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BirdNest Tech Talk

Author of the rpcx microservice framework, original book author, and chair of Baidu's Go CMC committee.

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Latest from BirdNest Tech Talk

100 recent articles max

BirdNest Tech Talk

Oct 30, 2025 · Artificial Intelligence

Master LangChain Chains with LCEL: From Simple Jokes to RAG and Agent Pipelines

This guide explains how LangChain’s Expression Language (LCEL) lets you declaratively connect prompts, models, and output parsers into chains, walks through environment setup, dependency installation, and detailed code examples ranging from a basic joke generator to retrieval‑augmented generation and memory‑enabled agents.

AgentLCELLangChain

0 likes · 5 min read

Master LangChain Chains with LCEL: From Simple Jokes to RAG and Agent Pipelines

BirdNest Tech Talk

Oct 30, 2025 · Artificial Intelligence

How to Build Multimodal Prompts with LangChain: A Step‑by‑Step Guide

Learn how LangChain enables multimodal interactions by preparing inputs, constructing prompts, invoking models like GPT‑4o, and processing responses, with a complete example that demonstrates image‑question answering, code walkthrough, environment setup, and key considerations for API keys and image URLs.

LLMLangChainOpenAI

0 likes · 9 min read

How to Build Multimodal Prompts with LangChain: A Step‑by‑Step Guide

BirdNest Tech Talk

Oct 30, 2025 · Artificial Intelligence

Mastering LangChain Tools: Define, Build, and Optimize Agent Functions

This guide explains what LangChain tools are, why clear descriptions matter, and walks through three ways to create them—using the @tool decorator, StructuredTool with Pydantic models, and custom BaseTool subclasses—plus examples of built‑in tools and reference links.

AgentLLMLangChain

0 likes · 7 min read

Mastering LangChain Tools: Define, Build, and Optimize Agent Functions

BirdNest Tech Talk

Oct 30, 2025 · Artificial Intelligence

How LangChain Agents Empower LLMs with Dynamic Reasoning and Tool Use

This article explains the core concept of LangChain agents—combining an LLM, a set of tools, and a reasoning‑action loop—to enable dynamic decision‑making, tool invocation, and iterative observation for solving complex, multi‑step tasks.

AI reasoningLLMLangChain

0 likes · 6 min read

How LangChain Agents Empower LLMs with Dynamic Reasoning and Tool Use

BirdNest Tech Talk

Oct 27, 2025 · Artificial Intelligence

How LangChain’s Indexing API Enables Efficient Incremental Updates for RAG Systems

This article explains how LangChain's Indexing API adds state management and synchronization to the classic load‑split‑embed‑store RAG pipeline, detailing the RecordManager component, the index function workflow, key parameters, implementation considerations, and best‑practice code examples for production‑grade vector stores.

FAISSIndexing APILangChain

0 likes · 12 min read

How LangChain’s Indexing API Enables Efficient Incremental Updates for RAG Systems

BirdNest Tech Talk

Oct 27, 2025 · Artificial Intelligence

Mastering LangChain Retrievers: From Basics to Multi‑Query and Ensemble Techniques

This article explains the concept of LangChain retrievers, compares them with vector stores, and provides step‑by‑step code examples for MultiQueryRetriever and EnsembleRetriever, showing how to boost recall and combine semantic and keyword search for robust RAG pipelines.

AIEnsembleRetrieverLangChain

0 likes · 9 min read

Mastering LangChain Retrievers: From Basics to Multi‑Query and Ensemble Techniques

BirdNest Tech Talk

Oct 24, 2025 · Backend Development

Bridging Go and Python with pyproc: Ultra‑Low‑Latency Interprocess Calls

This article introduces pyproc, a library that lets Go applications invoke Python functions via Unix Domain Sockets with sub‑45 µs latency, explaining the problem of mixing Go and Python ecosystems, the architecture, performance benefits, suitable use cases, and a step‑by‑step quick‑start guide with full code examples.

AI infrastructureGoHigh Performance

0 likes · 7 min read

Bridging Go and Python with pyproc: Ultra‑Low‑Latency Interprocess Calls

BirdNest Tech Talk

Oct 21, 2025 · Artificial Intelligence

How Vector Stores Enable Lightning‑Fast Semantic Search in LangChain

This article explains what vector stores are, outlines their core workflow of adding, querying, and searching embeddings, compares popular back‑ends like FAISS, Chroma, and Pinecone, and walks through a complete Chinese‑language example using LangChain’s FAISS integration with detailed code and result analysis.

AIEmbeddingsFAISS

0 likes · 10 min read

How Vector Stores Enable Lightning‑Fast Semantic Search in LangChain

BirdNest Tech Talk

Oct 20, 2025 · Artificial Intelligence

How Embedding Models Power Semantic Search: A Hands‑On LangChain Guide

This article explains what embeddings are, how LangChain’s Embeddings interface abstracts various providers, compares common models, and walks through a complete Python example that uses a Chinese‑optimized HuggingFace model to generate document and query vectors, compute cosine similarity, and identify the most relevant text.

EmbeddingsLangChainNLP

0 likes · 9 min read

How Embedding Models Power Semantic Search: A Hands‑On LangChain Guide

BirdNest Tech Talk

Oct 17, 2025 · Artificial Intelligence

How to Extend Claude with Custom Agent Skills Using SKILL.md

Claude’s new Agent Skills let developers package domain expertise into organized SKILL.md files and resource folders, enabling progressive disclosure, code execution, and scalable context loading, with detailed guidance on structure, bundling, evaluation, and security considerations for building robust, reusable AI agents.

AI agentsAgent SkillsClaude

0 likes · 11 min read

How to Extend Claude with Custom Agent Skills Using SKILL.md