Ju mund të konfiguroni modelet Gemini për të gjeneruar përgjigje që i përmbahen një skeme JSON të dhënë. Kjo siguron rezultate të parashikueshme dhe të sigurta për llojin dhe thjeshton nxjerrjen e të dhënave të strukturuara nga teksti i pastrukturuar.
Përdorimi i rezultateve të strukturuara është ideal për:
- Nxjerrja e të dhënave: Nxirrni informacione specifike si emrat dhe datat nga teksti.
- Klasifikimi i strukturuar: Klasifikoni tekstin në kategori të paracaktuara.
- Flukset e punës agjentike: Gjeneroni të dhëna të strukturuara për mjete ose API.
Përveç mbështetjes së Skemës JSON në API-n REST, SDK-të e Google GenAI lejojnë përcaktimin e skemave duke përdorur Pydantic (Python) dhe Zod (JavaScript).
Shembuj të rezultateve të strukturuara
Ekstraktor Recetash
Ky shembull demonstron se si të nxirren të dhëna të strukturuara nga teksti duke përdorur llojet themelore të skemës JSON si object , array , string dhe integer .
Python
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.
"""
interaction = client.interactions.create(
model="gemini-3.8-flash",
input=prompt,
response_format={
"type": "text",
"mime_type": "application/json",
"schema": Recipe.model_json_schema()
},
)
recipe = Recipe.model_validate_json(interaction.output_text)
print(recipe)
JavaScript
// Note: Ensure zod is installed (npm install zod)
import { GoogleGenAI } from "@google/genai";
import * as z from "zod";
const recipeJsonSchema = {
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"]
};
const recipeSchema = z.fromJSONSchema(recipeJsonSchema);
const client = 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 interaction = await client.interactions.create({
model: "gemini-3.8-flash",
input: prompt,
response_format: {
type: 'text',
mime_type: 'application/json',
schema: recipeJsonSchema
},
});
const recipe = recipeSchema.parse(JSON.parse(interaction.output_text));
console.log(recipe);
Java
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.interactions.TextResponseFormat;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> schema = new HashMap<>();
schema.put("type", "object");
CreateModelInteractionResponseFormat format =
CreateModelInteractionResponseFormat.of(
ResponseFormat.of(TextResponseFormat.builder().schema(schema).build()));
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("List 3 popular cookie recipes."))
.responseFormat(format)
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
System.out.println(interaction.outputText().orElse(""));
PUSHTIM
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "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.",
"response_format": {
"type": "text",
"mime_type": "application/json",
"schema": {
"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"]
}
}
}
}'
Shembull Përgjigjeje:
{
"recipe_name": "Delicious Chocolate Chip Cookies",
"ingredients": [
{ "name": "all-purpose flour", "quantity": "2 and 1/4 cups" },
{ "name": "baking soda", "quantity": "1 teaspoon" },
{ "name": "salt", "quantity": "1 teaspoon" },
{ "name": "unsalted butter (softened)", "quantity": "1 cup" },
{ "name": "granulated sugar", "quantity": "3/4 cup" },
{ "name": "packed brown sugar", "quantity": "3/4 cup" },
{ "name": "vanilla extract", "quantity": "1 teaspoon" },
{ "name": "large eggs", "quantity": "2" },
{ "name": "semisweet chocolate chips", "quantity": "2 cups" }
],
"instructions": [
"Preheat the oven to 375°F (190°C).",
"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.",
"Stir in the chocolate chips.",
"Drop by rounded tablespoons onto ungreased baking sheets and bake for 9 to 11 minutes."
]
}
Moderimi i Përmbajtjes
Ky shembull tregon anyOf për skemat kushtëzuese dhe enum për klasifikim, duke lejuar që struktura e daljes të ndryshojë në bazë të përmbajtjes.
Python
from google import genai
from pydantic import BaseModel, Field
from typing import Union, Literal
class SpamDetails(BaseModel):
reason: str = Field(description="The reason why the content is considered spam.")
spam_type: Literal["phishing", "scam", "unsolicited promotion", "other"] = Field(description="The type of spam.")
class NotSpamDetails(BaseModel):
summary: str = Field(description="A brief summary of the content.")
is_safe: bool = Field(description="Whether the content is safe for all audiences.")
class ModerationResult(BaseModel):
decision: Union[SpamDetails, NotSpamDetails]
client = genai.Client()
prompt = """
Please moderate the following content and provide a decision.
Content: 'Congratulations! You''ve won a free cruise to the Bahamas. Click here to claim your prize: www.definitely-not-a-scam.com'
"""
interaction = client.interactions.create(
model="gemini-3.8-flash",
input=prompt,
response_format={
"type": "text",
"mime_type": "application/json",
"schema": ModerationResult.model_json_schema()
},
)
result = ModerationResult.model_validate_json(interaction.output_text)
print(result)
JavaScript
// Note: Ensure zod is installed (npm install zod)
import { GoogleGenAI } from "@google/genai";
import * as z from "zod";
const moderationResultJsonSchema = {
type: "object",
properties: {
decision: {
anyOf: [
{
type: "object",
title: "SpamDetails",
description: "Details for content classified as spam.",
properties: {
reason: { type: "string", description: "The reason why the content is considered spam." },
spam_type: { type: "string", enum: ["phishing", "scam", "unsolicited promotion", "other"], description: "The type of spam." }
},
required: ["reason", "spam_type"]
},
{
type: "object",
title: "NotSpamDetails",
description: "Details for content classified as not spam.",
properties: {
summary: { type: "string", description: "A brief summary of the content." },
is_safe: { type: "boolean", description: "Whether the content is safe for all audiences." }
},
required: ["summary", "is_safe"]
}
]
}
},
required: ["decision"]
};
const moderationResultSchema = z.fromJSONSchema(moderationResultJsonSchema);
const client = new GoogleGenAI({});
const prompt = `
Please moderate the following content and provide a decision.
Content: 'Congratulations! You''ve won a free cruise to the Bahamas. Click here to claim your prize: www.definitely-not-a-scam.com'
`;
const interaction = await client.interactions.create({
model: "gemini-3.8-flash",
input: prompt,
response_format: {
type: 'text',
mime_type: 'application/json',
schema: moderationResultJsonSchema
},
});
const result = moderationResultSchema.parse(JSON.parse(interaction.output_text));
console.log(result);
Java
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.CreateModelInteractionResponseFormat;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ResponseFormat;
import com.google.genai.gaos.models.interactions.TextResponseFormat;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> schema = new HashMap<>();
schema.put("type", "object");
CreateModelInteractionResponseFormat format =
CreateModelInteractionResponseFormat.of(
ResponseFormat.of(TextResponseFormat.builder().schema(schema).build()));
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("List 3 popular cookie recipes."))
.responseFormat(format)
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
System.out.println(interaction.outputText().orElse(""));
PUSHTIM
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "Please moderate the following content and provide a decision.\nContent: '\''Congratulations! You have won a free cruise to the Bahamas. Click here to claim your prize: www.definitely-not-a-scam.com'\''",
"response_format": {
"type": "text",
"mime_type": "application/json",
"schema": {
"type": "object",
"properties": {
"decision": {
"anyOf": [
{
"type": "object",
"title": "SpamDetails",
"description": "Details for content classified as spam.",
"properties": {
"reason": { "type": "string", "description": "The reason why the content is considered spam." },
"spam_type": { "type": "string", "enum": ["phishing", "scam", "unsolicited promotion", "other"], "description": "The type of spam." }
},
"required": ["reason", "spam_type"]
},
{
"type": "object",
"title": "NotSpamDetails",
"description": "Details for content classified as not spam.",
"properties": {
"summary": { "type": "string", "description": "A brief summary of the content." },
"is_safe": { "type": "boolean", "description": "Whether the content is safe for all audiences." }
},
"required": ["summary", "is_safe"]
}
]
}
},
"required": ["decision"]
}
}
}
}'
Shembull Përgjigjeje:
{
"decision": {
"reason": "The content is an unsolicited prize notification attempting to trick the user into clicking a suspicious link.",
"spam_type": "scam"
}
}
Strukturat Rekursive
Ky shembull ilustron se si të përcaktohet një skemë rekursive siç është një tabelë organizative.