json_generation

# 综合 JSON 生成指南 使用 Pydantic 模型和 JSON 模式通过 Outlines 进行 JSON 生成的完整指南。 ## 目录 - Pydantic 模型 - JSON 模式支持 - 高级模式 - 嵌套结构 - 复杂类型 - 验证 - 性能优化 ## Pydantic 模型 ### 基础模型 python from pydantic import BaseModel import outlines class User(BaseModel): name: str age: int email: str model = outlines.models.transformers("microsoft/Phi-3-mini-4k-instruct") generator = outlines.generate.json(model, User) user = generator("Generate user: Alice, 25, [email protected]") print(user.name) # "Alice" print(user.age) # 25 print(user.email) # "[email protected]" ### 字段约束 python from pydantic import BaseModel, Field class Product(BaseModel): name: str = Field(min_length=1, max_length=100) price: float = Field(gt=0, description="美元价格") discount: float = Field(ge=0, le=100, description="折扣百分比") quantity: int = Field(ge=0, description="可用数量") sku: str = Field(pattern=r"^[A-Z]{3}-d{6}$") model = outlines.models.transformers("microsoft/Phi-3-mini-4k-instruct") generator = outlines.generate.json(model, Product) product = generator("Generate product: iPhone 15, $999") # 保证所有字段满足约束 **可用约束：** - `min_length`, `max_length`: 字符串长度 - `gt`, `ge`, `lt`, `le`: 数值比较 - `multiple_of`: 数值必须是该值的倍数 - `pattern`: 字符串的正则表达式 - `min_items`, `max_items`: 列表长度 ### 可选字段 python from typing import Optional class Article(BaseModel): title: str # 必填 author: Optional[str] = None # 可选 published_date: Optional[str] = None # 可选 tags: list[str] = [] # 默认空列表 view_count: int = 0 # 默认值 generator = outlines.generate.json(model, Article) # 即使缺少可选字段也能生成 article = generator("Title: Introduction to AI") print(article.author) # None (未提供) print(article.tags) # [] (默认) ### 默认值 python class Config(BaseModel): debug: bool = False max_retries: int = 3 timeout: float = 30.0 log_level: str = "INFO" # 未指定时生成器使用默认值 generator = outlines.generate.json(model, Config) config = generator("Generate config with debug enabled") print(config.debug) # True (from pro