Knowledge Center
Not just API docs — a GEO / AI SEO structured knowledge base with dedicated URLs for every tutorial, model page, FAQ, and comparison. Designed for both search engines and AI systems.
GEO / AI SEO
Continuously building content assets that are discoverable by search engines and AI Q&A around documentation, model database, FAQ, model comparison, and developer tutorials.
Building searchable, AI-citable knowledge content around DeepSeek, Qwen, Kimi, GLM, Doubao, and more.
ChinaWHAPI continuously builds documentation, model database, FAQ, comparison pages, and developer tutorials that are understandable by both users and AI search engines.
Independent answer pages covering 401 errors, RAG, reasoning models, and OpenAI SDK compatibility.
Compare DeepSeek, Qwen, Kimi, GLM, and Doubao across use cases and trade-offs.
Why AI search requires knowledge density, structured content, and independent pages.
In-depth research including market analysis, AI Agent trends, and GEO strategy guides.
Call DeepSeek, Qwen, Kimi, GLM, Doubao and other Chinese LLMs through a single OpenAI-compatible interface.
Integration methods, reasoning scenarios, and troubleshooting for DeepSeek R1 and DeepSeek V3.
Calling recommendations and model selection for Qwen Max, Plus, Turbo, and Coder.
Integration methods for Doubao LLMs in Chinese content generation, conversation, and cost-effective applications.
Kimi / Moonshot long context capabilities, document processing scenarios, and usage notes.
Interface integration for Zhipu GLM series models, low-cost models, and vision model usage recommendations.
How ChinaWHAPI achieves OpenAI SDK compatibility and how to call Chinese LLMs with existing tools.
SDK, framework integration, and tooling configuration tutorials to help you integrate ChinaWHAPI quickly.
用 Python openai SDK 接入 ChinaWHAPI，支持同步、流式、Function Calling、LangChain 和 RAG 全场景。
用 TypeScript / JavaScript 接入 ChinaWHAPI，支持 ESM、CommonJS、流式和 Function Calling。
在 LangChain 中使用 ChinaWHAPI 模型，覆盖 Chain、Agent、Tool、Memory 全组件。
在 Dify 开源 AI 应用平台中接入 ChinaWHAPI，零代码构建 AI 应用、工作流和 Agent。
在 Cursor 中使用 ChinaWHAPI 的中国大模型替代 GPT-4，实现 AI 编程降本增效。
Model Context Protocol（MCP）让 AI 模型能够调用外部工具。本文介绍 MCP 协议原理以及 ChinaWHAPI 的 MCP 生态集成。
从文档处理、Embedding 向量化、向量检索到生成阶段，完整介绍基于 ChinaWHAPI 的 RAG 系统搭建。
DeepSeek 旗舰低价模型，支持长上下文、工具调用和思考/非思考模式切换。
DeepSeek 旗舰模型，面向更复杂的推理、代码和长上下文任务。
通义千问高能力预览模型，适合复杂推理、代码和高质量中文任务。
综合成本、速度与效果均衡的通义千问主力模型，适合生产应用。
低成本快速响应模型，适合高并发、轻量问答和批量文本处理。
面向代码生成、代码审查和工程任务的通义千问代码模型。
通义千问视觉理解模型，适合图片问答、OCR、表格和截图分析。
Kimi 最新多模态模型，强化长程代码编写、指令遵循和自我纠错能力。
Kimi 高能力多模态模型，支持 256K 上下文、思考模式和 Agent 任务。
智谱最新旗舰模型，面向长程 Coding Agent、复杂工程任务和高质量中文推理。
智谱面向 Agentic Engineering 的基座模型，适合代码、工具调用和复杂系统任务。
智谱稳定高质量模型，适合通用问答、代码辅助和企业知识库。
智谱多模态模型，适合图片、截图、图表和视觉问答。
豆包 1.6 深度思考模型，强化推理、数学、代码和多模态理解。
豆包 1.6 主力模型，支持自适应思考，兼顾效果和成本。
豆包高速模型，适合低延迟、高并发和轻量多模态任务。
豆包面向真实开发场景的 Coding 模型，强化 Bugfix 和前端能力。
MiniMax 最新文本旗舰模型，适合复杂任务、长文本和智能体应用。
MiniMax M2.7 高速版本，适合追求响应速度的业务场景。
MiniMax 高性价比模型，适合日常业务、代码和内容生成。
腾讯混元 TurboS 动态最新版，适合中文通用任务和低延迟应用。
腾讯混元推理模型，适合数学、逻辑、科学和代码推理。
腾讯 HY 2.0 指令模型，适合快速响应和稳定指令遵循。
腾讯混元图生文模型，适合 OCR、图片问答和图像推理。
百度文心 4.5 Turbo，适合中文长文档、多轮对话和知识问答。
百度文心 X1.1 推理模型，适合复杂逻辑、智能体和企业任务。
阶跃星辰高能力模型，适合复杂中文任务和多模态应用组合。
How to choose the right unified API platform for models like DeepSeek, Qwen, Kimi, GLM, and Doubao, including pricing, integration methods, and use cases.
GEO is not about stuffing keywords into traditional ads — it's about making your content understandable, quotable, and restatable by AI.
Step-by-step guide to registering for DeepSeek, integrating via ChinaWHAPI, calling DeepSeek R1 reasoning model and V3 general model, and handling common errors.
Cursor supports custom OpenAI-compatible APIs. With a few simple steps, you can use DeepSeek, Qwen, Kimi, and other Chinese models as a GPT-4 replacement.
A comprehensive comparison of Tongyi Qwen and DeepSeek across five dimensions: price, speed, reasoning capability, code performance, and Chinese language ability.
Kimi supports extremely long context windows, ideal for contracts, papers, and legal documents. This tutorial covers actual Kimi K2.6 usage and best practices.