这些都是预先确定的动作序列和对 LLM 的调用,可以让我们更轻松地构建复杂的应用程序,这些应用程序需要 LLM 之间或 LLM 与其他组件之间的链式连接。 一个链条的例子可能是:接收用户查询,将其分成小块,嵌入这些小块,在 VectorDB 中搜索相似的嵌入,使用 VectorDB 中最相似的前三个小块作为上下文提供答案,并生成答案。
Building LLM-based applications can undoubtedly provide valuable solutions for several problems. However, understanding and proactively addressing challenges such as hallucinations, prompt context, reliability, prompt engineering, and security will be instrumental in harnessing the true potential of LLMs while...
Tools like Semantic Kernel, TypeChat, and LangChain make it possible to build applications around generative AI technologies like Azure OpenAI. That’s because they allow you to put constraints around the underlying large language model (LLM), using it as a tool for building and running n...
LangChain: a general-purpose framework for LLMs LangChain is a comprehensive framework designed for the development of LLM applications, offering extensive control and adaptability for various use cases. It provides greater granularity than LlamaIndex, enabling developers to create applications such as ...
specifically, this article focuses on aspects of how we stream messages and responses to the front-end UI while giving some overview of what happens on the server-side. As more teams and enterprises consider leveraging Large Language Models (LLMs), we hope this article helps expand the...
LLM-powered apps with Docker GenAI Stack TheDocker GenAI Stacklets teams easily integrate NVIDIA accelerated computing into their AI workflows. This stack, designed for seamless component integration, can be set up on a developer’s laptop using Docker Desktop for Windows. It helps deliver the powe...
This combination enables developers to build AI-powered intelligent applications using MongoDB Atlas Vector Search and large language models from providers like OpenAI, Azure OpenAI, and Hugging Face. Despite all their incredible capabilities, LLMs have a knowledge cutoff date an...
Start building LLM-empowered multi-agent applications in an easier way. If you find our work helpful, please kindly citeour paper. Visit ourworkstationto build multi-agent applications with dragging-and-dropping. Welcome to join our community on ...
The development and release of ChatGPT and other state-of-the-art large language models (LLMs) has renewed interest in the concept of AI agents, a term that evokes a range of assumptions about their potential as applications to independently automate many tasks along with the risks they presen...
(ex.Llama-2-70b,gpt-4, etc.) are only aware of the information that they've been trained on and will fall short when we require them to know information beyond that. Retrieval augmented generation (RAG) based LLM applications address this exact issue and extend the utility of LLMs to ...