Ashhadul Islam

Ashhadul Islam

Harnessing AI to bridge visionary innovation with real-world impact.

Super Quick: Retrieval Augmented Generation Using Ollama

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In this post, I delve into the capabilities of Ollama, a powerful infrastructure that simplifies local execution of open-source models and interactions with PDFs. Ollama acts like a Docker system for Large Language Models (LLMs), allowing easy setup of local LLM servers, fine-tuning, and more.

I demonstrate how to use Ollama by setting up a system where I can chat with an LLM to extract specific information from a folder containing all my research articles. This process showcases how Ollama can be a game-changer for managing and retrieving detailed insights from extensive research data.

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MemGPT: Assimilating Information from Multiple PDFs

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In this post, I explore the capabilities of MemGPT in handling Retrieval-Augmented Generation (RAG) tasks, particularly focusing on its ability to assimilate information from multiple PDF files. While GPT-4 has its strengths, it often struggles with tasks requiring the consolidation of information from several documents. MemGPT, on the other hand, excels in this area, as demonstrated through a series of comparisons.

Advanced Retrieval with LlamaPacks: Elevating RAG in Fewer Lines of Code!

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In this post, I explore five Retrieval-Augmented Generation (RAG) methods open-sourced by LlamaIndex, which claim to simplify the RAG process to just about one line of code. Through a series of experiments, I test these methods and compare their effectiveness in terms of accuracy and efficiency.