58 articles with this tag
AutoGen vs LangChain for multi-agent systems in 2026 — feature comparison, same use case in both frameworks, and an honest verdict on when each wins.
Compare AutoGPT's zero-shot autonomy against LangChain's ReAct agents. Discover which handles complex tasks better and when to choose each framework.
Go beyond basic similarity search with ParentDocumentRetriever, MultiQueryRetriever, EnsembleRetriever, HyDE, and 6 more LangChain retrieval strategies — with code for each.
Build a complete LangChain conversational agent with persistent memory, multiple tools, and step-by-step trace — from setup to a production-ready implementation with code.
Understand every major LangChain agent type — ZeroShotAgent, ReAct, ConversationalAgent, and more — with Python code and agent trace walkthroughs.
Serve a LangChain app as a production FastAPI REST endpoint with streaming, async chains, error handling, and Docker deployment — full Python code included.
Connect LangChain to Azure OpenAI Service for enterprise deployments. Covers AzureChatOpenAI, managed identity, embeddings, content filtering, and a comparison table.
Master 7 LangChain callbacks including StdOutCallbackHandler, LangSmith tracing, custom callbacks, streaming tokens, and token usage monitoring with working Python examples.
Track OpenAI API spend with LangChain callbacks — get_openai_callback, custom cost trackers, per-chain breakdowns, budget alerts, and monthly cost estimation.
Master all major LangChain chain types — LLMChain, SequentialChain, RouterChain, and more — with real Python code and a guide on when to use each.
Learn how to persist and restore LangChain agent state using InMemoryCheckpointer, SqliteSaver, and PostgresSaver with full Python code examples.
Use LangChain with ChromaDB for persistent local embeddings — setup, metadata filtering, similarity search, and collection management with full Python code.
Build a LangChain coding assistant that writes Python code, runs it in a sandbox, captures errors, and auto-fixes bugs in a write→test→fix loop with full code.
Build a production LangChain customer support agent: KB ingestion, intent classification, RAG retrieval, escalation logic, and feedback collection in Python.
Learn 10 LangChain document compressors that slash context length, cut LLM costs, and keep RAG pipelines fast and accurate in production.
A practical guide to LangChain's S3FileLoader, NotionDirectoryLoader, YoutubeLoader, TwitterTweetLoader, and building custom API loaders with real code examples.
Build a complete LangChain document Q&A system that loads PDF, HTML, and DOCX files with PyPDFLoader, RecursiveCharacterTextSplitter, and a full retrieval pipeline.
Master LangChain document transformers to preprocess documents for RAG — splitters, filters, embeddings, and redundancy removal in Python.
Track entities across conversations with LangChain's ConversationEntityMemory and EntityStore backends — build chatbots that remember people, places, and facts.
Master LangChain Expression Language (LCEL) with complete examples of pipe syntax, RunnableSequence, RunnableParallel, streaming, batching, and async invocation.
Build a LangChain stock analysis agent using Yahoo Finance, SEC EDGAR, and custom financial ratio tools — with a full comparison of financial data sources.
Run open source LLMs locally with LangChain and Hugging Face. Complete guide covering HuggingFacePipeline, Llama, Mistral, and sentence-transformers embeddings.
Master LangChain's Indexing API with RecordManager for deduplication, incremental sync, and deletion cleanup in production vector store pipelines.
Set up LanceDB as a serverless, open-source vector database with LangChain. Covers local and cloud modes, IVF_PQ indexing, ANN search, and a full RAG example.
Learn how to use LangSmith to trace, debug, and evaluate LangChain apps — with run inspection, dataset creation, A/B testing chains, and a practical debugging workflow.
Master LangChain LCEL with 10 real patterns for RunnableParallel, RunnableLambda, branching, fan-out, and streaming with full Python code examples.
Learn every major LangChain memory type — ConversationBufferMemory, SummaryMemory, VectorStoreMemory, and EntityMemory — with working code and a comparison table.
Master LangChain message types for accurate chat history formatting. Complete guide to HumanMessage, AIMessage, SystemMessage, ToolMessage with code examples.
Deploy LangChain pipelines on Modal's serverless GPU infrastructure — run local LLMs, scale to zero, and cut inference costs with cold-start optimization.
Learn how to build conversational agents with persistent memory using LangChain's ConversationBufferMemory, RunnableWithMessageHistory, and a FastAPI chatbot endpoint.
Set up LangChain with the OpenAI API — configure ChatOpenAI, implement function calling, bind tools, and run parallel tool calls in a production-ready setup.
Stop losing data to malformed LLM outputs. Learn 7 LangChain error recovery strategies including OutputFixingParser, RetryOutputParser, fallbacks, and exponential backoff.
Learn to use all 5 essential LangChain output parsers — JsonOutputParser, PydanticOutputParser, CSV, Datetime, and StructuredOutputParser — with complete code examples.
Build a LangChain pandas agent that answers natural language questions about your data, generates charts, and writes Python code — full working tutorial.
Deploy cloud-native RAG with LangChain and Pinecone Serverless. Complete guide covering setup, upsert, query, namespaces, metadata filtering, and cost estimates.
Build reusable LangChain prompts with PromptTemplate, ChatPromptTemplate, FewShotPromptTemplate, and partial variables — 10 practical patterns with Python code.
Evaluate your LangChain RAG pipeline with Ragas: faithfulness, answer relevancy, context recall, context precision, and answer correctness — full Python code.
Evaluate your LangChain RAG pipelines with Ragas: faithfulness, answer relevancy, context recall, TestsetGenerator, and CI/CD integration for production quality.
Build a complete RAG pipeline with LangChain, Chroma, and OpenAI embeddings — document loading, chunking, vector storage, and retrieval in one guide.
Build 10 real LangChain projects from email automation to research agents and data analysis tools. Complete code snippets plus difficulty and time estimates.
Use LangChain with Redis for low-latency AI responses. Covers RedisCache, RedisSemanticCache, RedisVL vector search, and a Redis vs alternatives comparison.
Improve RAG relevance with LangChain rerankers — CohereRerank, CrossEncoderReranker, FlashrankRerank, RankGPT, and more, with BEIR benchmark results and code.
Build an AI research assistant that searches ArXiv and PubMed, synthesizes findings, and formats citations automatically. Full Python code included.
Combine multiple retrievers in LangChain using EnsembleRetriever, BM25 fusion, and Reciprocal Rank Fusion to build higher-accuracy RAG pipelines.
Build a LangChain SQL agent that converts natural language to accurate SQL queries — with few-shot prompting, JOIN handling, security safeguards, and a working demo endpoint.
Master LangChain streaming with 7 real examples: .stream(), .astream(), astream_events(), FastAPI SSE endpoints, and React token consumers for real-time AI output.
A practical guide to all 10 LangChain text splitters — Recursive, Markdown, Code, HTML, Semantic, Token — with comparison table and chunking best practices.
Explore 10 LangChain toolkits including SQLDatabaseToolkit, PlaywrightBrowserToolkit, GitHubToolkit, and SlackToolkit with full Python code and comparison table.
Master 10 essential LangChain tools including SerpAPI, TavilySearch, Calculator, Python REPL, and custom tools with @tool decorator for building AI agents.
Learn LangChain from scratch. Install the library, write your first LLMChain, and build a real LLM app with PromptTemplate and ChatOpenAI in Python.
Master LangChain's 5 core retriever types — SimilaritySearch, MMR, ContextualCompression, MultiVectorRetriever, and SelfQueryRetriever — with code, benchmarks, and guidance.
Compare Pinecone, Weaviate, FAISS, Chroma, Milvus, Qdrant, and PGVector for LangChain RAG — with code snippets, cost breakdown, and honest recommendations.
Integrate LangChain with Google Vertex AI and Gemini models. Complete guide covering ChatVertexAI, embeddings, multimodal inputs, function calling, and cost comparison.
An honest comparison of LangChain and AutoGen for multi-agent orchestration — feature tables, same task coded in both frameworks, and a clear verdict on when to use each.
LangChain vs LlamaIndex: an honest 2026 comparison of RAG capabilities, indexing strategies, query engines, community size, and when to choose each framework.
Connect LangChain to Weaviate for hybrid vector and keyword search. Covers local and cloud setup, nearText, BM25, metadata filtering, and a comparison table.
Learn to build a LangChain web browsing agent using Playwright, newspaper3k, and FireCrawl with rate limiting, multi-page crawling, and real code examples.
Build a full LangChain agent that loads YouTube transcripts, falls back to Whisper, and summarizes long videos with MapReduceDocumentsChain and GPT-4o.
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