LangChain Programming Tutorials & Engineering Articles

The article discusses the importance of evaluations (evals) for AI agents, emphasizing how they help teams identify and resolve issues before they reach production.

The article discusses the advancements in AI agents with the introduction of Gemini 3 Pro Preview, highlighting its capabilities for building sophisticated agents using open-source frameworks.

The article discusses the launch of NVIDIA's new Nemotron models designed for developing specialized AI agents that integrate language and vision capabilities.

The article provides a comprehensive guide on building a Retrieval-Augmented Generation (RAG) agent using NVIDIA Nemotron, emphasizing the integration of external information to enhance text genera...

EmbeddingGemma is an innovative open embedding model designed for on-device AI applications, featuring 308 million parameters for efficient performance.

This article explores the rise of Forward Deployed Engineering (FDE) as a strategic role in B2B tech companies, tracing its origins from Palantir to its current adoption across companies like OpenA...

The article discusses the evolution of AI agents from relying on static training data to utilizing dynamic knowledge through Retrieval-Augmented Generation (RAG) and AI query engines.

The article discusses Finch, Uber's conversational AI data agent designed to streamline financial data retrieval within the Slack environment.

The article discusses the importance of LLM observability using ClickStack, OpenTelemetry, and MCP, highlighting how to instrument LibreChat for enhanced insights into AI-driven applications.

The article discusses the AI-Q NVIDIA Blueprint, an open-source framework designed to help enterprises leverage their data through AI-powered agents.

The article discusses the integration of ClickHouse with the Model Context Protocol (MCP), highlighting its benefits for connecting third-party services to large language models (LLMs).

The article discusses the integration of AI workflows in automating trade capture and evaluation processes, emphasizing the challenges of achieving high reliability with free-form text inputs.

The article discusses optimizing Vanna's text-to-SQL inference using NVIDIA NIM to enhance analytics performance.

The article discusses the Enhanced Agentic-RAG (EAg-RAG) framework developed by Uber to improve the accuracy and relevance of chatbot responses in the engineering security and privacy domain.

The article discusses how to build AI agents using Google Gemini models in conjunction with various open-source frameworks.

The article discusses the integration of NVIDIA NIM microservices into Azure AI Foundry, highlighting how this collaboration enhances enterprise AI development by enabling efficient deployment of A...

The article discusses the NVIDIA NeMo Agent toolkit, an open-source library designed for building and optimizing AI agent workflows.

The article discusses the benchmarking of agentic large language models (LLMs) and vision-language models (VLMs) using NVIDIA NIM and the BALROG benchmark suite.

The article discusses the development of an AI-powered tool for automatic citation validation using NVIDIA NIM, aimed at improving the accuracy of citations in academic and AI-generated content.

The article introduces the Agent2Agent (A2A) protocol, a new open standard aimed at enhancing interoperability among AI agents across various enterprise platforms.

The article introduces the Agent Development Kit (ADK), an open-source framework by Google designed to facilitate the development of multi-agent applications.

The article discusses the launch of NVIDIA NIM microservices designed to enhance AI development on NVIDIA RTX AI PCs and workstations.

The article discusses the introduction of Gemma 3, a range of lightweight, multimodal, and multilingual models optimized for performance in AI applications.

This article discusses the creation of a multimodal information retrieval system using NVIDIA NIM and LangGraph, focusing on the deployment of vision language models (VLMs) to process diverse data ...

The article discusses how LinkedIn utilized Jupyter Notebooks to create collaborative prompt engineering playgrounds, enhancing the development of AI-powered features like AccountIQ.

The article discusses the development of effective agents using large language models (LLMs), emphasizing the importance of simplicity and composability in their design.

The article discusses the automation of early security patching in continuous integration (CI) pipelines on AWS using NVIDIA AI Blueprints.

The article introduces the Prompt Engineering Toolkit developed by Uber, which aims to streamline the process of creating and managing prompts for Large Language Models (LLMs).

The article discusses how Tata Consultancy Services (TCS) has doubled the speed of automotive software testing by leveraging NVIDIA's Generative AI technologies.

This article provides a comprehensive guide on building a human-in-the-loop AI agent using NVIDIA NIM microservices.

This article provides a comprehensive guide on creating a custom Slackbot LLM agent using NVIDIA NIM and LangChain.

The article discusses how to integrate payments into workflows utilizing Large Language Models (LLMs) and function calling, specifically through the Stripe agent toolkit.

The Web AI Summit 2024, hosted by Google on October 18, 2024, focused on client-side AI for developers, showcasing how machine learning models can operate offline in web browsers.

The article discusses advanced Retrieval-Augmented Generation (RAG) techniques applied to telecommunications standards, specifically O-RAN, using NVIDIA NIM microservices.

The article discusses the integration of retrieval-augmented generation (RAG) in medical applications, emphasizing its potential to enhance patient care and research by combining large language mod...

The article discusses how NVIDIA optimizes data center performance using AI agents and the OODA loop strategy.

The article discusses how xpander AI enhances NVIDIA NIM applications by providing agentic tools that facilitate real-time data fetching and interaction with external systems.

The article discusses how to build AI agents using NVIDIA NIM microservices in conjunction with LangChain, focusing on the capabilities of the Llama 3. 1 model.

The article discusses the integration of NVIDIA NIM and NVIDIA NeMo Guardrails to enhance the security and compliance of generative AI applications powered by large language models (LLMs).

The article discusses the significance of re-ranking in enhancing retrieval-augmented generation (RAG) pipelines and semantic search results.

The article discusses the launch of Meta's Llama 3.

The article discusses the implementation of a retrieval-augmented generation (RAG) pipeline using Llama 3. 1 and NVIDIA NeMo Retriever NIMs.

The article discusses the Llama 3. 1 collection of large language models (LLMs) and their applications in enterprise settings.

The article discusses how Infosys leverages NVIDIA NIM and NeMo Retriever to enhance network operations centers (NOCs) for telecom companies.

The article discusses how Infosys has automated the generation of TOSCA templates for telecom network design using NVIDIA NIM and NVIDIA NeMo.

The article discusses how hybrid retrieval-augmented generation (RAG) can optimize AI model performance while maintaining data privacy.

The article discusses Uber's GenAI Gateway, a unified platform designed to streamline the integration of Large Language Models (LLMs) across various teams within the company.

The article discusses the integration of generative AI with a focus on privacy and confidentiality, highlighting Google's GenC open-source project and its application in mobile and cloud environmen...

The article discusses the deployment of multilingual large language models (LLMs) using NVIDIA NIM, highlighting the importance of effective communication across languages in a globalized business ...

The article discusses how NVIDIA NIM can transform financial analysis by enabling faster and more accurate insights extraction from earnings call transcripts.