#ChatModel
6 related articles
·3 min
Spring AI + Ollama: Run Large Language Models Locally at Zero Cost
Learn how to integrate Spring AI with Ollama to run open-source LLMs like Llama and Gemma locally for free. Covers setup, configuration, and code — switch from OpenAI by just changing dependencies.
Read more →
·3 min
Complete Guide to LangChain 0.3: Module Architecture & Core Development in Practice
A deep dive into LangChain 0.3's module architecture, message abstraction, prompt templates, output parsers, LCEL chains, LangSmith tracing, and LangGraph for mastering LLM application development.
Read more →
·3 min
AI Large Model Learning Roadmap Breakdown: Three Stages from Application Development to Model Fine-Tuning
Deep breakdown of a popular AI large model learning roadmap covering LangChain, RAG, Agent, and LoRA fine-tuning across three stages, with analysis of its strengths and limitations for career changers.
Read more →
·3 min
LangGraph Core Explained: Its Relationship with LangChain and Multi-Agent Orchestration Principles
Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
Read more →
Tutorials·2 min
Getting Started with Spring AI Alibaba: Best Practices for Java Developers to Integrate LLMs
Deep dive into Spring AI Alibaba's positioning and value, using a JDBC analogy to help Java developers understand how to integrate LLM capabilities into existing microservices architecture.
Read more →
Tutorials
Getting Started with LangChain: Core C…
·3 min
Getting Started with LangChain: Core Concepts and Hands-On Guide for LLM and Agent Development
A systematic guide to LangChain's core features, covering LLM vs. Agent concepts, unified interface design, multi-provider support, environment setup, and hands-on code examples for AI app development.
Read more →