Frameworks are a collection of tools and libraries that provide a structured foundation for developing applications. These frameworks have reusable components that enable customization and integration of LLMs into AI applications. These frameworks have been used to create Document Summarizers, Virtual Assistants, Chatbots and AI agents. In this blog, I will provide you with a brief overview of the frameworks, their main features and what makes them unique. LANGCHAIN LangChain began as an open-source project in October 2022, but as the GitHub stars piled up, it was quickly turned into a company led by Harrison Chase. It provides tools for chaining together LLMs, APIs, and other components to create more complex workflows. It also emphasizes the use of external knowledge sources (like databases, APIs, or documents) with LLMs to enhance their capabilities. LangChain is fascinating because it lets you augment existing LLMs with memory and context. They can artificially add “reason
Every day there are breakthroughs around the world, a baby makes its first step, a teenager completes an objective on his video game and a developer creates a new feature. But once every few years, there is a breakthrough that changes the world forever. We may think of it as something that just happens overnight. But as an obese person doesn't get fat after only eating 2 buckets of chicken in one sitting, major technological advancements require multiple strings in play for it to occur. In our lives today, we've used or seen AI in one way or another. We may be afraid of its intelligence reaching the heights of a human brain or we may be concerned that we are more exposed than ever. I want you to think about other advancements that have happened during your lifetime; smartphones, social media boom, adoption of WiFi, TikTok short video craze. All these advancements faced skeptism during the early stages but have been highly impactful to our lives. We've heard that jobs and