2023) 是一个特别有意思的实验,25个虚拟任务,每个都被基于LLM-powered agent控制,同时生活在一个沙箱环境中且能够相互沟通。这些agent能产生类似人类在交往时的模拟效果。 generative agents的设计结合了使用memory的LLM, 有规划有反馈的机制能让这些agnet去基于历史的经验做后续的行为,比如与其他的agnet交流沟通. ...
只需定义 Pydantic 对象,将其附加到 LLM(as_structured_llm(...)),就能使你通过块级 RAG 或文档级 RAG 进行结构化抽取,支持异步和流式输出。 下面让我们一起来探索llamaindex这项全新能力。 环境设置 这里演示使用的是gpt,也可以通过HuggingFaceLLM加载本地模型。 import nest_asyncio nest_asyncio.apply() fr...
In this tutorial, you’ll learn how to useLangChainandLangSmithto build and debug custom LLM-powered applications. You’ll also learn how you can leverage these tools in acontinuous integration and continuous delivery (CI/CD) pipelinefor faster, more consistent model evaluations and a more scala...
In this follow-up tutorial, we’ll show you how to build the continuous delivery (CD) portion of the pipeline to help bring your LLM-powered apps safely into production. The pipeline will run a scheduled set of nightly evaluations on your LLM application, wait for a human to review the ...
Awesome LLM-Powered Agent Thanks to the impressive planning, reasoning, and tool-calling capabilities of Large Language Models (LLMs), people are actively studying and developingLLM-powered agents.These agents are possible to autonomously (and collaboratively) solve complex tasks, or simulate human int...
Community health workers (CHWs) provide last-mile healthcare services but face challenges due to limited medical knowledge and training. This paper describes the design, deployment, and evaluation of ASHABot, an LLM-powered, experts-in-the-loop, Whats...
from_pretrained( repo_id="Gigax/NPC-LLM-3_8B-GGUF", filename="npc-llm-3_8B.gguf" # n_gpu_layers=-1, # Uncomment to use GPU acceleration # n_ctx=2048, # Uncomment to increase the context window ) model = models.LlamaCpp(llm) # Instantiate a stepper: handles prompting + output ...
A web-based, LLM-powered AI symptom summarization tool (ASST) for monitoring of breast cancer treatment toxicity.doi:10.1200/JCO.2024.42.16_suppl.e1362222222e13622#Background:Traditional methods for capturing patient-reported outcomes (PROs) are often time-consuming and may lead to underreporting...
We introduce Patchview, a customizable LLM-powered system that visually aids worldbuilding by allowing users to interact with story concepts and elements through the physical metaphor of magnets and dust. Elements in Patchview are visually dragged closer to concepts with high relevance, facilitating ...
-- 目前公开的评估数据集,主要针对通用大模型。对于个人打造的 LLMs powered 应用,我们应该怎么评估呢: - 第一步:看是否有标准答案(尤其是是数值型的结果),那么就使用传统的机器学习方法评估(Accuracy、Confusion Matrix,F1、Sensitivity,Specificity 等等); ...