Python

为什么需要多模型智能路由？ # 2026年，AI大模型生态已经高度成熟。OpenAI发布了GPT-5和GPT-5-mini，Anthropic推出了Claude Opus 4和Claude Sonnet 4，Google的Gemini 2.5 Pro全面铺开，国内DeepSeek-V4、Qwen3-235B、GLM-5等模型也在飞速迭代。

Why Multi-Model Smart Routing? # In 2026, the AI model ecosystem has matured dramatically. OpenAI shipped GPT-5 and GPT-5-mini, Anthropic launched Claude Opus 4 and Claude Sonnet 4, Google’s Gemini 2.5 Pro is widely available, and Chinese models like DeepSeek-V4, Qwen3-235B, and GLM-5 are evolving at breakneck speed. As a developer, you probably face these pain points:

Introduction # In 2026, Anthropic released Claude 4.7 — a landmark model that pushes the boundaries of reasoning, code generation, multimodal understanding, and long-context processing. For developers, knowing how to efficiently and reliably integrate the Claude 4.7 API into production systems is now an essential skill. This guide walks you through everything: from your first API call to production-grade deployment, covering the latest API changes, pricing structure, and battle-tested best practices.

引言 # 2026年，Anthropic推出了全新的Claude 4.7模型，在推理能力、代码生成、多模态理解和长上下文处理等方面均实现了重大突破。对于开发者而言，如何高效、稳定地接入Claude 4.7 API，并将其应用于生产环境，已成为一项关键技能。

前置准备 # 在开始之前，你需要： Python 3.8+ 环境 XiDao API Key（免费注册） 安装依赖 # pip install openai 基础调用 # from openai import OpenAI client = OpenAI( api_key="your-xidao-api-key", base_url="https://global.xidao.online/v1" ) response = client.chat.completions.create( model="gpt-4o", messages=[ {"role": "system", "content": "你是一个友好的AI助手。"}, {"role": "user", "content": "用Python写一个快速排序算法"} ], temperature=0.7 ) print(response.choices[0].message.content) 流式输出 # stream = client.chat.completions.create( model="claude-4", messages=[{"role": "user", "content": "解释量子计算的基本原理"}], stream=True ) for chunk in stream: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) 多模型切换 # models = { "代码生成": "claude-4", "文本总结": "gpt-4o-mini", "创意写作": "gemini-2.5-pro", "数据分析": "gpt-4o" } def ask_ai(task_type, question): model = models.get(task_type, "gpt-4o") response = client.chat.completions.create( model=model, messages=[{"role": "user", "content": question}] ) return response.choices[0].message.content 👉 免费注册获取 API Key：global.xidao.online

Quick Start # from openai import OpenAI client = OpenAI( api_key="your-xidao-api-key", base_url="https://global.xidao.online/v1" ) response = client.chat.completions.create( model="gpt-4o", messages=[{"role": "user", "content": "Write quicksort in Python"}] ) 👉 Get your API Key: global.xidao.online