The lab notebook
Field notes on AI engineering
824 articles · page 23 of 28
LangChain Prompt Templates: Reusable, Versioned Prompts
Learn how LangChain prompt templates make prompts reusable, testable, and version-controlled across your LLM applications.
LangChain Retrievers Explained: From Vector Stores to Ensembles
A practical guide to LangChain retrievers, from basic vector store lookups to multi-query and ensemble retrieval for production RAG.
LangChain Router Chains: Directing Queries to the Right Handler
Learn how LangChain router chains use RunnableBranch and RunnableLambda to send each query to the right specialized handler.
LangChain Runnable Interface: The Core Abstraction Explained
Learn how LangChain's Runnable interface unifies invoke, batch, stream, and LCEL pipes into one predictable contract for building LLM chains.
LangChain Security: Preventing Prompt Injection in Chains
A practical guide to prompt injection attacks in LangChain apps, with real attack patterns and concrete mitigations for chains, tools, and agents.
LangChain for SQL: Building a Database Question-Answering Chain
Learn how to build a production-ready LangChain SQL chain that turns plain English into safe, accurate database queries.
LangChain Streaming: Returning Tokens as They're Generated
Learn how to stream LLM tokens in real time with LangChain's `.stream()` and `.astream()` methods, from basic chains to async FastAPI endpoints.
LangChain Structured Output with Pydantic Models
Learn how to force reliable, typed JSON out of any LLM using LangChain's with_structured_output() and Pydantic models, with production patterns.
LangChain for Summarization: Map-Reduce and Refine Strategies
Learn how to summarize long documents in LangChain using map-reduce and refine chains, with working code and guidance on when to use each.
LangChain Testing: Unit Testing Chains and Agents
A practical guide to unit testing LangChain chains and agents with fakes, mocks, and deterministic assertions instead of flaky live LLM calls.
LangChain Text Splitters Compared: Which One for Which Content
A practical comparison of LangChain's text splitters so you stop guessing and start picking the right chunking strategy for your content.
LangChain Vector Store Comparison: Choosing the Right Backend
A practical, code-first comparison of Chroma, FAISS, Pinecone, Weaviate, and pgvector for LangChain RAG apps.
LangChain for Voice Apps: Combining STT, LLM and TTS
Learn how to architect production voice apps by chaining speech-to-text, LangChain LLM logic, and text-to-speech into one coherent pipeline.
LangFlow for Agent Prototyping: Visual Tool-Calling Flows
A practical guide to prototyping tool-calling AI agents visually in LangFlow before you commit to code.
LangFlow API Deployment: Turning a Flow Into a Callable Endpoint
Learn how to turn any LangFlow flow into a production-ready API endpoint with curl, Python, and JavaScript examples.
LangFlow Authentication Nodes: Securing Access to Your Flow API
Learn how to secure LangFlow flows in production with API keys, auth nodes, environment secrets, and role-based access patterns.
LangFlow for Chatbot Prototyping: A Complete Walkthrough
Learn how to prototype chatbots visually in LangFlow, from your first flow to RAG, memory, and export-ready pipelines.
LangFlow Debugging: Inspecting Data Between Nodes
Learn practical techniques for inspecting the exact data flowing between LangFlow nodes so you can catch broken pipelines before they reach production.
LangFlow for Document Processing Pipelines
A practical guide to building document processing pipelines in LangFlow, from ingestion and chunking to extraction, embeddings, and production deployment.
LangFlow Environment Variables: Managing Secrets Safely
A practical guide to configuring LangFlow environment variables and keeping API keys, database URLs, and secrets out of your flows and version control.
LangFlow for Classroom Teaching: Visualizing LLM Concepts
LangFlow turns invisible LLM pipelines into draggable nodes, making it one of the fastest ways to teach prompting, RAG, and agents in a classroom.
LangFlow for Internal Tools: Rapid Prototyping for Non-Engineers
How LangFlow's drag-and-drop canvas lets non-engineers prototype real AI-powered internal tools without waiting on an engineering sprint.
LangFlow for Non-Developers: Building AI Apps Without Code
Learn how non-developers can use LangFlow's drag-and-drop canvas to build real AI apps, chatbots, and agents without writing Python.
LangFlow Import/Export: Moving Flows Between Environments
A practical guide to exporting, importing, and safely migrating LangFlow flows across dev, staging, and production environments.
LangFlow Memory Nodes: Adding Conversation History to a Flow
Learn how LangFlow's memory nodes work and how to wire them into a flow so your chatbot actually remembers what the user said three turns ago.
LangFlow for Multi-Step Form Processing Automations
Learn how to build resilient multi-step form processing pipelines in LangFlow, from validation to routing to human review.
LangFlow Playground Mode: Testing Flows Before You Ship Them
A practical guide to using LangFlow's Playground to test, debug, and validate flows before pushing them into production.
LangFlow for Prototyping Voice Assistants
Learn how LangFlow's visual canvas lets you prototype voice assistant logic in hours instead of weeks, before you write a line of production code.
LangFlow for RAG Prototyping: A Step-by-Step Build
Learn how to prototype a full RAG pipeline in LangFlow's visual canvas before you write a single line of production code.
LangFlow Rate Limiting Nodes: Protecting Downstream APIs
Learn how to design LangFlow rate limiting nodes that protect downstream APIs from throttling, cost overruns, and cascading failures.