展示HN:Praxos – AI代理的上下文管理
大家好!我们是Praxos的创始人Lucas和Soheil(网址:<a href="https://praxos.ai">https://praxos.ai</a>)。Praxos是一个AI代理的上下文管理器,提供构建状态保持代理所需的一切,确保它们在生产环境中不会出现故障。
Praxos能够解析任何数据源,从非结构化的PDF和API流到对话消息,再到结构化数据库,并将其转换为一个统一的知识图谱。这个图谱中的所有内容都是语义化的,并且其关系是明确的,从而将数据转化为一个干净、可查询的理解宇宙,AI可以在其中使用而不会出错。
无论您需要查询问题的答案,还是以适合当前用例的方式提取数据,Praxos都能做到,无需重新查询。这使得AI应用能够端到端解析数据,然后基于这些数据进行操作,提供单链和多链推理步骤的输出。中间结果、最终结果和用户编辑的输出都可以重新添加到知识图谱中,使Praxos能够实时学习。
在我们从事保险行业的开发时,常常遇到两个主要问题:
首先,大型语言模型(LLMs)无法解析诸如财产清单和保险政策等文档。举个例子,财产清单可能是一个包含50页的Word、Excel和PDF文档的集合,详细说明了一系列物理财产的建设、使用和地理信息。重建一个对象(财产)意味着需要仔细梳理这些文件,以建立数据之间的语义、概念、空间,甚至是隐含的联系。
结果是:关系信息可能会丢失、留空或被虚构。
其次,重复调用搜索、检索和更新信息有时会导致级联错误。这在处理复杂任务时变得更加频繁,比如阅读文档、获取之前的用户信息、进行计算、存储结果,然后再呈现给用户。
我们意识到,为了让AI提供更有用和准确的响应,正确使用文档中的关系,这些关系需要被明确化。许多上下文信息是以非语言的方式表示的。这意味着我们无法直接以编程方式与它们互动,LLMs被迫每次都自行解释。这就是我们开始构建Praxos的原因。
我们为爱好者和早期采用者设置了一个自助选项,提供免费层(有数据上限)。作为参考,这应该能覆盖您最多200页文档。您可以在这里注册:<a href="https://data.praxos.ai/sign-up">https://data.praxos.ai/sign-up</a>。
我们的第一个版本是一个SDK,旨在满足您所有的数据提取、检索和更新需求。
以下是它的工作原理:
组织信息:Praxos将信息分类为本体,这是一种用于存储数据的结构化模式。这些本体允许您引入预定义的类型、属性和关系,指导知识图谱的构建和解释。
处理输入数据:Praxos可以处理任何数据源,从PDF到表格数据、JSON和对话式交换。提取过程是端到端的。您无需进行OCR、分块或预处理输入。处理过程简单到只需传入您的文件并选择一个本体。
检索信息/记忆:对于每个查询,Praxos通过结合图遍历技术、向量相似性和键值查找来搜索和检索相关的存储信息。搜索对象将返回实体及其连接,以及一句话的描述。
我们非常希望听到您的想法!请随时参与讨论,并通过Discord与我们分享任何想法或建议(链接:<a href="https://discord.gg/wVmrXD2dJA" rel="nofollow">https://discord.gg/wVmrXD2dJA</a>)。
您的反馈将帮助我们决定Praxos的未来发展方向!
查看原文
Hey HN! We're Lucas and Soheil, the founders of Praxos (<a href="https://praxos.ai">https://praxos.ai</a>). Praxos is a context manager for AI Agents, providing everything you need to build stateful agents that don't break in production.<p>Praxos can parse any data source, from unstructured PDFs and API streams to conversational messages, to structured databases, and transform them into a single Knowledge Graph. Everything in this graph is semantically typed and its relationships are made explicit, turning data into a clean, queryable universe of understanding that AI can use without making mistakes.<p>Whether you need to query for the answer to a question or to extract data in a way that makes sense for the current use case, Praxos does it all, with no requerying needed. This enables AI apps to parse data end-to-end, and then act on it to deliver outputs across single-chain and multi-chain reasoning steps. Intermediate, final, and user-edited outputs can be added back to the knowledge graph, allowing Praxos to learn on the fly.<p>When we were building in insurance, we often ran into two major problems deploying AI:<p>First, LLMs would prove incapable of parsing documents such as property schedules and insurance policies. For reference, a property schedule may be a 50-page collection of Word, Excel, and PDF documents detailing construction, usage, and geographical information about a collection of physical properties. Recreating one object (a property) would mean combing through the files establish semantic, conceptual, spatial, and sometimes implicit linkages between the data.<p>The outcome: relationship information would be lost, left blank, or hallucinated.<p>Second, repeated calls to search, retrieve, and update information would sometimes lead to cascading errors. This became more frequent across complex tasks such as reading a document, fetching previous user information, performing a calculation, storing it, and then presenting it to the user.<p>We realized that for AI to deliver more useful and accurate responses that correctly use relationships in the document, these relationships need to be made explicit. Much of the contextual information is represented without the usage of words. In turn, this means that we cannot directly interact with them programmatically, and LLMs are forced to interpret them themselves, every single time. That’s when we started building Praxos.<p>We've set up a self-serve option with a free tier (up to a data cap) for hobbyists and early-adopters. For context (no pun intended), this should cover you for up to 200 document pages. You can register here: <a href="https://data.praxos.ai/sign-up">https://data.praxos.ai/sign-up</a>.<p>Our first version is an SDK meant to cover you across all your data extraction, retrieval, and update needs.<p>Here's how it works:<p>Organizing information: Praxos sorts information into ontologies, which are structured schemas for storing data. These allow you to introduce predefined types, attributes, and relationships that guide how the knowledge graph is built and interpreted.<p>Processing input data: Praxos can handle any data source, ranging from PDFs to tabular data, JSONs, and dialog-like exchanges. Extraction is performed end-to-end. You don't need to OCR, chunk, or pre-process your inputs. Processing is as simple as passing in your file and selecting an ontology.<p>Retrieving information / memories: For each query, Praxos searches and retrieves related stored information by leveraging a combination of graph traversal techniques, vector similarity and key-value lookups. Search objects will return both the entities/their connections, as well as a sentence.<p>We’d love to hear what you think! Please feel free to dive in, and share any thoughts or suggestions with us over Discord (<a href="https://discord.gg/wVmrXD2dJA" rel="nofollow">https://discord.gg/wVmrXD2dJA</a>).<p>Your feedback will help shape where we take Praxos from here!