#LangChain callback handler
5 related articles
·3 min
Introducing LLM Gateways in Production: Five Key Concerns and the Prerequisites for Trust
Introducing an LLM Gateway in LangChain production brings unified APIs and auto-fallback, but also quality drift, cost spikes, and debug black boxes. This article breaks down the five key engineering concerns and what it takes to earn trust.
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·6 min
Getting Started with LangChain: A Deep Dive into Model and Agent Core Concepts
Deep dive into LangChain's core Model and Agent concepts, covering unified model interfaces, agent tool calling, middleware mechanisms, and key principles for building LLM applications.
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Tutorials·3 min
Complete Guide to Building AI Agent Projects with WindSurf: Practical Tips & Techniques
Complete practical guide to building AI Agent Frameworks with WindSurf, covering technology selection, component generation, code refactoring, debugging, and deployment tips.
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Tutorials·2 min
LangChain AI Agent in Practice: Complete Tutorial on Streaming Output + Parallel Tool Calling
Learn how to build a production-grade AI Agent chat app with LangChain and FastAPI, covering streaming tokens, asyncio parallel tool calling, SerpAPI async conversion, and structured output.
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Tutorials·2 min
LangChain Streaming Output & Async in Practice: Complete Implementation for Agent Scenarios
Deep dive into LangChain streaming output and async implementation, covering astream usage, custom AsyncQueueCallbackHandler, and Agent streaming executor architecture for production AI apps.
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