Blog Posts

Langchain 与 Pydanticai:哪个框架*能真正*驾驭 Ai 代理开发?
构建对话式AI代理的框架比较 在这里,我比较了这两个流行框架如何用于构建一个简单的对话式AI Agent,涉及以下功能:动态模型选择 人工干预输入 带依赖的工具调用 对话历史/记忆 动态系统提示 结构化输出Agent Behaviour 目标是构建一个 AI Agent,它将在餐厅中扮演一个古怪的服务员,询问您的饮食要求并接受您的订单。一个示例
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Llm Evaluation Exposed: the Ultimate Guide to Unlocking Superior Ai Output!
引言 大型语言模型 (LLMs) 正在重塑我们与技术的互动方式。从虚拟助手到文本摘要工具,它们的应用范围广泛。但我们如何确保这些模型产生的输出准确、有意义且与上下文相关呢?评估LLMs不仅仅是检查它们是否“看起来正确”。这关系到确保它们的响应在多个维度上与任务要求相一致。 在本博客中,我们将带您了解一个实用的LLMs评估框架,探索我们将使用的工具和指标,并演示使用谷歌的Flan-T5模
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O3-mini Vs Deepseek R1:Openai的新编码模式碾压竞争对手?
o3-mini 在 ChatGPT 中免费提供给 Plus 和 Pro 订阅用户 昨天,OpenAI 发布了 o3-mini 和 o3-mini-high,现在可以在 ChatGPT 和 API 中使用。 o3-mini 在高级推理方面表现快速,而 o3-mini-high 在编码和逻辑方面表现出色。 这里有个惊人的部分:o3-mini-high 在 [LiveBench](http
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Qwen 2.5 Max 与 Deepseek V3:这一开源 Ai 模型如何实现前所未有的性能?
- Rifx.Online
- Large Language Models , Generative AI , AI Research
- 05 Mar, 2025
AI领域正在迅速发展,新发布的Qwen 2.5 Max和Qwen 2.5 VL模型作为强大的开源替代品,正在引起轰动,与顶级闭源解决方案如GPT-4o和Gemini相抗衡。我们将看到所有新发布的模型,如Qwen 2.5 VL系列和百万令牌上下文模型。在这次深入探讨中,我们将探索这些模型如何在性能、多样性和可访问性方面突破界限——同时又是免费的。 Qwe
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Qwen2.5-max Vs.Deepseek V3 和 Gpt-4o:阿里巴巴是否重新定义了 Llm 格局?
- Rifx.Online
- Large Language Models , Generative AI , AI Research
- 05 Mar, 2025
介绍 人工智能领域正在迅速发展,几乎每天都有新的进展。如果你一直在关注混合专家 (MoE) 模型的增长,你可能听说过DeepSeek V3。这个模型因其高效性和大规模而声名显赫。然而,一个新模型已经进入市场,提供更强大的性能:Qwen2.5-Max,阿里巴巴最新发布的产品。 大语言模型 (LLMs) 已经改变了人工智能,使得从聊天机器人到复杂推理系统的各种应
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DeepSeek 对 LLM 推理的创新方法 DeepSeek 通过强化学习 (RL) 提出了提高大型语言模型 (LLMs) 推理能力的创新方法,详细内容见他们最近关于 DeepSeek-R1 的论文。这项研究代表了我们通过纯强化学习增强 LLM 解决复杂问题能力的重大进展,而不需要过多依赖监督微调。 DeepSeek-R1 的技术概述 模型架构: Dee
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Agentic Ai Revolution:构建为你工作的自主系统!
- Rifx.Online
- Generative AI , Large Language Models , AI Applications
- 05 Mar, 2025
介绍 生成式人工智能的兴起是数字时代的新平台转变。它解决了从大型企业的自动化到各种类型的研发和创造力的问题。预计到2024年,全球市场将超过650亿美元,86%的IT领导者预见到大型组织变革[1]。到目前为止,最大的回报来自于聊天机器人(更通用和丰富的用例)、代码助手和企业搜索。 投资持续流入人工智能,2024年投资达到138亿美元(比2023年增长六倍)[1]。此外,企业
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对比分析:ai Agents与agentic Ai的关键区别及其重要性解析
- Rifx.Online
- AI Applications , Technology Trends , Industry Insights
- 05 Mar, 2025
如果你最近一直关注人工智能 (AI),你可能听过“人工智能代理”和“自主人工智能”这两个术语。虽然它们听起来像是华丽的科技术语,但实际上它们指的是两种不同类型的人工智能,这两者都对我们的世界产生了重大影响。那么它们究竟是什么,它们之间有什么不同?更重要的是,我们为什么要关心? 让我们用简单的术语来解析,探讨人工智能代理和自主人工智能的区别、实际应用和未来。 什么是人工智能代理和自主
阅读更多Ai-powered Bi Revolution:使用 Crewai 和 Openai 自动生成商业报告!
- Rifx.Online
- Generative AI , Large Language Models , AI Applications
- 05 Mar, 2025
如何直接从 CSV 数据创建简单的 BI 报告 作者通过 ChatGPT 绘制的图像 商业信息应用程序帮助企业将数据作为资源用于做出关键决策,我们将利用 AI 构建一个。 AI 在 BI 工具中的作用必将日益增加;更具体地说,基于 LLM 的应用程序将允许 BI 应用程序创建可视化,提供数据分析的洞察,并自动化商业报告。 因此,在本文中,我们将探讨 LLM 应用程序如何帮助
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AI新时代来临!rStar、SimRAG、mR2AG三大创新技术让你惊叹不已!
本文是这个引人入胜的系列中的第24篇。 今天,我们将探讨人工智能中的三个引人入胜的话题,分别是:rStar:两个思维,一个解决方案 SimRAG:一个通过生成和回答自己问题来自我提升的学生 mR2AG:基于知识的视觉问答智能导航系统
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完整指南:如何将api转变为ai代理,简化集成流程与开发体验!
API as an AI Agent _Ever found yourself drowning in API documentation, wrestling with schemas, and wondering if there’s a better way? Well, grab your cuppa, because we’re about to explore a rathe
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掌握 Llm 代理:构建多功能通用代理的分步指南
LLM代理的高级概述。 (作者提供的图片) 为什么要构建一个通用代理? 因为它是原型设计用例的优秀工具,并为设计您自己的自定义代理架构奠定基础。 在我们深入之前,让我们快速介绍一下LLM代理。 随意跳过。 什么是LLM代理?LLM代理是一个程序,其执行逻辑由其底层模型控制。
构建智能系统:使用openai Lancedb和phidata实现高效的agentic Rag解决方案
为企业文档检索构建智能系统 构建智能系统,在响应特定客户提示和请求之前,查找企业文档(文本、PDF、文档)中的相关信息。 将人工智能集成到企业应用程序中,通常面临从 大型语言模型 获取准确和高效结果的挑战。主要原因是大型语言模型是在大型数据集上训练的,而不是专门针对您的企业数据。这
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构建新闻代理的实用指南:使用ollama Langchain Chromadb和huggingface Embeddings实现高效问答系统
对话式人工智能:使用 LangChain、ChromaDB 和 Hugging Face 构建检索系统 对话式人工智能是现代人工智能技术中最引人入胜的应用之一,它将大型语言模型(LLMs)与高效的向量存储结合在一起。 在本博客中,我们将引导您设置一个管道,该管道结合了 LangChain、ChromaDB 和 Hugging Face 嵌入,以构建一个使用网页抓取文档进行检索和回答问题
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释放 Langflow 的力量:使用 Rag 构建多工具代理
在 上一篇文章 中,我们探讨了在 Langflow 中创建代理的基础知识,这些是设计动态的、由 AI 驱动的工作流的基础工具。现在,让我们更进一步! 这次,我们将构建一个由多个工具驱动的 [Langflow](ht
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- Documentai
- Idp
- Crawler
- Cloudflare
- Expertise
- Supervised
- Cross entropy
- Dropout
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- Colab
- Llama 3
- Modal
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- Crossencoder
- Re ranking
- Transfer
- Soft labels
- Documents
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- Feedback
- Drugbot
- Drugdb
- Voicebot
- Ontology
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- Json ld
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- Texttospeech
- Imageprocessing
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- Subtasks
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- Squad
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- Edgecases
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- Entities
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- Social
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- Disengagement
- Human
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- Makecom
- Text to speech
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- Graph rag
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- Notebook
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- Structure
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- Bot
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- Multi actor
- Duckdb
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- Pretraining
- Sqlite
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- Text extraction
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- Screenwriters
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- Non determinism
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- Startups
- R1
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- Beautifulsoup
- Captchas
- Newsletters
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- Aggregators
- Schedules
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- Wireframes
- Stackblitz
- Nativescript
- Blogging
- Interactive
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- Swift
- Configuration
- Lechat
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- Evaluations
- Querygpt
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- Neuronwriter
- Codeagent
- Lm
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- Langsmith
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- Languageunderstanding
- Variants
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- Phi 4
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- Genomics
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- Dynamic
- Reporting
- Erd
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- Phoenix
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- Entity
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- Incremental
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- Storyboard
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- Publishers
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- Logfire
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- 32b
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- Openvino
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- Ble
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- Heuristics
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- Deep learning
- Data science
- Statistics
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- Role playing
- Drag and drop
- Ngrok
- Endpoint
- Raspberrypi
- Arm64
- Bindings
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- Interface
- Documentloader
- Extractor
- Contracts
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- Sky t1 32b
- O1 pro
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- Data extraction
- Cloud based
- E commerce
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- Selectionfunction
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- Homebrew
- Reference
- Local
- Pinn
- Neural
- Preprocessing