最新博客文章
40 / 200AI 开发实战教程，从零到一构建你的 AI 应用。
All200
Beginner32
Intermediate92
Advanced76
All
Prompt Engineering12
RAG Retrieval Augmented17
Agent Development34
Model Fine-tuning21
Deployment and Operations25
AI Application Development40
DeepSeek API16
Multimodal Development6
AI Safety6
Model Inference3
Retrieval Systems1
RAG Retrieval1
Model Architecture3
API Development1
Agent Development10
Model Deployment1
Multimodal1
Model Evaluation2
Tutorial
Date
DeepSeek API Development Documentation
AI Application Development
Beginner
Complete DeepSeek API development documentation: authentication configuration, Chat Completions, Function Calling, streaming output, JSON mode, and token calculation. Includes Python/JavaScript/Go SDK examples and best practices to quickly get started with the DeepSeek API.
Code Agent Engineering: Repo Indexing, Context Collection, and Patch Verification
AI Application Development
Advanced
The hard part of an agent editing a large repository is not writing code, it is knowing what the code means. AST-level indexing that text grep cannot match, seed expansion and layered window budgets across files, reducing requests to the smallest change set, a four-tier verification set, and gating destructive changes such as bulk deletes and dependency upgrades.
DeepSeek Enterprise Application Tutorial
AI Application Development
Advanced
DeepSeek enterprise-level application architecture design: multi-tenant isolation, permission management, audit logs, API gateway, and cost control. Includes practical solutions for enterprise RAG systems, intelligent customer service, and knowledge base management, providing an AI implementation guide for large organizations.
DeepSeek Model Introduction
AI Application Development
Beginner
Comprehensive Introduction to DeepSeek Company and Model Ecosystem: Development History, Core Technologies, Model Matrix, and Application Scenarios. Understand how DeepSeek became a leading global AI model provider and how to choose the best DeepSeek model for your needs.
Model Routing and Multi-model Orchestration: Choosing by Task, Cost, and Latency
AI Application Development
Intermediate
"Which model should serve this request" is a measurable engineering problem. This guide covers three routes for task classifiers and their failure modes, cold-start label acquisition, the dimensions a capability matrix should track, making cost and latency hard constraints, cross-provider failover, and quantifying routing with oracle upper bounds and Pareto curves.
Connecting Agents to Real Business Systems: SaaS Integration and Transactional Consistency
AI Application Development
Advanced
Once an Agent can write, the hard part is no longer calling the API but undoing, explaining, and tracing a mistake. This article splits permissions along read, write, and cross-tenant dimensions, shows what to do when a vendor ignores your idempotency key, and walks Saga compensation, two-phase commit patterns, human confirmation points, and append-only event logs.
DeepSeek Getting Started Guide
AI Application Development
Beginner
Getting Started with DeepSeek from Scratch: Register Account, Get API Key, First Conversation, Model Selection, and Pricing. The most comprehensive beginner tutorial, get started with DeepSeek in ten minutes and embark on your AI application development journey.
DeepSeek + LangChain Development Tutorial
AI Application Development
Intermediate
DeepSeek and LangChain Integration Development Tutorial: Chain Construction, Agent Development, Memory Management, and Tool Integration. Includes complete LangChain project practice, with a progressive learning path from basic Chains to complex Agent systems.
Large Model Safety and Alignment Techniques
AI Application Development
Advanced
AI safety is the baseline requirement for production deployment. This article provides an in-depth explanation of alignment techniques such as RLHF, DPO, and Constitutional AI, as well as security practices like content moderation and prompt injection defense, to help you build safe and reliable AI applications.
Deep Research Systems in Practice: From Question Decomposition to Cited Reports
AI Application Development
Advanced
The hard part of deep research is not retrieval, it is making every claim trace back to concrete evidence. The design runs from intent clarification and question decomposition through gap-driven query planning, deduplication, evidence quality grading and sentence-level citation alignment, to contradictory evidence, long-report coherence, and end-to-end evaluation.
Test-Driven Development for LLM Applications: Practical Prompt Regression Testing
AI Application Development
Intermediate
Prompts are changed repeatedly, but how can we ensure that production behavior does not regress? This article introduces TDD to LLM applications: from assertion-based unit tests, regression test suites to Golden Sets and evaluation pipelines, building a maintainable AI application quality system.
DeepSeek Multimodal Application Tutorial
AI Application Development
Intermediate
In-depth analysis of DeepSeek's multimodal capabilities: visual understanding, image generation, document analysis, and OCR recognition. Includes tutorials for DeepSeek-VL2 and Janus series models, and practical development of multimodal RAG and visual agents.
AI-Native Product Design: Interfaces That Fit How Models Think
AI Application Development
Intermediate
Streaming output, undo points, and visible reasoning decide how trustworthy an AI product feels. This article compares three streaming strategies and their failure modes, explains partial results and undo points so users can stop early, outlines three levels of thinking visibility, and covers honest uncertainty display and interrupting long tasks.
Design of AI Writing Assistant Tools
AI Application Development
Beginner
AI writing assistance is a productivity multiplier for content creators. This article designs an AI writing assistance tool from scratch that supports multiple writing modes (article continuation, style polishing, outline generation, and summary extraction), using the DeepSeek API for streaming output and context management.
Multimodal AI Application Development in Practice
AI Application Development
Intermediate
Multimodal AI is changing the way humans interact with machines. This article explains the usage of vision-language models (VLMs), image-text understanding and generation, multimodal RAG, and the construction of multimodal agents, enabling you to master the complete skills of multimodal AI development.
LangChain Basics: Building Your First AI Application
AI Application Development
Beginner
LangChain is currently the most popular AI application development framework. This article starts from scratch, guiding you through LangChain's core concepts and building a complete AI application hands-on—from environment setup to feature implementation.
AI-Driven Data Analysis Pipeline
AI Application Development
Advanced
Traditional data analysis relies on extensive manual coding, while AI-driven data analysis pipelines make natural language the interface for data queries. This article builds a complete data analysis pipeline with NL2SQL + automatic visualization + insight generation, allowing anyone to explore data using natural language.
Enterprise AI Middleware Architecture Design
AI Application Development
Advanced
When an enterprise needs to manage dozens of AI services in a unified manner, the middleware layer is crucial. This article explains the complete architecture design of AI gateways, rate limiting, load balancing, model routing, and monitoring.
AI-Driven Automated Testing Systems
AI Application Development
Intermediate
Using AI to automatically generate test cases, detect bugs, and generate test reports greatly improves software testing efficiency. This article explains the architecture design and core implementation of an AI testing system.
DeepSeek Harness Hands-On Review: Setup, Modes & Token Usage
AI Application Development
Beginner
A full hands-on guide to dsh: 5-minute install, Web UI setup, four run modes, directory permissions, Token usage and Trajectory review, plus common pitfalls.
Building a Smart Customer Service Agent from Scratch
AI Application Development
Intermediate
Intelligent customer service is one of the most widespread AI application scenarios. This article builds an intelligent customer service Agent from scratch with intent recognition, knowledge retrieval, ticket creation, sentiment analysis, and human-machine collaboration capabilities, fully covering the core needs of customer service scenarios.
RAG Agent Application Implementation: From Knowledge Base to Autonomous Decision-Making
AI Application Development
Intermediate
The combination of RAG and Agents is reshaping enterprise knowledge applications. This article builds a production-grade RAG Agent step by step, from knowledge base construction, retrieval augmentation, tool calling to autonomous decision-making, and discusses evaluation and iteration methods.
Constrained Decoding and Structured Output: Grammar, JSON Schema, and Sampling Repair
AI Application Development
Intermediate
Prompting a model to emit JSON is not a guarantee. Three layers make output reliably parseable: per-token masking that admits only legal tokens, compiling JSON Schema into a decoding grammar, and a post-sampling repair layer with validation and bounded retries. It also covers joint constraints for tool calls and structured edits, per-layer latency, and a launch checklist.
AI Application Performance Optimization and Cost Control
AI Application Development
Advanced
The performance and cost of AI applications directly impact product experience and commercial viability. This article systematically explains methods for AI application performance optimization and cost control from dimensions such as prompt optimization, caching strategies, model selection, and architecture design.
DeepSeek API Quick Start: From Registration to First Application
AI Application Development
Beginner
DeepSeek provides cost-effective LLM API services. This article starts from scratch, guiding you through DeepSeek API registration, key acquisition, SDK installation, and building your first AI application—all within ten minutes.
Voice AI Application Development in Practice
AI Application Development
Intermediate
Voice interaction is becoming a new entry point for AI applications. This article starts from the complete chain of ASR speech recognition, LLM dialogue generation, and TTS speech synthesis, and builds an end-to-end voice AI application, covering real-time streaming processing and latency optimization.
DeepSeek API in Action: From Getting Started to Production Deployment
AI Application Development
Intermediate
In-depth understanding of DeepSeek API features, from basic calls to production best practices. Covers core topics such as streaming output, Function Calling, rate limits, error retries, and multi-model switching.
AI Search Architecture: Engineering Trade-offs in Retrieval, Reranking, and Generation
AI Application Development
Advanced
Every layer of AI search has a trade-off: forward, inverted, and vector indexes cost storage; multi-path recall fuses sparse and dense hits, trading recall for latency; query understanding handles intent, rewrite, freshness, multi-turn context; reranking buys precision at a price; generation brings hallucination and citation tracing; offline and online metrics drift apart.
Building AI Applications with Dify Low-Code Platform
AI Application Development
Beginner
Dify is an open-source low-code AI application development platform that enables users without programming knowledge to quickly build AI applications. This article comprehensively explains how to use Dify, from installation and deployment to application release.
Building an AI Code Review System
AI Application Development
Intermediate
Code review is an indispensable part of software development, but manual review is time-consuming and inconsistent in quality. This article teaches you step by step how to build an automated code review system using the DeepSeek API, covering security vulnerability detection, performance analysis, code style checking, and best practice suggestions.
Getting Started with Low-Code AI Application Development
AI Application Development
Beginner
You don't need deep programming skills to build powerful AI applications. This article introduces how to quickly build RAG applications, agents, and automated workflows using low-code platforms such as Dify and Flowise.
DeepSeek-V3 vs R1: Complete Model Selection Guide (2026 Latest)
AI Application Development
Beginner
DeepSeek-V3 and R1 are the two most popular model series currently. This article compares them from multiple dimensions such as performance, cost, applicable scenarios, and token consumption to help you make the best selection decision.
Advanced Prompt Engineering: Structured Prompts, CoT, Self-Reflection
AI Application Development
Intermediate
Explore advanced prompt engineering paradigms: structured prompts, chain-of-thought, self-reflection, and least-to-most. Includes DeepSeek API examples and evaluation sets for measurable, iterative optimization.
DeepSeek Safety and Content Moderation
AI Application Development
Advanced
Production environment security protection guide: from prompt injection defense to content moderation systems, from jailbreak detection to red team testing. Complete security architecture design and Python implementation code to ensure AI applications are safe and reliable.
AI Workflow Engine in Practice: From Scripts to Visual Orchestration
AI Application Development
Intermediate
Complex AI applications should not be a pile of coupled scripts. This article explains how to build a lightweight AI workflow engine, including node abstraction, conditional branching, loop execution, and breakpoint recovery, with a complete runnable Python implementation.
DeepSeek Open Source Project Selection: Top 10 Tools Worth Following on GitHub
AI Application Development
Beginner
There are many excellent open-source projects based on DeepSeek on GitHub. This article selects 10 of the most noteworthy tools and frameworks, covering directions such as chat clients, API proxies, Agent frameworks, and RAG systems, to help you quickly find the right open-source solution for your project.
DeepSeek + Dify Application Development
AI Application Development
Beginner
Quickly Build DeepSeek-Powered AI Applications with the Dify Platform: Chat Assistant, Knowledge Base Q&A, and Agent Workflows. Build production-grade AI applications without writing code through visual orchestration, including complete configuration and deployment tutorials.
DeepSeek Open Source Project Hands-on
AI Application Development
Intermediate
Collection of Practical Open-Source Projects Based on DeepSeek: Intelligent Customer Service System, Code Review Assistant, Document Q&A Bot, AI Search, and Data Analysis Assistant. Each project includes complete code, architecture design, and deployment guide, ready for production use.
DeepSeek Development Tools Ecosystem
AI Application Development
Intermediate
DeepSeek Development Tool Ecosystem Overview: IDE Plugins, Command-Line Tools, Debugging Tools, Prompt Management, and Evaluation Frameworks. Covers DeepSeek integration solutions and productivity tools for mainstream development environments such as VSCode, JetBrains, and Cursor.
LangChain + DeepSeek Complete Integration Guide
AI Application Development
Beginner
LangChain is the most popular framework for AI application development. This article details how to deeply integrate DeepSeek API into the LangChain ecosystem, covering complete usage of ChatModel, Embeddings, Tool Calling, Chain, and Agent.
