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Developing End-to-End AI Apps Locally: Deep Seek R1 Integration with Krish Naik

Developing End-to-End AI Apps Locally: Deep Seek R1 Integration with Krish Naik
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In this thrilling episode on Krish Naik's channel, he takes us on a high-octane journey into the world of developing cutting-edge generative AI applications using the powerful Deep Seek R1 model. Krish dives headfirst into the process, showcasing how to seamlessly integrate this game-changing model locally without compromising data security by steering clear of sending information to far-off lands. He deftly maneuvers through the complexities, emphasizing the importance of using the Lang chain framework and the AMA tool to maximize efficiency and control.

With the precision of a seasoned race car driver, Krish meticulously selects the 1.5 billion parameters model, ensuring optimal performance without unnecessary bulk. He revs up the engine by demonstrating the seamless installation and execution of the model on his local machine, highlighting the critical role of system specifications in achieving lightning-fast responses. Krish's masterful handling of the technical intricacies sets the stage for a thrilling showcase of the model's capabilities, promising a ride filled with exhilarating AI interactions and lightning-quick insights.

As the adrenaline builds, Krish shifts gears to showcase the seamless integration of the AI model into the coding environment of VS Code using Streamlit and a carefully curated set of essential libraries. With the finesse of a seasoned pro, he deftly sets up the chat engine, configures system prompts, and expertly manages chat history to ensure a smooth and engaging user experience. The culmination of Krish's efforts is a high-performance AI chatbot that responds promptly to user queries, delivering Python code examples with the speed and precision of a well-tuned sports car on a racetrack.

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