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AI Workflow

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Nightwalker Tech
Nightwalker Tech
Apr 17, 2025 · Artificial Intelligence

LangGraph Explained: Advanced AI Workflow Framework and Hands‑On Guide

This article introduces LangGraph, the next‑generation framework built on LangChain for constructing complex, stateful AI applications, compares it with LangChain, showcases real‑world deployments, and provides a step‑by‑step Python tutorial for building a smart customer‑service chatbot with looped reasoning, tool integration, and human‑in‑the‑loop support.

AI WorkflowAgentChatbot
0 likes · 20 min read
LangGraph Explained: Advanced AI Workflow Framework and Hands‑On Guide
DataFunTalk
DataFunTalk
Mar 27, 2025 · Artificial Intelligence

OpenAI Adds MCP Support to Agents SDK, Advancing Standardized AI Workflows

OpenAI has updated its Agents SDK to support Anthropic's Model Context Protocol (MCP), enabling developers to connect AI agents with diverse data sources and tools through a standardized interface, while providing official documentation, example code, caching, and tracing features to streamline AI workflow integration.

AI WorkflowAgents SDKMCP
0 likes · 8 min read
OpenAI Adds MCP Support to Agents SDK, Advancing Standardized AI Workflows
Code Mala Tang
Code Mala Tang
Feb 25, 2025 · Artificial Intelligence

How Resources, Tools, and Prompts Power LLM Super‑Agents

This article explains how the Resources data hub, Tools capability engine, and Prompts interaction templates work together to create a secure, extensible workflow that enables large language models to ingest data, execute tasks, and generate structured outputs.

AI WorkflowArtificial IntelligenceData Resources
0 likes · 5 min read
How Resources, Tools, and Prompts Power LLM Super‑Agents
Code Mala Tang
Code Mala Tang
Sep 12, 2024 · Artificial Intelligence

Unlocking LangChain.js: The Swiss Army Knife for LLM Applications

This article introduces LangChain.js, explains its origins, core concepts such as chats, templates, tools, and chains, demonstrates practical JavaScript code examples, and explores the LangChain Execution Language (LCEL) for building flexible, conditional AI workflows.

AI WorkflowJavaScriptLCEL
0 likes · 17 min read
Unlocking LangChain.js: The Swiss Army Knife for LLM Applications
Code Mala Tang
Code Mala Tang
Sep 7, 2024 · Artificial Intelligence

Unlocking LangChain.js: The Swiss Army Knife for LLM Applications

This article introduces LangChain.js, its core concepts such as chats, templates, tools, and chains, demonstrates how to use LCEL for flexible workflow composition, and shows practical JavaScript code examples for building AI-powered applications with large language models.

AI WorkflowJavaScriptLCEL
0 likes · 17 min read
Unlocking LangChain.js: The Swiss Army Knife for LLM Applications
DataFunTalk
DataFunTalk
Nov 19, 2021 · Artificial Intelligence

Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing

This article examines industrial intelligence from the perspectives of flow and fusion, detailing its current state, talent needs, pain points, AI development processes, edge‑cloud architecture, and key characteristics such as timeliness, reliability, explainability, and applicability in manufacturing.

AI WorkflowTalentdata science
0 likes · 22 min read
Industrial Intelligence: Current Status, Talent, Challenges, and AI Application in Manufacturing
AntTech
AntTech
Jul 10, 2020 · Artificial Intelligence

SQLFlow: End‑to‑End AI Workflow Construction Using SQL

SQLFlow is an open‑source system that lets users describe and execute end‑to‑end AI tasks—including data extraction, preprocessing, model training, evaluation, prediction, and explanation—entirely with SQL, simplifying workflow construction across multiple databases and machine‑learning engines while supporting scalable execution on Kubernetes.

AI WorkflowKubernetesModel Zoo
0 likes · 19 min read
SQLFlow: End‑to‑End AI Workflow Construction Using SQL
JD Tech Talk
JD Tech Talk
Feb 13, 2020 · Artificial Intelligence

Full-Process Traceability Management for Machine Learning Models: Challenges, Methods, and Solutions

This article analyzes the challenges of managing the entire machine‑learning lifecycle, reviews existing traceability approaches, and proposes comprehensive methods for versioned management of model training, prediction, and online service to improve efficiency, reproducibility, and maintenance of AI systems.

AI WorkflowModel DeploymentModel Management
0 likes · 18 min read
Full-Process Traceability Management for Machine Learning Models: Challenges, Methods, and Solutions