LangChain Memory Types: Choose the Right Agent Memory
The most surprising thing about LangChain memory is that it's not about remembering past conversations, but about remembering past tool calls and their .
LangChain Articles
53 articles
LangChain Multi-Agent: Orchestrate Specialized AI Agents
LangChain's multi-agent setup allows a collection of specialized AI agents to collaborate on a complex task, each agent leveraging its unique strengths .
LangChain Multi-Query Retriever: Expand Search Coverage
The LangChain Multi-Query Retriever doesn't actually expand search coverage in the way you might think; it enhances the quality of the retrieved results.
LangChain Vision Agents: Process Images with LLM Tools
LangChain Vision Agents can process images by converting them into a format an LLM can understand, allowing the LLM to then use its tools to interact wi.
LangChain LLM Switching: Swap OpenAI and Anthropic Models
When you need to switch between OpenAI and Anthropic models in LangChain, it's not just about changing an API key; it's about understanding how LangChai.
LangChain Output Parsers: Extract Structured Data from LLMs
Output parsers in LangChain are how you turn the freeform, often messy, text output of a Large Language Model LLM into structured data that your program.
LangChain Parent Document Retriever: Improve Chunk Context
The LangChain Parent Document Retriever is actually a clever way to trade off retrieval accuracy for context length, and it’s a lot more flexible than y.
LangChain PDF Pipeline: Ingest Documents at Production Scale
Ingesting PDFs into a LangChain pipeline at production scale isn't just about loading files; it's about strategically transforming unstructured chaos in.
LangChain Prompt Templates: Structure Inputs Correctly
LangChain's PromptTemplate isn't just about filling in blanks; it's about orchestrating the precise information flow that a language model needs to perf.
LangChain RAG Pipeline: Build and Deploy in Production
LangChain's Retrieval Augmented Generation RAG pipeline isn't just about stuffing documents into a vector database; it's about dynamically querying that.
LangChain Rate Limiting: Retry LLM Calls Without Crashes
LangChain's rate limiting for LLM calls isn't about stopping requests; it's about gracefully handling the inevitable slowdowns from external services.
LangChain Text Splitter: Tune Chunks for Better RAG
LangChain's text splitters are the unsung heroes of Retrieval Augmented Generation RAG, and tuning them is the difference between a RAG system that hall.
LangChain Refine Chain: Iteratively Summarize Documents
The Refine Chain in LangChain doesn't actually refine anything; it's a way to summarize documents by repeatedly applying a summarization model, passing .
LangChain Reranking: Boost RAG Precision with Cross-Encoders
LangChain's reranking module, powered by cross-encoders, can dramatically improve the relevance of documents retrieved by your RAG system, often surfaci.
LangChain Routing: Direct Queries to Specialized Chains
LangChain Routing: Direct Queries to Specialized Chains — practical guide covering langchain setup, configuration, and troubleshooting with real-world e...
LangChain Self-Query Retriever: Auto-Generate Filters
The LangChain Self-Query Retriever is less about "self-querying" and more about letting the LLM generate the query based on natural language questions.
LangChain SQL Agent: Query Databases with Natural Language
A SQL Agent's primary magic trick is letting you talk to your database in English, but the real surprise is how it can write SQL you might not have thou.
LangChain Streaming: Stream LLM Output via WebSocket
LangChain streaming via WebSocket is surprisingly similar to how you'd stream any data over a WebSocket, with the LLM being just a very specific, albeit.
LangChain Structured Output: Extract Typed Data with Pydantic
LangChain's Pydantic integration lets you pull structured, typed data out of LLM responses, moving beyond simple strings.
LangChain Testing: Unit and Integration Test Your Chains
LangChain unit and integration tests are often skipped because the "chain" itself feels like the atomic unit, but in reality, it's the interactions betw.
LangChain Chunking Strategies: Optimize Text Splitting for RAG
LangChain's RecursiveCharacterTextSplitter is often the default choice for chunking, but it's a blunt instrument that can destroy semantic meaning by sp.
LangChain Tool Calling: OpenAI Functions Integration
OpenAI's function calling feature in LangChain isn't just about letting an LLM pick a tool; it's a sophisticated negotiation where the LLM proposes a pl.
LangChain Vector Stores: Pinecone vs Chroma vs Weaviate
Pinecone, Chroma, and Weaviate are all popular vector stores, but they approach the problem of storing and querying high-dimensional embeddings with fun.
LangChain v0.2 Migration: Upgrade Without Breaking Changes
LangChain v0.2 Migration: Upgrade Without Breaking Changes — LangChain's v0.2 release dramatically changed how its core components, like LLMs and ChatMo...
LangChain Web Scraping Agents: Fetch and Parse Live Data
The most surprising thing about LangChain web scraping agents is that they often don't need to scrape the web at all, and their real power lies in their.
Fix LangChain VectorStore Query Returning No Results
Fix LangChain VectorStore Query Returning No Results — The LangChain VectorStore.similaritysearch method is failing to return any results because the un...
Fix LangChain Agent Stopped at Max Iterations Error
The LangChain agent is failing because it's exceeding the maximum number of tool calls allowed in a single execution cycle, preventing it from reaching .
Fix LangChain Pinecone Index Not Found Errors
Pinecone is refusing to find your index, and it's because the pinecone-client library is trying to talk to a Pinecone API endpoint that doesn't exist, o.
LangChain Agent Tools: Build Custom Function Calling
LangChain Agent Tools: Build Custom Function Calling — practical guide covering langchain setup, configuration, and troubleshooting with real-world exam...
LangChain Agentic RAG: Corrective and Adaptive Retrieval
A LangChain Agentic RAG system doesn't find information; it negotiates with information. Let's watch this agent work through a query about "the impact o.
LangChain Async Chains: Run Parallel LLM Calls
LangChain's async chains let you run multiple LLM calls concurrently, drastically speeding up operations that involve independent, parallel LLM interact.
LangChain LLM Caching: Cache Responses with Redis
LangChain's LLM caching can drastically reduce latency and cost by storing previous LLM responses, but it often fails to cache anything at all.
LangChain Callbacks: Log and Monitor Chain Execution
Callbacks are how LangChain lets you peer inside the execution of your chains and agents, giving you a window into every step, every LLM call, and every.
LangChain LCEL vs Chains: Migrate to Runnable Interface
LangChain Expression Language LCEL isn't just a new way to write chains; it's a fundamental shift in how LangChain components interact, making them comp.
LangChain Contextual Compression: Reduce Retrieval Noise
LangChain's Contextual Compression is a technique to make your retrieval systems smarter by filtering out irrelevant information after you've already fe.
LangChain Memory: Buffer vs Summary Conversation Memory
LangChain's memory isn't about remembering past conversations; it's about selectively forgetting them to manage token limits.
LangChain Cost Tracking: Monitor Token Usage and Spend
LangChain's cost tracking is a surprisingly effective way to prevent your LLM experiments from becoming an unexpected bill at the end of the month.
LangChain CSV Agent: Query Spreadsheets with LLMs
LangChain's CSV agent lets you query your spreadsheets using natural language, but the real magic is that it generates Python code on the fly to do the .
LangChain Custom Retrievers: Integrate Any Vector Store
LangChain custom retrievers let you plug in any data source, not just the ones it natively supports, by framing it as a similarity search.
LangChain Production Deploy: Docker and FastAPI Setup
LangChain Production Deploy: Docker and FastAPI Setup — practical guide covering langchain setup, configuration, and troubleshooting with real-world exa...
LangChain Document Loaders: Parse PDFs, HTML, and More
LangChain's document loaders are the unsung heroes of LLM applications, acting as the crucial bridge between raw, unstructured data and the organized, c.
LangChain Metadata Filtering: Narrow Retrieval Results
Metadata filtering in LangChain is how you tell your retrieval system to be incredibly picky about what it looks at, but not in the way you'd expect.
LangChain Enterprise Security: Handle PII Safely
LangChain Enterprise Security: Handle PII Safely A surprising truth about handling PII in LangChain is that the "security" isn't typically in the LLM ca.
LangChain RAG Evaluation: Measure Retrieval Quality
LangChain's RAG evaluation tools let you measure how well your Retrieval Augmented Generation system is actually retrieving relevant information.
LangChain Few-Shot Prompts: Guide LLMs with Examples
LangChain's few-shot prompting isn't just about showing an LLM examples; it's about subtly coercing its latent knowledge into a specific, reproducible o.
LangChain Fine-Tuned Embeddings: Improve RAG Retrieval
Fine-tuning embeddings for RAG is less about teaching a model to understand language and more about teaching it to recognize patterns that signal releva.
LangChain Graph RAG: Query Knowledge Graphs with LLMs
LangChain's Graph RAG allows LLMs to query knowledge graphs, but the real magic is how it turns unstructured text into structured graph data on the fly .
LangChain Guardrails: Validate and Filter LLM Outputs
LangChain Guardrails: Validate and Filter LLM Outputs — practical guide covering langchain setup, configuration, and troubleshooting with real-world exa...
LangChain Hybrid Search: Combine BM25 and Semantic Search
Hybrid search is the secret sauce for getting the best of both worlds in information retrieval, and LangChain makes it surprisingly straightforward to i.
LangGraph Stateful Agents: Build Multi-Step AI Workflows
LangGraph Stateful Agents: Build Multi-Step AI Workflows — practical guide covering langchain setup, configuration, and troubleshooting with real-world ...
LangSmith Tracing: Debug LangChain Apps in Production
LangSmith tracing lets you see exactly what's happening inside your LangChain applications when they run, making it way easier to find and fix bugs.
LangChain LCEL Streaming: Stream LLM Responses in Prod
LangChain's LCEL LangChain Expression Language enables streaming LLM responses in production by allowing you to construct LLM chains as a series of step.
LangChain Map-Reduce: Summarize Long Documents with LLMs
The Map-Reduce summarization technique in LangChain doesn't actually "reduce" your document's complexity; it distributes the summarization work across a.