结构化输出

from google import genai from pydantic import BaseModel, Field from typing import List, Optional  class Ingredient(BaseModel):     name: str = Field(description="Name of the ingredient.")     quantity: str = Field(description="Quantity of the ingredient, including units.")  class Recipe(BaseModel):     recipe_name: str = Field(description="The name of the recipe.")     prep_time_minutes: Optional[int] = Field(description="Optional time in minutes to prepare the recipe.")     ingredients: List[Ingredient]     instructions: List[str]  client = genai.Client()  prompt = """ Please extract the recipe from the following text. The user wants to make delicious chocolate chip cookies. They need 2 and 1/4 cups of all-purpose flour, 1 teaspoon of baking soda, 1 teaspoon of salt, 1 cup of unsalted butter (softened), 3/4 cup of granulated sugar, 3/4 cup of packed brown sugar, 1 teaspoon of vanilla extract, and 2 large eggs. For the best part, they'll need 2 cups of semisweet chocolate chips. First, preheat the oven to 375°F (190°C). Then, in a small bowl, whisk together the flour, baking soda, and salt. In a large bowl, cream together the butter, granulated sugar, and brown sugar until light and fluffy. Beat in the vanilla and eggs, one at a time. Gradually beat in the dry ingredients until just combined. Finally, stir in the chocolate chips. Drop by rounded tablespoons onto ungreased baking sheets and bake for 9 to 11 minutes. """  response = client.models.generate_content(     model="gemini-2.5-flash",     contents=prompt,     config={         "response_mime_type": "application/json",         "response_json_schema": Recipe.model_json_schema(),     }, )  recipe = Recipe.model_validate_json(response.text) print(recipe) 

import { GoogleGenAI } from "@google/genai"; import { z } from "zod"; import { zodToJsonSchema } from "zod-to-json-schema";  const ingredientSchema = z.object({   name: z.string().describe("Name of the ingredient."),   quantity: z.string().describe("Quantity of the ingredient, including units."), });  const recipeSchema = z.object({   recipe_name: z.string().describe("The name of the recipe."),   prep_time_minutes: z.number().optional().describe("Optional time in minutes to prepare the recipe."),   ingredients: z.array(ingredientSchema),   instructions: z.array(z.string()), });  const ai = new GoogleGenAI({});  const prompt = ` Please extract the recipe from the following text. The user wants to make delicious chocolate chip cookies. They need 2 and 1/4 cups of all-purpose flour, 1 teaspoon of baking soda, 1 teaspoon of salt, 1 cup of unsalted butter (softened), 3/4 cup of granulated sugar, 3/4 cup of packed brown sugar, 1 teaspoon of vanilla extract, and 2 large eggs. For the best part, they'll need 2 cups of semisweet chocolate chips. First, preheat the oven to 375°F (190°C). Then, in a small bowl, whisk together the flour, baking soda, and salt. In a large bowl, cream together the butter, granulated sugar, and brown sugar until light and fluffy. Beat in the vanilla and eggs, one at a time. Gradually beat in the dry ingredients until just combined. Finally, stir in the chocolate chips. Drop by rounded tablespoons onto ungreased baking sheets and bake for 9 to 11 minutes. `;  const response = await ai.models.generateContent({   model: "gemini-2.5-flash",   contents: prompt,   config: {     responseMimeType: "application/json",     responseJsonSchema: zodToJsonSchema(recipeSchema),   }, });  const recipe = recipeSchema.parse(JSON.parse(response.text)); console.log(recipe); 

package main  import (     "context"     "fmt"     "log"      "google.golang.org/genai" )  func main() {     ctx := context.Background()     client, err := genai.NewClient(ctx, nil)     if err != nil {         log.Fatal(err)     }      prompt := `   Please extract the recipe from the following text.   The user wants to make delicious chocolate chip cookies.   They need 2 and 1/4 cups of all-purpose flour, 1 teaspoon of baking soda,   1 teaspoon of salt, 1 cup of unsalted butter (softened), 3/4 cup of granulated sugar,   3/4 cup of packed brown sugar, 1 teaspoon of vanilla extract, and 2 large eggs.   For the best part, they'll need 2 cups of semisweet chocolate chips.   First, preheat the oven to 375°F (190°C). Then, in a small bowl, whisk together the flour,   baking soda, and salt. In a large bowl, cream together the butter, granulated sugar, and brown sugar   until light and fluffy. Beat in the vanilla and eggs, one at a time. Gradually beat in the dry   ingredients until just combined. Finally, stir in the chocolate chips. Drop by rounded tablespoons   onto ungreased baking sheets and bake for 9 to 11 minutes.   `     config := &genai.GenerateContentConfig{         ResponseMIMEType: "application/json",         ResponseJsonSchema: map[string]any{             "type": "object",             "properties": map[string]any{                 "recipe_name": map[string]any{                     "type":        "string",                     "description": "The name of the recipe.",                 },                 "prep_time_minutes": map[string]any{                     "type":        "integer",                     "description": "Optional time in minutes to prepare the recipe.",                 },                 "ingredients": map[string]any{                     "type": "array",                     "items": map[string]any{                         "type": "object",                         "properties": map[string]any{                             "name": map[string]any{                                 "type":        "string",                                 "description": "Name of the ingredient.",                             },                             "quantity": map[string]any{                                 "type":        "string",                                 "description": "Quantity of the ingredient, including units.",                             },                         },                         "required": []string{"name", "quantity"},                     },                 },                 "instructions": map[string]any{                     "type":  "array",                     "items": map[string]any{"type": "string"},                 },             },             "required": []string{"recipe_name", "ingredients", "instructions"},         },     }      result, err := client.Models.GenerateContent(         ctx,         "gemini-2.5-flash",         genai.Text(prompt),         config,     )     if err != nil {         log.Fatal(err)     }     fmt.Println(result.Text()) } 

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \     -H "x-goog-api-key: $GEMINI_API_KEY" \     -H 'Content-Type: application/json' \     -X POST \     -d '{       "contents": [{         "parts":[           { "text": "Please extract the recipe from the following text.\nThe user wants to make delicious chocolate chip cookies.\nThey need 2 and 1/4 cups of all-purpose flour, 1 teaspoon of baking soda,\n1 teaspoon of salt, 1 cup of unsalted butter (softened), 3/4 cup of granulated sugar,\n3/4 cup of packed brown sugar, 1 teaspoon of vanilla extract, and 2 large eggs.\nFor the best part, they will need 2 cups of semisweet chocolate chips.\nFirst, preheat the oven to 375°F (190°C). Then, in a small bowl, whisk together the flour,\nbaking soda, and salt. In a large bowl, cream together the butter, granulated sugar, and brown sugar\nuntil light and fluffy. Beat in the vanilla and eggs, one at a time. Gradually beat in the dry\ningredients until just combined. Finally, stir in the chocolate chips. Drop by rounded tablespoons\nonto ungreased baking sheets and bake for 9 to 11 minutes." }         ]       }],       "generationConfig": {         "responseMimeType": "application/json",         "responseJsonSchema": {           "type": "object",           "properties": {             "recipe_name": {               "type": "string",               "description": "The name of the recipe."             },             "prep_time_minutes": {                 "type": "integer",                 "description": "Optional time in minutes to prepare the recipe."             },             "ingredients": {               "type": "array",               "items": {                 "type": "object",                 "properties": {                   "name": { "type": "string", "description": "Name of the ingredient."},                   "quantity": { "type": "string", "description": "Quantity of the ingredient, including units."}                 },                 "required": ["name", "quantity"]               }             },             "instructions": {               "type": "array",               "items": { "type": "string" }             }           },           "required": ["recipe_name", "ingredients", "instructions"]         }       }     }' 

from google import genai from pydantic import BaseModel, Field from typing import Literal  class Feedback(BaseModel):     sentiment: Literal["positive", "neutral", "negative"]     summary: str  client = genai.Client() prompt = "The new UI is incredibly intuitive and visually appealing. Great job. Add a very long summary to test streaming!"  response_stream = client.models.generate_content_stream(     model="gemini-2.5-flash",     contents=prompt,     config={         "response_mime_type": "application/json",         "response_json_schema": Feedback.model_json_schema(),     }, )  for chunk in response_stream:     print(chunk.candidates[0].content.parts[0].text) 

import { GoogleGenAI } from "@google/genai"; import { z } from "zod"; import { zodToJsonSchema } from "zod-to-json-schema";  const ai = new GoogleGenAI({}); const prompt = "The new UI is incredibly intuitive and visually appealing. Great job! Add a very long summary to test streaming!";  const feedbackSchema = z.object({   sentiment: z.enum(["positive", "neutral", "negative"]),   summary: z.string(), });  const stream = await ai.models.generateContentStream({   model: "gemini-2.5-flash",   contents: prompt,   config: {     responseMimeType: "application/json",     responseJsonSchema: zodToJsonSchema(feedbackSchema),   }, });  for await (const chunk of stream) {   console.log(chunk.candidates[0].content.parts[0].text) }