While designing each "leaf" of my LLM workflow graph, or LLM-native architecture, I follow theLLM Triangle Principles³ to determine where and when to cut the branches, split them, or thicken the roots (by using prompt engineering techniques) and squeeze more of the lemon. 在设计 LLM 工作...
You will get a hands-on introduction in how to build your own LLM application. During the workshop, you will learn: Interfacing with LLMs in Python Building your first RAG Creating a simple Agent Usage Follow these setup instructions. Open the first Notebook in ./notebooks/ Follow along ...
An LLM agent is a modern AI system that utilizes large language models (LLMs) and is trained on massive amounts of data to think, plan, and take action autonomously. Unlike traditional AI systems, LLM agents are trained to consider sequential reasoning. Hence, they analyze data, utilize memo...
Advancements in LLMs have recently unveiled challenges tied to computational efficiency and continual scalability due to their requirements of huge parameters, making the applications and evolution of these models on devices with limited computation resources and scenarios requiring various abilities ...
Check outThe 5 Best Vector Databasesfor your specific use case. They provide a simple API and fast performance. Qdrant getting started example. Image source:Local Quickstart - Qdrant Serving An essential component for your application is a high-throughput inference and serving engine for LLMs that...
we will build an AI application that loads Microsoft Word files from a folder, converts them into embeddings, indexes them into the vector store, and builds a simple query engine. After that, we will build a proper RAG chatbot with history using vector store as a retriever, LLM, and the...
Dr. Robert Kübler August 20, 2024 13 min read Hands-on Time Series Anomaly Detection using Autoencoders, with Python Data Science Here’s how to use Autoencoders to detect signals with anomalies in a few lines of… Piero Paialunga ...
Welcome to Building AI Projects with LLM, Langchain, GAN course. This is a comprehensive project based course where you will learn how to develop advanced AI applications using Large Language Models, integrate workflow using Langchain, and generate images using Generative Adversarial Networks. This ...
You can now have a conversation with the chat LLM at OpenAI:Streamlining the project Recall that in the previous section our project had a PromptTemplate component? In fact, for building a conversational chatbot our project can be streamlined a little without needing to use the PromptTemplate ...
Lanarky provides a powerful abstraction layer to allow developers to build simple LLM microservices in just a few lines of code. Here's an example to build a simple microservice that uses OpenAI'sChatCompletionservice: fromlanarkyimportLanarkyfromlanarky.adapters.openai.resourcesimportChatCompletionReso...