A gentle introduction with Python — In last months, we witnessed the extraordinary capabilities of Large Language Models (LLMs) like ChatGPT. However, the real paradigm shift occurred when we started embedding those LLMs within our applications. This implies the integration of a new set of LLMs-related components within our application logic, including memory, metaprompt, plug-ins and…

Enabling LLM-powered agents to cooperate — In my latest article, we’ve introduced the concept of Agents as a type of LLM application that are powered with a set of external tools or plug-ins that allow them to “do stuff”. In ther words, agents can be seen as AI systems that, given a user’s query, are able…

An implementation with LangChain and GPT-3.5-turbo — In last months, we’ve witnessed the great capabilities of LLMs in the context of code understanding and generation. …

An implementation with LangChain and Azure OpenAI — Large Language Models have shown incredible capabilities in the field of Generative AI, and the potential to unlock new applications in many industries. An interesting analysis that have also emerged in last months is how LLMs can enhance or even substitute current technological approaches that we use to solve specific…

Overview of new features of Azure AI | Machine Learning Studio — A few weeks ago at Build 2023, Microsoft announced a re-branding of the Azure service called Azure Machine Learning (AML), the workspace where data scientist could train, test, deploy and orchestrate with powerful MLOps tools their ML projects lifecycle (you can read more about AML here). The former AML is…

Deploy a ChatGPT web app in minutes — On May 23rd, a stunning announcement was released, stating that new feature would have been added to the Playground soon, so that users could directly upload and chat with their own document, without worrying about the backend embedding and documents’ pre-processing. Well, the day has finally come. In this article…

Building a multimodal application powered by GPT — In my previous article, I introduced LangChain agents as applications powered by LLMs and integrated with a set of tools like search engines, databases, websites, and so on. Within an agent, the LLM is the reasoning engine that, based on the user input, is able to plan and execute a…

Embed LLMs into your applications with no code — LangChain is a Python library that makes it easier to combine the power of LLMs with the logic of an application. LangChain allows users to create and compose modular components, such as prompt serializers, agents, and chains, to achieve various natural language tasks. However, designing and testing LangChain flows can…

An implementation with Azure OpenAI and Python — Large Language Models (LLMs) like GPT-3.5-turbo (the model behind ChatGPT) and GPT-4 have been proving their generative power in last few months. However, as they are today they suffer from a limitation: they are limited to the knowledge on which they have been trained and the additional knowledge provided as…