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Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 28, 2024 · Artificial Intelligence

Step-by-Step Guide to Registering Volcengine API, Configuring .cloudiderc, and Running LangChain Quickstart

This tutorial provides detailed instructions for registering the Volcengine API, locating and editing the .cloudiderc file, setting environment variables, installing the Volcengine Python SDK, and troubleshooting common issues when running the LangChain quick‑start examples on a cloud IDE.

AIAPILangChain
0 likes · 6 min read
Step-by-Step Guide to Registering Volcengine API, Configuring .cloudiderc, and Running LangChain Quickstart
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 20, 2024 · Artificial Intelligence

Resolving 02_DocQA.py Errors and Using LangChain to Call Large Models Locally

This guide explains how to fix the ArkNotFoundError in the 02_DocQA.py script by configuring a Doubao‑embedding endpoint, setting up a Conda environment with the latest LangChain packages, and provides step‑by‑step code examples for invoking both Zhipu glm‑4 and Volcano large language models via LangChain.

EmbeddingEnvironment setupLangChain
0 likes · 9 min read
Resolving 02_DocQA.py Errors and Using LangChain to Call Large Models Locally
System Architect Go
System Architect Go
Nov 19, 2024 · Artificial Intelligence

Retrieval Augmented Generation (RAG) System Overview and Implementation with LangChain, Redis, and llama.cpp

This article explains the concept, architecture, and step‑by‑step implementation of Retrieval Augmented Generation (RAG), covering indexing, retrieval & generation processes, a practical LangChain‑Redis‑llama.cpp example on Kubernetes, code snippets, test results, challenges, and references.

AIEmbeddingLLM
0 likes · 6 min read
Retrieval Augmented Generation (RAG) System Overview and Implementation with LangChain, Redis, and llama.cpp
37 Interactive Technology Team
37 Interactive Technology Team
Nov 4, 2024 · Artificial Intelligence

Developing RAG and Agent Applications with LangChain: A Case Study of an AI Assistant for Activity Components

The article outlines a step‑by‑step methodology for creating Retrieval‑Augmented Generation and custom Agent applications with LangChain, illustrated by an AI assistant for activity components that evolves from a rapid Dify prototype to a LangChain‑based RAG system and finally a hand‑crafted ReAct‑style agent, detailing LCEL chain composition, vector‑search integration, model performance trade‑offs, and a unified routing layer.

AI AssistantAgentCloud-native
0 likes · 6 min read
Developing RAG and Agent Applications with LangChain: A Case Study of an AI Assistant for Activity Components
AI Large Model Application Practice
AI Large Model Application Practice
Oct 30, 2024 · Artificial Intelligence

How to Efficiently Incrementally Update Knowledge in RAG Applications

Incremental knowledge updates in Retrieval‑Augmented Generation (RAG) systems can be achieved by using document‑level or chunk‑level strategies, leveraging hash fingerprints, record managers, and framework‑specific APIs such as LangChain’s index() with cleanup modes or LlamaIndex’s ingestion pipeline, reducing redundant computation and cost.

LangChainLlamaIndexRAG
0 likes · 12 min read
How to Efficiently Incrementally Update Knowledge in RAG Applications
JavaEdge
JavaEdge
Oct 15, 2024 · Artificial Intelligence

Build a Real‑Time Search & Bazi AI Agent with LangChain & FastAPI

This tutorial walks through creating a LangChain tool‑calling agent that combines a real‑time web search tool, a Qdrant vector store for local knowledge retrieval, and a custom Bazi fortune‑telling service, all wrapped in a FastAPI application for interactive use.

AI AgentFastAPILangChain
0 likes · 15 min read
Build a Real‑Time Search & Bazi AI Agent with LangChain & FastAPI
JD Cloud Developers
JD Cloud Developers
Sep 29, 2024 · Artificial Intelligence

Build a Local AI Q&A System with Java, Ollama, and LangChain4J

This article walks through building a local AI question‑answer system using Java, Ollama, LangChain4J, embeddings, and a Chroma vector database, covering LLM fundamentals, embedding techniques, RAG architecture, setup steps, Maven dependencies, and sample code to retrieve and answer queries.

AIEmbeddingJava
0 likes · 19 min read
Build a Local AI Q&A System with Java, Ollama, and LangChain4J
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 workflowLCELLLM
0 likes · 17 min read
Unlocking LangChain.js: The Swiss Army Knife for LLM Applications
Code Mala Tang
Code Mala Tang
Sep 12, 2024 · Artificial Intelligence

Boost LLM Accuracy with Retrieval‑Augmented Generation Using LangChain.js

This article explains the core concepts of Retrieval‑Augmented Generation (RAG), walks through its implementation steps with LangChain.js—including text chunking, embedding, storage, retrieval, and generation—and showcases practical use cases, challenges, and best practices for building reliable AI‑powered applications.

AI applicationsEmbeddingLLM
0 likes · 16 min read
Boost LLM Accuracy with Retrieval‑Augmented Generation Using LangChain.js
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 workflowLCELLLM
0 likes · 17 min read
Unlocking LangChain.js: The Swiss Army Knife for LLM Applications
iKang Technology Team
iKang Technology Team
Sep 5, 2024 · Artificial Intelligence

What Is LangChain? Overview, Core Advantages, Components, and Use Cases

LangChain is a modular framework that streamlines integration of large language models by providing unified model interfaces, prompt optimization, memory handling, indexing, chains, and agents, enabling developers to quickly build and deploy sophisticated NLP applications such as text generation, information extraction, and dynamic tool‑driven workflows across various industries.

AI FrameworkChainsLLM
0 likes · 6 min read
What Is LangChain? Overview, Core Advantages, Components, and Use Cases
DaTaobao Tech
DaTaobao Tech
Aug 30, 2024 · Artificial Intelligence

Overview of Large Model Application Development Platforms: LangChain, Dify, Flowise, and Coze

The article reviews open‑source and commercial large‑model development platforms—LangChain, Dify, Flowise, and Coze—detailing their architectures, low‑code visual tools, model integrations, extensibility, and a step‑by‑step Dify example, and concludes they are essential infrastructure for rapid AI application deployment.

AI application developmentDifyFlowise
0 likes · 13 min read
Overview of Large Model Application Development Platforms: LangChain, Dify, Flowise, and Coze
Baobao Algorithm Notes
Baobao Algorithm Notes
Aug 27, 2024 · Artificial Intelligence

Unlock Free GLM-4-Flash API: Step-by-Step Guide, Code Samples, and Logic Puzzle Test

This article explores the free GLM-4-Flash API from Zhipu AI, detailing its lightweight architecture, performance specs, a logic‑puzzle demonstration, and provides a comprehensive step‑by‑step tutorial—including data upload, model fine‑tuning, deployment commands and example code for building a LangChain‑based knowledge‑base retrieval system.

AI deploymentFine-tuningFree API
0 likes · 11 min read
Unlock Free GLM-4-Flash API: Step-by-Step Guide, Code Samples, and Logic Puzzle Test
Python Programming Learning Circle
Python Programming Learning Circle
Aug 23, 2024 · Artificial Intelligence

Getting Started with Python Generative AI: Six Practical Projects Using Llama 2, LangChain, Streamlit, Gradio, FastAPI and SQL

This article presents six hands‑on Python generative‑AI projects—ranging from a Llama 2 chatbot built with Streamlit and Replicate to natural‑language‑to‑SQL conversion using LlamaIndex and SQLAlchemy—complete with environment setup, required code snippets, deployment tips and resource links for further exploration.

FastAPIGradioLangChain
0 likes · 20 min read
Getting Started with Python Generative AI: Six Practical Projects Using Llama 2, LangChain, Streamlit, Gradio, FastAPI and SQL
AI Large Model Application Practice
AI Large Model Application Practice
Aug 16, 2024 · Artificial Intelligence

How to Query a Microsoft GraphRAG Knowledge Graph with Neo4j: Local and Global Modes

This guide explains how to query a Microsoft GraphRAG knowledge graph using the official CLI, API, and a custom Neo4j implementation, covering both local and global retrieval modes, vector index creation, Cypher query customization, and integration with LangChain for end‑to‑end RAG pipelines.

LangChainMicrosoft GraphRAGNeo4j
0 likes · 13 min read
How to Query a Microsoft GraphRAG Knowledge Graph with Neo4j: Local and Global Modes
37 Interactive Technology Team
37 Interactive Technology Team
Aug 12, 2024 · Backend Development

Intelligent Backend Menu Search with OpenAI Embeddings, LangChain, and DIFY

The article demonstrates how to improve backend menu navigation by building a knowledge base of menu metadata, generating concise Chinese descriptions with OpenAI embeddings, and implementing RAG retrieval using both LangChain code orchestration and DIFY’s visual workflow, highlighting each approach’s flexibility and ease of use.

Backend SearchKnowledge BaseLangChain
0 likes · 9 min read
Intelligent Backend Menu Search with OpenAI Embeddings, LangChain, and DIFY
JavaEdge
JavaEdge
Aug 9, 2024 · Artificial Intelligence

Build a Graph‑Based LLM Agent with LangGraph: Step‑by‑Step Tutorial

This article introduces LangGraph, a Python library for creating stateful, multi‑agent LLM workflows, explains its loop, persistence, and human‑in‑the‑loop features, shows how to install it, and provides a complete code example that builds, runs, and reuses a searchable AI agent with thread‑level state saving.

AILLMLangChain
0 likes · 10 min read
Build a Graph‑Based LLM Agent with LangGraph: Step‑by‑Step Tutorial
Model Perspective
Model Perspective
Jul 23, 2024 · Artificial Intelligence

Building Your Own AI Agent with LangChain: A Hands‑On Guide

This article walks through the author’s experience creating a custom AI agent using LangChain and OpenAI APIs, explains the concepts of AI agents and the ReAct reasoning framework, provides step‑by‑step code, discusses required libraries and APIs, and shares practical tips and challenges encountered.

AI AgentLLMLangChain
0 likes · 16 min read
Building Your Own AI Agent with LangChain: A Hands‑On Guide
JavaEdge
JavaEdge
Jun 28, 2024 · Artificial Intelligence

Designing Agent Personality and Emotion Handling with LangChain Prompt Templates

This article explains how to craft system prompts that give an AI agent a distinct personality and emotional behavior, shows how to implement an emotion‑detection chain, compares ChatPromptTemplate.from_messages with from_template, and integrates the agent into a FastAPI service with full code examples.

AI AgentEmotion DetectionFastAPI
0 likes · 13 min read
Designing Agent Personality and Emotion Handling with LangChain Prompt Templates
JavaEdge
JavaEdge
Jun 27, 2024 · Backend Development

Build a FastAPI Chatbot with LangChain and WebSocket – Step‑by‑Step Guide

This tutorial walks through installing FastAPI and related packages, creating a basic FastAPI app, adding chat, PDF, and text endpoints, integrating LangChain tools for AI responses, implementing a WebSocket echo service, and running the server with uvicorn, all illustrated with code snippets and screenshots.

APIBackendFastAPI
0 likes · 8 min read
Build a FastAPI Chatbot with LangChain and WebSocket – Step‑by‑Step Guide
JavaEdge
JavaEdge
Jun 26, 2024 · Artificial Intelligence

Add Memory to LangChain Agents for Context‑Aware Multi‑Turn Conversations

This guide walks through adding ConversationBufferMemory to a LangChain agent, covering tool creation, memory setup, agent initialization with OpenAI function calling, prompt inspection, configuration tweaks using agent_kwargs, and best‑practice considerations for maintaining context in multi‑turn AI conversations.

Agent MemoryConversationBufferMemoryLangChain
0 likes · 8 min read
Add Memory to LangChain Agents for Context‑Aware Multi‑Turn Conversations
JavaEdge
JavaEdge
Jun 23, 2024 · Artificial Intelligence

Build a Cultural Name‑Generator with LangChain, Custom Prompts, and Output Parsers

This tutorial walks through installing LangChain, creating an LLM (via own GPU resources or third‑party APIs), designing parameterized prompt templates, implementing a custom output parser for structured results, and running a complete Python example that generates culturally specific names.

AILLMLangChain
0 likes · 7 min read
Build a Cultural Name‑Generator with LangChain, Custom Prompts, and Output Parsers
JavaEdge
JavaEdge
Jun 23, 2024 · Artificial Intelligence

What Is LangChain? Features, Pros, Cons, and Setup Guide

This article introduces LangChain, an open‑source framework for building LLM‑powered applications, outlines its key components such as prompts, chains, agents, and retrieval‑augmented generation, compares its advantages and drawbacks, and provides step‑by‑step instructions for setting up a Python development environment.

AIFrameworkLLM
0 likes · 7 min read
What Is LangChain? Features, Pros, Cons, and Setup Guide
Architecture and Beyond
Architecture and Beyond
Jun 23, 2024 · Artificial Intelligence

AI Programming Paradigms Unveiled: Visual ComfyUI Workflows and LangChain LLM Apps

The article examines two emerging AI programming paradigms—visual, node‑based development with ComfyUI for image generation and modular LLM application construction with LangChain—detailing their architectures, key components, workflow examples, advantages, limitations, and practical guidance for leveraging these tools to boost development efficiency in the rapidly evolving AI landscape.

AIComfyUILLM applications
0 likes · 20 min read
AI Programming Paradigms Unveiled: Visual ComfyUI Workflows and LangChain LLM Apps
JavaEdge
JavaEdge
Jun 17, 2024 · Artificial Intelligence

Build Simple LLM Agents with LangChain: A Hands‑On Tutorial

This guide explains what AI agents are, how they combine large language models with planning, memory, and tool use, and provides a step‑by‑step LangChain implementation—including environment setup, tool integration, and a runnable example that solves math and performs web searches.

LLMLangChainPython
0 likes · 6 min read
Build Simple LLM Agents with LangChain: A Hands‑On Tutorial
AI Large Model Application Practice
AI Large Model Application Practice
Jun 7, 2024 · Artificial Intelligence

Mastering Advanced Retrieval: Fusion and Recursive Strategies for RAG

This article explores two advanced retrieval paradigms—Fusion Retrieval, which merges results from multiple retrievers using re‑ranking, and Recursive Retrieval, which builds hierarchical chunk‑to‑chunk or chunk‑to‑retriever links—to boost the quality and flexibility of Retrieval‑Augmented Generation pipelines.

Fusion RetrievalLLMLangChain
0 likes · 12 min read
Mastering Advanced Retrieval: Fusion and Recursive Strategies for RAG
Bilibili Tech
Bilibili Tech
Jun 7, 2024 · Artificial Intelligence

AI Development for Frontend Developers: From Basics to Agent Implementation

This article guides frontend developers through AI development, comparing model training, fine‑tuning, prompt engineering, and Retrieval‑Augmented Generation, then explains agent creation via ReAct and tool‑call methods, and showcases Langchain and Flowise as low‑code frameworks for building domain‑specific AI agents.

AI DevelopmentAgentFlowise
0 likes · 13 min read
AI Development for Frontend Developers: From Basics to Agent Implementation
JD Tech
JD Tech
Jun 7, 2024 · Artificial Intelligence

Automated Test Case Generation Using LangChain, Vector Databases, and Large Language Models

This article presents a practical approach to automatically generate software test cases by leveraging LangChain, PDF parsing, vector‑database retrieval, and large language models, comparing it with existing tools, detailing implementation steps, code examples, experimental results, and future improvement directions.

LLMLangChainPDF parsing
0 likes · 14 min read
Automated Test Case Generation Using LangChain, Vector Databases, and Large Language Models
Sohu Tech Products
Sohu Tech Products
Jun 5, 2024 · Artificial Intelligence

Retrieval Augmented Generation (RAG): Concepts, Workflow, and LangChain Implementation

The article outlines LLM issues such as hallucination, outdated knowledge, and data privacy, then explains Retrieval‑Augmented Generation—detailing its data‑preparation and query‑time retrieval workflow, demonstrates a full LangChain implementation, and contrasts RAG with fine‑tuning as complementary strategies for up‑to‑date, grounded responses.

LLMLangChainPrompt engineering
0 likes · 15 min read
Retrieval Augmented Generation (RAG): Concepts, Workflow, and LangChain Implementation
JavaEdge
JavaEdge
Jun 5, 2024 · Artificial Intelligence

Step‑by‑Step Guide to Building a Name‑Generator with LangChain and OpenAI

This tutorial walks through installing LangChain, creating an LLM with either self‑hosted or third‑party models, designing custom prompt templates, configuring output parsers for structured results, and running a complete Python example that generates culturally specific names using OpenAI's API.

LLMLangChainOpenAI
0 likes · 8 min read
Step‑by‑Step Guide to Building a Name‑Generator with LangChain and OpenAI
Tencent Cloud Developer
Tencent Cloud Developer
Jun 5, 2024 · Artificial Intelligence

Introduction to AI Development and Practical Applications

The article surveys AI development from early GPT experiments to real‑world deployments, explaining how tools like LangChain and Retrieval‑Augmented Generation enable sophisticated agents, multi‑prompt workflows, and function calls for chatbots, education, and creative content while addressing accuracy, resource, and ethical challenges.

AI DemosAI DevelopmentAgent Frameworks
0 likes · 34 min read
Introduction to AI Development and Practical Applications
JD Retail Technology
JD Retail Technology
Jun 4, 2024 · Databases

How to Deploy and Query JD’s Open‑Source Vearch Vector Database for LLM Retrieval

This article walks through the practical use of JD’s self‑developed Vearch vector database—covering cluster creation, space setup, data insertion, and both text and vector search—illustrating how it integrates with LangChain and OpenAI embeddings to enable retrieval‑augmented generation for large language models.

EmbeddingLLM RetrievalLangChain
0 likes · 16 min read
How to Deploy and Query JD’s Open‑Source Vearch Vector Database for LLM Retrieval
Practical DevOps Architecture
Practical DevOps Architecture
May 30, 2024 · Artificial Intelligence

Eight‑Week LLM and Large Model Training Course Outline

This article outlines an eight‑week curriculum covering LLM evolution, PyTorch fundamentals, CUDA training, large‑model fine‑tuning, LangChain application development, cloud‑based quantization, industry case studies, and a recruitment session, providing video resources for each topic.

AIFine-tuningLLM
0 likes · 5 min read
Eight‑Week LLM and Large Model Training Course Outline
JD Retail Technology
JD Retail Technology
May 27, 2024 · Artificial Intelligence

Automating Test Case Generation with Large Language Models and LangChain

This article describes how large language models and the LangChain framework can be combined with PDF parsing, text chunking, memory management, and a vector database to automatically generate software test cases, achieving significant efficiency gains while outlining implementation details, results, and future challenges.

AILangChainPython
0 likes · 10 min read
Automating Test Case Generation with Large Language Models and LangChain
21CTO
21CTO
Apr 23, 2024 · Artificial Intelligence

How an AI‑Powered Interview Simulator Can Boost Your Job Prep

The AI Interview Simulator is a web app that uses AI to analyze users’ spoken answers via camera and microphone, offering real‑time, constructive feedback, and is built with Angular, Tailwind, HonoJS, LangChainJS, and Cloudflare services for hosting, edge computing, and data storage.

AIAngularCloudflare
0 likes · 4 min read
How an AI‑Powered Interview Simulator Can Boost Your Job Prep
JD Tech
JD Tech
Apr 18, 2024 · Artificial Intelligence

Getting Started with LangChain: Overview, Core Components, and Python Code Samples

This article introduces the LangChain framework for large language model integration, explains its key components and advantages, and provides step‑by‑step Python examples for setting up environment variables, creating prompts, chaining models, and using embeddings, completions, and chat models.

ChatModelEmbeddingLLM
0 likes · 7 min read
Getting Started with LangChain: Overview, Core Components, and Python Code Samples
DaTaobao Tech
DaTaobao Tech
Apr 17, 2024 · Artificial Intelligence

Challenges and Practices of LLM‑Based Knowledge Bases and Personal Assistants

The article examines how LLM‑driven knowledge‑base QA and personal‑assistant agents struggle with context management, token limits, multimodal data, and tool‑parameter parsing, reviews open‑source frameworks such as LangChain, AutoGen and MetaGPT, and argues that fine‑tuning (e.g., LoRA) is essential for domain‑specific, scalable solutions.

AgentFine-tuningKnowledge Base
0 likes · 11 min read
Challenges and Practices of LLM‑Based Knowledge Bases and Personal Assistants
21CTO
21CTO
Apr 12, 2024 · Artificial Intelligence

How I Built an AI‑Powered Resume Chatbot with LLMs and RAG

Senior developer Jon Olson shares how he created an AI resume assistant using GPT‑4/3.5, LangChain, LlamaIndex, and retrieval‑augmented generation, detailing prompt engineering, backend integration, and future routing features to help job seekers showcase their skills.

AI chatbotLLMLangChain
0 likes · 8 min read
How I Built an AI‑Powered Resume Chatbot with LLMs and RAG
HelloTech
HelloTech
Apr 10, 2024 · Artificial Intelligence

An Overview of LangChain: Architecture, Core Components, and Code Examples

LangChain is an open‑source framework that provides Python and JavaScript SDKs, templates, and services such as LangServe and LangSmith to compose models, embeddings, prompts, indexes, memory, chains, and agents via a concise expression language, enabling rapid prototyping, debugging, and deployment of LLM‑driven applications.

AI EngineeringJavaScriptLLM
0 likes · 19 min read
An Overview of LangChain: Architecture, Core Components, and Code Examples
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 10, 2024 · Artificial Intelligence

Master LangChain in 10 Minutes: From Basics to Advanced AI Engineering

This guide walks AI engineers through a rapid 10‑minute boot‑strap of LangChain, explaining its purpose, core concepts, design questions, environment setup, and step‑by‑step code examples that cover APIs, chains, memory, retrieval‑augmented generation, tools, agents, and the overall architecture.

AI EngineeringLLMLangChain
0 likes · 28 min read
Master LangChain in 10 Minutes: From Basics to Advanced AI Engineering
AI Large Model Application Practice
AI Large Model Application Practice
Mar 29, 2024 · Artificial Intelligence

How RAG Architecture Evolves: From Simple Chains to Flexible RAG Flows

This article examines the evolution of Retrieval‑Augmented Generation (RAG) architectures for large language models, outlines the challenges they face, introduces the modular RAG Flow concept with four workflow paradigms, and provides a step‑by‑step implementation using LangChain and LlamaIndex with code examples.

LLMLangChainRAG
0 likes · 15 min read
How RAG Architecture Evolves: From Simple Chains to Flexible RAG Flows
Sohu Tech Products
Sohu Tech Products
Mar 27, 2024 · Artificial Intelligence

Building a RAG Application with Baidu Vector Database and Qianfan Embedding

This tutorial walks through building a Retrieval‑Augmented Generation application by setting up Baidu’s Vector Database and Qianfan embedding service, configuring credentials, creating a document database and vector table, loading and chunking PDFs, generating embeddings, storing them, and performing scalar, vector and hybrid similarity searches, ready for integration with Wenxin LLM for answer generation.

AI applicationsBaidu QianfanEmbedding
0 likes · 11 min read
Building a RAG Application with Baidu Vector Database and Qianfan Embedding
NewBeeNLP
NewBeeNLP
Mar 18, 2024 · Artificial Intelligence

Mastering RAG and LLM Techniques: From Retrieval to Fine‑Tuning

This article provides a comprehensive technical guide on Retrieval‑Augmented Generation (RAG), open‑source large language models such as LLaMA, fine‑tuning methods, evaluation metrics, memory‑optimization tricks, and attention‑related optimizations for modern AI systems.

LLMLangChainMemory Optimization
0 likes · 19 min read
Mastering RAG and LLM Techniques: From Retrieval to Fine‑Tuning
Ops Development & AI Practice
Ops Development & AI Practice
Mar 17, 2024 · Artificial Intelligence

How LangChain Is Transforming Code Generation and Software Development

LangChain, an open‑source framework that combines large‑language‑model capabilities with code understanding, enables automatic code generation, intelligent code analysis, documentation creation, and interactive programming tutoring, offering software engineers a powerful tool to accelerate development, improve quality, and stay ahead of emerging AI‑driven programming trends.

AICode GenerationLangChain
0 likes · 4 min read
How LangChain Is Transforming Code Generation and Software Development
Ctrip Technology
Ctrip Technology
Mar 15, 2024 · Artificial Intelligence

Real‑time Debugging Boosts the Effectiveness of AI‑Generated UI Automation Scripts

This article examines how integrating real‑time debugging with large‑model AI can dramatically improve the accuracy and success rate of automatically generated UI test scripts, presenting a LangChain‑based architecture, toolchain design, experimental results, and future challenges in AI‑driven UI automation.

AILangChainReal-time Debugging
0 likes · 10 min read
Real‑time Debugging Boosts the Effectiveness of AI‑Generated UI Automation Scripts
Baidu Geek Talk
Baidu Geek Talk
Mar 13, 2024 · Artificial Intelligence

Understanding Retrieval-Augmented Generation (RAG) and Building a Personal Knowledge Base with ERNIE SDK and LangChain

The article explains Retrieval-Augmented Generation (RAG), its workflow, advantages, comparison with fine-tuning, and provides a step-by-step implementation using Baidu's ERNIE SDK, LangChain, and ChromaDB to build a personal knowledge base that answers queries with retrieved context.

AIERNIE SDKKnowledge Base
0 likes · 13 min read
Understanding Retrieval-Augmented Generation (RAG) and Building a Personal Knowledge Base with ERNIE SDK and LangChain
AI Large Model Application Practice
AI Large Model Application Practice
Mar 12, 2024 · Artificial Intelligence

How to Build a Corrective RAG Agent with LangGraph: A Step‑by‑Step Guide

This article explains how to use LangGraph—a graph‑based extension of LangChain—to implement a corrective RAG (C‑RAG) pipeline that evaluates retrieved documents, rewrites queries when needed, performs web search, and generates accurate answers, complete with code snippets and a runnable example.

Corrective RAGLLMLangChain
0 likes · 14 min read
How to Build a Corrective RAG Agent with LangGraph: A Step‑by‑Step Guide
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 6, 2024 · Artificial Intelligence

Unlocking LangChain: Build Powerful LLM Apps Like LEGO with Real-World Examples

This article explains how LangChain simplifies building and integrating large language model applications by providing modular components such as models, prompts, indexes, tools, memory, chains, and agents, illustrated with practical use cases like travel assistants, face‑recognition troubleshooting, and multi‑agent workflows.

AI agentsLLMLangChain
0 likes · 44 min read
Unlocking LangChain: Build Powerful LLM Apps Like LEGO with Real-World Examples
Alibaba Cloud Native
Alibaba Cloud Native
Feb 28, 2024 · Cloud Native

Building a Unified Cloud‑Native Serverless Platform Across Public Cloud and IDC with ACK One & Knative

This guide explains how to design and implement a unified cloud‑native serverless platform that runs seamlessly on public clouds and on‑premise IDC clusters using Alibaba Cloud ACK One, Kubernetes, and Knative, covering architecture, key components, deployment steps, and best‑practice recommendations.

ACK OneKnativeKubernetes
0 likes · 11 min read
Building a Unified Cloud‑Native Serverless Platform Across Public Cloud and IDC with ACK One & Knative
DaTaobao Tech
DaTaobao Tech
Feb 21, 2024 · Artificial Intelligence

An Overview of LangChain: Core Concepts and Practical Implementations

The article introduces LangChain as a framework that unifies LLM providers through model I/O, connects external data via retrievers, composes workflows with chains, maintains context with memory, and enables tool use through agents, and demonstrates Java examples for TongYi embeddings, a ChatGLM‑6B RetrievalQA chain, and discusses agent registration and micro‑service‑based agent factories.

EmbeddingJavaLLM
0 likes · 9 min read
An Overview of LangChain: Core Concepts and Practical Implementations
DaTaobao Tech
DaTaobao Tech
Feb 19, 2024 · Artificial Intelligence

AI/ML Technology Articles Collection

This collection compiles technical articles that explore diverse AI/ML applications, from deploying large language models on MacBooks and building e‑commerce recommendation engines, to leveraging the LangChain framework, creating AIGC‑driven fashion solutions, and implementing Stable Diffusion for image generation.

AIAIGCDeployment
0 likes · 1 min read
AI/ML Technology Articles Collection
Baidu Geek Talk
Baidu Geek Talk
Feb 7, 2024 · Artificial Intelligence

Design and Implementation of a Knowledge-Base Intelligent Q&A System for Database Operations Using Large Models

The paper details Baidu Intelligent Cloud’s design and deployment of a domain‑specific knowledge‑base Q&A system for database operations, combining prompt‑engineered LLMs with hybrid vector‑search using LangChain, BES vector store, and custom ingestion, addressing recall, token limits, and hallucination challenges across dashboard and IM bot interfaces.

AIDatabase operationsKnowledge Base
0 likes · 16 min read
Design and Implementation of a Knowledge-Base Intelligent Q&A System for Database Operations Using Large Models
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 7, 2024 · Artificial Intelligence

Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab

This tutorial walks through installing LangChain, LangGraph and related packages in Google Colab, configuring environment variables, defining search and Twitter‑writer tools, constructing a StateGraph workflow with supervisor logic, and executing a multi‑agent LLM pipeline using LangChain’s new multi‑agent capabilities.

AIGoogle ColabLLM
0 likes · 11 min read
Step-by-Step Guide to Building Multi‑Agent Applications with LangChain LangGraph in Google Colab
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 31, 2024 · Artificial Intelligence

Advanced RAG with Semi‑Structured Data Using LangChain, Unstructured, and ChromaDB

This tutorial demonstrates how to build an advanced Retrieval‑Augmented Generation (RAG) system for semi‑structured PDF data by leveraging LangChain, the unstructured library, ChromaDB vector store, and OpenAI models, covering installation, PDF partitioning, element classification, summarization, and query execution.

AIChromaDBLangChain
0 likes · 11 min read
Advanced RAG with Semi‑Structured Data Using LangChain, Unstructured, and ChromaDB
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jan 22, 2024 · Artificial Intelligence

Prompt Engineering and CAMEL: Role‑Playing AI Agents for Automated Prompt Generation

This article explains how Prompt Engineering combined with the CAMEL framework enables role‑playing AI agents to automatically generate and manage prompts, illustrates the concept with a stock‑trading example, and provides Python code using LangChain to build a marketing‑automation agent for a small business.

AI agentsCAMELInception Prompting
0 likes · 11 min read
Prompt Engineering and CAMEL: Role‑Playing AI Agents for Automated Prompt Generation
Data Thinking Notes
Data Thinking Notes
Dec 24, 2023 · Artificial Intelligence

Boost Text2SQL Accuracy with AI Agents: A LangChain Practical Guide

This article explores how AI agents, particularly those built with LangChain, can enhance Text2SQL performance by decomposing queries, leveraging tools, memory, and planning, and provides practical code examples and future directions for developers.

AI AgentLangChainPrompt engineering
0 likes · 16 min read
Boost Text2SQL Accuracy with AI Agents: A LangChain Practical Guide
37 Interactive Technology Team
37 Interactive Technology Team
Dec 18, 2023 · Frontend Development

Using LangChain to Automatically Generate Front‑End Code from Documentation

This guide shows how to use LangChain with OpenAI’s API, Puppeteer, and vector stores to automatically read local or web‑based API documentation, split and retrieve relevant text, and prompt an LLM to generate ready‑to‑use TypeScript front‑end code, highlighting setup, prompt design, and example outputs.

Front-end Code GenerationLangChainNode.js
0 likes · 15 min read
Using LangChain to Automatically Generate Front‑End Code from Documentation
Data Thinking Notes
Data Thinking Notes
Dec 12, 2023 · Artificial Intelligence

Boosting Text‑to‑SQL Accuracy with Prompt Engineering and LLMs

This article examines the challenges of LLM‑based Text‑to‑SQL such as hallucinations, data‑security risks, and user input errors, and presents prompt‑engineering strategies, fine‑tuning comparisons, prompt types, code examples, and experimental results to improve reliability and cost‑effectiveness.

LLMLangChainPrompt engineering
0 likes · 15 min read
Boosting Text‑to‑SQL Accuracy with Prompt Engineering and LLMs
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Dec 12, 2023 · Artificial Intelligence

How LangChain Powers AI Agents: Principles, Debugging, and Real‑World Optimizations

This article explains the concept of AI Agents in the large‑language‑model era, details LangChain's implementation mechanics, shares practical challenges and optimizations encountered by NetEase Cloud Music, and provides step‑by‑step code examples and performance insights for building robust AI Agents.

AI AgentDebuggingLLM
0 likes · 20 min read
How LangChain Powers AI Agents: Principles, Debugging, and Real‑World Optimizations
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 29, 2023 · Artificial Intelligence

Building a Private LLM‑Powered Knowledge Base with LangChain and ChatGLM3

This article explains how to migrate personal notes into a private knowledge base by combining a large language model with an external vector store, detailing the concepts of tokenization, embedding, vector databases, and step‑by‑step deployment using LangChain‑Chatchat and the open‑source ChatGLM3 model.

ChatGLM3EmbeddingKnowledge Base
0 likes · 10 min read
Building a Private LLM‑Powered Knowledge Base with LangChain and ChatGLM3
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Nov 24, 2023 · Artificial Intelligence

Step-by-Step Guide to Deploying LangChain‑Chatchat with ChatGLM‑2 on a Local Machine

This article provides a comprehensive tutorial on setting up the LangChain‑Chatchat open‑source project, covering environment preparation, model and embedding downloads, configuration files, database initialization, API service launch, and example curl commands for interacting with both the large language model and the local knowledge base.

APIChatGLMEmbedding
0 likes · 9 min read
Step-by-Step Guide to Deploying LangChain‑Chatchat with ChatGLM‑2 on a Local Machine
Baobao Algorithm Notes
Baobao Algorithm Notes
Nov 7, 2023 · Artificial Intelligence

A Complete Technical Guide to LLM Foundations, Advanced Topics, Fine‑Tuning, and LangChain Applications

This article provides an in‑depth technical overview of large language models (LLMs), covering core model families, architectural differences, emergent abilities, common challenges such as repetition and token limits, detailed fine‑tuning strategies including PEFT, practical guidance for training custom models, and a thorough introduction to the LangChain framework with code examples, core concepts, and troubleshooting tips for building LLM‑powered applications.

Fine-tuningLLMLangChain
0 likes · 97 min read
A Complete Technical Guide to LLM Foundations, Advanced Topics, Fine‑Tuning, and LangChain Applications
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Oct 19, 2023 · Artificial Intelligence

How to Build a Retrieval‑Augmented LLM Knowledge Base on Alibaba Cloud

This guide details a complete end‑to‑end solution for constructing a large‑language‑model knowledge‑base chatbot on Alibaba Cloud, covering background, modular architecture, vector database selection, text preprocessing, embedding models, LLM fine‑tuning, prompt engineering, deployment with PAI‑EAS and BladeLLM, and real‑world results.

AILLMLangChain
0 likes · 37 min read
How to Build a Retrieval‑Augmented LLM Knowledge Base on Alibaba Cloud
AI Large Model Application Practice
AI Large Model Application Practice
Oct 18, 2023 · Artificial Intelligence

How to Extract and Embed Tables and Images from PDFs for Multimodal RAG

This article explains a practical approach to parsing PDFs containing text, tables, and images, using the open‑source Unstructured library and LlaVA model, then embedding each modality into a vector store with multi‑vector retrieval to enable accurate semantic search in private‑knowledge RAG pipelines, with optional LangChain integration.

LLMLangChainPDF processing
0 likes · 12 min read
How to Extract and Embed Tables and Images from PDFs for Multimodal RAG
dbaplus Community
dbaplus Community
Oct 14, 2023 · Artificial Intelligence

Demystifying Retrieval‑Augmented Generation: From Theory to Working Chatbot

This guide explains the Retrieval‑Augmented Generation (RAG) technique, detailing how user queries are matched to private knowledge bases, how relevant passages are retrieved, and how large language models use those passages to generate context‑aware answers, complete with code examples and practical tips.

ChatbotEmbeddingLLM
0 likes · 19 min read
Demystifying Retrieval‑Augmented Generation: From Theory to Working Chatbot
UCloud Tech
UCloud Tech
Sep 11, 2023 · Artificial Intelligence

Build a Soul‑Healing Chatbot with LangChain & Llama 2: A Step‑by‑Step Guide

This article walks through constructing a domain‑specific, soul‑healing chatbot using LangChain and Llama 2, comparing fine‑tuning versus external knowledge bases, detailing environment setup, data loading, text splitting, embedding with a Chinese model, vector store creation, prompt engineering, inference, and optimization strategies.

Fine-tuningKnowledge BaseLangChain
0 likes · 14 min read
Build a Soul‑Healing Chatbot with LangChain & Llama 2: A Step‑by‑Step Guide
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Sep 1, 2023 · Artificial Intelligence

Understanding Function Calling and ReAct for LLM Agents with LangChain

This article explains how large language models can act as agents by using OpenAI's Function Calling and the ReAct prompting paradigm, compares their trade‑offs, and demonstrates practical implementations with LangChain, including code examples for defining tools, invoking functions, and orchestrating multi‑step reasoning.

AIAgentFunction Calling
0 likes · 21 min read
Understanding Function Calling and ReAct for LLM Agents with LangChain
Architect
Architect
Aug 31, 2023 · Artificial Intelligence

Building a Custom LLM Chatbot with LangChain, ChromaDB, and LLaMA‑2

This tutorial explains how to leverage generative AI tools—including LLMs, embedding models, vector databases, and the LangChain framework—to create a custom chatbot that answers user queries using a knowledge base, with step‑by‑step code examples for Google Colab.

ChatbotEmbeddingLLM
0 likes · 15 min read
Building a Custom LLM Chatbot with LangChain, ChromaDB, and LLaMA‑2
DataFunTalk
DataFunTalk
Aug 17, 2023 · Artificial Intelligence

Introduction to LangChain: Concepts, Tools, and Example Applications

This article introduces the LangChain framework, explains its core concepts such as models, prompts, agents, memory, indexes, and tools, provides detailed code examples for each component, and demonstrates practical applications ranging from chatbots to image generation, helping readers understand and build powerful LLM-powered solutions.

LangChainPythonagents
0 likes · 27 min read
Introduction to LangChain: Concepts, Tools, and Example Applications
21CTO
21CTO
Aug 16, 2023 · Artificial Intelligence

Top Python Libraries for Building Generative AI Apps: A Quick Reference

This cheat‑sheet summarizes the leading Python libraries for creating generative AI applications—covering OpenAI, Transformers, Gradio, LangChain, LlamaIndex and more—providing a concise, practical guide for both beginners and seasoned developers.

GradioLangChainLlamaIndex
0 likes · 3 min read
Top Python Libraries for Building Generative AI Apps: A Quick Reference
Architect's Guide
Architect's Guide
Aug 10, 2023 · Artificial Intelligence

Getting Started with LangChain: Building LLM Applications in Python

This tutorial introduces LangChain, an open‑source Python framework that provides unified model access, prompt management, memory, retrieval, and tool integration, enabling developers to quickly prototype AI‑driven applications using large language models and various external data sources.

LLMLangChainPrompt engineering
0 likes · 13 min read
Getting Started with LangChain: Building LLM Applications in Python
Architect
Architect
Jul 31, 2023 · Artificial Intelligence

Getting Started with LangChain: Building LLM‑Powered Applications

This article introduces LangChain, explains why it’s useful for building applications with large language models, walks through installation, API‑key setup, model and embedding selection, prompt engineering, chaining, memory, agents, and vector‑store indexing, and provides runnable Python code examples throughout.

LLMLangChainPromptEngineering
0 likes · 16 min read
Getting Started with LangChain: Building LLM‑Powered Applications
MoonWebTeam
MoonWebTeam
Jul 28, 2023 · Artificial Intelligence

Unlocking LangChain: A Complete Guide to Building LLM Applications

This article introduces LangChain, explains its architecture and core components, and provides step‑by‑step Python examples for chat models, embeddings, prompts, indexes, chains, memory, agents, and practical use‑cases such as QA bots, web search, summarization, and persistent vector stores.

LLMLangChainPython
0 likes · 34 min read
Unlocking LangChain: A Complete Guide to Building LLM Applications
DaTaobao Tech
DaTaobao Tech
Jul 26, 2023 · Artificial Intelligence

LangChain: A New Chapter in Large Language Models

In this event, a senior Alibaba Taobao Tech engineer introduces LangChain—a framework for large language models—explaining its core concepts, diverse applications, and future directions, and shows attendees how to leverage the platform to boost AI capabilities within their own businesses.

AIAlibabaDataFun
0 likes · 1 min read
LangChain: A New Chapter in Large Language Models
Tencent Cloud Developer
Tencent Cloud Developer
Jul 24, 2023 · Artificial Intelligence

Building an Internal Code Knowledge Base with Embedding and AST Interpreter

The author builds an internal code knowledge base for the TDesign Vue‑Next library by scraping documentation, chunking and embedding texts with OpenAI’s ada model into a vector store, then retrieving relevant chunks for LLM answers, and enhances context continuity using a JavaScript AST interpreter, achieving up to 90 % query accuracy and a 20 % productivity boost.

ASTEmbeddingKnowledge Base
0 likes · 11 min read
Building an Internal Code Knowledge Base with Embedding and AST Interpreter
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Jul 20, 2023 · Artificial Intelligence

How AI Agents and Tools Transform Operations: A Hands‑On LangChain Guide

This article explores how large AI models can act as autonomous agents equipped with tools, demonstrates practical LangChain examples for remote server queries and RSS parsing, explains the ReAct reasoning‑acting loop, and shows how decorators and object‑oriented patterns enable seamless AI‑driven programming.

AILangChainPython
0 likes · 32 min read
How AI Agents and Tools Transform Operations: A Hands‑On LangChain Guide