models and enhance the application's functionality. The journey takes a thrilling turn towards the creation of a PDF assistant, where agents are poised to engage with Vector databases, starting with the formidable PG Vector. Docker emerges as a key player in this saga, facilitating the seamless running of the Vector database and the extraction and storage of PDF content.
With an air of anticipation, Krish Naik navigates viewers through the meticulous setup of environment variables, the strategic importation of essential libraries such as assistant and PG assistant storage, and the crucial initialization of the PDF assistant file. The knowledge base comes to life through the integration of PDF URLs, while the Vector database stands ready to house the extracted PDF content. The assistant is meticulously crafted, with parameters fine-tuned to enable seamless program execution, including the exploration of chat history and knowledge base search functionalities. The stage is set, the players are in position, and the curtain rises as the program is set in motion using typer to run the PDF assistant.
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
Image copyright Youtube
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